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9,390,079 | 21 | 23 | 21. A computer-implemented method comprising: under direction of one or more hardware processors configured with specific software instructions, displaying, on an electronic display, a textual record including one or more nodes and one or more subnodes; receiving, from a user interacting with the textual record, a first input including a command, a node identifier, and a first subnode identifier; in response to receiving the command, the node identifier, and the first subnode identifier: identifying, based on the node identifier, a node of the textual record associated with the node identifier; identifying, based on the first subnode identifier, a first subnode of the identified node, the first subnode associated with the first subnode identifier; and determining a first portion of the textual record related to the identified first subnode; receiving, from the user, a second input including the command and a second subnode identifier; and in response to receiving the command and the second subnode identifier: identifying, based on the second subnode identifier, a second subnode of the identified node, the second subnode associated with the second subnode identifier; and determining a second portion of the textual record related to the identified second subnode. | 21. A computer-implemented method comprising: under direction of one or more hardware processors configured with specific software instructions, displaying, on an electronic display, a textual record including one or more nodes and one or more subnodes; receiving, from a user interacting with the textual record, a first input including a command, a node identifier, and a first subnode identifier; in response to receiving the command, the node identifier, and the first subnode identifier: identifying, based on the node identifier, a node of the textual record associated with the node identifier; identifying, based on the first subnode identifier, a first subnode of the identified node, the first subnode associated with the first subnode identifier; and determining a first portion of the textual record related to the identified first subnode; receiving, from the user, a second input including the command and a second subnode identifier; and in response to receiving the command and the second subnode identifier: identifying, based on the second subnode identifier, a second subnode of the identified node, the second subnode associated with the second subnode identifier; and determining a second portion of the textual record related to the identified second subnode. 23. The computer-implemented method of claim 21 , wherein further in response to receiving the command, the node identifier, and the first subnode identifier, the determined first portion of the textual record is deleted or replaced. | 0.850064 |
8,244,767 | 13 | 20 | 13. A computer system comprising: a storage subsystem configured to maintain a document information data store; and a processor coupled to the storage subsystem, the processor being configured to perform one or more content-based analysis operations on documents in a corpus of documents and to store results of the analysis in the document information data store, wherein the processor is further configured to: compute a composite hash value for each of the documents; assign each document to one of a plurality of groups, wherein all documents in a same group have a same composite hash value; perform the one or more content-based analysis operations on one document from each of the plurality of groups; and store a result of the one or more content-based analysis operations in the document information data store in association with each of the documents in the group. | 13. A computer system comprising: a storage subsystem configured to maintain a document information data store; and a processor coupled to the storage subsystem, the processor being configured to perform one or more content-based analysis operations on documents in a corpus of documents and to store results of the analysis in the document information data store, wherein the processor is further configured to: compute a composite hash value for each of the documents; assign each document to one of a plurality of groups, wherein all documents in a same group have a same composite hash value; perform the one or more content-based analysis operations on one document from each of the plurality of groups; and store a result of the one or more content-based analysis operations in the document information data store in association with each of the documents in the group. 20. The computer system of claim 13 wherein the processor is further configured to receive new documents to be added to the corpus, wherein when a new document is received, the processor is configured to: compute a composite hash value for the new document; determine whether the composite hash value for the new document matches a composite hash value associated with one of the groups of documents; add the new document to the one of the groups of documents in the event that the composite hash value matches the composite hash value associated with the one of the groups of documents; and perform the content-based analysis operation on the new document in the event that the composite hash value does not match the composite hash value associated with any of the groups of documents. | 0.5 |
8,510,347 | 24 | 25 | 24. The computer program product of claim 19 , wherein defining each set of meta-models the computer readable program code further performs defining one or more intent meta-models corresponding to the at least one requirement, each intent meta-model describing the corresponding at least one requirement. | 24. The computer program product of claim 19 , wherein defining each set of meta-models the computer readable program code further performs defining one or more intent meta-models corresponding to the at least one requirement, each intent meta-model describing the corresponding at least one requirement. 25. The computer program product of claim 24 , wherein defining each set of meta-models the computer readable program code further performs defining one or more inference meta-models corresponding to each defined intent meta-model, each inference meta-model describing business and technical requirements required for generating at least one software artifact of the one or more software artifacts, the business and technical requirements being determined based on the at least one requirement. | 0.5 |
8,370,734 | 1 | 8 | 1. A computer-implemented method of providing a graphical user interface (GUI), using a processor, that facilitates reusing information from one or more previous electronic documents in a new electronic document, the method comprising: displaying a query interface having at least one data filter component that presents a plurality of query parameters; receiving, via the query interface, at least one selected query parameter; querying a database of computer electronic documents with the at least one selected query parameter; grouping results of querying the database for display into a plurality of captioned sections, each of the plurality of captioned sections containing content from the electronic documents associated with the respective captioned section; displaying the results of querying the database in a section viewer component, the section viewer component displaying the results in a tree structure comprising: a section level component for displaying each of the plurality of captioned sections in association with a respective expand/collapse graphical component, each expand/collapse graphical component having a display state that is either in a collapsed state or an expanded state such that, when actuated, the section level component displays or hides content under the respective captioned section in accordance with the display state of the respective expand/collapse graphical component; and a content level component that selectively displays one or more contents associated with each of the plurality of captioned sections in accordance with whether the respective expand/collapse graphical component is in the collapsed state or the expanded state, each of the one or more contents having an associated selection graphical component displayed therewith, each of the one or more displayed selection graphical components comprising information indicating whether it is m a selected state or a non-selected state; in response to receiving input from a user via any one of the one or more displayed selection graphical components altering the state of that displayed selection graphical component; and in response to receiving an input from the user via the graphical user interface indicating that the user has finished altering the states of the one or more displayed selection graphical components copying each of the contents having an associated selection graphical component that is in the selected state into the new electronic document. | 1. A computer-implemented method of providing a graphical user interface (GUI), using a processor, that facilitates reusing information from one or more previous electronic documents in a new electronic document, the method comprising: displaying a query interface having at least one data filter component that presents a plurality of query parameters; receiving, via the query interface, at least one selected query parameter; querying a database of computer electronic documents with the at least one selected query parameter; grouping results of querying the database for display into a plurality of captioned sections, each of the plurality of captioned sections containing content from the electronic documents associated with the respective captioned section; displaying the results of querying the database in a section viewer component, the section viewer component displaying the results in a tree structure comprising: a section level component for displaying each of the plurality of captioned sections in association with a respective expand/collapse graphical component, each expand/collapse graphical component having a display state that is either in a collapsed state or an expanded state such that, when actuated, the section level component displays or hides content under the respective captioned section in accordance with the display state of the respective expand/collapse graphical component; and a content level component that selectively displays one or more contents associated with each of the plurality of captioned sections in accordance with whether the respective expand/collapse graphical component is in the collapsed state or the expanded state, each of the one or more contents having an associated selection graphical component displayed therewith, each of the one or more displayed selection graphical components comprising information indicating whether it is m a selected state or a non-selected state; in response to receiving input from a user via any one of the one or more displayed selection graphical components altering the state of that displayed selection graphical component; and in response to receiving an input from the user via the graphical user interface indicating that the user has finished altering the states of the one or more displayed selection graphical components copying each of the contents having an associated selection graphical component that is in the selected state into the new electronic document. 8. The method of claim 1 , wherein the new electronic document comprises a medical record. | 0.836364 |
8,056,049 | 15 | 18 | 15. A computer system comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a computer application model conflict reconciling program for controlling the processor, wherein the computer application models include i) an initial source computer application model, ii) an initial target computer application model generated by applying at least one transformation rule to the initial source computer application model, iii) a post-change target model produced by at least one change to the initial target model, and iv) a post-change source model produced by at least one change to the initial source model, and wherein the processor is operative with the program to execute the program for performing: automatically dividing the initial source and target models and the post-change source and target models into segments responsive to at least one segmentation rule, wherein the at least one segmentation rule is defined responsive to the at least one transformation rule such that use of the at least one segmentation rule divides the initial source and target models into corresponding, isomorphic segments, wherein the initial source and target models have an isomorphic structure in common on which to mark changes; automatically identifying change statuses of the initial segments relative to the post-change segments of the respective models responsive to comparing initial segments to post-change segments of the source model and initial segments to post-change segments of the target model; and automatically generating, on a data structure representing the in-common isomorphic structure, an indication of conflicts between the post-change source model and post-change target model for presentation to a user or to a computer automated conflict settlement process, wherein the generating is responsive to comparing the identified change statuses of the corresponding, isomorphic segments of the initial source model and initial target model, wherein at least part of the identifying and generating occurs after changes to both the initial source model and the initial target model. | 15. A computer system comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a computer application model conflict reconciling program for controlling the processor, wherein the computer application models include i) an initial source computer application model, ii) an initial target computer application model generated by applying at least one transformation rule to the initial source computer application model, iii) a post-change target model produced by at least one change to the initial target model, and iv) a post-change source model produced by at least one change to the initial source model, and wherein the processor is operative with the program to execute the program for performing: automatically dividing the initial source and target models and the post-change source and target models into segments responsive to at least one segmentation rule, wherein the at least one segmentation rule is defined responsive to the at least one transformation rule such that use of the at least one segmentation rule divides the initial source and target models into corresponding, isomorphic segments, wherein the initial source and target models have an isomorphic structure in common on which to mark changes; automatically identifying change statuses of the initial segments relative to the post-change segments of the respective models responsive to comparing initial segments to post-change segments of the source model and initial segments to post-change segments of the target model; and automatically generating, on a data structure representing the in-common isomorphic structure, an indication of conflicts between the post-change source model and post-change target model for presentation to a user or to a computer automated conflict settlement process, wherein the generating is responsive to comparing the identified change statuses of the corresponding, isomorphic segments of the initial source model and initial target model, wherein at least part of the identifying and generating occurs after changes to both the initial source model and the initial target model. 18. The computer system of claim 15 , wherein identifying change statuses includes: identifying change status for each pre-change segment relative to any corresponding existing or deleted post-change segment of the respective models. | 0.792705 |
8,522,135 | 10 | 12 | 10. A system for generating a transformation specification document describing transformations for transforming a received message to enable communication between first and second agents, wherein the first agent utilizes a first interface definition describing a first application programming interface and the second agent utilizes a second interface definition describing a second different application programming interface, the system comprising: a processor executing instructions; and a memory, operatively coupled to the processor, storing instructions, the instructions when executed by the processor operable to: compare elements of the first and second interface definitions to determine additional elements of the second interface definition absent from the first interface definition, wherein the second interface definition is constrained by one or more rules describing permissible differences relative to the first interface definition and the comparing elements identifies violations of the rules; generate processing logic for transforming a received message from the second agent conforming to the second interface definition to a message for the first agent conforming to the first interface definition by removing all of the additional elements from the received message not contained in the first interface definition to enable processing of the received message by the first agent and communication between the first and second agents; and generate the transformation specification document using the generated processing logic. | 10. A system for generating a transformation specification document describing transformations for transforming a received message to enable communication between first and second agents, wherein the first agent utilizes a first interface definition describing a first application programming interface and the second agent utilizes a second interface definition describing a second different application programming interface, the system comprising: a processor executing instructions; and a memory, operatively coupled to the processor, storing instructions, the instructions when executed by the processor operable to: compare elements of the first and second interface definitions to determine additional elements of the second interface definition absent from the first interface definition, wherein the second interface definition is constrained by one or more rules describing permissible differences relative to the first interface definition and the comparing elements identifies violations of the rules; generate processing logic for transforming a received message from the second agent conforming to the second interface definition to a message for the first agent conforming to the first interface definition by removing all of the additional elements from the received message not contained in the first interface definition to enable processing of the received message by the first agent and communication between the first and second agents; and generate the transformation specification document using the generated processing logic. 12. The system as claimed in claim 10 , wherein the instructions are further operable to: process the first and second interface definitions to indicate types and elements in the second interface definition as being: unmarked; marked for processing; or marked for deletion. | 0.5 |
8,630,961 | 22 | 24 | 22. A system for conducting an automated conversation with a correspondent, the system comprising: a chatbot server, the chatbot server including at least a processor and at least a memory; and one or more chatbot databases including a conversation data structure comprising a plurality of conversation nodes, and a correspondent profile comprising a plurality of profile variables, wherein the conversation nodes each comprise coded information adapted for processing to determine a successive conversation node for a conversation, the conversation including multiple conversational interactions including generated conversational responses to the correspondent, the multiple conversation interactions sufficiently associated in terms of subject matter to form a conversation path, the successive conversation node being in response to one or more of an input message received from the correspondent; and wherein the chatbot server includes an interpretation engine comprising instruction code executable to: process information coded in a conversation node along the conversation path, the conversation node being processed to determine and select a successive conversation node along the conversation path in response to at least a received input message. | 22. A system for conducting an automated conversation with a correspondent, the system comprising: a chatbot server, the chatbot server including at least a processor and at least a memory; and one or more chatbot databases including a conversation data structure comprising a plurality of conversation nodes, and a correspondent profile comprising a plurality of profile variables, wherein the conversation nodes each comprise coded information adapted for processing to determine a successive conversation node for a conversation, the conversation including multiple conversational interactions including generated conversational responses to the correspondent, the multiple conversation interactions sufficiently associated in terms of subject matter to form a conversation path, the successive conversation node being in response to one or more of an input message received from the correspondent; and wherein the chatbot server includes an interpretation engine comprising instruction code executable to: process information coded in a conversation node along the conversation path, the conversation node being processed to determine and select a successive conversation node along the conversation path in response to at least a received input message. 24. The system of claim 22 wherein the information coded in the conversation node to be processed to determine and select a successive conversation node along the conversation path in response to at least the received input message is further to comprise a dynamic node resolution process to be employed at selected points along the conversation path; wherein the dynamic node resolution process at the selected points along the conversation path to identify a prior conversation node along the conversation path to return to and to continue processing at least in art based on a predetermined criteria, a user input message and/or conversation context. | 0.5 |
5,418,942 | 1 | 10 | 1. An information storage system which is connectable to an input interface means and an output interface means, the information storage system comprising a computer, the computer having a memory, the memory of the computer having a plurality of nodes stored therein, each node having a unique identifier within the memory, the memory of the computer including means defining pointers between pairs of said nodes, the pointers comprising only identifiers of other nodes, the pointers having been assigned by the input interface means in response to transmission of input data to the input interface means by a user, wherein each node contains no application data elements other than pointers, wherein information to be stored is stored only as a pattern of said pointers, and wherein said stored pattern is convertible by the output interface means into data recognizable by the user. | 1. An information storage system which is connectable to an input interface means and an output interface means, the information storage system comprising a computer, the computer having a memory, the memory of the computer having a plurality of nodes stored therein, each node having a unique identifier within the memory, the memory of the computer including means defining pointers between pairs of said nodes, the pointers comprising only identifiers of other nodes, the pointers having been assigned by the input interface means in response to transmission of input data to the input interface means by a user, wherein each node contains no application data elements other than pointers, wherein information to be stored is stored only as a pattern of said pointers, and wherein said stored pattern is convertible by the output interface means into data recognizable by the user. 10. The system of claim 1, wherein wherein the information is arranged in a plurality of boxes, wherein a box may be connected to other boxes, wherein a given box may be assigned one or more "child boxes", said given box being called an "owner box", the computer being programmed to represent the boxes in outline format, wherein the child boxes of a given owner box are listed in an indented column relative to the owner box. | 0.571429 |
8,396,736 | 1 | 19 | 1. A method, performed by a computer system, for generating a process model representation for each of a plurality of activity chunks in a process such that each process model representation is arranged to be displayed on a single page, the method comprising: receiving, by one or more processors of the computer system, a Work Product/Activities/Roles (WAR) template for a process, the WAR template defining each work product that is used by the process, each activity performed by the process, and each role that performs an activity in the process, each activity being associated with one of a plurality of activity chunks defined for the process; generating, by one or more processors of the computer system, and for each of the activity chunks, a process activity template, each process activity template defining: any inputs used by the activity chunk; entry criteria defining when the activity chunk is to be performed; which role is responsible for performing each activity in the activity chunk; any outputs produced by the activity chunk; and exit criteria defining when the activity chunk is completed; generating, by one or more processors of the computer system, and for each process activity template, a process model representation, each process model representation being arranged to be displayed on a single page, each process model representation comprising: a graphical representation of the flow between the activities in the represented activity chunk; and a graphical representation of the inputs, entry criteria, roles involved in performing the activities of the represented activity chunk, outputs, and exit criteria. | 1. A method, performed by a computer system, for generating a process model representation for each of a plurality of activity chunks in a process such that each process model representation is arranged to be displayed on a single page, the method comprising: receiving, by one or more processors of the computer system, a Work Product/Activities/Roles (WAR) template for a process, the WAR template defining each work product that is used by the process, each activity performed by the process, and each role that performs an activity in the process, each activity being associated with one of a plurality of activity chunks defined for the process; generating, by one or more processors of the computer system, and for each of the activity chunks, a process activity template, each process activity template defining: any inputs used by the activity chunk; entry criteria defining when the activity chunk is to be performed; which role is responsible for performing each activity in the activity chunk; any outputs produced by the activity chunk; and exit criteria defining when the activity chunk is completed; generating, by one or more processors of the computer system, and for each process activity template, a process model representation, each process model representation being arranged to be displayed on a single page, each process model representation comprising: a graphical representation of the flow between the activities in the represented activity chunk; and a graphical representation of the inputs, entry criteria, roles involved in performing the activities of the represented activity chunk, outputs, and exit criteria. 19. The method of claim 1 , wherein at least one of process model representations also comprises an indication of measurements made by the activities of the represented activity chunk. | 0.828678 |
7,814,042 | 5 | 9 | 5. The method of claim 1 , wherein determining the set of candidate queries comprises determining a particular semantically equivalent query, and wherein determining costs comprises: determining a current-best cost based on a first cost for the query and costs for zero or more semantically equivalent queries; determining a partial cost for a first portion of the particular semantically equivalent query; and if the partial cost satisfies a first particular mathematical relationship with the current-best cost, determining a second cost based on the entire particular semantically equivalent query. | 5. The method of claim 1 , wherein determining the set of candidate queries comprises determining a particular semantically equivalent query, and wherein determining costs comprises: determining a current-best cost based on a first cost for the query and costs for zero or more semantically equivalent queries; determining a partial cost for a first portion of the particular semantically equivalent query; and if the partial cost satisfies a first particular mathematical relationship with the current-best cost, determining a second cost based on the entire particular semantically equivalent query. 9. The method of claim 5 , wherein the first particular mathematical relationship is “less than”. | 0.880247 |
9,135,310 | 20 | 23 | 20. The system of claim 18 , wherein the client determines whether the compiled skeletal query is available at the target database server, and, if the compiled skeletal query is not available at the target database server, provides the compiled skeletal query to the target database server. | 20. The system of claim 18 , wherein the client determines whether the compiled skeletal query is available at the target database server, and, if the compiled skeletal query is not available at the target database server, provides the compiled skeletal query to the target database server. 23. The system of claim 20 , wherein the client creates the compiled skeletal query based on the skeletal query form and the one or more arguments associated with the user query. | 0.548223 |
9,665,807 | 3 | 4 | 3. The method according to claim 1 , characterized in that the reuse type of the transparent Form comprises: mandatory replacement reuse and normal transparent reuse. | 3. The method according to claim 1 , characterized in that the reuse type of the transparent Form comprises: mandatory replacement reuse and normal transparent reuse. 4. The method according to claim 3 , characterized in that the assembling information of the transparent Form comprises: for a transparent Form of mandatory replacement reuse, Mask lattice information, color block lattice information, and corresponding block attribute tables and block memory tables generated for a sub-page; for a transparent Form of normal transparent reuse, Alpha block lattice information, Shape block lattic information, color block lattic information, and corresponding block attribute tables and block memory tables generated for a sub-page. | 0.578987 |
9,779,252 | 8 | 13 | 8. Apparatus, comprising: a processor; computer memory holding computer program instructions executed by one or more processors to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, the computer program instructions operative to: associate a social networking platform with the application development environments, the social networking platform being accessible by users of the application development environments anonymously; prior to publishing a message received for posting from an anonymous user, filter the message and, responsive to the filtering, automatically obfuscate sensitive data associated with a particular application development environment included in the message; receive security findings generated as users of the application development environments use the cloud-based static analysis security tool; process the received security findings into a knowledgebase; and provide social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. | 8. Apparatus, comprising: a processor; computer memory holding computer program instructions executed by one or more processors to reduce security vulnerability in association with a cloud-based static analysis security tool that is accessible by a set of application development environments, the computer program instructions operative to: associate a social networking platform with the application development environments, the social networking platform being accessible by users of the application development environments anonymously; prior to publishing a message received for posting from an anonymous user, filter the message and, responsive to the filtering, automatically obfuscate sensitive data associated with a particular application development environment included in the message; receive security findings generated as users of the application development environments use the cloud-based static analysis security tool; process the received security findings into a knowledgebase; and provide social network content associated with the processed security findings from the knowledgebase as crowdsourced security knowledge generated from use of the cloud-based static analysis security tool by users of the application development environments. 13. The apparatus as described in claim 8 wherein the social network content includes information identifying a third party that is available to provide assistance to a user to facilitate a remediation identified by the static security analysis tool. | 0.634503 |
9,287,893 | 3 | 4 | 3. The integrated circuit of claim 2 , wherein the end values are split into two equal sized fields. | 3. The integrated circuit of claim 2 , wherein the end values are split into two equal sized fields. 4. The integrated circuit of claim 3 , wherein the plurality of stages in the end value pipeline include adders that perform cumulative additions based on results of earlier stage adders, wherein adders are split across two or more of the stages. | 0.5 |
8,706,548 | 1 | 3 | 1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change. | 1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change. 3. The system of claim 1 wherein the first and second volumes of search traffic comprise traffic arising from unpaid search listings. | 0.798485 |
7,478,121 | 1 | 7 | 1. A system for receiving page-specific user feedback concerning a particular web page of a website, comprising: a first icon viewable on the particular web page, the first icon soliciting one or more page-specific subjective ratings concerning the particular web page as a whole from a user that has accessed the particular web page; a second icon viewable on the particular web page, the second icon soliciting one or more page-specific open-ended comments concerning the particular web page from the user; and software associated with the first and second icons and operable to receive one or more page-specific subjective ratings concerning the particular web page as a whole and one or more page-specific open-ended comments concerning the particular web page from the user for reporting to a website owner, the software operable to require the user to provide one or more page-specific subjective ratings concerning the particular web page as a whole in order to provide one or more page-specific open-ended comments concerning the particular web page, association of the one or more required page-specific subjective ratings concerning the particular web page as a whole with the one or more page-specific open-ended comments concerning the particular web page making the one or more page-specific open-ended comments concerning the particular web page more meaningful to and useable by the website owner. | 1. A system for receiving page-specific user feedback concerning a particular web page of a website, comprising: a first icon viewable on the particular web page, the first icon soliciting one or more page-specific subjective ratings concerning the particular web page as a whole from a user that has accessed the particular web page; a second icon viewable on the particular web page, the second icon soliciting one or more page-specific open-ended comments concerning the particular web page from the user; and software associated with the first and second icons and operable to receive one or more page-specific subjective ratings concerning the particular web page as a whole and one or more page-specific open-ended comments concerning the particular web page from the user for reporting to a website owner, the software operable to require the user to provide one or more page-specific subjective ratings concerning the particular web page as a whole in order to provide one or more page-specific open-ended comments concerning the particular web page, association of the one or more required page-specific subjective ratings concerning the particular web page as a whole with the one or more page-specific open-ended comments concerning the particular web page making the one or more page-specific open-ended comments concerning the particular web page more meaningful to and useable by the website owner. 7. The system of claim 1 , wherein the software associated with the first and second icons is incorporated into a web browser of the user. | 0.88707 |
8,140,557 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein determining that the abstract rule is semantically incompatible with the second data abstraction model comprises analyzing metadata describing the abstract rule to identify one or more values corresponding to a semantic concept of the abstract rule, and wherein translating the semantic attributes of the abstract rule comprises accessing the predefined ontology mapping, using the one or more identified values, to identify a semantic equivalent to the semantic concept of the abstract rule. | 2. The computer-implemented method of claim 1 , wherein determining that the abstract rule is semantically incompatible with the second data abstraction model comprises analyzing metadata describing the abstract rule to identify one or more values corresponding to a semantic concept of the abstract rule, and wherein translating the semantic attributes of the abstract rule comprises accessing the predefined ontology mapping, using the one or more identified values, to identify a semantic equivalent to the semantic concept of the abstract rule. 3. The computer-implemented method of claim 2 , wherein determining that the abstract rule is semantically incompatible with the second data abstraction model further comprises comparing the one or more identified values to metadata describing the semantic concept of the second data abstraction model. | 0.5 |
8,015,415 | 1 | 2 | 1. A computer program product, tangibly embodied in an information carrier, comprising instructions operable to cause a computer to: receive a document containing a template definition, the template definition including data bind nodes and identifying at least one of multiple data bind node classes; receive one or more modifications to the template definition, wherein the modification is a major modification at least if it edits or adds any data bind node having the identified data bind node class, and wherein the modification is a minor modification if it does not edit or add any data bind node having the identified data bind node class; identify one or more of the data bind nodes within the template definition having the identified data bind node class; find, for each identified data bind node, any corresponding predetermined hash previously calculated based on content of the corresponding identified data bind node; calculate a separate hash for each identified data bind node; compare the calculated separate hash for each identified data bind node with the corresponding predetermined hash; and flag the document as having the major modification at least if either the calculated separate hash for a data bind node does not match up with the corresponding predetermined hash or if no corresponding predetermined hash exists for one or more of the data bind nodes, wherein the minor modification does not cause the document to be flagged, wherein each data bind node comprises a link between at least one field in the document and an external data source. | 1. A computer program product, tangibly embodied in an information carrier, comprising instructions operable to cause a computer to: receive a document containing a template definition, the template definition including data bind nodes and identifying at least one of multiple data bind node classes; receive one or more modifications to the template definition, wherein the modification is a major modification at least if it edits or adds any data bind node having the identified data bind node class, and wherein the modification is a minor modification if it does not edit or add any data bind node having the identified data bind node class; identify one or more of the data bind nodes within the template definition having the identified data bind node class; find, for each identified data bind node, any corresponding predetermined hash previously calculated based on content of the corresponding identified data bind node; calculate a separate hash for each identified data bind node; compare the calculated separate hash for each identified data bind node with the corresponding predetermined hash; and flag the document as having the major modification at least if either the calculated separate hash for a data bind node does not match up with the corresponding predetermined hash or if no corresponding predetermined hash exists for one or more of the data bind nodes, wherein the minor modification does not cause the document to be flagged, wherein each data bind node comprises a link between at least one field in the document and an external data source. 2. The computer program product of claim 1 , further comprising instructions operable to cause a computer to: execute the template definition contained in the document, whether or not the document has been flagged. | 0.5 |
8,244,651 | 19 | 24 | 19. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a plurality of training examples; training a plurality of different types of predictive models using the received training examples, wherein each of the predictive models implements a different machine learning technique; measuring the performance of each trained model; computing a suggestion score for each training example according to each respective trained model, wherein the suggestion score is based on one or more factors that indicate whether additional examples similar to the training example would improve the performance of the model, including weighting each suggestion score by the measured performance of the respective trained model; combining the computed suggestion scores for each training example to compute an overall suggestion score for each training example; and ranking the training examples by overall suggestion scores. | 19. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: receiving a plurality of training examples; training a plurality of different types of predictive models using the received training examples, wherein each of the predictive models implements a different machine learning technique; measuring the performance of each trained model; computing a suggestion score for each training example according to each respective trained model, wherein the suggestion score is based on one or more factors that indicate whether additional examples similar to the training example would improve the performance of the model, including weighting each suggestion score by the measured performance of the respective trained model; combining the computed suggestion scores for each training example to compute an overall suggestion score for each training example; and ranking the training examples by overall suggestion scores. 24. The storage device of claim 19 , wherein one of the one or more factors is a sparseness score, wherein the sparseness score for a particular training example is based on a count of a category of the particular training example. | 0.686141 |
9,892,204 | 1 | 4 | 1. A computer program product for operating a computer using shortcuts, the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions comprising: program instructions to receive user preferences including information detailing a first shortcut input, wherein the first shortcut input is a single action utilized by a user; program instructions to map the first shortcut input to one or more documents based on the received user preferences; program instructions to detect that the first shortcut input has been utilized; and program instructions to display the one or more documents. | 1. A computer program product for operating a computer using shortcuts, the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions comprising: program instructions to receive user preferences including information detailing a first shortcut input, wherein the first shortcut input is a single action utilized by a user; program instructions to map the first shortcut input to one or more documents based on the received user preferences; program instructions to detect that the first shortcut input has been utilized; and program instructions to display the one or more documents. 4. The computer program product of claim 1 , wherein the program instructions creates the group based on similarities between the multiple documents. | 0.677489 |
9,330,195 | 11 | 19 | 11. A non-transitory computer readable storage medium storing instructions executable by a data processing apparatus and that upon such execution causes the data processing apparatus to perform operations comprising: accessing command input logs storing data defining user device sessions; identifying, from the command input logs, user device sessions that each respectively store: a sequence of two or more command inputs, each command input specifying one or more parameter values, and each command input having a respective ordinal position in the sequence, and wherein the sequence includes at least one pair of a first command input that precedes a second command input in ordinal position in the sequence; first operation data indicating a first operation performed on data from a first resource property in response to the first command input; second operation data indicating a second operation performed on data from a second resource property in response to the second command input; identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of a first operation failure and a second operation success; and determining, from the identified pairs of first and second command inputs, command inputs for which a parsing rule that is associated with the second operation is to be generated. | 11. A non-transitory computer readable storage medium storing instructions executable by a data processing apparatus and that upon such execution causes the data processing apparatus to perform operations comprising: accessing command input logs storing data defining user device sessions; identifying, from the command input logs, user device sessions that each respectively store: a sequence of two or more command inputs, each command input specifying one or more parameter values, and each command input having a respective ordinal position in the sequence, and wherein the sequence includes at least one pair of a first command input that precedes a second command input in ordinal position in the sequence; first operation data indicating a first operation performed on data from a first resource property in response to the first command input; second operation data indicating a second operation performed on data from a second resource property in response to the second command input; identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of a first operation failure and a second operation success; and determining, from the identified pairs of first and second command inputs, command inputs for which a parsing rule that is associated with the second operation is to be generated. 19. The non-transitory computer readable storage medium of claim 11 , wherein the first resource property is a search engine property for searching a plurality of corpora and the second resource property is a resource property that is different from the search engine property and for one particular corpus. | 0.807161 |
9,875,018 | 20 | 23 | 20. A text-input interface displaying method, applied to an electronic device having an input device and a display device, wherein the display device has a display region, the display region has a predetermined display area, the text-input interface displaying method comprises: displaying a text input interface on the display region, wherein the text input interface has a first display region and a second display region, the first display region and the second display region each comprising a plurality of display blocks, wherein each of the display blocks is arranged to display a character, wherein the first display region and the second display region are provided for users to do a text editing by the input device, and the text input interface has an interface area; and displaying a first set of characters in the display blocks of the second display region; determining whether the input device receives a number of input signals corresponding to selection of characters of the first set of characters exceeding a predetermined value; when the number of input signals corresponding to selection of characters of the first set of characters exceeds the predetermined value in the text editing, displaying a second set of characters in the display blocks of the first display region, wherein the second set of characters leaves at least one display block empty; and making the at least one empty display block transparent and making the at least one empty display block accumulate at the end of the first display region, thereby dynamically adjusting the interface area of the text input interface to change the ratio of the interface area and the predetermined display area of the display region according to the input signals of the characters that have been selected and an input rule table, wherein the input rule table comprises a variety of combinations of characters that are used for constructing words. | 20. A text-input interface displaying method, applied to an electronic device having an input device and a display device, wherein the display device has a display region, the display region has a predetermined display area, the text-input interface displaying method comprises: displaying a text input interface on the display region, wherein the text input interface has a first display region and a second display region, the first display region and the second display region each comprising a plurality of display blocks, wherein each of the display blocks is arranged to display a character, wherein the first display region and the second display region are provided for users to do a text editing by the input device, and the text input interface has an interface area; and displaying a first set of characters in the display blocks of the second display region; determining whether the input device receives a number of input signals corresponding to selection of characters of the first set of characters exceeding a predetermined value; when the number of input signals corresponding to selection of characters of the first set of characters exceeds the predetermined value in the text editing, displaying a second set of characters in the display blocks of the first display region, wherein the second set of characters leaves at least one display block empty; and making the at least one empty display block transparent and making the at least one empty display block accumulate at the end of the first display region, thereby dynamically adjusting the interface area of the text input interface to change the ratio of the interface area and the predetermined display area of the display region according to the input signals of the characters that have been selected and an input rule table, wherein the input rule table comprises a variety of combinations of characters that are used for constructing words. 23. The electronic device as claimed in claim 20 , wherein by default the processing unit enables the first display region to display a space key and a case switching key, and when the number of input signals corresponding to selection of characters of the first set of characters exceeds the predetermined value in the text editing, the processing unit enables the first display region to display the space key, the case switching key and the second set of characters according to the English input rule table and enables the second display region to keep displaying the first set of the English letters. | 0.5 |
7,930,295 | 2 | 6 | 2. The method of claim 1 , wherein said citation information comprises the number of times a publication was cited. | 2. The method of claim 1 , wherein said citation information comprises the number of times a publication was cited. 6. The method of claim 2 , wherein said citation information further comprises a publication title. | 0.509901 |
9,449,282 | 1 | 2 | 1. A method for ranking unlabeled matches, each of the unlabeled matches existing between a first member of a dating website and a corresponding one of a first set of members of the dating website, the method comprising: transmitting, by a first mobile device via a web server, messages and profile views directed toward one of a second set of members of the dating website, the first mobile device being associated with the first member of the dating website; transmitting, by each of a plurality of mobile devices via the web server, messages and profile views directed toward the first member of the dating website, each of the plurality of mobile devices being associated with a corresponding one of the second set of members of the dating website; receiving, by the web server, a plurality of labeled matches, wherein each of the plurality of labeled matches exists between the first member of the dating website and the corresponding one of the second set of members of the dating website, and wherein each of the plurality of labeled matches are labeled based on a dating profile of the first member of the dating website, a dating profile of the corresponding one of the second set of members of the dating website, and behavioral features, the behavioral features comprising: a first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website, the first density of profile views being measured within a time period between a first message and a last message exchanged between the first member of the dating website and the corresponding one of the second set of members of the dating website, a second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website, the second density of profile views being measured within the time period, a message disparity that identifies a difference between a number of messages sent by the first member of the dating website and a number of messages sent by the corresponding one of the second set of members of the dating website, a number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website, a number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and whether the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another; determining, by the web server, a probability of relevance of each of the plurality of labeled matches based on the behavioral features, wherein: the probability of relevance increases as a first difference decreases and the probability of relevance decreases as the first difference increases, the first difference being between the first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website within the time period and the second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website within the time period, the probability of relevance increases as the message disparity decreases and the probability of relevance decreases as the message disparity increases, the probability of relevance increases as a second difference decreases and the probability of relevance decreases as the second difference increases, the second difference being between the number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website and the number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another are assigned a higher probability of relevance than other ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website do not exchange phone numbers with one another; for each of the plurality of labeled matches: comparing, by a processor in the web server on an attribute-by-attribute basis, first binary data in each attribute of the dating profile of the first member of the dating website to second binary data in a corresponding attribute of the dating profile of the corresponding one of the second set of members of the dating website to produce ranking features of each of the plurality of labeled matches, and correlating, by the processor in the web server, the ranking features of each of the plurality of labeled matches to the probability of relevance of each of the plurality of labeled matches to produce a ranking function; training, by the web server, boosted regression trees based on the probability of relevance of each of the plurality of labeled matches, the behavioral features, the ranking features of each of the plurality of labeled matches, the ranking function, the dating profile of the first member of the dating website, and the dating profile of the corresponding one of the second set of members of the dating website, wherein, upon completion of the training, the boosted regression trees are configured to utilize, as input, ranking features observed from a given unlabeled match and generate, as output, a probability of relevance of the given unlabeled match; determining, by the processor in the web server utilizing the boosted regression trees, a probability of relevance of each of the unlabeled matches by: comparing, on an attribute-by-attribute basis, the first binary data in each attribute of the dating profile of the first member of the dating website to third binary data in a corresponding attribute of a dating profile of the corresponding one of the first set of members of the dating website to produce ranking features of each of the unlabeled matches, wherein each of the unlabeled matches lack the behavioral features, and calculating the probability of relevance each of the unlabeled matches by inputting, into the ranking function, the ranking features of each of the unlabeled matches and retrieving, from the ranking function, the probability of relevance each of the unlabeled matches, wherein the ranking features of each of the unlabeled matches are used as a proxy for the behavioral features; calculating, by the web server, a rank for each of the unlabeled matches based on the probability of relevance of each of the unlabeled matches to generate a set of ranked matches; and transmitting, by the web server over a network interface, at least a portion of the set of ranked matches to the first mobile device associated with the first member of the dating website. | 1. A method for ranking unlabeled matches, each of the unlabeled matches existing between a first member of a dating website and a corresponding one of a first set of members of the dating website, the method comprising: transmitting, by a first mobile device via a web server, messages and profile views directed toward one of a second set of members of the dating website, the first mobile device being associated with the first member of the dating website; transmitting, by each of a plurality of mobile devices via the web server, messages and profile views directed toward the first member of the dating website, each of the plurality of mobile devices being associated with a corresponding one of the second set of members of the dating website; receiving, by the web server, a plurality of labeled matches, wherein each of the plurality of labeled matches exists between the first member of the dating website and the corresponding one of the second set of members of the dating website, and wherein each of the plurality of labeled matches are labeled based on a dating profile of the first member of the dating website, a dating profile of the corresponding one of the second set of members of the dating website, and behavioral features, the behavioral features comprising: a first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website, the first density of profile views being measured within a time period between a first message and a last message exchanged between the first member of the dating website and the corresponding one of the second set of members of the dating website, a second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website, the second density of profile views being measured within the time period, a message disparity that identifies a difference between a number of messages sent by the first member of the dating website and a number of messages sent by the corresponding one of the second set of members of the dating website, a number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website, a number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and whether the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another; determining, by the web server, a probability of relevance of each of the plurality of labeled matches based on the behavioral features, wherein: the probability of relevance increases as a first difference decreases and the probability of relevance decreases as the first difference increases, the first difference being between the first density of profile views initiated by the first member of the dating website toward the corresponding one of the second set of members of the dating website within the time period and the second density of profile views initiated by the corresponding one of the second set of members of the dating website toward the first member of the dating website within the time period, the probability of relevance increases as the message disparity decreases and the probability of relevance decreases as the message disparity increases, the probability of relevance increases as a second difference decreases and the probability of relevance decreases as the second difference increases, the second difference being between the number of times that the first member of the dating website viewed the dating profile of the corresponding one of the second set of members of the dating website and the number of times that the corresponding one of the second set of members of the dating website viewed the dating profile of the first member of the dating website, and ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website exchange phone numbers with one another are assigned a higher probability of relevance than other ones of the plurality of labeled matches where the first member of the dating website and the corresponding one of the second set of members of the dating website do not exchange phone numbers with one another; for each of the plurality of labeled matches: comparing, by a processor in the web server on an attribute-by-attribute basis, first binary data in each attribute of the dating profile of the first member of the dating website to second binary data in a corresponding attribute of the dating profile of the corresponding one of the second set of members of the dating website to produce ranking features of each of the plurality of labeled matches, and correlating, by the processor in the web server, the ranking features of each of the plurality of labeled matches to the probability of relevance of each of the plurality of labeled matches to produce a ranking function; training, by the web server, boosted regression trees based on the probability of relevance of each of the plurality of labeled matches, the behavioral features, the ranking features of each of the plurality of labeled matches, the ranking function, the dating profile of the first member of the dating website, and the dating profile of the corresponding one of the second set of members of the dating website, wherein, upon completion of the training, the boosted regression trees are configured to utilize, as input, ranking features observed from a given unlabeled match and generate, as output, a probability of relevance of the given unlabeled match; determining, by the processor in the web server utilizing the boosted regression trees, a probability of relevance of each of the unlabeled matches by: comparing, on an attribute-by-attribute basis, the first binary data in each attribute of the dating profile of the first member of the dating website to third binary data in a corresponding attribute of a dating profile of the corresponding one of the first set of members of the dating website to produce ranking features of each of the unlabeled matches, wherein each of the unlabeled matches lack the behavioral features, and calculating the probability of relevance each of the unlabeled matches by inputting, into the ranking function, the ranking features of each of the unlabeled matches and retrieving, from the ranking function, the probability of relevance each of the unlabeled matches, wherein the ranking features of each of the unlabeled matches are used as a proxy for the behavioral features; calculating, by the web server, a rank for each of the unlabeled matches based on the probability of relevance of each of the unlabeled matches to generate a set of ranked matches; and transmitting, by the web server over a network interface, at least a portion of the set of ranked matches to the first mobile device associated with the first member of the dating website. 2. The method as recited in claim 1 , wherein the ranking features of each of the plurality of labeled matches further comprise at least one selected from a group consisting of: a query of the first member of the dating website and a query of the corresponding one of the second set of members of the dating website; and wherein the ranking features of each of the unlabeled matches further comprise at least one selected from a group consisting of: the query of the first member of the dating website and a query of the corresponding one of the first set of members of the dating website. | 0.619509 |
7,580,921 | 1 | 9 | 1. A computer implemented method for identifying phrases in a document collection, the method comprising: collecting possible phrases from documents in the document collection; classifying individual possible phrases as either a good phrase or a bad phrase according to a frequency of occurrence of the individual possible phrase; determining, for a pair of good phrases g j and g k in the document collection, an information gain of g k with respect to g j as a function of an actual co-occurrence rate of g j and g k and an expected co-occurrence rate of g j and g k in the document collection; selectively retaining as valid phrases those good phrases that, predict the occurrence of at least one other good phrase in the document collection, where a good phrase g j predicts the occurrence of another good phrase g k in the document collection when the determined information gain of g k in the presence of g j exceeds a first predetermined threshold; identifying, for a plurality of selectively retained valid phrases g x , a phrase g y as a related phrase of g x where the information gain of g y in the presence of g x exceeds a second predetermined threshold that is more restrictive than the first predetermined threshold; and storing the valid phrases and identified related phrases on a computer-readable storage medium. | 1. A computer implemented method for identifying phrases in a document collection, the method comprising: collecting possible phrases from documents in the document collection; classifying individual possible phrases as either a good phrase or a bad phrase according to a frequency of occurrence of the individual possible phrase; determining, for a pair of good phrases g j and g k in the document collection, an information gain of g k with respect to g j as a function of an actual co-occurrence rate of g j and g k and an expected co-occurrence rate of g j and g k in the document collection; selectively retaining as valid phrases those good phrases that, predict the occurrence of at least one other good phrase in the document collection, where a good phrase g j predicts the occurrence of another good phrase g k in the document collection when the determined information gain of g k in the presence of g j exceeds a first predetermined threshold; identifying, for a plurality of selectively retained valid phrases g x , a phrase g y as a related phrase of g x where the information gain of g y in the presence of g x exceeds a second predetermined threshold that is more restrictive than the first predetermined threshold; and storing the valid phrases and identified related phrases on a computer-readable storage medium. 9. The method of claim 1 , wherein the information gain of g j with respect to g k is:
I ( j,k )= A ( j,k )/ E ( j,k ) where A(j,k) is an actual co-occurrence rate of g j and g k ; and E(j,k) is an expected co-occurrence rate g j and g k . | 0.731027 |
10,019,142 | 10 | 19 | 10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the device to: generate a user interface for display on a display device, wherein the user interface includes a selection-indicator indicating a currently selected user interface element of a plurality of user interface elements; while the user interface is displayed on the display device, receive an indication of a first swipe input that includes a contact and movement of the contact detected on a touch-sensitive surface of the electronic device or a separate input device in communication with the electronic device, wherein the movement of the contact corresponds to a respective value for a movement metric; and in response to receiving the indication of the first swipe input: determine whether the first swipe input meets unitary-movement criteria; in accordance with a determination that the first swipe input meets the unitary-movement criteria, move the selection-indicator from the currently selected user interface element by a predefined amount to a second user interface element of the plurality of user interface elements in the user interface; and in accordance with a determination that the first swipe input does not meet the unitary-movement criteria, move the selection-indicator from the currently selected user interface element to a third user interface element of the plurality of user interface elements in accordance with the respective value of the movement metric associated with the first swipe input. | 10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the device to: generate a user interface for display on a display device, wherein the user interface includes a selection-indicator indicating a currently selected user interface element of a plurality of user interface elements; while the user interface is displayed on the display device, receive an indication of a first swipe input that includes a contact and movement of the contact detected on a touch-sensitive surface of the electronic device or a separate input device in communication with the electronic device, wherein the movement of the contact corresponds to a respective value for a movement metric; and in response to receiving the indication of the first swipe input: determine whether the first swipe input meets unitary-movement criteria; in accordance with a determination that the first swipe input meets the unitary-movement criteria, move the selection-indicator from the currently selected user interface element by a predefined amount to a second user interface element of the plurality of user interface elements in the user interface; and in accordance with a determination that the first swipe input does not meet the unitary-movement criteria, move the selection-indicator from the currently selected user interface element to a third user interface element of the plurality of user interface elements in accordance with the respective value of the movement metric associated with the first swipe input. 19. The non-transitory computer readable storage medium of claim 10 , wherein the unitary-movement criteria include a criterion that is met when: liftoff of the contact is detected within a first time period of touchdown of the contact, and the movement of the contact is greater than a first movement threshold but less than a second movement threshold. | 0.524194 |
7,792,846 | 18 | 22 | 18. A machine-accessible medium that provides instructions that, if executed by a processor, will cause the processor to perform operations comprising: selecting a plurality of N-grams from a second plurality of N-grams, wherein the second plurality of N-grams are associated with a range of values of N and the plurality of N-grams are associated with a sub-range of the range of values of N, wherein each of the second plurality of N-grams comprises a sequence of N bytes, where N is an integer; generating a statistical content classification model based on occurrences of the plurality of N-grams, if any, in a set of training documents and a set of validation documents; providing the statistical content classification model to content filters to classify content into one or more of a plurality of categories; determining a utility for each of the second plurality of N-grams using a frequency of occurrence of a respective N-gram in a subset of training documents of the set of training documents that have been classified in a respective category and a frequency of occurrence of the respective N-gram in remaining training documents of the set of training documents; and selecting the sub-range of values of N based on utilities of the second plurality of N-grams. | 18. A machine-accessible medium that provides instructions that, if executed by a processor, will cause the processor to perform operations comprising: selecting a plurality of N-grams from a second plurality of N-grams, wherein the second plurality of N-grams are associated with a range of values of N and the plurality of N-grams are associated with a sub-range of the range of values of N, wherein each of the second plurality of N-grams comprises a sequence of N bytes, where N is an integer; generating a statistical content classification model based on occurrences of the plurality of N-grams, if any, in a set of training documents and a set of validation documents; providing the statistical content classification model to content filters to classify content into one or more of a plurality of categories; determining a utility for each of the second plurality of N-grams using a frequency of occurrence of a respective N-gram in a subset of training documents of the set of training documents that have been classified in a respective category and a frequency of occurrence of the respective N-gram in remaining training documents of the set of training documents; and selecting the sub-range of values of N based on utilities of the second plurality of N-grams. 22. The machine-accessible medium of claim 18 , wherein the set of training documents includes one or more electronic mail messages. | 0.614035 |
8,014,039 | 1 | 10 | 1. A document management system, comprising: a scanning unit for reading a document and generating image data; an image data storing unit for storing a scanned image file; and a document management server that includes a destination folder for storing the scanned image file, and a file name conversion table; wherein the scanning unit acquires a document identifier assigned to the document using the image data generated by the scanning unit, assigns a file name to the image data based on the document identifier, stores the document in the image data storing unit as the scanned image file, and the document management server acquires the scanned image file stored in the image data storing unit, specifies a destination folder based on the document identifier contained in the file name of the scanned image file using the file name conversion table, and stores the scanned image file in the destination folder. | 1. A document management system, comprising: a scanning unit for reading a document and generating image data; an image data storing unit for storing a scanned image file; and a document management server that includes a destination folder for storing the scanned image file, and a file name conversion table; wherein the scanning unit acquires a document identifier assigned to the document using the image data generated by the scanning unit, assigns a file name to the image data based on the document identifier, stores the document in the image data storing unit as the scanned image file, and the document management server acquires the scanned image file stored in the image data storing unit, specifies a destination folder based on the document identifier contained in the file name of the scanned image file using the file name conversion table, and stores the scanned image file in the destination folder. 10. The document management system according to claim 1 , wherein the scanning unit is configured to acquire the document identifier assigned to the document by being further configured to compare the image data generated by the scanning unit with image patterns stored in a template database, to select a portion of the document based on which particular template is found to match the document in the comparison, and to perform a character recognition process on the selected portion of the document. | 0.5 |
8,024,334 | 1 | 10 | 1. A method, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising the steps of: a) associating with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) assessing at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) associatively indexing, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance. | 1. A method, relating to creating and maintaining, in at least one database available to a population of users, on a database server computer, information about a plurality of database of subjects, comprising the steps of: a) associating with each database subject of such plurality of database subjects at least one plurality of natural-language tags potentially descriptive of such each database subject according to an involved subset of such population of database users; said at least one plurality of natural language tags comprising other user chosen and/or other user provided natural language terms potentially descriptive of a subject or subjects of said database; b) assessing at least one measure of descriptive relevance of each of such at least one plurality of natural-language tags to such each database subject according to each particular database user of such involved subset of such population of database users; c) associatively indexing, in such at least one database, such respective particular database users, such respective natural-language tags, such respective measures of relevance, and such respective database subjects; and d) accumulating and storing such respective measures of relevance. 10. The method according to claim 1 , wherein said other users comprise other member users. | 0.892941 |
8,533,218 | 1 | 2 | 1. A debugger component of a data processing system for a multidimensional database structure on a computer architecture that facilitates interactive development, analysis, understanding and debugging of Multi-Dimensional expression (MDX) query processing operations on a multidimensional database comprising: a primary central or distributed processing component, wherein said primary central component comprises a CPU; a data storage component, wherein the data storage component is a Multidimensional OnLine Analytical Processing Server (MOLAP), comprising one or more physical computer-readable media units operatively coupled to the primary central processing component, and which physically stores both the multidimensional database and a plurality of computer executable instructions; wherein the computer executable instructions operate on the primary central or distributed processing component to achieve the following system debugging system components: an input component, comprising a visual terminal, for multidimensional database queries to be entered by an end user; an analysis component, analyzing the multidimensional database queries entered by the end user which operates to break down a parent query into constituent parts and then associates each constituent part with contextual information pertaining to it, wherein said constituent parts comprise query segments and said contextual information comprises the value or content assigned in computing said query segment; a linking component which links each constituent part of the parent query and its associated information with the parent query as well as with the end-result of that parent query operating on the multidimensional database; and a display component which converts the information about each constituent part, its associated information, linked parent query and linked end-result into various intermediate display-formatted results for an end-user, then displays these display-formatted results to that end-user, wherein said intermediate display-formatted results do not comprise raw data. | 1. A debugger component of a data processing system for a multidimensional database structure on a computer architecture that facilitates interactive development, analysis, understanding and debugging of Multi-Dimensional expression (MDX) query processing operations on a multidimensional database comprising: a primary central or distributed processing component, wherein said primary central component comprises a CPU; a data storage component, wherein the data storage component is a Multidimensional OnLine Analytical Processing Server (MOLAP), comprising one or more physical computer-readable media units operatively coupled to the primary central processing component, and which physically stores both the multidimensional database and a plurality of computer executable instructions; wherein the computer executable instructions operate on the primary central or distributed processing component to achieve the following system debugging system components: an input component, comprising a visual terminal, for multidimensional database queries to be entered by an end user; an analysis component, analyzing the multidimensional database queries entered by the end user which operates to break down a parent query into constituent parts and then associates each constituent part with contextual information pertaining to it, wherein said constituent parts comprise query segments and said contextual information comprises the value or content assigned in computing said query segment; a linking component which links each constituent part of the parent query and its associated information with the parent query as well as with the end-result of that parent query operating on the multidimensional database; and a display component which converts the information about each constituent part, its associated information, linked parent query and linked end-result into various intermediate display-formatted results for an end-user, then displays these display-formatted results to that end-user, wherein said intermediate display-formatted results do not comprise raw data. 2. The debugger component of the data processing system of claim 1 , wherein the query is in a language that follows the XMLA standard. | 0.669118 |
8,412,531 | 1 | 2 | 1. A method for providing input functionality for a speech recognition interaction module, comprising: receiving an indication of a touch anywhere on a touch screen interface of a mobile computing device; upon reception of the indication of the touch anywhere on the touch screen interface, activating a listening mechanism of a speech recognition module; and displaying dynamic visual feedback of a measured sound level of a spoken utterance received by the speech recognition module, wherein the displayed dynamic visual feedback is rendered as centered around an area on the touch screen at which the touch is received. | 1. A method for providing input functionality for a speech recognition interaction module, comprising: receiving an indication of a touch anywhere on a touch screen interface of a mobile computing device; upon reception of the indication of the touch anywhere on the touch screen interface, activating a listening mechanism of a speech recognition module; and displaying dynamic visual feedback of a measured sound level of a spoken utterance received by the speech recognition module, wherein the displayed dynamic visual feedback is rendered as centered around an area on the touch screen at which the touch is received. 2. The method of claim 1 , further comprising generating an acknowledgment in response to receiving the indication of the touch anywhere on the touch screen interface of the mobile computing device. | 0.63197 |
10,158,859 | 6 | 7 | 6. The data compression apparatus of claim 1 comprising a manipulator configured to alter the numerical values of the encoding to produce a manipulated encoding. | 6. The data compression apparatus of claim 1 comprising a manipulator configured to alter the numerical values of the encoding to produce a manipulated encoding. 7. The data compression apparatus of claim 6 comprising a decoder configured to decode the manipulated encoding to compute a new data item. | 0.855809 |
8,370,144 | 6 | 8 | 6. A method according to claim 4 , further comprising segmenting the audio stream into the plurality of windows. | 6. A method according to claim 4 , further comprising segmenting the audio stream into the plurality of windows. 8. A method according to claim 6 , wherein the windows are overlapping and the step of segmenting comprises segmenting the audio stream into the overlapping windows. | 0.753731 |
8,539,359 | 56 | 64 | 56. A machine system structured to automatically present as first presentations to a first user thereof, immediately acceptable invitations to join in on system-identified telecommunications-mediated information exchange forums based on automatically repeated determinations by the machine system of recent focused-attention activities of the first user on specific subsections of content made available to the first user by way of a user-accessible content presentation device, wherein the automatically repeated determinations regarding recent focused-attention activities are carried out transparently by the machine system without need for diverted focusing of attention by the user directed to aiding the repeated determinations automatically carried out by the machine system, and wherein: the first presentations are automatically presented in an invitations clustering area of a display viewable by the first user; and the first presentations, which are automatically presented in the invitations clustering area, can include immediately acceptable invitations to two or more different and system-identified kinds of telecommunications-mediated information exchange forums, the different kinds of information exchange forums each being one that has at least one other user co-invited to it or already participating in the forum and the presented different kinds of information exchange forums including two or more of: an open-to-the-public chat room; a private chat room; a restricted access blog; a peer-to-peer forum; a forum that sends emails to a predetermined one or more listed recipients; a twitter exchange; a live video conference; a live video web conference; a live voice only conference; a multi-cast-provided cross-exchange of relatively current informational content; a network-provided cross-exchange of relatively current informational content; a broadcast-provided cross-exchange of relatively current informational content; a chat room which is spawned by the machine system; a moderated online exchange service, or different forums which are respectively directed to different topics; different forums which are respectively logically linked with different ones of respective content elsewhere presented to the first user; pre-existing forums to which the first user was invited at different times; different forums whose respective participants are geographically clustered in respective different geographic areas; different forums which restrict their participant population to different ones of predetermined number of minimum and/or maximum simultaneous participants; different forums which restrict all or a pre-specified portion of their respective participant population to participants to different and respective variations of the participants having at least one of: specified credentials in a specific topic; specified minimum or maximum levels of education; specified proficiencies in specific topic areas; a specified mix of demographic attributes within the forum such as the forum's participants defining a specified mix of credentials in a specific topic, a specified mix of participant ages, participant genders, participant socioeconomic classes, participant political party affiliations; a validated set of one or more demographic attributes such as age, gender, socioeconomic class, education level, place of residence; a specified level of sophistication in a specific topic area; and a specified leaning in favor of, against, or undecided with respect to a specified proposition; wherein at least a portion of the machine system includes a data processing machine; and wherein said automatically determined and recent focused-attention activities of the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user. | 56. A machine system structured to automatically present as first presentations to a first user thereof, immediately acceptable invitations to join in on system-identified telecommunications-mediated information exchange forums based on automatically repeated determinations by the machine system of recent focused-attention activities of the first user on specific subsections of content made available to the first user by way of a user-accessible content presentation device, wherein the automatically repeated determinations regarding recent focused-attention activities are carried out transparently by the machine system without need for diverted focusing of attention by the user directed to aiding the repeated determinations automatically carried out by the machine system, and wherein: the first presentations are automatically presented in an invitations clustering area of a display viewable by the first user; and the first presentations, which are automatically presented in the invitations clustering area, can include immediately acceptable invitations to two or more different and system-identified kinds of telecommunications-mediated information exchange forums, the different kinds of information exchange forums each being one that has at least one other user co-invited to it or already participating in the forum and the presented different kinds of information exchange forums including two or more of: an open-to-the-public chat room; a private chat room; a restricted access blog; a peer-to-peer forum; a forum that sends emails to a predetermined one or more listed recipients; a twitter exchange; a live video conference; a live video web conference; a live voice only conference; a multi-cast-provided cross-exchange of relatively current informational content; a network-provided cross-exchange of relatively current informational content; a broadcast-provided cross-exchange of relatively current informational content; a chat room which is spawned by the machine system; a moderated online exchange service, or different forums which are respectively directed to different topics; different forums which are respectively logically linked with different ones of respective content elsewhere presented to the first user; pre-existing forums to which the first user was invited at different times; different forums whose respective participants are geographically clustered in respective different geographic areas; different forums which restrict their participant population to different ones of predetermined number of minimum and/or maximum simultaneous participants; different forums which restrict all or a pre-specified portion of their respective participant population to participants to different and respective variations of the participants having at least one of: specified credentials in a specific topic; specified minimum or maximum levels of education; specified proficiencies in specific topic areas; a specified mix of demographic attributes within the forum such as the forum's participants defining a specified mix of credentials in a specific topic, a specified mix of participant ages, participant genders, participant socioeconomic classes, participant political party affiliations; a validated set of one or more demographic attributes such as age, gender, socioeconomic class, education level, place of residence; a specified level of sophistication in a specific topic area; and a specified leaning in favor of, against, or undecided with respect to a specified proposition; wherein at least a portion of the machine system includes a data processing machine; and wherein said automatically determined and recent focused-attention activities of the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user. 64. The machine system of claim 56 wherein said presentation of two or more different and system-identified kinds of telecommunications-mediated information exchange forums includes an indication of at least one difference in kind as between the presented different kinds of forums. | 0.867357 |
9,507,825 | 14 | 22 | 14. One or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving a query statement comprising a filter predicate on a column of a first database table; and pruning a particular table partition of a second database table from access paths for processing the query statement based on determining, based on aggregated zone map information associated with the particular table partition, that the query statement cannot be satisfied by data stored in the particular table partition, the aggregated zone map information comprising an aggregated minimum value for the column and an aggregated maximum value for the column, the aggregated minimum value being a smallest minimum value for the column among a plurality of minimum values for the column, the aggregated maximum value being a greatest maximum value for the column among a plurality of maximum values for the column, the plurality of minimum values for the column and the plurality of maximum values for the column associated with the column by a zone map on the second database table, the plurality of minimum values for the column and the plurality of maximum values for the column associated with a plurality of zones by the zone map, the plurality of zones comprising the data stored in the particular table partition. | 14. One or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving a query statement comprising a filter predicate on a column of a first database table; and pruning a particular table partition of a second database table from access paths for processing the query statement based on determining, based on aggregated zone map information associated with the particular table partition, that the query statement cannot be satisfied by data stored in the particular table partition, the aggregated zone map information comprising an aggregated minimum value for the column and an aggregated maximum value for the column, the aggregated minimum value being a smallest minimum value for the column among a plurality of minimum values for the column, the aggregated maximum value being a greatest maximum value for the column among a plurality of maximum values for the column, the plurality of minimum values for the column and the plurality of maximum values for the column associated with the column by a zone map on the second database table, the plurality of minimum values for the column and the plurality of maximum values for the column associated with a plurality of zones by the zone map, the plurality of zones comprising the data stored in the particular table partition. 22. The one or more non-transitory computer-readable media of claim 14 , wherein the first database table is a dimension table of a star schema and the second database table is a fact table of the star schema. | 0.858593 |
7,644,052 | 24 | 25 | 24. The computer program product of claim 16 , wherein the calculating comprises calculating information gain for an attribute A in relation to documents S and categories C by which the documents S are grouped, and the calculating the information gain comprises handling separately a subset of the documents S, for which the attribute A is absent, to improve performance with respect to populating sub-concepts in the second ontology. | 24. The computer program product of claim 16 , wherein the calculating comprises calculating information gain for an attribute A in relation to documents S and categories C by which the documents S are grouped, and the calculating the information gain comprises handling separately a subset of the documents S, for which the attribute A is absent, to improve performance with respect to populating sub-concepts in the second ontology. 25. The computer program product of claim 24 , wherein the handling separately comprises using a fraction of entropy associated with the document subset for which the attribute A is absent. | 0.8125 |
9,600,227 | 1 | 7 | 1. A computer-implemented method comprising: obtaining (i) a view hierarchy that is of a user interface and that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of a particular viewable element in the user interface, and (ii) a transcription of a speech input that was spoken while the user interface was displayed; determining that the transcription of the speech input matches text that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken; and in response to determining that the transcription of the speech input matches text that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken, initiating an action that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken. | 1. A computer-implemented method comprising: obtaining (i) a view hierarchy that is of a user interface and that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of a particular viewable element in the user interface, and (ii) a transcription of a speech input that was spoken while the user interface was displayed; determining that the transcription of the speech input matches text that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken; and in response to determining that the transcription of the speech input matches text that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken, initiating an action that is associated with the particular viewable element (i) that is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken. 7. The method of claim 1 , comprising: determining that the that the transcription of the speech input matches text that is associated with another viewable element that (i) is included in the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface and (ii) that was displayed when the speech input was spoken; determining, based on the view hierarchy that includes textual representations, location data, and properties of text-based and non-text-based viewable elements in the user interface and of the particular viewable element in the user interface, that the particular viewable element has an equal priority to the other viewable element; providing data indicating that the transcription of the speech input matches text that is associated with the particular viewable element and the other viewable element; obtaining an additional transcription of an additional speech input; and determining that the additional transcription of the additional speech input matches the text that is associated with the particular viewable element, wherein the action is initiated based on determining that the additional transcription of the additional speech input matches the text that is associated with the particular viewable element. | 0.5 |
9,477,652 | 13 | 15 | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. | 13. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for creating a dialect-specific training data set, the operations comprising: selecting an initial training data set as a current training data set, wherein the initial training data set is selected by: receiving one or more initial content items; establishing dialect parameters for two or more of the initial content items, wherein the dialect parameters identify a first of the two or more of the initial content items as being composed in a first dialect and identify a second of the two or more of the initial content items as being composed in a second dialect; and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters; generating, based on the initial training data set and corresponding one or more dialect groups, a dialect classifier configured to detect language dialects of content items to be classified as being in one of two or more dialects, the two or more dialects including at least the first dialect and the second dialect; augmenting the current training data set with additional training data by applying the dialect classifier to candidate content items, wherein at least one of the candidate content items that is in the augmented current training data set was not included in the initial training data set; and updating the dialect classifier based on the augmented current training data set; and returning the updated dialect classifier, wherein the updated dialect classifier is configured to identify additional content items that are not in the initial training data and are not in the augmented current training data set as being in one of the two or more dialects. 15. The computer-readable storage medium of claim 13 , wherein establishing the dialect parameters comprises: identifying content items authored by one or more users identified as correlated to the dialect. | 0.536036 |
8,977,538 | 1 | 13 | 1. A method for constructing a word graph, the method comprising: obtaining a subject text; dividing the subject text into one or more units; dividing the units into one or more sub-units; and recording each of the one or more sub-units, wherein recording each of the one or more sub-units includes: determining whether each sub-unit has been previously encountered; storing the sub-unit as a node if the sub-unit has not been previously encountered; proceeding with an existing node if the sub-unit has been previously encountered; preserving a relationship of each of the one or more units to one another; and preserving a relationship of each of the one or more sub-units to one another; storing a repeat factor, wherein the repeat factor indicates a number of instances in which one or more repeated sub-units have been encountered since some prior point in each of the one or more units; incrementing the repeat factor each time a repeated sub-unit is encountered since some prior point in each of the one or more units; and preserving and analyzing the relationship of each of the one or more sub-units to one another to perform a function as directed by a user, wherein the function includes comparing the constructed word graph to a user input; and outputting a result of the function to the user. | 1. A method for constructing a word graph, the method comprising: obtaining a subject text; dividing the subject text into one or more units; dividing the units into one or more sub-units; and recording each of the one or more sub-units, wherein recording each of the one or more sub-units includes: determining whether each sub-unit has been previously encountered; storing the sub-unit as a node if the sub-unit has not been previously encountered; proceeding with an existing node if the sub-unit has been previously encountered; preserving a relationship of each of the one or more units to one another; and preserving a relationship of each of the one or more sub-units to one another; storing a repeat factor, wherein the repeat factor indicates a number of instances in which one or more repeated sub-units have been encountered since some prior point in each of the one or more units; incrementing the repeat factor each time a repeated sub-unit is encountered since some prior point in each of the one or more units; and preserving and analyzing the relationship of each of the one or more sub-units to one another to perform a function as directed by a user, wherein the function includes comparing the constructed word graph to a user input; and outputting a result of the function to the user. 13. The method of claim 1 , wherein at least one of the one or more sub-units is one of: a chapter; a section; a paragraph; a sentence; a phrase; a line; a class of word; a phrase type; a part of speech; a morpheme; a syllable; a punctuation mark; a number; a character; or a symbol. | 0.720356 |
9,396,272 | 1 | 14 | 1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, a text query comprising one or more character strings, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more nodes and one or more edges of the social graph by determining one or more nodes and one or more edges of the social graph that match at least a portion of one or more of the character strings, wherein each of the identified nodes is within a threshold degree of separation within the social graph of a node corresponding to the first user; generating one or more recommended queries that each comprise the character strings of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the recommended queries for presentation to the first user. | 1. A method comprising, by one or more computing devices: receiving, from a client device associated with a first user of an online social network, a text query comprising one or more character strings, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; identifying one or more nodes and one or more edges of the social graph by determining one or more nodes and one or more edges of the social graph that match at least a portion of one or more of the character strings, wherein each of the identified nodes is within a threshold degree of separation within the social graph of a node corresponding to the first user; generating one or more recommended queries that each comprise the character strings of the text query and references to one or more of the identified nodes and one or more of the identified edges; and sending, to the client device associated with the first user in response to receiving the text query, one or more of the recommended queries for presentation to the first user. 14. The method of claim 1 , wherein the text query is received from a third-party system via a call through an application programming interface associated with the online social network from the client device associated with the first user. | 0.788225 |
8,479,094 | 1 | 6 | 1. A computer implemented method of assisting a user in preparing a written document, comprising: receiving a user selected citation format for a document; determining a user writing style specific to said document via analysis of input entered by said user into said document wherein said user writing style determination is based on formatting applied to said document by said user based on grammatical person of textual input of said input entered in said document by said user; receiving one or more terms entered by said user into said document; submitting search data indicative of said terms to a plurality of reference sources via one or more application programming interface; receiving search results from said reference sources, said search results based on said search data and responsive to said submitting search data indicative of said terms; identifying a subset of said search results; providing aspects of each of said search results identified in said subset to said user for display along with said document; wherein which of said search results are identified in said subset is based on said user writing style specific to said document; and wherein each of said search results provided in said subset is provided in combination with an indication of from which of said reference sources said search result originates; receiving a user selection to add a selected one of said search results of said subset to said document; and inserting, in response to said user selection, text indicative of said selected one of said search results into said document, said text including a citation of said selected one of said search results in said user selected citation format. | 1. A computer implemented method of assisting a user in preparing a written document, comprising: receiving a user selected citation format for a document; determining a user writing style specific to said document via analysis of input entered by said user into said document wherein said user writing style determination is based on formatting applied to said document by said user based on grammatical person of textual input of said input entered in said document by said user; receiving one or more terms entered by said user into said document; submitting search data indicative of said terms to a plurality of reference sources via one or more application programming interface; receiving search results from said reference sources, said search results based on said search data and responsive to said submitting search data indicative of said terms; identifying a subset of said search results; providing aspects of each of said search results identified in said subset to said user for display along with said document; wherein which of said search results are identified in said subset is based on said user writing style specific to said document; and wherein each of said search results provided in said subset is provided in combination with an indication of from which of said reference sources said search result originates; receiving a user selection to add a selected one of said search results of said subset to said document; and inserting, in response to said user selection, text indicative of said selected one of said search results into said document, said text including a citation of said selected one of said search results in said user selected citation format. 6. The method of claim 1 , wherein said user writing style determination is based on grammatical person of textual input of said input entered in said document by said user. | 0.691071 |
9,262,522 | 1 | 2 | 1. A music messaging software-as-a-service platform, comprising: a computer hardware infrastructure accessible at a network domain and comprising: first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; and second program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. | 1. A music messaging software-as-a-service platform, comprising: a computer hardware infrastructure accessible at a network domain and comprising: first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; and second program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. 2. The music messaging software-as-a-service platform as described in claim 1 wherein vocal intervals are determined in the audio recording by detecting and then sharpening vocal and non-vocal edges. | 0.602 |
4,189,852 | 1 | 5 | 1. In a method of teaching reading in which a student looks at or scans the words in a book or the like containing written or printed words while said words at least in the main are simultaneously being audibly reproduced from previously recorded audible recording means and heard by said student while he looks at or scans said words, the improvement which comprises providing the student with a book or the like having written or printed words, providing said student with means for writing words or statements, providing in the aforesaid recorded material on said audible recording means a plurality of predetermined spaced audible signals each at the end of each of a plurality of the predetermined audible reproductions of words in said book or the like, said audible signals being followed by audible or written instructions to said student to perform writing acts in relation to the audibly reproduced words on said audible recording means, said student, in following said instructions, writing on said means for writing words or statements a word or words or a statement or statements responsive to the aforesaid instructions previously given to said student within given predetermined time periods, after each of said plurality of instructions has been given to said student, whereby a writing is produced by said student which readily permits of being graded to enable the nature of the progress of the student in learning to read to be ascertained and evaluated by the teacher and the student. | 1. In a method of teaching reading in which a student looks at or scans the words in a book or the like containing written or printed words while said words at least in the main are simultaneously being audibly reproduced from previously recorded audible recording means and heard by said student while he looks at or scans said words, the improvement which comprises providing the student with a book or the like having written or printed words, providing said student with means for writing words or statements, providing in the aforesaid recorded material on said audible recording means a plurality of predetermined spaced audible signals each at the end of each of a plurality of the predetermined audible reproductions of words in said book or the like, said audible signals being followed by audible or written instructions to said student to perform writing acts in relation to the audibly reproduced words on said audible recording means, said student, in following said instructions, writing on said means for writing words or statements a word or words or a statement or statements responsive to the aforesaid instructions previously given to said student within given predetermined time periods, after each of said plurality of instructions has been given to said student, whereby a writing is produced by said student which readily permits of being graded to enable the nature of the progress of the student in learning to read to be ascertained and evaluated by the teacher and the student. 5. The method of claim 1, wherein said instructions given to the student are audible instructions on said tape. | 0.84188 |
7,761,700 | 1 | 5 | 1. A system comprising means for: a memory; a processor coupled to the memory to perform acts comprising: while booting a computer and prior to allowing a user to logon to the computer, spawning a process, separate from a user logon process, arranging for a markup language rendering engine to be loaded at the beginning of an operating system initialization procedure; providing markup language code suitable for use with the markup language rendering engine, the markup language being capable of soliciting at least one user input when rendered by the markup language rendering engine, the user input being associated with the user logon process configured to selectively allow the user to logon to the computer; and providing a control permitting the markup language rendering engine to communicate with the user logon process, wherein the markup language rendering engine makes calls to the control which passes the calls to the user logon process. | 1. A system comprising means for: a memory; a processor coupled to the memory to perform acts comprising: while booting a computer and prior to allowing a user to logon to the computer, spawning a process, separate from a user logon process, arranging for a markup language rendering engine to be loaded at the beginning of an operating system initialization procedure; providing markup language code suitable for use with the markup language rendering engine, the markup language being capable of soliciting at least one user input when rendered by the markup language rendering engine, the user input being associated with the user logon process configured to selectively allow the user to logon to the computer; and providing a control permitting the markup language rendering engine to communicate with the user logon process, wherein the markup language rendering engine makes calls to the control which passes the calls to the user logon process. 5. The system of claim 1 , further comprising means for configuring the markup language code to provide the user input to an authorization entity for validation determination. | 0.756267 |
8,341,595 | 2 | 3 | 2. The method of claim 1 wherein said RIA process flow comprises at least an input UI state, a processing UI state, at least an output UI state and an error UI state. | 2. The method of claim 1 wherein said RIA process flow comprises at least an input UI state, a processing UI state, at least an output UI state and an error UI state. 3. The method of claim 2 wherein said graphical components comprise one of label for displaying content, textbox for entering content, or a selector for initiating processing via said web service calls. | 0.5 |
9,405,809 | 8 | 9 | 8. A method comprising: storing, by use of a processor, visited document data comprising one or more of a visited document address and a visited document description for each document visited, wherein each visited document address is an Internet protocol (IP) address and comprises a domain name; and displaying one or more of a first visited document address and a first visited document description with a search result in response to an initial portion of the visited document address matching an initial portion of a search result address, wherein the initial portion of the visited document address matched the initial portion of the search result address if an initial domain name of the visited document address matches an initial domain name of the search result address. | 8. A method comprising: storing, by use of a processor, visited document data comprising one or more of a visited document address and a visited document description for each document visited, wherein each visited document address is an Internet protocol (IP) address and comprises a domain name; and displaying one or more of a first visited document address and a first visited document description with a search result in response to an initial portion of the visited document address matching an initial portion of a search result address, wherein the initial portion of the visited document address matched the initial portion of the search result address if an initial domain name of the visited document address matches an initial domain name of the search result address. 9. The method of claim 8 , wherein the visited document data further comprises visited document activity data and a plurality of one or more of first visited document addresses and first visited document descriptions are displayed prioritized based on the visited document activity data for each of the first visited document addresses. | 0.5 |
8,781,227 | 1 | 4 | 1. A system, comprising: a processor configured to: extract a subimage from a received image comprising information pertaining to a plurality of numerical characters, wherein the extracted subimage is associated with one of the plurality of numerical characters; perform recognition based at least in part on a set of topological information associated with the subimage, including: process the subimage to obtain the set of topological information associated with the subimage, wherein the processing of the subimage includes: obtain the set of topological information by extracting one or more vertices and one or more edges associated with the subimage; and determine whether a closed ring associated with at least a portion of the one or more vertices and at least a portion of the one or more edges exists, wherein the determining whether the closed ring exists comprises: proceed from a first filled in pixel to a second filled in pixel, the second filled in pixel being adjacent to the first filled in pixel; proceed from the second filled in pixel to a third filled in pixel repeatedly until the first filled in pixel is reached, the third filled in pixel being adjacent to the second filled in pixel; and in the event that the first filled in pixel is reached: associate a point within the closed ring as representing the closed ring; and add a location of the point representing the closed ring to the set of topological information; compare the set of topological information associated with the subimage with a preset set of stored topological information; determine that in the event that the set of topological information associated with the subimage matches the preset set of stored topological information, the subimage is associated with a recognized numerical character associated with the preset set of stored topological information; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system, comprising: a processor configured to: extract a subimage from a received image comprising information pertaining to a plurality of numerical characters, wherein the extracted subimage is associated with one of the plurality of numerical characters; perform recognition based at least in part on a set of topological information associated with the subimage, including: process the subimage to obtain the set of topological information associated with the subimage, wherein the processing of the subimage includes: obtain the set of topological information by extracting one or more vertices and one or more edges associated with the subimage; and determine whether a closed ring associated with at least a portion of the one or more vertices and at least a portion of the one or more edges exists, wherein the determining whether the closed ring exists comprises: proceed from a first filled in pixel to a second filled in pixel, the second filled in pixel being adjacent to the first filled in pixel; proceed from the second filled in pixel to a third filled in pixel repeatedly until the first filled in pixel is reached, the third filled in pixel being adjacent to the second filled in pixel; and in the event that the first filled in pixel is reached: associate a point within the closed ring as representing the closed ring; and add a location of the point representing the closed ring to the set of topological information; compare the set of topological information associated with the subimage with a preset set of stored topological information; determine that in the event that the set of topological information associated with the subimage matches the preset set of stored topological information, the subimage is associated with a recognized numerical character associated with the preset set of stored topological information; and a memory coupled to the processor and configured to provide the processor with instructions. 4. The system of claim 1 , wherein the preset set of stored topological information is stored in a database. | 0.574803 |
8,082,497 | 1 | 6 | 1. A graphic user interface, stored on a computer memory, for authoring an electronic document viewed on a display device, comprising a user interface for authoring alternate versions of the same portion of document content, comprising an edit view pane for displaying a linear version of document content for a document adaptable to being created in a given display space that varies based on the size and resolution of different display devices and transmission bandwidth constraints, and an alternate version view pane for displaying multiple alternate versions of the document content for the linear version of document content displayed in the edit view pane, wherein one of the multiple versions of alternate content can be selected to create the document so that it will fit within the given display space that varies based on the size and resolution of different display devices and complies with transmission bandwidth constraints, wherein hovering with an input device cursor over a region of document content configurable into alternate document content further comprises bringing up a menu with editing choices, comprising the following user options: select version, which when activated highlights selected content in said alternate version view pane along with other unhighlighted versions of document content; pop selection, which when activated displays the highest level of alternate version content if nested versions of alternate content exist; create version, which when activated to creates a version of alternate content; and freeze version, which when activated to prevent a version of alternate content from being changed. | 1. A graphic user interface, stored on a computer memory, for authoring an electronic document viewed on a display device, comprising a user interface for authoring alternate versions of the same portion of document content, comprising an edit view pane for displaying a linear version of document content for a document adaptable to being created in a given display space that varies based on the size and resolution of different display devices and transmission bandwidth constraints, and an alternate version view pane for displaying multiple alternate versions of the document content for the linear version of document content displayed in the edit view pane, wherein one of the multiple versions of alternate content can be selected to create the document so that it will fit within the given display space that varies based on the size and resolution of different display devices and complies with transmission bandwidth constraints, wherein hovering with an input device cursor over a region of document content configurable into alternate document content further comprises bringing up a menu with editing choices, comprising the following user options: select version, which when activated highlights selected content in said alternate version view pane along with other unhighlighted versions of document content; pop selection, which when activated displays the highest level of alternate version content if nested versions of alternate content exist; create version, which when activated to creates a version of alternate content; and freeze version, which when activated to prevent a version of alternate content from being changed. 6. The graphic user interface of claim 1 wherein a user can change a first version of alternate content that is displayed in the edit view pane by selecting a second version of alternate content displayed in alternate version view pane, said second version of alternate content then replacing said first version in the edit view pane. | 0.5 |
8,065,343 | 6 | 8 | 6. A computer system for categorizing information items in a data storage and retrieval system, wherein each of said information items is associated with at least one property, said system including a computer readable memory having program code stored thereon, said program code comprising: program code for generating a tree structure providing an index, wherein said tree structure indexes a currently defined set of categories based on lists of properties required for membership in corresponding ones of said categories, wherein said tree structure includes a plurality of nodes, each node being associated with an individual property and a list of categories, and wherein each category in said list of categories for each node is a category that requires the property associated with the node as well as the properties associated with all ancestor nodes of the node in the up direction for membership in that category; program code for traversing said tree structure to select a subset of said defined set of categories for which an input item is a candidate member, wherein said traversing is limited to subtrees of said tree structure having nodes associated with properties that are associated with said input information item, wherein subtrees of said tree structure having nodes not associated with properties associated with said input information item are not traversed; and program code for categorizing said information item based on said selected subset of categories, wherein said categorizing includes applying a predicate associated with each category in said selected subset of categories to said properties associated with said input item to determine whether conditions for membership in each category in said selected subset of categories are met, wherein predicates associated with categories not within said selected subset of categories are not applied. | 6. A computer system for categorizing information items in a data storage and retrieval system, wherein each of said information items is associated with at least one property, said system including a computer readable memory having program code stored thereon, said program code comprising: program code for generating a tree structure providing an index, wherein said tree structure indexes a currently defined set of categories based on lists of properties required for membership in corresponding ones of said categories, wherein said tree structure includes a plurality of nodes, each node being associated with an individual property and a list of categories, and wherein each category in said list of categories for each node is a category that requires the property associated with the node as well as the properties associated with all ancestor nodes of the node in the up direction for membership in that category; program code for traversing said tree structure to select a subset of said defined set of categories for which an input item is a candidate member, wherein said traversing is limited to subtrees of said tree structure having nodes associated with properties that are associated with said input information item, wherein subtrees of said tree structure having nodes not associated with properties associated with said input information item are not traversed; and program code for categorizing said information item based on said selected subset of categories, wherein said categorizing includes applying a predicate associated with each category in said selected subset of categories to said properties associated with said input item to determine whether conditions for membership in each category in said selected subset of categories are met, wherein predicates associated with categories not within said selected subset of categories are not applied. 8. The system of claim 6 , wherein said program code for selecting is responsive to receipt of said information item. | 0.900679 |
7,689,587 | 1 | 8 | 1. A method of generating a repository template of a repository of data for a storage area network management tool, the repository defined to hold data describing storage area network elements and configurations, the method comprising: updating a configuration file to include current configuration data for a first repository, wherein the configuration file includes specifications for a set of schemas defining at least one repository structure; using configuration data from the configuration file to access the first repository currently stored on a host; removing any schemas and data currently stored by the first repository; creating a set of new schemas for the first repository according to the specifications from the configuration file; copying seed data to the host, wherein the seed data defines initial repository information; initializing the set of new schemas with the seed data; upon initializing the set of new schemas, generating a repository template from the set of new schemas and the seed data, the repository template defined for creating one or more repositories to hold storage area network data; creating a second repository from the repository template, wherein the second repository includes the seed data and the set of new schemas; establishing a test environment based on the repository template; wherein establishing the test environment includes: (i) exporting each schema in the set of new schemas into the test environment; (ii) replacing the seed data in each exported schema with data from at least one live storage area network (SAN); (iii) upon determining that each exported new schema properly handles data from the live SAN, indicating, in the test environment, that the second repository is acceptable; loading a prior version of the repository onto the host; comparing the schemas of the prior version of the repository with the schemas of the second repository to determine any differences; and creating at least one script that, when executed on a repository based on the prior version of the repository, will upgrade schemas according to the set of new schemas in the second repository; via the test environment, receiving a correction of at least one schema in the set of new schemas, wherein receiving the correction includes: upon determining that at least one exported schema does not properly handle the data from the live SAN: resolving at least one incompatibility between at least one portion of data from the live SAN and an exported new schema. | 1. A method of generating a repository template of a repository of data for a storage area network management tool, the repository defined to hold data describing storage area network elements and configurations, the method comprising: updating a configuration file to include current configuration data for a first repository, wherein the configuration file includes specifications for a set of schemas defining at least one repository structure; using configuration data from the configuration file to access the first repository currently stored on a host; removing any schemas and data currently stored by the first repository; creating a set of new schemas for the first repository according to the specifications from the configuration file; copying seed data to the host, wherein the seed data defines initial repository information; initializing the set of new schemas with the seed data; upon initializing the set of new schemas, generating a repository template from the set of new schemas and the seed data, the repository template defined for creating one or more repositories to hold storage area network data; creating a second repository from the repository template, wherein the second repository includes the seed data and the set of new schemas; establishing a test environment based on the repository template; wherein establishing the test environment includes: (i) exporting each schema in the set of new schemas into the test environment; (ii) replacing the seed data in each exported schema with data from at least one live storage area network (SAN); (iii) upon determining that each exported new schema properly handles data from the live SAN, indicating, in the test environment, that the second repository is acceptable; loading a prior version of the repository onto the host; comparing the schemas of the prior version of the repository with the schemas of the second repository to determine any differences; and creating at least one script that, when executed on a repository based on the prior version of the repository, will upgrade schemas according to the set of new schemas in the second repository; via the test environment, receiving a correction of at least one schema in the set of new schemas, wherein receiving the correction includes: upon determining that at least one exported schema does not properly handle the data from the live SAN: resolving at least one incompatibility between at least one portion of data from the live SAN and an exported new schema. 8. The method as in claim 1 , wherein updating the configuration file to include current configuration data for the repository includes: creating the specifications for the configuration file, the specifications for at least one first new schema, wherein the first new schema is designed to hold data that has not been previously collected for storage in the first repository. | 0.671329 |
9,002,958 | 2 | 13 | 2. The method of claim 1 further including providing a user option to assign multiple designations to the selected text, wherein the multiple designations include a designation as feedback. | 2. The method of claim 1 further including providing a user option to assign multiple designations to the selected text, wherein the multiple designations include a designation as feedback. 13. The method of claim 2 wherein the multiple designations include a designation identifying the email message as associated with a particular information category. | 0.631696 |
9,990,641 | 9 | 15 | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. 15. The advertising server network of claim 9 , wherein the selecting includes at least one of, a threshold feature, a top n feature, a CTR ratio feature, a top n gain feature, an in-category feature. | 0.661017 |
7,865,538 | 19 | 25 | 19. A computer system comprising: inputs providing the computer system with documents from diverse applications in respective formats unique to the respective applications; a processing system causing the computer system to automatically, without user interaction and without requiring a user to designate directory structures or other pre-imposed document categorizations structures, store the provided documents as a time-ordered main stream of documents associated with respective automatically generated time indicators; said time-ordered main stream being unbounded to thereby accommodate documents associated with time indicators related to past, present and future times; said time-ordered main stream requiring no fixed beginning or end and being maintained and being selectively retrievable and searchable by the computer system; said computer system maintaining the main stream live and responsive to subsequent events by automatically incorporating therein new documents as provided to the computer system while maintaining the thus expanded main stream time-ordered; a source providing selected search criteria; said processing system causing said computer system to search said time-ordered main stream according to said search criteria and use search results to create a time- ordered substream of documents from the main time-ordered stream; said processing system further causing said computer system to maintain said substream live and responsive to subsequent events by automatically incorporating therein new document provided to the computer system that meet the search criteria while maintaining the thus expanded substream time-ordered; said computer system: displaying at least selected portion of the live main stream or substream on computer display means as a display reflecting the time-ordered nature thereof; automatically showing on the display means a display of a glance view of a displayed document in response to touching with a cursor a screen area associated with the document; said glance view being an abbreviated version of the document and indicative of content thereof; and said showing of the glance view occurring essentially instantaneously in response to said touching with the cursor of the screen area associated with the document. | 19. A computer system comprising: inputs providing the computer system with documents from diverse applications in respective formats unique to the respective applications; a processing system causing the computer system to automatically, without user interaction and without requiring a user to designate directory structures or other pre-imposed document categorizations structures, store the provided documents as a time-ordered main stream of documents associated with respective automatically generated time indicators; said time-ordered main stream being unbounded to thereby accommodate documents associated with time indicators related to past, present and future times; said time-ordered main stream requiring no fixed beginning or end and being maintained and being selectively retrievable and searchable by the computer system; said computer system maintaining the main stream live and responsive to subsequent events by automatically incorporating therein new documents as provided to the computer system while maintaining the thus expanded main stream time-ordered; a source providing selected search criteria; said processing system causing said computer system to search said time-ordered main stream according to said search criteria and use search results to create a time- ordered substream of documents from the main time-ordered stream; said processing system further causing said computer system to maintain said substream live and responsive to subsequent events by automatically incorporating therein new document provided to the computer system that meet the search criteria while maintaining the thus expanded substream time-ordered; said computer system: displaying at least selected portion of the live main stream or substream on computer display means as a display reflecting the time-ordered nature thereof; automatically showing on the display means a display of a glance view of a displayed document in response to touching with a cursor a screen area associated with the document; said glance view being an abbreviated version of the document and indicative of content thereof; and said showing of the glance view occurring essentially instantaneously in response to said touching with the cursor of the screen area associated with the document. 25. A computer system as in claim 19 in which said processing system utilizes subsystems from another operating system. | 0.78442 |
7,983,478 | 14 | 17 | 14. A method for adapting trained Hidden Markov Models for generation of handwritten characters, implemented at least in part by a computing device, the method comprising: providing initial, trained Hidden Markov Models for generation of handwritten characters; providing training ink data to adapt the initial, trained Hidden Markov Models; applying an adaptation technique to adapt the initial, trained Hidden Markov Models to the training ink data, the adaptation technique including a technique selected from a group of maximum a posterior techniques, maximum likelihood linear regression techniques and Eigen-space techniques; and rendering the generated handwritten characters using a pen model, the pen model including a plurality of pen parameters. | 14. A method for adapting trained Hidden Markov Models for generation of handwritten characters, implemented at least in part by a computing device, the method comprising: providing initial, trained Hidden Markov Models for generation of handwritten characters; providing training ink data to adapt the initial, trained Hidden Markov Models; applying an adaptation technique to adapt the initial, trained Hidden Markov Models to the training ink data, the adaptation technique including a technique selected from a group of maximum a posterior techniques, maximum likelihood linear regression techniques and Eigen-space techniques; and rendering the generated handwritten characters using a pen model, the pen model including a plurality of pen parameters. 17. The method of claim 14 , wherein the initial, trained Hidden Markov Models comprise Hidden Markov Models trained using calligraphy data. | 0.663462 |
8,589,783 | 1 | 9 | 1. A processor implemented method for generating color information for at least one object in a spreadsheet document described in a markup language, the method comprising: parsing the spreadsheet document to generate at least one display list associated with the at least one object by: obtaining distinct color values from a plurality of spreadsheet color table objects, wherein color values in the plurality of spreadsheet color table objects are referenced by the at least one object in the spreadsheet by using a plurality of indexes of the color table objects; storing the distinct color values in a color palette table object, wherein color values in the color palette table object are accessed using a plurality of color palette indexes; and generating a mapping between each index in each of the plurality of color table objects and one of the plurality of color palette indexes that points to a same color value; and rasterizing the at least one object in a frame buffer by processing the display list using the mapping generated during parsing. | 1. A processor implemented method for generating color information for at least one object in a spreadsheet document described in a markup language, the method comprising: parsing the spreadsheet document to generate at least one display list associated with the at least one object by: obtaining distinct color values from a plurality of spreadsheet color table objects, wherein color values in the plurality of spreadsheet color table objects are referenced by the at least one object in the spreadsheet by using a plurality of indexes of the color table objects; storing the distinct color values in a color palette table object, wherein color values in the color palette table object are accessed using a plurality of color palette indexes; and generating a mapping between each index in each of the plurality of color table objects and one of the plurality of color palette indexes that points to a same color value; and rasterizing the at least one object in a frame buffer by processing the display list using the mapping generated during parsing. 9. The processor implemented method of claim 1 , wherein the plurality of color table objects comprise at least one of an indexed color table. object, a theme color object, and a color table object. | 0.789809 |
5,452,380 | 11 | 13 | 11. A system for imaging a text, comprising: means for designating text data including at least row area information for designating an area of each row of the text, said row area information including at least a row area width, character sequence information of words of the row and character size information for formatting, and imaging condition data including at least character size information for imaging; means for calculating a row area width, a character sequence width and a total blank width for imaging of a specified text, based on the designated row area information including at least row area width, character sequence information, character size information for formatting and character size information for imaging; means for calculating a word interval by substantially evenly dividing the total blank width using the number of intervals of the character sequences as a divisor, and positioning a starting word at a left edge of the row area and positioning other words with said word interval therebetween to determine a character sequence position for imaging; and means for outputting the text in accordance with the determined character sequence position for imaging. | 11. A system for imaging a text, comprising: means for designating text data including at least row area information for designating an area of each row of the text, said row area information including at least a row area width, character sequence information of words of the row and character size information for formatting, and imaging condition data including at least character size information for imaging; means for calculating a row area width, a character sequence width and a total blank width for imaging of a specified text, based on the designated row area information including at least row area width, character sequence information, character size information for formatting and character size information for imaging; means for calculating a word interval by substantially evenly dividing the total blank width using the number of intervals of the character sequences as a divisor, and positioning a starting word at a left edge of the row area and positioning other words with said word interval therebetween to determine a character sequence position for imaging; and means for outputting the text in accordance with the determined character sequence position for imaging. 13. A system for imaging a text according to claim 11, wherein the text data includes paragraph starting row information and paragraph ending row information, and said calculating means reserves a blank on the left of the starting word in the paragraph starting row and causes the word interval in the paragraph ending row to be close to an average word interval of the paragraph. | 0.5 |
7,984,287 | 9 | 11 | 9. A method for resource configuration in a multi-modal distributed computing system having at least one resource capable of being configured, the method comprising the steps of: obtaining information associated with a context of use of a mobile device within the system; obtaining one or more preferences of a user for applications and functions to be launched based on a location of the mobile device; obtaining information associated with the system; and providing the most appropriate mode of interaction for a user of the mobile device within the system. | 9. A method for resource configuration in a multi-modal distributed computing system having at least one resource capable of being configured, the method comprising the steps of: obtaining information associated with a context of use of a mobile device within the system; obtaining one or more preferences of a user for applications and functions to be launched based on a location of the mobile device; obtaining information associated with the system; and providing the most appropriate mode of interaction for a user of the mobile device within the system. 11. The method according to claim 9 , wherein the at least one resource to be configured is an information resource. | 0.809211 |
9,594,824 | 11 | 13 | 11. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause: receiving, by a processor, a query identifying a source entity, the source entity being of a first entity-type; generating, by the processor, a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; computing, by the processor, feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type; computing, by the processor, an aggregated score for each candidate entity by combining all of the feature values for each candidate entity; generating, by the processor, a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and identifying, by the processor, entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph. | 11. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause: receiving, by a processor, a query identifying a source entity, the source entity being of a first entity-type; generating, by the processor, a plurality of candidate entities from an analysis of an entity-relationship graph in response to the query based on the source entity; computing, by the processor, feature values for each candidate entity of the plurality of candidate entities by passing the source entity and the plurality of candidate entities to a type-specific entity recommender particular to the first entity-type; computing, by the processor, an aggregated score for each candidate entity by combining all of the feature values for each candidate entity; generating, by the processor, a plurality of ranked candidate entities by ranking each candidate entity in accordance with the computed aggregate score corresponding to that candidate entity to represent complex interactions between the plurality of candidate entities and leverage the complex interactions in the ranking; and identifying, by the processor, entity and relationship events that alter the entity-relationship graph by monitoring the entity-relationship graph. 13. The computer program product of claim 11 , wherein each entity recommender of the plurality of entity recommenders corresponds to one of a plurality of entity types. | 0.769126 |
8,713,462 | 15 | 21 | 15. A computer-program product, tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to: receive a plurality of concurrent requests to generate previews of a plurality of files, wherein the previews include pre-determined content or dynamically generated content, and wherein the plurality of files each have an associated file type; determine an order of the plurality of concurrent requests to generate the previews; determine the associated file types for the plurality of files; determine that an associated file type for a first file in the plurality of files is associated with pre-determined content; generate a preview of the first file, wherein the preview of the first file includes the predetermined content; determine that an associated file type for a second file in the plurality of files is not associated with pre-determined content; match the file type for the second file with a plug-in, wherein the plug-in is capable of processing content in the second file; use the plug-in for the second file to process the content in the second file and to dynamically generate content for a preview of the second file, wherein dynamically generating the content includes translating the second file, using the plug-in, from a native format to a format different than the native format, wherein the generated preview of the second file includes the dynamically generated content, and wherein the previews of the first and second files are generated in accordance with the determined order of the plurality of concurrent requests; and display the previews of the first and second files in an overlapping manner in a preview view area. | 15. A computer-program product, tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to: receive a plurality of concurrent requests to generate previews of a plurality of files, wherein the previews include pre-determined content or dynamically generated content, and wherein the plurality of files each have an associated file type; determine an order of the plurality of concurrent requests to generate the previews; determine the associated file types for the plurality of files; determine that an associated file type for a first file in the plurality of files is associated with pre-determined content; generate a preview of the first file, wherein the preview of the first file includes the predetermined content; determine that an associated file type for a second file in the plurality of files is not associated with pre-determined content; match the file type for the second file with a plug-in, wherein the plug-in is capable of processing content in the second file; use the plug-in for the second file to process the content in the second file and to dynamically generate content for a preview of the second file, wherein dynamically generating the content includes translating the second file, using the plug-in, from a native format to a format different than the native format, wherein the generated preview of the second file includes the dynamically generated content, and wherein the previews of the first and second files are generated in accordance with the determined order of the plurality of concurrent requests; and display the previews of the first and second files in an overlapping manner in a preview view area. 21. The computer-program product of claim 15 , further comprising instructions configured to cause a data processing apparatus to: display previews of the plurality of files, wherein the previews include a main preview, wherein the main preview is currently interactive, and wherein other previews are displayable to the left or the right of the main preview. | 0.547859 |
8,788,498 | 7 | 8 | 7. The method of claim 1 further comprising: maintaining the plurality of sets of answers to the set of objective questions as previous answers; receiving a modification to the set of objective questions; and reusing at least some of the previous answers for each sample to re-label the data sample based upon the modification to the set of objective questions. | 7. The method of claim 1 further comprising: maintaining the plurality of sets of answers to the set of objective questions as previous answers; receiving a modification to the set of objective questions; and reusing at least some of the previous answers for each sample to re-label the data sample based upon the modification to the set of objective questions. 8. The method of claim 7 wherein receiving the modification to the set of objective questions comprises at least one of adding at least one question, changing at least one question, or deleting at least one question. | 0.5 |
8,855,413 | 13 | 14 | 13. One or more non-transitory computer readable media encoded with instructions for performing a method, the method comprising: identifying a region in an image containing text (a text region); identifying an element boundary for each pair of elements in the text region, the text region including one or more elements including one or more words that are arranged in an arced line; electronically displaying elements from the image by way of a device by wrapping successive elements onto one or more successive lines at a respective element boundary to accommodate the device; and rotating a first word in the arced line relative to a second word in the arced line to electronically display the first word and the second word in one or more non-arced lines, wherein: the displayed elements comprise bordering elements, the bordering elements are elements sharing a boundary, and the displaying comprises smoothing representations of boundaries between bordering elements. | 13. One or more non-transitory computer readable media encoded with instructions for performing a method, the method comprising: identifying a region in an image containing text (a text region); identifying an element boundary for each pair of elements in the text region, the text region including one or more elements including one or more words that are arranged in an arced line; electronically displaying elements from the image by way of a device by wrapping successive elements onto one or more successive lines at a respective element boundary to accommodate the device; and rotating a first word in the arced line relative to a second word in the arced line to electronically display the first word and the second word in one or more non-arced lines, wherein: the displayed elements comprise bordering elements, the bordering elements are elements sharing a boundary, and the displaying comprises smoothing representations of boundaries between bordering elements. 14. The one or more non-transitory computer readable media of claim 13 , wherein the text has a stylistic appearance, and wherein the element boundary is a natural language boundary. | 0.5 |
9,058,362 | 4 | 5 | 4. The apparatus of claim 2 , wherein a decision for further refining the query search query provided by the recommendation engine is automatically decided by the search engine based on a plurality of factors; wherein, if further refinement is to be done, said search engine informs a refinement engine. | 4. The apparatus of claim 2 , wherein a decision for further refining the query search query provided by the recommendation engine is automatically decided by the search engine based on a plurality of factors; wherein, if further refinement is to be done, said search engine informs a refinement engine. 5. The apparatus of claim 4 , wherein said factors comprise a number of results that are returned by the predicted search query. | 0.5 |
8,417,710 | 1 | 4 | 1. A method for managing queries using semantic analysis, the method comprising: receiving, with a processor, a public relations query from a user, wherein the public relations query comprises query of expressed sentiments about at least one person, entity, or action taken thereby; identifying, with a processor, a set of relevant topics and subjects associated with the query; identifying, based on the set of topics and subjects, a set of information sources that are identified as relevant information sources for the user and that comprise data associated with the set of topics and subjects; identifying a set of data from the set of information sources that satisfies the query; determining, with a processor, for each data element in the set of data, a number of web pages that a) point to a web page comprising the each data element, and b) are in the set of information sources that are identified as relevant information sources for the user; assigning a weight to the each data element based on the determined number of web pages, where a higher number of web pages results in a higher weight being assigned than a lower number of web pages; identifying a set of data elements within the set of data that comprises a set of weights above a given threshold; and generating a response to the query using the set of data elements that has been identified. | 1. A method for managing queries using semantic analysis, the method comprising: receiving, with a processor, a public relations query from a user, wherein the public relations query comprises query of expressed sentiments about at least one person, entity, or action taken thereby; identifying, with a processor, a set of relevant topics and subjects associated with the query; identifying, based on the set of topics and subjects, a set of information sources that are identified as relevant information sources for the user and that comprise data associated with the set of topics and subjects; identifying a set of data from the set of information sources that satisfies the query; determining, with a processor, for each data element in the set of data, a number of web pages that a) point to a web page comprising the each data element, and b) are in the set of information sources that are identified as relevant information sources for the user; assigning a weight to the each data element based on the determined number of web pages, where a higher number of web pages results in a higher weight being assigned than a lower number of web pages; identifying a set of data elements within the set of data that comprises a set of weights above a given threshold; and generating a response to the query using the set of data elements that has been identified. 4. The method of claim 1 , wherein the set of information sources comprises a set of proprietary information sources and a set of public information sources. | 0.649554 |
4,715,011 | 1 | 7 | 1. A calculator for use by teachers for converting numeric scores into student letter grades comprising: means for inputting a high numeric standard and a low numeric standard; means for calculating numeric ranges between said high and low numeric standards, each of said ranges corresponding to a letter grade; means for inputting a student numeric score; means for determining the numeric range encompassing the student numeric score and for determining the corresponding student letter grade; and display means for displaying the corresponding student letter grade. | 1. A calculator for use by teachers for converting numeric scores into student letter grades comprising: means for inputting a high numeric standard and a low numeric standard; means for calculating numeric ranges between said high and low numeric standards, each of said ranges corresponding to a letter grade; means for inputting a student numeric score; means for determining the numeric range encompassing the student numeric score and for determining the corresponding student letter grade; and display means for displaying the corresponding student letter grade. 7. A calculator as defined in claim 1 further comprising means for manually inputting numbers modifying the numeric ranges. | 0.742678 |
7,917,547 | 13 | 15 | 13. A method implemented within a computer system that includes a processor and memory storing instructions which, when executed by the processor implement the method for responding to a query using a query evaluator that utilizes a data provider to virtualize data access to an object so that a subset of a plurality of properties of the object are accessible to the query evaluator without constructing the entire object, the method comprising: an act of a computer system that includes one or more processors receiving a property value access query, wherein the property value access query queries for a property value of a property identified in a previously received data construction statement that describes at least a portion of a syntax tree of an object having a plurality of properties, and wherein the value of at least one of the plurality of properties is determinable by execution of a query expression; an act of the computer system identifying a data provider created from the previously received data construction statement based on data contained in the property value access query, wherein the data provider virtualizes data access to the object and facilitates lazy evaluation of queries on the object by creating a partial construction of the object based on the data construction statement, wherein the partial construction of the object provides access to values of one or more properties of the object by executing one or more query expressions corresponding to the one or more properties without having to evaluate the entire data construction statement or fully construct the entire object; an act of the computer system placing the identified data provider in a known location associated with the query evaluator; an act of the computer system creating a data consumer for the property value access query; an act of the data consumer accessing the identified data provider from the known location; an act of the data consumer requesting the property value of the identified property from the data provider; an act of the data consumer receiving the property value of the identified property from the data provider; an act of the data consumer placing the received property value in the known location for further processing. | 13. A method implemented within a computer system that includes a processor and memory storing instructions which, when executed by the processor implement the method for responding to a query using a query evaluator that utilizes a data provider to virtualize data access to an object so that a subset of a plurality of properties of the object are accessible to the query evaluator without constructing the entire object, the method comprising: an act of a computer system that includes one or more processors receiving a property value access query, wherein the property value access query queries for a property value of a property identified in a previously received data construction statement that describes at least a portion of a syntax tree of an object having a plurality of properties, and wherein the value of at least one of the plurality of properties is determinable by execution of a query expression; an act of the computer system identifying a data provider created from the previously received data construction statement based on data contained in the property value access query, wherein the data provider virtualizes data access to the object and facilitates lazy evaluation of queries on the object by creating a partial construction of the object based on the data construction statement, wherein the partial construction of the object provides access to values of one or more properties of the object by executing one or more query expressions corresponding to the one or more properties without having to evaluate the entire data construction statement or fully construct the entire object; an act of the computer system placing the identified data provider in a known location associated with the query evaluator; an act of the computer system creating a data consumer for the property value access query; an act of the data consumer accessing the identified data provider from the known location; an act of the data consumer requesting the property value of the identified property from the data provider; an act of the data consumer receiving the property value of the identified property from the data provider; an act of the data consumer placing the received property value in the known location for further processing. 15. The method as recited in claim 13 , wherein the act of receiving the actual property value of the property from the data provider comprises an act of receiving the actual property value of the property without having to evaluate query expressions for other properties described by the previously received data construction statement. | 0.510174 |
8,589,439 | 6 | 9 | 6. The system as defined in claim 5 further comprising program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to match the selected one or more rules from the set of stored rules with one or more facts of the set of facts about archive data; and program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to route, to a scheduler, the matched one or more rules from the set of stored rules matched with the one or more facts of the set of facts about archive data. | 6. The system as defined in claim 5 further comprising program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to match the selected one or more rules from the set of stored rules with one or more facts of the set of facts about archive data; and program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to route, to a scheduler, the matched one or more rules from the set of stored rules matched with the one or more facts of the set of facts about archive data. 9. The system as defined in claim 6 further comprising program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to archive data archive tasks of the input data based on the selected one or more rules from the set of stored rules matched with the one or more facts of the set of facts about archive data. | 0.5 |
8,745,077 | 1 | 15 | 1. A method implemented by a computer comprising at least one processor and at least one memory for facilitating searching and matching of data, comprising: receiving an input data string including one or more ideographic elements; converting the input data string to a Latin-based input data string at least in part by deconstructing the one or more ideographic elements into constituent radicals or strokes and cross-referencing a constituent radical or stroke to a pre-defined Latin character so as to generate one or more sets of Latin characters; generating one or more input keys based on the Latin-based input data string, including replacing any element in the Latin-based input data string that has a corresponding sounds-alike element to generate a phonetic key; searching, using the one or more input keys, a reference database stored in a memory device for one or more candidate records, wherein similar records in the database are indexed by a common lookup key; and if the one or more candidate records are found, determining a match score of the one or more candidate records. | 1. A method implemented by a computer comprising at least one processor and at least one memory for facilitating searching and matching of data, comprising: receiving an input data string including one or more ideographic elements; converting the input data string to a Latin-based input data string at least in part by deconstructing the one or more ideographic elements into constituent radicals or strokes and cross-referencing a constituent radical or stroke to a pre-defined Latin character so as to generate one or more sets of Latin characters; generating one or more input keys based on the Latin-based input data string, including replacing any element in the Latin-based input data string that has a corresponding sounds-alike element to generate a phonetic key; searching, using the one or more input keys, a reference database stored in a memory device for one or more candidate records, wherein similar records in the database are indexed by a common lookup key; and if the one or more candidate records are found, determining a match score of the one or more candidate records. 15. The method of claim 1 wherein the reference database comprises an index table, wherein each record in the index table comprises a standard key, a phonetic key, a radical key, a stroke key, or a combination thereof. | 0.55144 |
9,342,627 | 1 | 2 | 1. A system, comprising: one or more processors configured to: determine one or more categories that correspond to a plurality of queries; sort the plurality of queries into one or more groups based at least in part on the determined one or more categories of the plurality of queries; segment queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determine occurrence probabilities for the first plurality of phrases, the determined occurrence probabilities being computed based at least in part on a number of times a phrase occurs in a corresponding group and a number of times the phrase occurs across the one or more groups; determine word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; perform a first search using a subsequent query, wherein the subsequent query includes a second plurality of phrases: determine that one or more search results found for the subsequent query do not meet a predetermined rule associated with search results being close matches to the subsequent query; and in response to the determination that the one or more search results returned for the subsequent query do not meet the predetermined rule associated with search results being close matches to the subsequent query: determine a first phrase of the second plurality of phrases of the subsequent query that is associated with a corresponding word information entropy that is less than a threshold value; determine a second phrase of the second plurality of phrases of the subsequent query that is associated with a second corresponding word information entropy that is equal to or greater than the threshold value; generate a new query that includes the first phrase and excludes the second phrase; and perform a second search using the new query; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. | 1. A system, comprising: one or more processors configured to: determine one or more categories that correspond to a plurality of queries; sort the plurality of queries into one or more groups based at least in part on the determined one or more categories of the plurality of queries; segment queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determine occurrence probabilities for the first plurality of phrases, the determined occurrence probabilities being computed based at least in part on a number of times a phrase occurs in a corresponding group and a number of times the phrase occurs across the one or more groups; determine word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; perform a first search using a subsequent query, wherein the subsequent query includes a second plurality of phrases: determine that one or more search results found for the subsequent query do not meet a predetermined rule associated with search results being close matches to the subsequent query; and in response to the determination that the one or more search results returned for the subsequent query do not meet the predetermined rule associated with search results being close matches to the subsequent query: determine a first phrase of the second plurality of phrases of the subsequent query that is associated with a corresponding word information entropy that is less than a threshold value; determine a second phrase of the second plurality of phrases of the subsequent query that is associated with a second corresponding word information entropy that is equal to or greater than the threshold value; generate a new query that includes the first phrase and excludes the second phrase; and perform a second search using the new query; and one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions. 2. The system of claim 1 , wherein a category for a query of the plurality of categories is determined based at least in part on a category associated with a webpage that is associated with a search result for the query. | 0.74359 |
9,753,723 | 15 | 20 | 15. A non-transitory computer-readable medium having stored thereon a plurality of instructions for generating a language-independent representation of a software project's structure from its code, the instructions, when executed by a processor, causing the processor to perform: generating a language-specific representation of code structure from the software project via one or more language structurer systems, augmenting the language-specific representation with additional, inferred information via one or more language inferencer systems; mapping from language-specific components to language-independent components via one or more language translators in communication with said one or more language analyzers, wherein said language-independent components represent a source-to-source translation that maintains a semantic structure of the software project's source code such that each language-independent component corresponds to at least one of a function, a method, a package, a class, a type, a field, a variable declaration, a comment, an interface, a reference to the function, a reference to the method, a reference to the package, a reference to the class, a reference to the type, a reference to the field, and a reference to the variable declaration; and storing the language-independent components in a database. | 15. A non-transitory computer-readable medium having stored thereon a plurality of instructions for generating a language-independent representation of a software project's structure from its code, the instructions, when executed by a processor, causing the processor to perform: generating a language-specific representation of code structure from the software project via one or more language structurer systems, augmenting the language-specific representation with additional, inferred information via one or more language inferencer systems; mapping from language-specific components to language-independent components via one or more language translators in communication with said one or more language analyzers, wherein said language-independent components represent a source-to-source translation that maintains a semantic structure of the software project's source code such that each language-independent component corresponds to at least one of a function, a method, a package, a class, a type, a field, a variable declaration, a comment, an interface, a reference to the function, a reference to the method, a reference to the package, a reference to the class, a reference to the type, a reference to the field, and a reference to the variable declaration; and storing the language-independent components in a database. 20. The non-transitory computer-readable medium of claim 15 , wherein said augmenting the language-specific representation further comprises augmenting the language-specific representation with global information regarding the language-specific components of the software project. | 0.5 |
9,171,542 | 16 | 18 | 16. The one or more non-transitory computer-readable media of claim 15 , wherein the instructions, when executed by the one or more computers, cause the one or more computers to determine a plurality of key-value pairs corresponding to different possible resolutions for the unresolved anaphora. | 16. The one or more non-transitory computer-readable media of claim 15 , wherein the instructions, when executed by the one or more computers, cause the one or more computers to determine a plurality of key-value pairs corresponding to different possible resolutions for the unresolved anaphora. 18. The one or more non-transitory computer-readable media of claim 16 , wherein the instructions, when executed by the one or more computers, cause the one or more computers to determine, for each element of a plurality of elements of the list, a key-value pair comprising a context type and a context value. | 0.70794 |
9,953,649 | 6 | 7 | 6. The method of claim 1 , the method further comprising: storing, by the voice-click component, a list of the plurality of electronic devices from which the voice-click components is configured to receive nonvoice interactions and/or voice interactions; monitoring, by the voice-click component, the plurality of electronic devices based on the list. | 6. The method of claim 1 , the method further comprising: storing, by the voice-click component, a list of the plurality of electronic devices from which the voice-click components is configured to receive nonvoice interactions and/or voice interactions; monitoring, by the voice-click component, the plurality of electronic devices based on the list. 7. The method of claim 6 , the method further comprising: determining, by the first electronic device, a first time at which the nonvoice interaction was detected at the first electronic device; determining, by the second electronic device, a second time at which the natural language utterance was detected at the first electronic device; obtaining, by the voice-click component, the first time and the second time; and determining, by the voice-click component, that the nonvoice interaction and the natural language utterance relate form a multi-modal interaction that is to be interpreted together based on the first time and the second time. | 0.5 |
7,698,255 | 2 | 11 | 2. A system for organizing knowledge data comprising: a place module that enables a user to specify a subset of knowledge data, wherein the knowledge data is organized according to one or more topical categories, the knowledge data comprising (i) user profiles that include information about one or more individuals, and (ii) documents that include information content created, edited, and/or accessed by the individuals, and wherein the information about the individuals included in the user profiles includes affinities of the individuals to documents and affinities of the individuals to the topical categories; a place, said place associated with the subset of the knowledge data, and said place including at least one portal having a search window for searching the subset of the knowledge data, a list for displaying indicia associated with individuals having user profile that include an affinity to the subset of the knowledge data, and communication means to initiate communication with these individuals; a search module that enables the user to initiate a search of the subset of the knowledge data using the search window and performs the search initiated by the user, and wherein performing the search comprises (i) identifying one or more of the documents that include information content related to the search and (ii) identifying one or more of the user profiles that include affinities to the identified documents; a display module that disp 1 ays indicia associated with the individuals that correspond to the user profiles that include affinities to the identified documents; a selection module that enables selection of one or more of the displayed indicia; and a communication module that enables initiation of communication with the individual or individuals associated with the selected indicia. | 2. A system for organizing knowledge data comprising: a place module that enables a user to specify a subset of knowledge data, wherein the knowledge data is organized according to one or more topical categories, the knowledge data comprising (i) user profiles that include information about one or more individuals, and (ii) documents that include information content created, edited, and/or accessed by the individuals, and wherein the information about the individuals included in the user profiles includes affinities of the individuals to documents and affinities of the individuals to the topical categories; a place, said place associated with the subset of the knowledge data, and said place including at least one portal having a search window for searching the subset of the knowledge data, a list for displaying indicia associated with individuals having user profile that include an affinity to the subset of the knowledge data, and communication means to initiate communication with these individuals; a search module that enables the user to initiate a search of the subset of the knowledge data using the search window and performs the search initiated by the user, and wherein performing the search comprises (i) identifying one or more of the documents that include information content related to the search and (ii) identifying one or more of the user profiles that include affinities to the identified documents; a display module that disp 1 ays indicia associated with the individuals that correspond to the user profiles that include affinities to the identified documents; a selection module that enables selection of one or more of the displayed indicia; and a communication module that enables initiation of communication with the individual or individuals associated with the selected indicia. 11. The system of claim 2 , wherein the display module displays indicia associated with the identified documents. | 0.880042 |
9,179,313 | 9 | 10 | 9. The media of claim 8 , wherein each of the second user nodes are connected to the first node in the social graph. | 9. The media of claim 8 , wherein each of the second user nodes are connected to the first node in the social graph. 10. The media of claim 9 , the software being further operable when executed by one or more processors to: determine that a number of the second user nodes connected to the first node in the social graph is too small; and retrieve, from the social graph, information indicating that a social-networking account for each of one or more third users of the social-networking system has been compromised, wherein the third users are respectively associated with third user nodes in the social graph, wherein none of the third user nodes are connected to the first node in the social graph, and wherein the third users previously accessed the shared device; and wherein the message further comprises information indicating that the social-networking accounts for the third users has been compromised. | 0.5 |
4,015,087 | 15 | 16 | 15. The invention as set forth in claim 14 wherein said vertical sweep generator includes a first digital to analog converter connected to said second counter for providing as a vertical sweep signal a staircase voltage which increases with increasing counts in said second counter, said fast horizontal sweep generator comprises circuit means for generating a ramp wave which increases in amplitude in the interval between said first and second pulses, and said slow horizontal sweep generator includes a second digital to analog converter connected to said third counter. | 15. The invention as set forth in claim 14 wherein said vertical sweep generator includes a first digital to analog converter connected to said second counter for providing as a vertical sweep signal a staircase voltage which increases with increasing counts in said second counter, said fast horizontal sweep generator comprises circuit means for generating a ramp wave which increases in amplitude in the interval between said first and second pulses, and said slow horizontal sweep generator includes a second digital to analog converter connected to said third counter. 16. The invention as set forth in claim 15 wherein said visual display is a scan converter unit having a composite video signal output and a video monitor responsive to said composite video signal output for producing said spectrogram, said scan converter having a video input connected to said switch means and having slow and fast deflection inputs, means for applying said vertical sweep signals and the sum of said fast and slow horizontal sweep signals respectively to said slow and fast deflection inputs of said converter, means responsive to said third pulses for providing a square wave repetitive at the same rate as said third pulses, means connecting said square wave to said switch means for blanking said video signal during one half the period thereof, means for applying said square wave to said third counter such that said third counter is incremented synchronously with alternate ones of said third pulses, and means for controlling the amplitude of said slow horizontal sweep signals with respect to said fast horizontal sweep signals such that the rasters of successive interval spectrograms are written adjacent to each other in said scan converter. | 0.5 |
9,661,093 | 19 | 20 | 19. The electronic device of claim 16 , wherein the processor is configured to: receive, via the network interface, a disable connection monitor request to terminate the connection monitor; and send, via the network interface, a status report indicating whether a commissioning device has received the disable connection monitor and disabled the connection monitor. | 19. The electronic device of claim 16 , wherein the processor is configured to: receive, via the network interface, a disable connection monitor request to terminate the connection monitor; and send, via the network interface, a status report indicating whether a commissioning device has received the disable connection monitor and disabled the connection monitor. 20. The electronic device of claim 19 , wherein the connection monitor request is configured to cause an active connection monitoring link to prevent unintended tunnel termination until a timeout indicated in the connection monitor timeout field has elapsed even if the remote device closes a read-write side of its connection to the electronic device through the tunnel. | 0.5 |
8,549,072 | 19 | 31 | 19. A computer program product for providing information associated with a user of a social networking system, the computer program product comprising a non-transitory computer-readable storage medium containing a markup language document for being rendered by a web browser application executing on a computer system, the markup language document comprising: information items encoded in a markup language comprising instructions for rendering information from an external website in a web browser application; and instructions to a web browser application executing on a computer system for to retrieve information associated with a user of a social networking system, the instructions for causing the computer system to: send a request to a social network server for information associated with the user of the social networking system, receive the requested information associated with the user from the social network server in response to the request for the information, and incorporate the information received from the social network server with the information items related to the external website to produce a displayable web page. | 19. A computer program product for providing information associated with a user of a social networking system, the computer program product comprising a non-transitory computer-readable storage medium containing a markup language document for being rendered by a web browser application executing on a computer system, the markup language document comprising: information items encoded in a markup language comprising instructions for rendering information from an external website in a web browser application; and instructions to a web browser application executing on a computer system for to retrieve information associated with a user of a social networking system, the instructions for causing the computer system to: send a request to a social network server for information associated with the user of the social networking system, receive the requested information associated with the user from the social network server in response to the request for the information, and incorporate the information received from the social network server with the information items related to the external website to produce a displayable web page. 31. The computer program product of claim 19 , wherein the information associated with the user received from the social networking system comprises information associated with connections of the user that are associated with the external website. | 0.706651 |
7,552,055 | 18 | 19 | 18. The computer-implemented method of claim 17 wherein generating client side markup includes combining the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property. | 18. The computer-implemented method of claim 17 wherein generating client side markup includes combining the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property. 19. The computer-implemented method of claim 18 wherein generating client side markup includes combining the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported extra answer property. | 0.728022 |
9,858,602 | 1 | 8 | 1. A computer-implemented method for enabling learner billing of time-limited access to one or more learning content modules, one or more time-limited tangible tutoring services, time-limited access to one or more tangible learning facilities, or time-limited access to one or more learning tools in a learning system, the learning system including one or more processors and a plurality of user computing devices, the plurality of user computing devices being remotely linked over a computer network through a network interface device configured to perform functions enabling communication to and from the computer network via a mobile or browser-based web application, a computer desktop application, an electronic module or subsystem of a social networking environment, an electronic learning content management system, a professional networking environment, an electronic commerce system, an electronic payments system, or an Internet-based website, each of the plurality of user computing devices including an electronic user interface and an electronic display, the one or more processors configured with one or more computer-implemented modules or generators including a learner billing module, a billing cycle module, a microlearning purchase management module, a performance management module, an aggregation module, a learning plans adjustments module, a billing adjustments module, a service usage timing module, a prepaid balance module, and a bill interface generator, at least one of the one or more modules or generators including at least one learning database with learning data arranged in data fields, the method comprising steps of: displaying a time-limited access control interface on the electronic display of a user computing device of a learning user through the network interface device, the time-limited access control interface including an option to purchase microlearning items each associated with a pre-determined billable usage value per unit of time including time-limited access to at least one learning content module, the learning content module comprising instructional content and associated electronic media related to the instructional content or at least one of the plurality of metadata associated with the learning system, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool; accepting a selection from the learning user associated with the user computing device via the electronic user interface for time-limited access to least one learning content module or time-limited access to at least one tangible tutoring service or time-limited access to at least one tangible learning facility or time-limited access to at least one tangible learning tool via the network interface device; granting time-limited access to at least one learning content module or time-limited access to at least one tangible tutoring service or time-limited access to at least one tangible learning facility or time-limited access to at least one tangible learning tool via an electronic access control interface on the user computing device associated with at least one learning user or at least one tutoring user or at least one learning facility administering user via a performance management module at multiple dates and times, and recording the duration, dates, and times of all time-limited accesses as a variety of access events; monitoring, via the service usage timing module, via an electronic access control interface on the user computing device associated with at least one of the learning user, tutoring user, or learning facility administering user, time-limited access by the learning user to at least one learning content module, to at least one tangible tutoring service, to at least one tangible learning facility, or to at least one tangible learning tool, at different dates and times, and recording the duration, dates, and times of each time-limited access as a variety of billable usage events; receiving, via the bill interface generator, a billing cycle completion reminder from the billing cycle module at a predetermined time after the completion of a user billing cycle; receiving, via the bill interface generator, an electronic bill generation request for at least one time-limited access event or at least one time-limited billable usage event from the billing cycle module for the completed billing cycle; determining, via the microlearning purchase management module, a plurality of microlearning items purchased by the learning user in the billing cycle, the plurality of microlearning items including time-limited access to at least one learning content module, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool being included in the learning data and retrieved from respective data fields of the learning database; determining, via the microlearning purchase management module, a pre-determined billable usage value per unit of time for the purchased or accessed microlearning items including time-limited access to at least one learning content module, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool, wherein the unit of time includes at least one of seconds, or minutes, or hours or days, computing, by the aggregation module, pro-rated billable usage values of microlearning items accessed by the learning user in the completed billing cycle to determine the aggregate pro-rated billable usage value due from the learning user, wherein the computing includes consolidating the variety of learning content module access events as a first consolidated billing item and the variety of billable usage events as a second consolidated billing item; determining, by the billing cycle module, if a prepaid value is previously associated with the learning user; determining, by the prepaid balance module, the prepaid value and balance pro-rated billable usage value after adjustment of prepaid value against aggregate billable usage value for the completed billing cycle; and displaying, by the bill interface generator, an electronic learner bill designating at least one of an itemized or aggregate a zero or non-zero balance pro-rated billable usage value on the electronic display of the user computing device operated by the learning user, the balance pro-rated billable usage value being based on the first consolidated billing item and the second consolidated billing items, and any adjustments by the billing adjustments module to the balance pro-rated billable usage value due. | 1. A computer-implemented method for enabling learner billing of time-limited access to one or more learning content modules, one or more time-limited tangible tutoring services, time-limited access to one or more tangible learning facilities, or time-limited access to one or more learning tools in a learning system, the learning system including one or more processors and a plurality of user computing devices, the plurality of user computing devices being remotely linked over a computer network through a network interface device configured to perform functions enabling communication to and from the computer network via a mobile or browser-based web application, a computer desktop application, an electronic module or subsystem of a social networking environment, an electronic learning content management system, a professional networking environment, an electronic commerce system, an electronic payments system, or an Internet-based website, each of the plurality of user computing devices including an electronic user interface and an electronic display, the one or more processors configured with one or more computer-implemented modules or generators including a learner billing module, a billing cycle module, a microlearning purchase management module, a performance management module, an aggregation module, a learning plans adjustments module, a billing adjustments module, a service usage timing module, a prepaid balance module, and a bill interface generator, at least one of the one or more modules or generators including at least one learning database with learning data arranged in data fields, the method comprising steps of: displaying a time-limited access control interface on the electronic display of a user computing device of a learning user through the network interface device, the time-limited access control interface including an option to purchase microlearning items each associated with a pre-determined billable usage value per unit of time including time-limited access to at least one learning content module, the learning content module comprising instructional content and associated electronic media related to the instructional content or at least one of the plurality of metadata associated with the learning system, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool; accepting a selection from the learning user associated with the user computing device via the electronic user interface for time-limited access to least one learning content module or time-limited access to at least one tangible tutoring service or time-limited access to at least one tangible learning facility or time-limited access to at least one tangible learning tool via the network interface device; granting time-limited access to at least one learning content module or time-limited access to at least one tangible tutoring service or time-limited access to at least one tangible learning facility or time-limited access to at least one tangible learning tool via an electronic access control interface on the user computing device associated with at least one learning user or at least one tutoring user or at least one learning facility administering user via a performance management module at multiple dates and times, and recording the duration, dates, and times of all time-limited accesses as a variety of access events; monitoring, via the service usage timing module, via an electronic access control interface on the user computing device associated with at least one of the learning user, tutoring user, or learning facility administering user, time-limited access by the learning user to at least one learning content module, to at least one tangible tutoring service, to at least one tangible learning facility, or to at least one tangible learning tool, at different dates and times, and recording the duration, dates, and times of each time-limited access as a variety of billable usage events; receiving, via the bill interface generator, a billing cycle completion reminder from the billing cycle module at a predetermined time after the completion of a user billing cycle; receiving, via the bill interface generator, an electronic bill generation request for at least one time-limited access event or at least one time-limited billable usage event from the billing cycle module for the completed billing cycle; determining, via the microlearning purchase management module, a plurality of microlearning items purchased by the learning user in the billing cycle, the plurality of microlearning items including time-limited access to at least one learning content module, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool being included in the learning data and retrieved from respective data fields of the learning database; determining, via the microlearning purchase management module, a pre-determined billable usage value per unit of time for the purchased or accessed microlearning items including time-limited access to at least one learning content module, or time-limited access to at least one tangible tutoring service, or time-limited access to at least one tangible learning facility, or time-limited access to at least one tangible learning tool, wherein the unit of time includes at least one of seconds, or minutes, or hours or days, computing, by the aggregation module, pro-rated billable usage values of microlearning items accessed by the learning user in the completed billing cycle to determine the aggregate pro-rated billable usage value due from the learning user, wherein the computing includes consolidating the variety of learning content module access events as a first consolidated billing item and the variety of billable usage events as a second consolidated billing item; determining, by the billing cycle module, if a prepaid value is previously associated with the learning user; determining, by the prepaid balance module, the prepaid value and balance pro-rated billable usage value after adjustment of prepaid value against aggregate billable usage value for the completed billing cycle; and displaying, by the bill interface generator, an electronic learner bill designating at least one of an itemized or aggregate a zero or non-zero balance pro-rated billable usage value on the electronic display of the user computing device operated by the learning user, the balance pro-rated billable usage value being based on the first consolidated billing item and the second consolidated billing items, and any adjustments by the billing adjustments module to the balance pro-rated billable usage value due. 8. The computer-implemented method of claim 1 , wherein the displaying of the electronic learner bill designating the balance pro-rated billable usage value further comprises: sending, by the bill interface generator, at regular predetermined intervals, an electronic learner bill or bill summary in text format as a text message to the mobile number provided by the learning user and present in the learning database. | 0.700143 |
8,694,320 | 12 | 13 | 12. The device of claim 9 , wherein the said tag processor adds randomness. | 12. The device of claim 9 , wherein the said tag processor adds randomness. 13. The device of claim 12 , wherein the tag processor implements said randomness by changes in the instructions, such that said changes vary at least one of manners or parameters, for generating the audio. | 0.5 |
8,712,770 | 14 | 16 | 14. At least one computer-readable storage device storing computer-executable instructions that, when executed by at least one processor, perform a method for extracting a target speech from two input speeches, wherein said input speeches are obtained using at least two speech input devices, said method comprising: determining a noise power spectrum, wherein said determination uses at least one of said two input speeches; applying a spectrum subtraction process to subtract at least part of said noise power spectrum from a speech spectrum of at least one of said two input speeches to obtain a subtracted power spectrum; computing cross-power spectrum phase (CSP) coefficients based on said two input speeches, said CSP coefficients indicative of a direction of a speaker relative to one of said at least two speech input devices; applying a gain control to said subtracted power spectrum based on said CSP coefficients, wherein said gain control amplifies speech received from a direction indicated by said CSP coefficients, to obtain a resultant power spectrum; and applying a flooring process to the resultant power spectrum to obtain a processed power spectrum of the target speech suitable for speech recognition. | 14. At least one computer-readable storage device storing computer-executable instructions that, when executed by at least one processor, perform a method for extracting a target speech from two input speeches, wherein said input speeches are obtained using at least two speech input devices, said method comprising: determining a noise power spectrum, wherein said determination uses at least one of said two input speeches; applying a spectrum subtraction process to subtract at least part of said noise power spectrum from a speech spectrum of at least one of said two input speeches to obtain a subtracted power spectrum; computing cross-power spectrum phase (CSP) coefficients based on said two input speeches, said CSP coefficients indicative of a direction of a speaker relative to one of said at least two speech input devices; applying a gain control to said subtracted power spectrum based on said CSP coefficients, wherein said gain control amplifies speech received from a direction indicated by said CSP coefficients, to obtain a resultant power spectrum; and applying a flooring process to the resultant power spectrum to obtain a processed power spectrum of the target speech suitable for speech recognition. 16. The at least one computer-readable storage device of claim 14 , wherein applying a flooring process to said resultant power spectrum comprises increasing at least one value of at least part of said resultant power spectrum. | 0.5 |
8,488,146 | 15 | 21 | 15. An image forming apparatus configured to function as a groupware terminal and connectable to a groupware server of a groupware, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database, said image forming apparatus comprising: a scan part configured to scan a paper document and to obtain document data; a first display screen that displays a selection screen enabling selection of one of the plural document databases; an acquiring part configured to acquire one of the lists of attribute information from the attribute database corresponding to the selected document database; a second display screen that displays an input screen to set the unique predetermined setting items included in the acquired attribute information; a setting part configured to add the attribute information including the set setting items to the document data obtained by the scan part; and a sending part configured to send to the groupware server the document data having the set attribute information, so that said groupware server stores the document data having the added attribute information including the set setting items, in the document database, wherein: the document data having the added attribute information including the set setting item sent from the image forming apparatus is stored in the document database of the groupware server. | 15. An image forming apparatus configured to function as a groupware terminal and connectable to a groupware server of a groupware, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database, said image forming apparatus comprising: a scan part configured to scan a paper document and to obtain document data; a first display screen that displays a selection screen enabling selection of one of the plural document databases; an acquiring part configured to acquire one of the lists of attribute information from the attribute database corresponding to the selected document database; a second display screen that displays an input screen to set the unique predetermined setting items included in the acquired attribute information; a setting part configured to add the attribute information including the set setting items to the document data obtained by the scan part; and a sending part configured to send to the groupware server the document data having the set attribute information, so that said groupware server stores the document data having the added attribute information including the set setting items, in the document database, wherein: the document data having the added attribute information including the set setting item sent from the image forming apparatus is stored in the document database of the groupware server. 21. The image forming apparatus as claimed in claim 15 , wherein: said first display screen of said image forming apparatus is further configured to display a list of the document data stored in the selected document database in response to an input, and to display a search part enabling searching of a document data from the list based on a search key. | 0.682226 |
8,996,555 | 4 | 5 | 4. A method as in claim 3 wherein the parse graph is captured in Resource Description Framework (RDF) form by the search plugin, and the plurality of structured queries are created in the SparQL query language. | 4. A method as in claim 3 wherein the parse graph is captured in Resource Description Framework (RDF) form by the search plugin, and the plurality of structured queries are created in the SparQL query language. 5. A method as in claim 4 wherein the search plugin is written in Java. | 0.5 |
8,898,182 | 1 | 2 | 1. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to receive a partial user query phrase, the partial query phrase comprising a final word element; computer readable program code configured to access a vocabulary; computer readable program code configured to ascertain from the vocabulary, at least one possible completion of the final word element; computer readable program code configured to access a phrase index derived from a document corpus; computer readable program code configured to ascertain, from the phrase index, at least two phrases corresponding to completions of the partial user query phrase with the at least one possible completion of the final word element; computer readable program code configured to assign a probability score to each of the at least two phrases; and computer readable program code configured to rank the at least two phrases based on probability; wherein to assign a probability score comprises determining a phrase selection probability, the phrase selection probability corresponding to the probability that a given phrase from the phrase index represents a completion of the partial query phrase given the final word element; wherein to assign a probability score comprises determining a phrase-query correlation, the phrase-query correlation corresponding to a measurement of correlation between a given phrase from the phrase index and that portion of the partial query phrase preceding the final word element; and wherein the phrase-query correlation comprises a function of a probability of observing a phrase from the phrase index alone and of a probability of a joint occurrence between a phrase from the phrase index and the portion of the partial query phrase preceding the final word element. | 1. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to receive a partial user query phrase, the partial query phrase comprising a final word element; computer readable program code configured to access a vocabulary; computer readable program code configured to ascertain from the vocabulary, at least one possible completion of the final word element; computer readable program code configured to access a phrase index derived from a document corpus; computer readable program code configured to ascertain, from the phrase index, at least two phrases corresponding to completions of the partial user query phrase with the at least one possible completion of the final word element; computer readable program code configured to assign a probability score to each of the at least two phrases; and computer readable program code configured to rank the at least two phrases based on probability; wherein to assign a probability score comprises determining a phrase selection probability, the phrase selection probability corresponding to the probability that a given phrase from the phrase index represents a completion of the partial query phrase given the final word element; wherein to assign a probability score comprises determining a phrase-query correlation, the phrase-query correlation corresponding to a measurement of correlation between a given phrase from the phrase index and that portion of the partial query phrase preceding the final word element; and wherein the phrase-query correlation comprises a function of a probability of observing a phrase from the phrase index alone and of a probability of a joint occurrence between a phrase from the phrase index and the portion of the partial query phrase preceding the final word element. 2. The apparatus according to claim 1 , wherein the vocabulary is derived from a document corpus. | 0.5 |
7,624,078 | 19 | 20 | 19. A method according to claim 18 , further comprising: transforming said at least one set theory expression into DNF, wherein said at least one set theory expression contains at least one subexpression that only uses the AND operator and has no parentheses. | 19. A method according to claim 18 , further comprising: transforming said at least one set theory expression into DNF, wherein said at least one set theory expression contains at least one subexpression that only uses the AND operator and has no parentheses. 20. A method according to claim 19 , further comprising: creating slices that represent said expressions and/or said subexpressions. | 0.5 |
6,078,924 | 4 | 5 | 4. An information platform for performing data collection, interpretation and analysis, comprising: a data retrieval module comprising: a catalog including a data store for collecting internal and external information from relevant sources; and a parsing engine for interpreting the format of a stream of information and then returning requested elements to a user by reading a source document and determining said source document page geometry, wherein said parsing engine locates an element by finding a specific string or pattern within a source document, where regular expressions are character strings in which plain text indicates that that text must exist in a target string, and special characters are used to indicate what variability is allowed in said target strings, and wherein said parsing engine performs any of: a simple content match which looks for a sub-string on regular expression in said source document and returns a primary document element containing the match; a bounded content match in which the search scope is limited to one contiguous part of said source document; and a simple/bounded content match in element type which is a bounded or document wide search that look for a sub-string within a specific element type; and a data classification and storage module; and an information browsing, query, analysis, and report creation module. | 4. An information platform for performing data collection, interpretation and analysis, comprising: a data retrieval module comprising: a catalog including a data store for collecting internal and external information from relevant sources; and a parsing engine for interpreting the format of a stream of information and then returning requested elements to a user by reading a source document and determining said source document page geometry, wherein said parsing engine locates an element by finding a specific string or pattern within a source document, where regular expressions are character strings in which plain text indicates that that text must exist in a target string, and special characters are used to indicate what variability is allowed in said target strings, and wherein said parsing engine performs any of: a simple content match which looks for a sub-string on regular expression in said source document and returns a primary document element containing the match; a bounded content match in which the search scope is limited to one contiguous part of said source document; and a simple/bounded content match in element type which is a bounded or document wide search that look for a sub-string within a specific element type; and a data classification and storage module; and an information browsing, query, analysis, and report creation module. 5. The information platform of claim 4, wherein said parsing engine subdivides a source document into elements at include any of a section, a sub-section, a paragraph including any of a sentence, phrase, and word; a table including any of a title, column, row, column header, spanned column header, header, row header, spanned row header, and cell; an image, a link, form, and a line, optionally within a range. | 0.5 |
10,043,511 | 8 | 14 | 8. A computer program product comprising: a non-transitory computer readable storage medium readable by one or more processor and storing instructions for execution by the one or more processor for performing a method for expanding a language model corresponding to a domain, comprising: collecting at least one feature vector from one or more external domain distinctive from the domain, wherein the domain and the one or more external domain are interconnected via a cloud; expanding the language model, stored in a corpora coupled to the cloud, with a feature vector of the at least one feature vector from the collecting, wherein the feature vector is, based on a logistic regression threshold, more relevant to the domain than not, the expanding comprising: (i) calculating a logistic regression value for the feature vector by use of σ(t)=e t /(e t +1)=1/(1+e −t ), wherein σ(t) indicates a standard equation of logistic regression for sentence t that represents the feature vector, (ii) ascertaining that the logistic regression value for the feature vector indicating that the probability of the feature vector to be relevant to the domain is greater than or equal to the logistic regression threshold of zero point five (0.5); and (iii) updating the language model in the corpora by adding the feature vector from the ascertaining to the language model; enhancing the language model by machine learning live content from one or more subject website in which the domain is interested such that the language model includes the live content and one or more secondary term derived from the live content that are more relevant to the domain than not, such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. | 8. A computer program product comprising: a non-transitory computer readable storage medium readable by one or more processor and storing instructions for execution by the one or more processor for performing a method for expanding a language model corresponding to a domain, comprising: collecting at least one feature vector from one or more external domain distinctive from the domain, wherein the domain and the one or more external domain are interconnected via a cloud; expanding the language model, stored in a corpora coupled to the cloud, with a feature vector of the at least one feature vector from the collecting, wherein the feature vector is, based on a logistic regression threshold, more relevant to the domain than not, the expanding comprising: (i) calculating a logistic regression value for the feature vector by use of σ(t)=e t /(e t +1)=1/(1+e −t ), wherein σ(t) indicates a standard equation of logistic regression for sentence t that represents the feature vector, (ii) ascertaining that the logistic regression value for the feature vector indicating that the probability of the feature vector to be relevant to the domain is greater than or equal to the logistic regression threshold of zero point five (0.5); and (iii) updating the language model in the corpora by adding the feature vector from the ascertaining to the language model; enhancing the language model by machine learning live content from one or more subject website in which the domain is interested such that the language model includes the live content and one or more secondary term derived from the live content that are more relevant to the domain than not, such that the language model accurately and comprehensively facilitates an automatic speech recognition (ASR) system for the domain; and performing speech recognition on a received speech input utilizing at least the enhanced language model. 14. The computer program product of claim 8 , further comprising: utilizing, by the ASR system for the domain, the language model from the expanding and the enhancing in domain-specific disambiguation and recognition of terminologies used in the domain. | 0.846667 |
9,990,436 | 8 | 13 | 8. An information processing system, comprising: a processor device comprising hardware; and a memory operably coupled with the processor device, the memory comprising computer-executable instructions causing a computer to perform acts of: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity of the user; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics using a frequency index; selecting a subset of highest ranked third trending topics; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics. | 8. An information processing system, comprising: a processor device comprising hardware; and a memory operably coupled with the processor device, the memory comprising computer-executable instructions causing a computer to perform acts of: determining first trending topics associated with a user; receiving, via a first network communication, an in-stream feed of second trending topics based on on-line activity of the user; augmenting a social timeline associated with the user with at least one of the second trending topics to produce an interim list of third trending topics, wherein the social timeline is produced by logging content, retrieved via a second network communication, posted on one or more accounts of the user, wherein recently posted content on the social timeline corresponds to a summary of the first trending topics; ranking the third trending topics using a frequency index; selecting a subset of highest ranked third trending topics; and controlling a graphical user interface on a computer display to display a personalized trends module highlighting at least some of the subset of the highest ranked third trending topics to distinguish at least some of the subset of the highest ranked third trending topics from one or more other topics by allocating one or more positions to at least some of the subset of the highest ranked third trending topics to customize an online experience of the user with customized trending topics. 13. The information processing system of claim 8 wherein the computer-executable instructions further comprise instructions for: allocating a position for a sponsored trending topic in the personalized trends module. | 0.758389 |
9,355,168 | 14 | 17 | 14. A non-transitory computer readable medium storing instructions for developing user profiles within a profile corpus, the instructions comprising: determining topics associated with digital content items; organizing user profiles of users into a plurality of demographic groups based on demographics of the users; retrieving access data indicating interactions of users in a demographic group from one of the plurality of demographic groups with a plurality of the digital content items; identifying the topics associated with the plurality of digital content items interacted with by the users from the demographic group as candidate topics to include in user profiles of the users in the demographic group based on the access data; for each candidate topic, identifying topics included in the user profiles of the users in the demographic group that co-occur in the user profiles with that candidate topic; selecting, by a computer, a candidate topic from the candidate topics to include in a target user profile of a target user from the demographic group based on co-occurrence of the candidate topic with one or more topics included in the target user profile that were identified from the user profiles of the users in the demographic group as co-occurring with the candidate topic; and adding the selected candidate topic to the target user profile of the target user from the demographic group. | 14. A non-transitory computer readable medium storing instructions for developing user profiles within a profile corpus, the instructions comprising: determining topics associated with digital content items; organizing user profiles of users into a plurality of demographic groups based on demographics of the users; retrieving access data indicating interactions of users in a demographic group from one of the plurality of demographic groups with a plurality of the digital content items; identifying the topics associated with the plurality of digital content items interacted with by the users from the demographic group as candidate topics to include in user profiles of the users in the demographic group based on the access data; for each candidate topic, identifying topics included in the user profiles of the users in the demographic group that co-occur in the user profiles with that candidate topic; selecting, by a computer, a candidate topic from the candidate topics to include in a target user profile of a target user from the demographic group based on co-occurrence of the candidate topic with one or more topics included in the target user profile that were identified from the user profiles of the users in the demographic group as co-occurring with the candidate topic; and adding the selected candidate topic to the target user profile of the target user from the demographic group. 17. The non-transitory computer readable medium of claim 14 , further comprising: calculating, for each of the candidate topics, a count at which the candidate topic co-occurs with the topics identified from the user profiles of the users in the demographic group; ranking, by the computer, the candidate topics for the target user profile based on the count at which each of the candidate topics co-occurs with topics included in the target user profile; and wherein selecting the candidate topic to add to the target user profile of the target user from the demographic group is based on a rank of the candidate topic in the ranking of candidate topics for the target user profile. | 0.520365 |
9,286,668 | 9 | 15 | 9. A system comprising: a memory; and a processing device operatively coupled to the memory, the processing device configured to: receive digital data representing a page of a publication, the page including panels set against a background region; identify a plurality of potential panels in the page of the publication; determine a first confidence level for a first potential panel of the plurality of potential panels; add the first potential panel to a panel view for the publication, wherein the first confidence level automatically identifies the first potential panel as an actual panel of the publication, wherein the panel view is a digital representation of the publication that allows panel by panel navigation of a set of actual panels of the publication; determine a second confidence level for a second potential panel of the plurality of potential panels; receive user input to manually identify the second potential panel as an actual panel; add the second potential panel to the set of actual panels in the panel view; store the user input pertaining to at least one of size, shape, location, position or layout of a previously-identified panel to identify additional comic panels as actual comic panels of the publication; determine a third confidence level for a third potential panel using the stored user input; add the third potential panel to the panel view for the publication, wherein the third confidence level automatically identifies the third potential panel as an actual panel of the publication; create panel previews of reduced versions of the set of actual panels; receive a request for the panel view; send first data enabling a graphical user interface (GUI) to display at least some of the panel previews of the set of actual panels in a display region; and send second data enabling the GUI to display an enlarged version of a selected one of the panel previews in the same display region. | 9. A system comprising: a memory; and a processing device operatively coupled to the memory, the processing device configured to: receive digital data representing a page of a publication, the page including panels set against a background region; identify a plurality of potential panels in the page of the publication; determine a first confidence level for a first potential panel of the plurality of potential panels; add the first potential panel to a panel view for the publication, wherein the first confidence level automatically identifies the first potential panel as an actual panel of the publication, wherein the panel view is a digital representation of the publication that allows panel by panel navigation of a set of actual panels of the publication; determine a second confidence level for a second potential panel of the plurality of potential panels; receive user input to manually identify the second potential panel as an actual panel; add the second potential panel to the set of actual panels in the panel view; store the user input pertaining to at least one of size, shape, location, position or layout of a previously-identified panel to identify additional comic panels as actual comic panels of the publication; determine a third confidence level for a third potential panel using the stored user input; add the third potential panel to the panel view for the publication, wherein the third confidence level automatically identifies the third potential panel as an actual panel of the publication; create panel previews of reduced versions of the set of actual panels; receive a request for the panel view; send first data enabling a graphical user interface (GUI) to display at least some of the panel previews of the set of actual panels in a display region; and send second data enabling the GUI to display an enlarged version of a selected one of the panel previews in the same display region. 15. The system of claim 9 , wherein the processing device is further configured to: determine whether a boundary of the first potential panel of the plurality of potential panels comprises a geometric shape; determine whether an edge of the boundary of the first potential panel of the plurality of potential panels is parallel to an edge of the page of the publication; analyzing previously received user input associated with previously identified panels; or determining whether a layout of the plurality of panels matches a pre-defined layout. | 0.5 |
8,914,313 | 1 | 16 | 1. A method of searching for a query object within an object class, said method comprising: (a) accessing a collection of unique training samples of multiple training objects within said object class; (b) defining a separate training set of training item descriptors from each of said training samples; (c) extracting the training item descriptors from the separate training sets into a single composite collection of individual training item descriptors; (d) creating a hierarchical tree from said composite collection of individual training item descriptors according to relations in the individual training item descriptors, said hierarchical tree having a plurality of leaf nodes; (e) accessing registration sets of registration item descriptors, each registration set being defined from a respective registration sample obtained from a registration objects to be registered, said registration object being of said object class, individually distributing each registration item descriptor from each registration set into said hierarchical tree according to said relations defined in the creation of said hierarchical tree, indexing the registration item descriptors clustered within each leaf node to their corresponding registration samples; (f) defining a separate registration model for each registration sample based on the clustering of its corresponding registration item descriptors in each leaf node; (g) accessing a query sample from said query object, defining a query set of query item descriptors from said query sample, individually distributing each query item descriptor into said hierarchical tree according to said relations defined in the creation of said hierarchical tree; (h) defining a query model for said query sample based on the clustering of said query item descriptors in each leaf node; and (i) using the query model, x, and the registration models to identify as a potential candidate match the registration object, i, that renders the highest confidence i* of matching the query object, defined as i*=arg max i P(x|i)P(i). | 1. A method of searching for a query object within an object class, said method comprising: (a) accessing a collection of unique training samples of multiple training objects within said object class; (b) defining a separate training set of training item descriptors from each of said training samples; (c) extracting the training item descriptors from the separate training sets into a single composite collection of individual training item descriptors; (d) creating a hierarchical tree from said composite collection of individual training item descriptors according to relations in the individual training item descriptors, said hierarchical tree having a plurality of leaf nodes; (e) accessing registration sets of registration item descriptors, each registration set being defined from a respective registration sample obtained from a registration objects to be registered, said registration object being of said object class, individually distributing each registration item descriptor from each registration set into said hierarchical tree according to said relations defined in the creation of said hierarchical tree, indexing the registration item descriptors clustered within each leaf node to their corresponding registration samples; (f) defining a separate registration model for each registration sample based on the clustering of its corresponding registration item descriptors in each leaf node; (g) accessing a query sample from said query object, defining a query set of query item descriptors from said query sample, individually distributing each query item descriptor into said hierarchical tree according to said relations defined in the creation of said hierarchical tree; (h) defining a query model for said query sample based on the clustering of said query item descriptors in each leaf node; and (i) using the query model, x, and the registration models to identify as a potential candidate match the registration object, i, that renders the highest confidence i* of matching the query object, defined as i*=arg max i P(x|i)P(i). 16. The method of claim 1 , further including destroying said training samples and said training sets of training item descriptors. | 0.80848 |
9,767,357 | 1 | 8 | 1. A computer-implemented method comprising: calculating, by a computing system, raw scores for a plurality of media items based on a classifier model and a target concept; ranking, by the computing system, the plurality of media items based on the raw scores; determining, by the computing system, a review set of the plurality of media items, the review set comprising a subset of the plurality of media items; associating, by the computing system, each of the media items of the review set with a content depiction determination, wherein the content depiction determination is indicative of whether a media item depicts the target concept; and calculating, by the computing system, a normalized score formula based on the raw scores and the content depiction determinations for the media items of the review set. | 1. A computer-implemented method comprising: calculating, by a computing system, raw scores for a plurality of media items based on a classifier model and a target concept; ranking, by the computing system, the plurality of media items based on the raw scores; determining, by the computing system, a review set of the plurality of media items, the review set comprising a subset of the plurality of media items; associating, by the computing system, each of the media items of the review set with a content depiction determination, wherein the content depiction determination is indicative of whether a media item depicts the target concept; and calculating, by the computing system, a normalized score formula based on the raw scores and the content depiction determinations for the media items of the review set. 8. The computer-implemented method of claim 1 , wherein the normalized score formula is configured to convert a raw score calculated by the classifier model into a normalized score. | 0.640873 |
7,809,711 | 9 | 10 | 9. A method of providing a service to analyze electronic documents in an intranet, wherein the intranet comprises a plurality of web sites, the method comprising: crawling HTML content and text content in a set of the sites, wherein the crawling comprises writing each crawled content to a file-based storage system, annotating each crawled content, and generating a first 4-tuple entry for each annotated, crawled content; deep-scanning non-HTML content and non-text content in the set of sites, wherein the deep-scanning comprises fetching all static non-HTML content and non-text content in the set of sites and generating a second 4-tuple entry; reverse-scanning the set of sites; performing a semantic analysis of the crawled content and the deep-scanned content by using the first 4-tuple entry and the second 4-tuple entry; correlating the results of the semantic analysis with the results of the reverse-scanning; and comparing user navigation patterns and content from members of the set of sites. | 9. A method of providing a service to analyze electronic documents in an intranet, wherein the intranet comprises a plurality of web sites, the method comprising: crawling HTML content and text content in a set of the sites, wherein the crawling comprises writing each crawled content to a file-based storage system, annotating each crawled content, and generating a first 4-tuple entry for each annotated, crawled content; deep-scanning non-HTML content and non-text content in the set of sites, wherein the deep-scanning comprises fetching all static non-HTML content and non-text content in the set of sites and generating a second 4-tuple entry; reverse-scanning the set of sites; performing a semantic analysis of the crawled content and the deep-scanned content by using the first 4-tuple entry and the second 4-tuple entry; correlating the results of the semantic analysis with the results of the reverse-scanning; and comparing user navigation patterns and content from members of the set of sites. 10. The method of claim 9 further comprising combining the results of the performing, the results of the correlating, and the results of the comparing. | 0.742321 |
8,589,398 | 10 | 11 | 10. The method of claim 1 , further comprising evaluating the merged cluster to determine a coverage value for the merged cluster and a second overlap value relating to the at least one document contained within the merged cluster. | 10. The method of claim 1 , further comprising evaluating the merged cluster to determine a coverage value for the merged cluster and a second overlap value relating to the at least one document contained within the merged cluster. 11. The method of claim 10 , further comprising merging the compacted cluster representation to generate the merged cluster based upon the coverage value and the second overlap value. | 0.5 |
7,580,929 | 21 | 22 | 21. A computer readable storage medium storing a computer program executable by a processor for personalizing a search of a document collection to a user, the operations of the computer program comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the cluster counts of the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. | 21. A computer readable storage medium storing a computer program executable by a processor for personalizing a search of a document collection to a user, the operations of the computer program comprising: monitoring a plurality of documents accessed by a user; identifying a plurality of first phrases present in one or more of the accessed documents; for each of the identified first phrases, identifying one or more corresponding first related phrases, wherein the one or more first related phrases are related to the corresponding identified first phrase; storing a user model associated with the user, and comprising a plurality of the first related phrases; receiving a query from the user, the query including one or more second phrases; selecting search results comprising a plurality of documents responsive to the query; identifying, by operation of a processor configured to manipulate data within a computer system, one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model; weighting a plurality of scores of a corresponding plurality of the search results according to the cluster counts of the identified one or more second related phrases; ranking the plurality of the search results for presentation to the user according to their weighted scores, to provide personalized search results; and presenting the personalized search results to the user. 22. The computer readable storage medium of claim 21 , wherein identifying one or more second related phrases that are related to the second phrase(s) of the query and that are present in the user model, comprises: for each phrase of the query, accessing a related phrase bit vector for the phrase of the query, wherein each bit of the related phrase bit vector indicates the presence or absence of a related phrase of the phrase of the query; determining from the related phrase bit vector which of the second related phrases are present in the user model; and forming a related phrase bit mask corresponding to the related phrases that are present in the user model. | 0.5 |
9,076,448 | 1 | 2 | 1. A method of performing distributed voice recognition, the method comprising: (a) receiving speech utterance signals representing utterances of a user, the speech utterance signals comprising one or more words; (b) generating, via a processing circuit of a client device, speech data values from the utterance signals during an utterance evaluation time frame corresponding to each utterance signal, wherein the speech data values comprise compressed mel-frequency cepstral coefficient vectors (MFCC vectors) further comprising MFCC delta parameters and MFCC acceleration parameters automatically determined based on at least an amount of computational resources available on the client device and a speed of a transceiver used to transmit data between the client device and a server; (c) encoding the speech data values into a transmission format suitable for transmission over a communications channel to the server; and (d) communicating user context information over the communications channel to the server, wherein the server uses the context information to dynamically select a grammar to use for recognizing the speech data values. | 1. A method of performing distributed voice recognition, the method comprising: (a) receiving speech utterance signals representing utterances of a user, the speech utterance signals comprising one or more words; (b) generating, via a processing circuit of a client device, speech data values from the utterance signals during an utterance evaluation time frame corresponding to each utterance signal, wherein the speech data values comprise compressed mel-frequency cepstral coefficient vectors (MFCC vectors) further comprising MFCC delta parameters and MFCC acceleration parameters automatically determined based on at least an amount of computational resources available on the client device and a speed of a transceiver used to transmit data between the client device and a server; (c) encoding the speech data values into a transmission format suitable for transmission over a communications channel to the server; and (d) communicating user context information over the communications channel to the server, wherein the server uses the context information to dynamically select a grammar to use for recognizing the speech data values. 2. The method of claim 1 wherein receiving speech utterance signals further comprises receiving speech utterance signals representative of a speech based query issued by the user. | 0.673358 |
8,447,609 | 8 | 9 | 8. An apparatus for adjustment of temporal acoustical characteristics of words in an item structure, the apparatus comprising: a device to determine a number of speeds of audio playback for the item structure and to determine, in response to the number of speeds of audio playback for the item structure, a representation of the item structure for each of the number of speeds of audio playback by determining at least a first abbreviated item for one of the number of speeds, the device comprising: a keyword extractor to receive the item structure comprising at least a first item, the first item to represent a first set of one or more words, the keyword extractor to extract one or more keywords or phonemes from the first set to generate a first keyword item; and an abbreviations generator to abbreviate the keyword item by generating a first alternative representation for the first keyword item to create a first abbreviated item, the abbreviations generator to store the first abbreviated item; wherein abbreviated items for a faster speed are shorter than abbreviated items for a slower speed by extracting less keywords or phonemes from the first set for the faster speed, generating a shorter alternative representation for the faster speed, or both. | 8. An apparatus for adjustment of temporal acoustical characteristics of words in an item structure, the apparatus comprising: a device to determine a number of speeds of audio playback for the item structure and to determine, in response to the number of speeds of audio playback for the item structure, a representation of the item structure for each of the number of speeds of audio playback by determining at least a first abbreviated item for one of the number of speeds, the device comprising: a keyword extractor to receive the item structure comprising at least a first item, the first item to represent a first set of one or more words, the keyword extractor to extract one or more keywords or phonemes from the first set to generate a first keyword item; and an abbreviations generator to abbreviate the keyword item by generating a first alternative representation for the first keyword item to create a first abbreviated item, the abbreviations generator to store the first abbreviated item; wherein abbreviated items for a faster speed are shorter than abbreviated items for a slower speed by extracting less keywords or phonemes from the first set for the faster speed, generating a shorter alternative representation for the faster speed, or both. 9. The apparatus of claim 8 , further comprising a text mining knowledge base coupled with the keyword extractor to store data related to word comprehension and grammar, wherein the keyword extractor comprises logic to extract the one or more keywords or phonemes based upon the data related to word comprehension and grammar. | 0.554645 |
9,652,799 | 1 | 6 | 1. A method comprising: receiving, from a user, a text input expressing a question asking for recommendation of a product having a first requested characteristic and a second requested characteristic; identifying a product having the first requested characteristic, at least in part by locating in an ontology a node corresponding to the first requested characteristic, and traversing a relationship in the ontology from the node corresponding to the first requested characteristic to a node corresponding to the product; analyzing, using a natural language analysis component implemented via at least one processor, a plurality of product reviews comprising natural language text evaluations of the product identified from the ontology as having the first requested characteristic, including analyzing the natural language in at least one passage of text in at least one product review of the plurality of product reviews to determine whether the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic; in response to determining via the natural language analysis that the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic, identifying the at least one passage of text in the at least one product review as providing supporting evidence for the product in answer to the question; generating, in response to the question, an answer that identifies the product having the first and second requested characteristics for recommendation to the user; and presenting to the user, in response to the text input, the answer and the at least one passage in the at least one product review identified as providing supporting evidence for the answer. | 1. A method comprising: receiving, from a user, a text input expressing a question asking for recommendation of a product having a first requested characteristic and a second requested characteristic; identifying a product having the first requested characteristic, at least in part by locating in an ontology a node corresponding to the first requested characteristic, and traversing a relationship in the ontology from the node corresponding to the first requested characteristic to a node corresponding to the product; analyzing, using a natural language analysis component implemented via at least one processor, a plurality of product reviews comprising natural language text evaluations of the product identified from the ontology as having the first requested characteristic, including analyzing the natural language in at least one passage of text in at least one product review of the plurality of product reviews to determine whether the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic; in response to determining via the natural language analysis that the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic, identifying the at least one passage of text in the at least one product review as providing supporting evidence for the product in answer to the question; generating, in response to the question, an answer that identifies the product having the first and second requested characteristics for recommendation to the user; and presenting to the user, in response to the text input, the answer and the at least one passage in the at least one product review identified as providing supporting evidence for the answer. 6. The method of claim 1 , wherein analyzing the plurality of product reviews further comprises: scoring passages in at least some of the plurality of product reviews based at least in part on strength of the passages' supporting evidence for the product in answer to the question; and selecting the at least one passage in the at least one product review for presentation to the user based at least in part on the scoring. | 0.5 |
7,603,661 | 1 | 6 | 1. A state transition table defining a plurality of statements in a programming language, each statement defined by at least one token, comprising: a table defining an array of states; a plurality of sub-tables associated with said table, each sub-table corresponding to one of said plurality of statements and including at least one relocatable state that changes in response to said sub-table being assembled within said table, wherein each sub-table is a two-dimensional array defining an action for at least one token in at least one state; and a software module operable to output a state in response to an input, wherein the table, plurality of sub-tables, and software module are stored on a computer. | 1. A state transition table defining a plurality of statements in a programming language, each statement defined by at least one token, comprising: a table defining an array of states; a plurality of sub-tables associated with said table, each sub-table corresponding to one of said plurality of statements and including at least one relocatable state that changes in response to said sub-table being assembled within said table, wherein each sub-table is a two-dimensional array defining an action for at least one token in at least one state; and a software module operable to output a state in response to an input, wherein the table, plurality of sub-tables, and software module are stored on a computer. 6. The state transition table of claim 1 , wherein the state transition table is one selected from the group consisting of a scanner table, a parser table, and a compiler table. | 0.513736 |
8,972,268 | 8 | 16 | 8. A device-comprising: at least one microphone for receiving an utterance in a first language from a user; and a speech translation system in communication with the at least one microphone, wherein the speech translation system is for translating the utterance into a second language, and wherein the speech translation system comprises: a first automatic speech recognition module for the first language for recognizing speech in the utterance in the first language; a first machine translation module in communication with the first speech recognition module, wherein the first machine translation module is for translating the recognized speech in the first language, recognized by the first speech recognition module, into the second language; and; a user interface in communication with the speech translation system for outputting the translation of the utterance in the second language determined by the first machine translation module; wherein the speech translation system is configured to: receive from the user, the utterance in the first language that is to be translated by the speech translation system from the first language to the second language; receive an indication to add a new word in the first language to the first recognition lexicon of the first automatic speech recognition module of the speech translation system; determine for the new word, by a processor, word class information, a pronunciation in the first language, the translation in the second language, and a pronunciation in the second language; add the new word, the determined word class information and the determined pronunciation in the first language to the first recognition lexicon of the first language of the first automatic speech recognition module; and add the new word, the determined word class information, the determined translation in the second language and the pronunciation of the translation in the second language, to the first machine translation module. | 8. A device-comprising: at least one microphone for receiving an utterance in a first language from a user; and a speech translation system in communication with the at least one microphone, wherein the speech translation system is for translating the utterance into a second language, and wherein the speech translation system comprises: a first automatic speech recognition module for the first language for recognizing speech in the utterance in the first language; a first machine translation module in communication with the first speech recognition module, wherein the first machine translation module is for translating the recognized speech in the first language, recognized by the first speech recognition module, into the second language; and; a user interface in communication with the speech translation system for outputting the translation of the utterance in the second language determined by the first machine translation module; wherein the speech translation system is configured to: receive from the user, the utterance in the first language that is to be translated by the speech translation system from the first language to the second language; receive an indication to add a new word in the first language to the first recognition lexicon of the first automatic speech recognition module of the speech translation system; determine for the new word, by a processor, word class information, a pronunciation in the first language, the translation in the second language, and a pronunciation in the second language; add the new word, the determined word class information and the determined pronunciation in the first language to the first recognition lexicon of the first language of the first automatic speech recognition module; and add the new word, the determined word class information, the determined translation in the second language and the pronunciation of the translation in the second language, to the first machine translation module. 16. The device of claim 8 , wherein the speech translation system: further comprises: a second automatic speech recognition module for recognizing speech in the second language; and a second machine translation module for translating recognized speech in the second language to the first language: and is further configured to identify whether the utterance is in the first language or the second language. | 0.70537 |
9,262,520 | 1 | 22 | 1. A computer network-implemented method for displaying a data structure and enabling one or more users to interact with the data structure via a user interface, the data structure including data entities and relationships between the data entities, the method comprising: populating the user interface, via one or more computer processors executing stored program instructions, with text labels representing data entities from the data structure; enabling a user to make a change to a first text label within the user interface using one or more computer processors, the user's change comprising a change to a position of the first text label from a first location on the user interface to a second location specified by the user on the user interface and one or more textual visual properties of the first text label within the user interface; and automatically determining, based on the user's change to the position and the one or more textual visual properties of the first text label, a relationship between a first data entity and a second data entity in the data structure, wherein the relationship was not represented in the data structure prior to the user's change to the first text label, wherein automatically determining the relationship comprises applying translation rules to a combination of (a) at least one positional visual property relating the position of the first text label to a position of a second text label in the user interface, and (b) at least one textual visual property of the first text label and/or the second text label, after the user's change to the first text label. | 1. A computer network-implemented method for displaying a data structure and enabling one or more users to interact with the data structure via a user interface, the data structure including data entities and relationships between the data entities, the method comprising: populating the user interface, via one or more computer processors executing stored program instructions, with text labels representing data entities from the data structure; enabling a user to make a change to a first text label within the user interface using one or more computer processors, the user's change comprising a change to a position of the first text label from a first location on the user interface to a second location specified by the user on the user interface and one or more textual visual properties of the first text label within the user interface; and automatically determining, based on the user's change to the position and the one or more textual visual properties of the first text label, a relationship between a first data entity and a second data entity in the data structure, wherein the relationship was not represented in the data structure prior to the user's change to the first text label, wherein automatically determining the relationship comprises applying translation rules to a combination of (a) at least one positional visual property relating the position of the first text label to a position of a second text label in the user interface, and (b) at least one textual visual property of the first text label and/or the second text label, after the user's change to the first text label. 22. The method of claim 1 , wherein the enabling comprises providing a mechanism allowing the one or more users to create one or more visual properties that are not already generated. | 0.739316 |
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