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8,832,556 | 1 | 2 | 1. A system comprising: one or more processors; a distributed database configured with items of data, the distributed database storing information of a social networking system describing a plurality of existing users; a scripting language configured to extract data from the social networking system, the data extraction applying access control comprising privacy settings of each user of the social networking system, the privacy settings restricting the information about the user that is accessible to other users of the social networking system; and a structured query language interface for extracting information of the social networking system, the structured query language interface in communication with the scripting language, the structured query language interface configured to access database systems and further configured to receive a query over a network, to send the query to the scripting language, and to receive extracted data from the scripting language comprising the requested information subject to the privacy settings of users of the social networking system in response to the query, wherein the distributed database allows an addition by the social networking system of a new field or category of data to the plurality of existing users, the new field or category of data representing an attribute describing each user of the plurality of existing users and storing data directly received from one or more users of the social networking system rather than data derived from one or more existing fields of data; and wherein the structured query language is further configured to receive a request from an application or website maintained by a third party separate from the social networking system, the request identifying the new field or category of data, generate a response to the request comprising the new field or category of data, determine a format for the response to accommodate a database of the third party, convert the response into the determined format, and provide the response in the determined format to the third party. | 1. A system comprising: one or more processors; a distributed database configured with items of data, the distributed database storing information of a social networking system describing a plurality of existing users; a scripting language configured to extract data from the social networking system, the data extraction applying access control comprising privacy settings of each user of the social networking system, the privacy settings restricting the information about the user that is accessible to other users of the social networking system; and a structured query language interface for extracting information of the social networking system, the structured query language interface in communication with the scripting language, the structured query language interface configured to access database systems and further configured to receive a query over a network, to send the query to the scripting language, and to receive extracted data from the scripting language comprising the requested information subject to the privacy settings of users of the social networking system in response to the query, wherein the distributed database allows an addition by the social networking system of a new field or category of data to the plurality of existing users, the new field or category of data representing an attribute describing each user of the plurality of existing users and storing data directly received from one or more users of the social networking system rather than data derived from one or more existing fields of data; and wherein the structured query language is further configured to receive a request from an application or website maintained by a third party separate from the social networking system, the request identifying the new field or category of data, generate a response to the request comprising the new field or category of data, determine a format for the response to accommodate a database of the third party, convert the response into the determined format, and provide the response in the determined format to the third party. 2. The system of claim 1 , wherein the scripting language is further configured to apply business logic rules to the extracted data before the extracted data is sent to the structured query language interface. | 0.539648 |
8,190,618 | 15 | 20 | 15. A computer program product to aggregate document usage information for an electronic document, the computer program product comprising: one or more computer-readable tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to receive usage indication data for a plurality of users of the electronic document on a segment by segment basis, wherein: the usage indication data provides a measure of time spent using the electronic document; the electronic document is divided into a plurality of segments; and each segment of the plurality of segments of the electronic document has a unique identifier; program instructions, stored on at least one of the one or more storage devices, to aggregate the usage indication data for the plurality of users of the electronic document on a segment by segment basis; and program instructions, stored on at least one of the one or more storage devices, to communicate to a user of the electronic document aggregate usage indication data on a segment by segment basis. | 15. A computer program product to aggregate document usage information for an electronic document, the computer program product comprising: one or more computer-readable tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to receive usage indication data for a plurality of users of the electronic document on a segment by segment basis, wherein: the usage indication data provides a measure of time spent using the electronic document; the electronic document is divided into a plurality of segments; and each segment of the plurality of segments of the electronic document has a unique identifier; program instructions, stored on at least one of the one or more storage devices, to aggregate the usage indication data for the plurality of users of the electronic document on a segment by segment basis; and program instructions, stored on at least one of the one or more storage devices, to communicate to a user of the electronic document aggregate usage indication data on a segment by segment basis. 20. The computer program product of claim 15 , wherein the program instructions to aggregate the usage indication data for the plurality of users of the electronic document on a segment by segment basis aggregate the usage information for a plurality of versions of the electronic document on a segment by segment basis. | 0.5 |
5,566,330 | 2 | 29 | 2. A stored program computer comprising: a central processor and a memory; a client application program in said memory; and a self-contained reusable database interface program object in said memory but external to the client application program and providing an interface between a computer database manager program for managing a database table and said client application program, the database interface object comprising: associations between columns of the database table and associated editing styles, each editing style specifying a display format for data of the associated column, said column/style associations specifying modifying methods for modifying data of respective columns of said database table, said database interface object providing to an applications programmer the ability to tailor said column/style associations to said database table without access to source code of said database interface object; a database communication portion for issuing database commands to the database manager program and receiving database results from the database through the database manager program; a portion, comprising methods, for communicating with said client application program and providing for reuse of said database interface object among a plurality of client application programs, said methods being routines invocable by receipt of a message from the user or client program and including: a retrieve method programmed to accept an invocation message from said client program, execution of said retrieve method using said column/style associations to issue commands to said database manager program to retrieve data from said database table into a buffer maintained by and within said database interface object; said modifying methods accepting directives to modify said retrieved data in said buffer and store a transcript of corresponding modification directives; and an update method programmed to accept an invocation message from said client program, execution of said update method using said column/style associations and said modification directives of said transcript to generate and issue commands to said database manager program to update the data of said database table in accordance with said modification directives. | 2. A stored program computer comprising: a central processor and a memory; a client application program in said memory; and a self-contained reusable database interface program object in said memory but external to the client application program and providing an interface between a computer database manager program for managing a database table and said client application program, the database interface object comprising: associations between columns of the database table and associated editing styles, each editing style specifying a display format for data of the associated column, said column/style associations specifying modifying methods for modifying data of respective columns of said database table, said database interface object providing to an applications programmer the ability to tailor said column/style associations to said database table without access to source code of said database interface object; a database communication portion for issuing database commands to the database manager program and receiving database results from the database through the database manager program; a portion, comprising methods, for communicating with said client application program and providing for reuse of said database interface object among a plurality of client application programs, said methods being routines invocable by receipt of a message from the user or client program and including: a retrieve method programmed to accept an invocation message from said client program, execution of said retrieve method using said column/style associations to issue commands to said database manager program to retrieve data from said database table into a buffer maintained by and within said database interface object; said modifying methods accepting directives to modify said retrieved data in said buffer and store a transcript of corresponding modification directives; and an update method programmed to accept an invocation message from said client program, execution of said update method using said column/style associations and said modification directives of said transcript to generate and issue commands to said database manager program to update the data of said database table in accordance with said modification directives. 29. The stored program computer of claim 2 wherein: said modifying methods are programmed to provide capabilities to invoke at least two of said modifying methods to modify said retrieved data in said buffer between invocation of said retrieve and update methods, said at least two modifying methods being programmed to store corresponding modification directives in said transcript; and said update method being programmed to issue two or more database commands to said database manager program to update the data of said database table in accordance with said transcript of modification directives, said database commands being issued sequentially to said database table until all said modification directives of said transcript are applied or until one of said issued database commands fails. | 0.651926 |
7,809,796 | 8 | 12 | 8. A data processing apparatus, comprising: one or more processors; an HTTP proxy server hosted on one or more of the one or more processors; an SMTP mail transfer agent that is coupled to the HTTP proxy server; electronic mail processing logic that comprises one or more sequences of instructions which, when executed by the one or more processors, cause the one or more processors to perform the steps of: receiving an electronic mail message that comprises one or more hyperlinks; determining sender information that identifies a sender of the electronic mail message; creating and storing a record that associates the sender information with each of the one or more hyperlinks; receiving a request to access a specified hyperlink among the one or more hyperlinks; retrieving, based on the specified hyperlink, the record; retrieving, based on the sender information associated with the specified hyperlink, sender reputation information associated with the sender; determining, based on the sender reputation information, a particular action among a plurality of allowed actions; issuing a network request to access the specified hyperlink only when the particular action is allowing user access to the specified hyperlink. | 8. A data processing apparatus, comprising: one or more processors; an HTTP proxy server hosted on one or more of the one or more processors; an SMTP mail transfer agent that is coupled to the HTTP proxy server; electronic mail processing logic that comprises one or more sequences of instructions which, when executed by the one or more processors, cause the one or more processors to perform the steps of: receiving an electronic mail message that comprises one or more hyperlinks; determining sender information that identifies a sender of the electronic mail message; creating and storing a record that associates the sender information with each of the one or more hyperlinks; receiving a request to access a specified hyperlink among the one or more hyperlinks; retrieving, based on the specified hyperlink, the record; retrieving, based on the sender information associated with the specified hyperlink, sender reputation information associated with the sender; determining, based on the sender reputation information, a particular action among a plurality of allowed actions; issuing a network request to access the specified hyperlink only when the particular action is allowing user access to the specified hyperlink. 12. An apparatus as recited in claim 8 , wherein the sender information comprises a network address of a sender of the electronic mail message. | 0.704545 |
7,596,749 | 6 | 10 | 6. A computer-implemented system for extracting status information from within a script of a web page stored on a monitored device communicatively coupled to a network using an HTTP communication protocol, comprising: means for obtaining, based on vendor and model information, an identification of the web page and at least one parameter string used to extract the status information from within the script of the web page; means for accessing the web page using the identification of the web page and the HTTP protocol to obtain a line of the web page within the script; means for parsing the obtained line of the web page to determine if a parameter string of the at least one parameter string is located within the obtained line; means for causing the repeated execution of the means for accessing and the means for parsing until the parameter string is located, if the means for parsing determines that the parameter string is not located within the obtained line; means for determining whether all parameter strings in the at least one parameter string have been located, if the means for parsing determines that the parameter string is located within the obtained line; means for causing the repeated execution of the means for accessing, the means for parsing, the means for causing, and the means for determining until all parameter strings in the at least one parameter string have been located, if the means for determining determines that all parameter strings in the at least one parameter string have not been located; and means for extracting the status information from the web page based on the location of a last located parameter string, if the means for determining determines that all parameter strings have been located within the script. | 6. A computer-implemented system for extracting status information from within a script of a web page stored on a monitored device communicatively coupled to a network using an HTTP communication protocol, comprising: means for obtaining, based on vendor and model information, an identification of the web page and at least one parameter string used to extract the status information from within the script of the web page; means for accessing the web page using the identification of the web page and the HTTP protocol to obtain a line of the web page within the script; means for parsing the obtained line of the web page to determine if a parameter string of the at least one parameter string is located within the obtained line; means for causing the repeated execution of the means for accessing and the means for parsing until the parameter string is located, if the means for parsing determines that the parameter string is not located within the obtained line; means for determining whether all parameter strings in the at least one parameter string have been located, if the means for parsing determines that the parameter string is located within the obtained line; means for causing the repeated execution of the means for accessing, the means for parsing, the means for causing, and the means for determining until all parameter strings in the at least one parameter string have been located, if the means for determining determines that all parameter strings in the at least one parameter string have not been located; and means for extracting the status information from the web page based on the location of a last located parameter string, if the means for determining determines that all parameter strings have been located within the script. 10. The system of claim 6 , wherein means for accessing comprises: means for accessing an HTML file stored on the monitored device to obtain a line of the HTML file within a JAVA script. | 0.518135 |
7,607,082 | 1 | 8 | 1. A computer-implemented method comprising: analyzing, using multiple block function criteria, content of a document; assigning, based on the analyzing, a respective block function of multiple block functions to semantic blocks of the content; and generating one or more customized documents for browsing by a user, each customized document having a respective layout based on block function(s) assigned to respective ones of the semantic blocks, wherein the analyzing comprises: partitioning the document into multiple semantic blocks; for each semantic block of the semantic blocks, extracting spatial features and content features; for each semantic block of the semantic blocks, generating a respective feature vector from respective spatial and content features; creating a semantic tree of the document from respective feature vectors generated from the semantic blocks, the semantic tree grouping related content in respective blocks of the multiple semantic blocks; and assigning a respective degree of coherence to node(s) of the semantic tree. | 1. A computer-implemented method comprising: analyzing, using multiple block function criteria, content of a document; assigning, based on the analyzing, a respective block function of multiple block functions to semantic blocks of the content; and generating one or more customized documents for browsing by a user, each customized document having a respective layout based on block function(s) assigned to respective ones of the semantic blocks, wherein the analyzing comprises: partitioning the document into multiple semantic blocks; for each semantic block of the semantic blocks, extracting spatial features and content features; for each semantic block of the semantic blocks, generating a respective feature vector from respective spatial and content features; creating a semantic tree of the document from respective feature vectors generated from the semantic blocks, the semantic tree grouping related content in respective blocks of the multiple semantic blocks; and assigning a respective degree of coherence to node(s) of the semantic tree. 8. A method as recited in claim 1 , wherein generating the one or more customized documents further comprises configuring layout of the one or more customized documents to generate a thumbnail view, an optimized one-column view, or a main content view for each of the one or more customized documents. | 0.734099 |
9,760,562 | 1 | 6 | 1. A computer system, for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the computer system comprising: a processor set; and a software storage device; wherein: the processor set is structured, located, connected or programmed to run software stored on the software storage device; and the software comprises: first program instructions programmed to set up and maintain a synchronous computer-mediated communication system between a plurality of chat participants; second program instructions programmed to check for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and third program instructions programmed to take a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant. | 1. A computer system, for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the computer system comprising: a processor set; and a software storage device; wherein: the processor set is structured, located, connected or programmed to run software stored on the software storage device; and the software comprises: first program instructions programmed to set up and maintain a synchronous computer-mediated communication system between a plurality of chat participants; second program instructions programmed to check for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and third program instructions programmed to take a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant. 6. The computer system of claim 1 wherein: performing a first text analytics analysis includes using a context hint provided in the list, the context hint corresponding to the text-based signal; and the context hint is a contextual clue that supports a determination of whether the text-based signal indicates potential frustration as evidenced by the text transcript. | 0.561905 |
8,751,284 | 1 | 3 | 1. A non-transitory computer-readable medium containing code executable by a computer processor to generate a workflow engine comprising: a Petri net domain model comprising a set of objects comprising a token object, a place object, an arc object, a transition object, and one or more trigger objects, wherein (a) each object represents a particular type of element of a Petri net model and (b) the one or more trigger objects represent triggering a transition object based at least in part on stimuli external to the workflow engine; and one or more runtime components configured for: reading source code representing a particular workflow, wherein the source code indicates elements of the particular workflow and connectors between elements of the particular workflow to sequence the elements of the particular workflow; loading the particular workflow into memory by mapping each element of the particular workflow to one or more objects of the set of objects and by mapping each connector of the particular workflow to one or more objects of the set of objects based on rules governing the Petri net model; and executing the particular workflow loaded into the memory, wherein the workflow engine further comprises one or more abstraction layer components comprising a transition layer from the Petri net domain model to an operating system, the abstraction layer configured to delegate one or more tasks associated with elements of the particular workflow of the Petri net domain to the operating system, via the transition layer, the delegated tasks to be performed by the operating system. | 1. A non-transitory computer-readable medium containing code executable by a computer processor to generate a workflow engine comprising: a Petri net domain model comprising a set of objects comprising a token object, a place object, an arc object, a transition object, and one or more trigger objects, wherein (a) each object represents a particular type of element of a Petri net model and (b) the one or more trigger objects represent triggering a transition object based at least in part on stimuli external to the workflow engine; and one or more runtime components configured for: reading source code representing a particular workflow, wherein the source code indicates elements of the particular workflow and connectors between elements of the particular workflow to sequence the elements of the particular workflow; loading the particular workflow into memory by mapping each element of the particular workflow to one or more objects of the set of objects and by mapping each connector of the particular workflow to one or more objects of the set of objects based on rules governing the Petri net model; and executing the particular workflow loaded into the memory, wherein the workflow engine further comprises one or more abstraction layer components comprising a transition layer from the Petri net domain model to an operating system, the abstraction layer configured to delegate one or more tasks associated with elements of the particular workflow of the Petri net domain to the operating system, via the transition layer, the delegated tasks to be performed by the operating system. 3. The computer-readable medium of claim 1 wherein each object of the set of objects is a class in a computer programming language. | 0.755597 |
9,934,429 | 1 | 2 | 1. A non-transitory computer-readable storage medium storing therein a recognition program that causes a computer to execute a process comprising: recognizing a plurality of characters from handwritten characters in input handwritten data; setting reference positions of a specific handwritten character and an adjacent handwritten character included in the handwritten characters based on recognition results of the recognized characters, the specific handwritten character and the adjacent handwritten character corresponding to a specific character and an adjacent character included in the recognized characters, respectively, the adjacent character being located adjacent to the specific character; determining whether a space is present between the specific character and the adjacent character based on the reference positions; and generating space information indicating a result of the determining, wherein each of the reference positions is a position of a vertical stroke in or a position of a central axis of a corresponding one of the specific handwritten character and the adjacent handwritten character. | 1. A non-transitory computer-readable storage medium storing therein a recognition program that causes a computer to execute a process comprising: recognizing a plurality of characters from handwritten characters in input handwritten data; setting reference positions of a specific handwritten character and an adjacent handwritten character included in the handwritten characters based on recognition results of the recognized characters, the specific handwritten character and the adjacent handwritten character corresponding to a specific character and an adjacent character included in the recognized characters, respectively, the adjacent character being located adjacent to the specific character; determining whether a space is present between the specific character and the adjacent character based on the reference positions; and generating space information indicating a result of the determining, wherein each of the reference positions is a position of a vertical stroke in or a position of a central axis of a corresponding one of the specific handwritten character and the adjacent handwritten character. 2. The storage medium as claimed in claim 1 , the process further comprising: determining a character string in the handwritten data based on the recognition results and the space information. | 0.847377 |
7,936,476 | 1 | 7 | 1. A method for setting font pitch during a print process, the method comprising: using a computer which is programmed to perform the following: displaying on a graphical user interface a target template for receiving information being parsed from a spool file generated in response to a print command being issued by an application, wherein in the target template is an image of a consumable business form with a plurality of target zones for printing at least a portion of the information from the spool file thereon; graphically indicating on the graphical user interface at least one of the plurality of target zones in the target template for receiving the portion of the information from the spool file thereinto; generating an output file based on the spool file that has been generated, the output file comprising a set of information extracted from the spool file based on a set of source zones within the spool file as defined by a source template, the set of information comprises a set of characters; modifying the set of information within the output file to conform to the target template by including the plurality of target zones within the output file to form an image to print onto a consumable business form; determining whether each character in the set of characters in the output file is a numeric type or non-numeric type; setting, in the output file within the plurality of target zones in to print onto the consumable business form, a font pitch of each character based on the plurality of target zones to: a fixed pitch font in response to the character being the numeric type, thereby aligning the characters within at least one column of the output file; or a variable pitch font in response to the character being the non-numeric type; and sending the output file to an output destination. | 1. A method for setting font pitch during a print process, the method comprising: using a computer which is programmed to perform the following: displaying on a graphical user interface a target template for receiving information being parsed from a spool file generated in response to a print command being issued by an application, wherein in the target template is an image of a consumable business form with a plurality of target zones for printing at least a portion of the information from the spool file thereon; graphically indicating on the graphical user interface at least one of the plurality of target zones in the target template for receiving the portion of the information from the spool file thereinto; generating an output file based on the spool file that has been generated, the output file comprising a set of information extracted from the spool file based on a set of source zones within the spool file as defined by a source template, the set of information comprises a set of characters; modifying the set of information within the output file to conform to the target template by including the plurality of target zones within the output file to form an image to print onto a consumable business form; determining whether each character in the set of characters in the output file is a numeric type or non-numeric type; setting, in the output file within the plurality of target zones in to print onto the consumable business form, a font pitch of each character based on the plurality of target zones to: a fixed pitch font in response to the character being the numeric type, thereby aligning the characters within at least one column of the output file; or a variable pitch font in response to the character being the non-numeric type; and sending the output file to an output destination. 7. The method of claim 1 , wherein determining the type of each character further comprises: determining whether each character in the output file is a numeric -type used to denote currency and/or a number of items and a non-numeric type used to denote all else. | 0.782392 |
9,607,035 | 10 | 11 | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: generate a candidate answer to an input question using a natural language processing of the input question and a corpus of information from which the candidate answer is identified; select a validator to apply to the candidate answer based on a characteristic of a correct answer for the input question; apply the validator to the candidate answer to evaluate whether or not one or more criteria of the validator are satisfied by the candidate answer; generate validation information based the evaluation of whether or not criteria of the validator are met by the candidate answer; and store the validation information in a validation status object associated with the input question, wherein the validator is one of a plurality of validators registered with a pluggable validator framework, and wherein registration of the validator with the pluggable validator framework comprises specifying for which answer type or answer extension type in an answer key data structure the validator corresponds to. | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: generate a candidate answer to an input question using a natural language processing of the input question and a corpus of information from which the candidate answer is identified; select a validator to apply to the candidate answer based on a characteristic of a correct answer for the input question; apply the validator to the candidate answer to evaluate whether or not one or more criteria of the validator are satisfied by the candidate answer; generate validation information based the evaluation of whether or not criteria of the validator are met by the candidate answer; and store the validation information in a validation status object associated with the input question, wherein the validator is one of a plurality of validators registered with a pluggable validator framework, and wherein registration of the validator with the pluggable validator framework comprises specifying for which answer type or answer extension type in an answer key data structure the validator corresponds to. 11. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to select a validator to apply to the candidate answer based on a characteristic of the correct answer for the input question at least by: performing a lookup operation in an answer key data structure for an entry corresponding to a question type of the input question, wherein the entry comprises at least one of an answer type or an answer extension type, and wherein the answer type is either a literal answer type or a regular expression answer type and the answer extension type is an extended answer type other than a literal answer type or regular expression answer type; and selecting the validator based on a correspondence between the validator and at least one of the answer type or the answer extension type. | 0.5 |
6,018,708 | 32 | 34 | 32. A machine readable storage medium containing a program element for directing a computer to recognize a spoken utterance, the computer including: memory unit including: a) a speech recognition dictionary including a plurality of orthographies potentially recognizable on a basis of the spoken utterance; b) a standard text lexicon including a plurality of orthographies; processor in operative relationship with the memory unit, said program clement being executable by the processor and being operative for: a) processing said speech recognition dictionary to derive on the basis of the spoken utterance a list of orthographies, said list containing a plurality of orthographies, each orthography in said list being a candidate having a certain probability to correspond to the spoken utterance; b) inserting at least one orthography from the standard text lexicon into said list to form an augmented list. | 32. A machine readable storage medium containing a program element for directing a computer to recognize a spoken utterance, the computer including: memory unit including: a) a speech recognition dictionary including a plurality of orthographies potentially recognizable on a basis of the spoken utterance; b) a standard text lexicon including a plurality of orthographies; processor in operative relationship with the memory unit, said program clement being executable by the processor and being operative for: a) processing said speech recognition dictionary to derive on the basis of the spoken utterance a list of orthographies, said list containing a plurality of orthographies, each orthography in said list being a candidate having a certain probability to correspond to the spoken utterance; b) inserting at least one orthography from the standard text lexicon into said list to form an augmented list. 34. A machine readable storage medium as defined in claim 32, wherein said program element instructing the processor to rank orthographies in the augmented list on a basis of acoustic match with the spoken utterance. | 0.598513 |
10,042,927 | 26 | 29 | 26. One or more non-transitory computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request by a client device to access a first content that is not available from a first Web domain; identifying at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying the first content that is not available based on the at least one interest keyword; identifying a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. | 26. One or more non-transitory computer readable storage media storing computer-executable instructions for performing a computer process, the computer process comprising: receiving a request by a client device to access a first content that is not available from a first Web domain; identifying at least one interest keyword based on a combination of keywords that yield search results including the first Web domain and a user's clickstream data responsive to the search results; classifying the first content that is not available based on the at least one interest keyword; identifying a second web domain based on historical relevance data and the classification of the first content that is not available, the historical relevance data including one or more previous attempts to access the first Web domain and session data representing activity performed with respect to the first Web domain; and providing the user access to second content similar to the first content from the second Web domain using the identified at least one keyword. 29. The one or more computer readable storage media of claim 26 , wherein the computer process further comprises: receiving the user's keyword search results and the user's clickstream data prior to the identifying operation. | 0.762658 |
9,767,158 | 15 | 16 | 15. A server computer system comprising: a processing device; a memory coupled to the processing device; and a user bucketing module, executable by the processing device from the memory, to: identify, in a content sharing platform, a bucket comprising a plurality of content items associated with a group of users of the content sharing platform that have similar interests; associate a bucketing token pertaining to the bucket with each of the plurality of content items the bucketing token comprising a unique identifier that identifies the plurality of content items as being associated with the group of users of the content sharing platform that have similar interests; receive a request for the bucketing token from a ranking service; and provide the bucketing token to the ranking service, the ranking service to use the bucketing token to determine, with respect to a first user of a social network platform, a ranking score for a content item of the plurality of associated content items in view of one or more interests of the first user of the social network platform that is separate from the content sharing platform. | 15. A server computer system comprising: a processing device; a memory coupled to the processing device; and a user bucketing module, executable by the processing device from the memory, to: identify, in a content sharing platform, a bucket comprising a plurality of content items associated with a group of users of the content sharing platform that have similar interests; associate a bucketing token pertaining to the bucket with each of the plurality of content items the bucketing token comprising a unique identifier that identifies the plurality of content items as being associated with the group of users of the content sharing platform that have similar interests; receive a request for the bucketing token from a ranking service; and provide the bucketing token to the ranking service, the ranking service to use the bucketing token to determine, with respect to a first user of a social network platform, a ranking score for a content item of the plurality of associated content items in view of one or more interests of the first user of the social network platform that is separate from the content sharing platform. 16. The server computer system of claim 15 , wherein to identify the bucket, the user bucketing module further to: identifying the first user of the content sharing platform; identifying a first set of content items previously viewed by the first user on the content sharing platform; identifying a second set of content items previously viewed by a second user of the content sharing platform, wherein the second user also viewed the first set of content items; determining if a bucket that contains both the first and second sets of content items exists in the content sharing platform; and if a bucket that contains both the first and second sets of content items does not exist, creating a new bucket. | 0.5 |
9,652,496 | 13 | 14 | 13. A system comprising: one or more first computers and one or more first storage devices storing instructions that are operable, when executed by the one or more first computers, to cause the one or more first computers to implement a select operator node that is operable to request, from a first table, one or more tuples having respective values according to a predicate expression in a query; one or more second computers and one or more second storage devices storing instructions that are operable, when executed by the one or more second computers, to cause the one or more second computers to implement a partition selector node that is operable to determine, from the predicate expression in the query according to a partition selection function, one or more partitions of a table that may include tuples having respective values that satisfy the predicate expression and provides respective identifiers for the one or more partitions to a dynamic scanner node; one or more third computers and one or more third storage devices storing instructions that are operable, when executed by the one or more third computers, to cause the one or more third computers to implement a dynamic scanner node that is operable to receive, from the partition selector node, respective identifiers of the one or more partitions, obtains tuples of the one or more partitions from storage, and provides the one or more obtained tuples to the select operator node; and one or more fourth computers and one or more fourth storage devices storing instructions that are operable, when executed by the one or more fourth computers, to cause the one or more fourth computers to implement a master node that is operable to generate, using a representation of a query plan for the query, a modified query plan for the query that comprises a plurality of operators that, when executed by one or more computing nodes, cause the one or more computing nodes to compute a result for the query, wherein the modified query plan includes a select operator that represents the select operator node, a partition selector operator that represents the partition selector node, and a dynamic scan operator that represents the dynamic scanner node; and wherein the master node is operable to generate the modified query plan by determining a location in the query plan for the partition selector operator by performing operations comprising: determining, for each operator of a subset of operators in the query plan, whether the dynamic scan operator occurs in a subtree of the query plan that is rooted at the respective operator of the subset of operators; determining, using results of the determinations of whether the dynamic scan operator occurs in a subtree of the query plan that is rooted at the respective operator of the subset of operators, a first operator in the query plan that is i) a parent operator of the partition selector operator and the dynamic scan operator or ii) a child operator of the partition selector operator; and determining, using the first operator, the location in the query plan for the partition selector operator. | 13. A system comprising: one or more first computers and one or more first storage devices storing instructions that are operable, when executed by the one or more first computers, to cause the one or more first computers to implement a select operator node that is operable to request, from a first table, one or more tuples having respective values according to a predicate expression in a query; one or more second computers and one or more second storage devices storing instructions that are operable, when executed by the one or more second computers, to cause the one or more second computers to implement a partition selector node that is operable to determine, from the predicate expression in the query according to a partition selection function, one or more partitions of a table that may include tuples having respective values that satisfy the predicate expression and provides respective identifiers for the one or more partitions to a dynamic scanner node; one or more third computers and one or more third storage devices storing instructions that are operable, when executed by the one or more third computers, to cause the one or more third computers to implement a dynamic scanner node that is operable to receive, from the partition selector node, respective identifiers of the one or more partitions, obtains tuples of the one or more partitions from storage, and provides the one or more obtained tuples to the select operator node; and one or more fourth computers and one or more fourth storage devices storing instructions that are operable, when executed by the one or more fourth computers, to cause the one or more fourth computers to implement a master node that is operable to generate, using a representation of a query plan for the query, a modified query plan for the query that comprises a plurality of operators that, when executed by one or more computing nodes, cause the one or more computing nodes to compute a result for the query, wherein the modified query plan includes a select operator that represents the select operator node, a partition selector operator that represents the partition selector node, and a dynamic scan operator that represents the dynamic scanner node; and wherein the master node is operable to generate the modified query plan by determining a location in the query plan for the partition selector operator by performing operations comprising: determining, for each operator of a subset of operators in the query plan, whether the dynamic scan operator occurs in a subtree of the query plan that is rooted at the respective operator of the subset of operators; determining, using results of the determinations of whether the dynamic scan operator occurs in a subtree of the query plan that is rooted at the respective operator of the subset of operators, a first operator in the query plan that is i) a parent operator of the partition selector operator and the dynamic scan operator or ii) a child operator of the partition selector operator; and determining, using the first operator, the location in the query plan for the partition selector operator. 14. The system of claim 13 , further comprising: a sequence operator that causes the dynamic scanner node to begin obtaining tuples from the one or more partitions after the partition selector node has provided all the respective identifiers to the dynamic scanner node. | 0.764398 |
8,701,087 | 12 | 14 | 12. A system for controlling a computer system to annotate software objects, comprising: a server computer that is configured to connect to a client computer via a network, wherein the server computer is configured to determine a software object, wherein the software object is an instance of a class in an object-oriented computing environment; wherein the server computer is configured to determine a plurality of rules based on the class, wherein the plurality of rules define how to annotate a software object, wherein the server computer is configured to process the software object according to the plurality of rules, wherein the server computer is configured to generate an annotation document based on the software object having been processed according to the plurality of rules, and wherein the server computer is configured to generate an annotated software object based on the software object and the annotation document, wherein the annotated software object corresponds to the software object as annotated by the annotation document; wherein the server computer is configured to process the software object in a non-intrusive manner with regard to the software component such that the software component is not modified; and wherein the plurality of rules define how to create the annotation document, wherein the plurality of rules includes a plurality of categories and a plurality of relations, and wherein the plurality of categories and the plurality of relations relate to a domain ontology. | 12. A system for controlling a computer system to annotate software objects, comprising: a server computer that is configured to connect to a client computer via a network, wherein the server computer is configured to determine a software object, wherein the software object is an instance of a class in an object-oriented computing environment; wherein the server computer is configured to determine a plurality of rules based on the class, wherein the plurality of rules define how to annotate a software object, wherein the server computer is configured to process the software object according to the plurality of rules, wherein the server computer is configured to generate an annotation document based on the software object having been processed according to the plurality of rules, and wherein the server computer is configured to generate an annotated software object based on the software object and the annotation document, wherein the annotated software object corresponds to the software object as annotated by the annotation document; wherein the server computer is configured to process the software object in a non-intrusive manner with regard to the software component such that the software component is not modified; and wherein the plurality of rules define how to create the annotation document, wherein the plurality of rules includes a plurality of categories and a plurality of relations, and wherein the plurality of categories and the plurality of relations relate to a domain ontology. 14. The system of claim 12 , wherein the server computer is configured to execute a storage component, an annotation engine component, and an application programming interface component, wherein the storage component is configured to store the plurality of rules, wherein the annotation engine component is configured to process the software object according to the plurality of rules, and to generate an annotation document based on the software object having been processed according to the plurality of rules, and wherein the application programming interface component is configured to generate the annotated software object based on the software object and the annotation document. | 0.5 |
9,898,529 | 8 | 10 | 8. A computer program product for augmenting a semantic model from unstructured data, the computer program product comprising: a computer readable storage medium having program instructions embodied therewith, wherein the program instructions are executable by a computer processor to cause the computer processor to perform a method comprising: determining a root of a first element selected from a domain of a semantic model, wherein the domain includes a plurality of elements that lack relationship information between the plurality of elements; generating a search token, based at least in part on morphological rules applied to the root of the first element and a preposition added to the root of the first element, wherein a selection of the preposition that is added to the root of the first element depends upon whether the root is determined as a noun or a verb, as the root occurs in the first element of the domain of the semantic model; performing a search of one or more unstructured data sources, based on the search token that is generated; determining whether results of the search, at least one phrase that contains an approximate match to the search token; in response to determining the results of the search include at least one phrase that contains an approximate match to the search token, generating a triple from the at least one phrase, and adding the triple to the semantic model; and adding a predicate of the triple, to a second element of the domain of the semantic model forming a second triple, wherein the predicate of the triple expresses a relationship between the first element of the domain of the semantic model and the second element of the domain of the semantic model. | 8. A computer program product for augmenting a semantic model from unstructured data, the computer program product comprising: a computer readable storage medium having program instructions embodied therewith, wherein the program instructions are executable by a computer processor to cause the computer processor to perform a method comprising: determining a root of a first element selected from a domain of a semantic model, wherein the domain includes a plurality of elements that lack relationship information between the plurality of elements; generating a search token, based at least in part on morphological rules applied to the root of the first element and a preposition added to the root of the first element, wherein a selection of the preposition that is added to the root of the first element depends upon whether the root is determined as a noun or a verb, as the root occurs in the first element of the domain of the semantic model; performing a search of one or more unstructured data sources, based on the search token that is generated; determining whether results of the search, at least one phrase that contains an approximate match to the search token; in response to determining the results of the search include at least one phrase that contains an approximate match to the search token, generating a triple from the at least one phrase, and adding the triple to the semantic model; and adding a predicate of the triple, to a second element of the domain of the semantic model forming a second triple, wherein the predicate of the triple expresses a relationship between the first element of the domain of the semantic model and the second element of the domain of the semantic model. 10. The computer program product of claim 8 , further comprising: parsing the at least one phrase to form a phrase-structure tree; determining a type of phrase for each portion of the phrase-structure tree, and a part of speech for each word of each portion of the phrase-structure tree; determining a probability of an accurate determination of the type of phrase and part of speech of each portion of the phrase-structure tree; and generating a triple from the phrase-structure tree based on the parsing, the determining of the type of phrase and the part of speech, and the determining of the probability of the accurate determination of the type of phrase and the part of speech, wherein the triple includes a subject, a predicate, and an object. | 0.5 |
7,500,201 | 8 | 14 | 8. A data input method comprising: executing a script that is a list of commands that are embedded in the Hypertext Markup Language code defining a web page and can be executed by or within the browser; generating and displaying on a web page a graphical data input field as a non-menu, text-input graphic device in place of the defined drop-down menu; however, the graphical input device has the general appearance of the drop-down menu and is associated with the input parameter; sensing user entry in the graphical data input field of a character sequence including at least one character; associating an ordered set of data containing at least two selection lists, each one of said at least two selection lists including at least two character strings; associating at least two character strings from said at least two selection lists wherein each character string of said at least two selection lists is separated by a delimiter from an adjacent character string of said at least two selection lists; searching sequentially and character-by-character each character string of one of said at least two selection lists according to each user-entered character for a character match; searching as needed sequentially and character-by-character each character string of each remaining list of said at least two selection lists according to each user entered character for a character match; matching each character sequence with each character string of said at least two selection lists; sensing an acceptance action by the user, reflecting the current user selected choice. | 8. A data input method comprising: executing a script that is a list of commands that are embedded in the Hypertext Markup Language code defining a web page and can be executed by or within the browser; generating and displaying on a web page a graphical data input field as a non-menu, text-input graphic device in place of the defined drop-down menu; however, the graphical input device has the general appearance of the drop-down menu and is associated with the input parameter; sensing user entry in the graphical data input field of a character sequence including at least one character; associating an ordered set of data containing at least two selection lists, each one of said at least two selection lists including at least two character strings; associating at least two character strings from said at least two selection lists wherein each character string of said at least two selection lists is separated by a delimiter from an adjacent character string of said at least two selection lists; searching sequentially and character-by-character each character string of one of said at least two selection lists according to each user-entered character for a character match; searching as needed sequentially and character-by-character each character string of each remaining list of said at least two selection lists according to each user entered character for a character match; matching each character sequence with each character string of said at least two selection lists; sensing an acceptance action by the user, reflecting the current user selected choice. 14. A data input method as in claim 8 defining the mark-up language as selected from the group including Hypertext Markup Language derivatives. | 0.830569 |
9,367,571 | 1 | 2 | 1. A method for collaboratively accessing information resources in a computer network by specifying a class of parameterized information requests and making instances of parameterized information requests that belong to the class, the method implemented by a processor having access to a data storage, the method, comprising: accessing, by the processor, objects in the data storage including a connector object in the data storage, the connector object representing the class of parameterized information requests; providing, by the processor, a request parameter object in the data storage that defines a request parameter for parameterized information requests belonging to the class; providing, by the processor, a bind parameter and a bind parameter value; using the request parameter in an instance of a parameterized information request, comprising replacing the bind parameter with the bind value; and providing, by the processor, an information source access object in the data storage that specifies attributes of an information source which will receive the instances of the parameterized information request that belong to the class, the processor responding to an input specifying creation of an instance of the class of parameterized information requests represented by the connector object by using the request parameter defined in the request parameter object and the attributes of the source of information to make the instance of the class. | 1. A method for collaboratively accessing information resources in a computer network by specifying a class of parameterized information requests and making instances of parameterized information requests that belong to the class, the method implemented by a processor having access to a data storage, the method, comprising: accessing, by the processor, objects in the data storage including a connector object in the data storage, the connector object representing the class of parameterized information requests; providing, by the processor, a request parameter object in the data storage that defines a request parameter for parameterized information requests belonging to the class; providing, by the processor, a bind parameter and a bind parameter value; using the request parameter in an instance of a parameterized information request, comprising replacing the bind parameter with the bind value; and providing, by the processor, an information source access object in the data storage that specifies attributes of an information source which will receive the instances of the parameterized information request that belong to the class, the processor responding to an input specifying creation of an instance of the class of parameterized information requests represented by the connector object by using the request parameter defined in the request parameter object and the attributes of the source of information to make the instance of the class. 2. The method of claim 1 , wherein: the request parameter object defines a plurality of request parameters; and the input further specifies a request parameter of the plurality of request parameters, and the method further comprises responding, by the processor to the input by using the specified request parameter to make the instance of the class. | 0.832856 |
9,158,757 | 11 | 12 | 11. A non-transitory computer-readable medium having computer-executable instructions for use in a continuous stroke system having a virtual keyboard with an integrated correction display, comprising: instructions for receiving a portion of a first part of a continuous stroke which has been input into a virtual keyboard, wherein the first part of the continuous stroke corresponds to locations, on the virtual keyboard, of multiple letters of the beginning of a word in sequence, without indicating a last letter of the word; and wherein the portion of the first part of the continuous stroke corresponds to one or more initial letters that comprise less than all the letters of the word; instructions for determining, while the first part of the continuous stroke is being received and before the last letter corresponding to the first part of the continuous stroke has been indicated, a matching set of word patterns that at least partially match the first part of the continuous stroke, wherein the determining is performed, at least in part, by comparing the received portion of the first part of the continuous stroke with an initial portion of multiple known word patterns which correspond to multiple known words; instructions for generating, from the matching set of word patterns, multiple known words which correspond to the received portion of the first part of the continuous stroke; instructions for displaying, in response to a trigger event, at least one of the multiple known words on the integrated correction display, integrated with the virtual keyboard, before the continuous stroke has been completed, wherein the trigger event is based on a comparison between speed information concerning a current rate of movement of the continuous stroke and a threshold speed value; and instructions for updating the received portion of the first part of the continuous stroke with a second part of the continuous stroke which has been input into the virtual keyboard before the last letter corresponding to the first part of the continuous stroke has been indicated. | 11. A non-transitory computer-readable medium having computer-executable instructions for use in a continuous stroke system having a virtual keyboard with an integrated correction display, comprising: instructions for receiving a portion of a first part of a continuous stroke which has been input into a virtual keyboard, wherein the first part of the continuous stroke corresponds to locations, on the virtual keyboard, of multiple letters of the beginning of a word in sequence, without indicating a last letter of the word; and wherein the portion of the first part of the continuous stroke corresponds to one or more initial letters that comprise less than all the letters of the word; instructions for determining, while the first part of the continuous stroke is being received and before the last letter corresponding to the first part of the continuous stroke has been indicated, a matching set of word patterns that at least partially match the first part of the continuous stroke, wherein the determining is performed, at least in part, by comparing the received portion of the first part of the continuous stroke with an initial portion of multiple known word patterns which correspond to multiple known words; instructions for generating, from the matching set of word patterns, multiple known words which correspond to the received portion of the first part of the continuous stroke; instructions for displaying, in response to a trigger event, at least one of the multiple known words on the integrated correction display, integrated with the virtual keyboard, before the continuous stroke has been completed, wherein the trigger event is based on a comparison between speed information concerning a current rate of movement of the continuous stroke and a threshold speed value; and instructions for updating the received portion of the first part of the continuous stroke with a second part of the continuous stroke which has been input into the virtual keyboard before the last letter corresponding to the first part of the continuous stroke has been indicated. 12. The non-transitory computer-readable medium of claim 11 : wherein the continuous stroke is associated with an active application; and wherein the computer-readable medium further comprises instructions for outputting to the associated active application a user selected one of the multiple known words. | 0.867761 |
7,565,345 | 11 | 29 | 11. A system, comprising: one or more computers, and one or more processors configured to perform operations comprising: generating revised queries for an initial query using differing query revision strategies; calculating a confidence measure for each revised query based on a frequency of occurrence of a query pair comprising the revised query and the initial query; comparing the confidence measures amongst the generated revised queries; automatically selecting a subset of the revised queries based on the comparison, the subset of the revised queries including fewer than all of the revised queries; evaluating search results associated with each query of the subset of the revised queries; automatically selecting a subset of the evaluated search results associated with each revised query of the subset of the revised queries, the subset of the evaluated search results including, for each of the revised queries, fewer than all of the evaluated search results; providing, on a first web page, initial search results associated with the initial query; and providing, on a second web page, a simultaneous display of a plurality of revised queries from the subset of the revised queries and, with each of the plurality of revised queries, one or more evaluated search results associated with the respective query. | 11. A system, comprising: one or more computers, and one or more processors configured to perform operations comprising: generating revised queries for an initial query using differing query revision strategies; calculating a confidence measure for each revised query based on a frequency of occurrence of a query pair comprising the revised query and the initial query; comparing the confidence measures amongst the generated revised queries; automatically selecting a subset of the revised queries based on the comparison, the subset of the revised queries including fewer than all of the revised queries; evaluating search results associated with each query of the subset of the revised queries; automatically selecting a subset of the evaluated search results associated with each revised query of the subset of the revised queries, the subset of the evaluated search results including, for each of the revised queries, fewer than all of the evaluated search results; providing, on a first web page, initial search results associated with the initial query; and providing, on a second web page, a simultaneous display of a plurality of revised queries from the subset of the revised queries and, with each of the plurality of revised queries, one or more evaluated search results associated with the respective query. 29. The system of claim 11 , wherein the initial query represents a previously revised query. | 0.906439 |
8,271,476 | 17 | 18 | 17. The method of claim 15 , further comprising calculating the mathematical difference by computing a difference vector running from an end of a first vector representing the first community user fingerprint to an end of a second vector representing the second community user fingerprint. | 17. The method of claim 15 , further comprising calculating the mathematical difference by computing a difference vector running from an end of a first vector representing the first community user fingerprint to an end of a second vector representing the second community user fingerprint. 18. The method of claim 17 , further comprising finding specific documents that discuss the side effects of drugs by calculating a mathematical overlap between the difference vector and vectors of the documents that contributed to the difference vector. | 0.5 |
7,865,519 | 12 | 13 | 12. A system for generating business component names, the system comprising: memory; and a data processing apparatus communicatively coupled to the memory, the data processing apparatus operable to: present a plurality of selectable business process models to a user in response to at least a request to add a business data component to a business process model, the request including a textual description of the business data component generated by the user; receive a selection of one of the plurality of business models; in response to at least the request for the selection, execute software means for identifying terms from a library, including associates between the terms, used to generate proposed names for business data components in connection with adding the business data components to business process models, the library includes terms and associates for each of the plurality of selectable business models; execute software means for searching the identified terms and the associations between the identified terms using a matching algorithm and the textual description to select terms associated with the business data component and used to add business components to the selected business model; execute software means for combining at least a portion of the selected terms to generate at least one proposed name for the business data component in accordance with a predefined naming format, the predefined naming format defining a name as including a plurality of terms for semantically describing a business data component, wherein the plurality of terms include at least two terms from the group consisting of an object class term, a property term, a representation class term, a qualifier term, a context category, and a context value; execute software means for receiving context information for defining the business data component; identify a predefined business data model based on the context information; receive a request to add the business data component to the business data model, wherein the matching algorithm uses a context defined by at least one of the context information or the predefined business data model to select terms from the library of available terms; update the selected business process model with the business data component using the proposed name, wherein the at least one proposed name includes a business data component name included in a business data model for a different context; and a topic map defines associations between a plurality of business data models including the predefined business data model and the business data model for the different context, identifying the business data model for the different context based on a relationship with the predefined business data model defined in the topic map. | 12. A system for generating business component names, the system comprising: memory; and a data processing apparatus communicatively coupled to the memory, the data processing apparatus operable to: present a plurality of selectable business process models to a user in response to at least a request to add a business data component to a business process model, the request including a textual description of the business data component generated by the user; receive a selection of one of the plurality of business models; in response to at least the request for the selection, execute software means for identifying terms from a library, including associates between the terms, used to generate proposed names for business data components in connection with adding the business data components to business process models, the library includes terms and associates for each of the plurality of selectable business models; execute software means for searching the identified terms and the associations between the identified terms using a matching algorithm and the textual description to select terms associated with the business data component and used to add business components to the selected business model; execute software means for combining at least a portion of the selected terms to generate at least one proposed name for the business data component in accordance with a predefined naming format, the predefined naming format defining a name as including a plurality of terms for semantically describing a business data component, wherein the plurality of terms include at least two terms from the group consisting of an object class term, a property term, a representation class term, a qualifier term, a context category, and a context value; execute software means for receiving context information for defining the business data component; identify a predefined business data model based on the context information; receive a request to add the business data component to the business data model, wherein the matching algorithm uses a context defined by at least one of the context information or the predefined business data model to select terms from the library of available terms; update the selected business process model with the business data component using the proposed name, wherein the at least one proposed name includes a business data component name included in a business data model for a different context; and a topic map defines associations between a plurality of business data models including the predefined business data model and the business data model for the different context, identifying the business data model for the different context based on a relationship with the predefined business data model defined in the topic map. 13. The system of claim 12 wherein the software means for generating at least one proposed name is operable to select, for each proposed name, a plurality of terms from the available terms based on a correspondence between the description and a semantic meaning of the selected plurality of terms and a relationship between a context of the at least one proposed name and a context of each of the selected plurality of terms. | 0.5 |
8,612,243 | 26 | 27 | 26. The non-transitory computer readable data storage medium article of manufacture of claim 25 , wherein the selected best-fit successor node sends a keeper handoff accept message to the users on the information network. | 26. The non-transitory computer readable data storage medium article of manufacture of claim 25 , wherein the selected best-fit successor node sends a keeper handoff accept message to the users on the information network. 27. The non-transitory computer readable data storage medium article of manufacture of claim 26 , wherein the method further comprises: broadcasting the identity of the best-fit successor node as the keeper. | 0.5 |
4,684,926 | 21 | 29 | 21. An apparatus for encoding Chinese characters and phrases, each of the phrases including at least two characters, comprising: (a) at least twenty-five keys arranged in a traditional Western alphabetic placement and the twenty-five keys corresponding to a break-down of the characters and phrases into five basic types of strokes, four basic patterns of characters, and twenty-five blocks of roots, wherein: (i) the five basic types of strokes are characterized by forms of the strokes; (ii) the four basic patterns of characters are characterized by relative locations of roots within each character; (iii) roots, selected according to a frequency distribution both in constituting characters and in practical Chinese usage, are classified into five sections, each root being classified according to a first one of the five basic types of strokes which characterizes a first stroke of the root, and each of the five basic types of stroke is also considered to be a root and each of the five sections is divided into five blocks, each of the five blocks being identified by one of: a second one of the five basic types which characterizes a second stroke of each root; and a number of strokes forming a root, and wherein the twenty-five keys are assigned so that each of the twenty-five keys corresponds to one of the twenty-five blocks of roots and in accordance with a frequency of the twenty-five blocks in practical Chinese usage, and each of twenty of the twenty-five keys corresponds to one of twenty combinations of one of the five basic types of strokes with one of the four basic patterns of characters; and (b) means for encoding the characters and phrases in response to a plurality of actuations of the twenty-five keys. | 21. An apparatus for encoding Chinese characters and phrases, each of the phrases including at least two characters, comprising: (a) at least twenty-five keys arranged in a traditional Western alphabetic placement and the twenty-five keys corresponding to a break-down of the characters and phrases into five basic types of strokes, four basic patterns of characters, and twenty-five blocks of roots, wherein: (i) the five basic types of strokes are characterized by forms of the strokes; (ii) the four basic patterns of characters are characterized by relative locations of roots within each character; (iii) roots, selected according to a frequency distribution both in constituting characters and in practical Chinese usage, are classified into five sections, each root being classified according to a first one of the five basic types of strokes which characterizes a first stroke of the root, and each of the five basic types of stroke is also considered to be a root and each of the five sections is divided into five blocks, each of the five blocks being identified by one of: a second one of the five basic types which characterizes a second stroke of each root; and a number of strokes forming a root, and wherein the twenty-five keys are assigned so that each of the twenty-five keys corresponds to one of the twenty-five blocks of roots and in accordance with a frequency of the twenty-five blocks in practical Chinese usage, and each of twenty of the twenty-five keys corresponds to one of twenty combinations of one of the five basic types of strokes with one of the four basic patterns of characters; and (b) means for encoding the characters and phrases in response to a plurality of actuations of the twenty-five keys. 29. The apparatus of claim 21 comprising: an additional key reserved for representing a root which has not been identified; means for displaying on the screen in response to actuation of the additional key, along with actuation of at least one of the twenty-five keys, a second plurality of characters with respective numerical codes, wherein each of the second plurality of characters corresponds to at least one of the twenty-five keys and wherein each of the second plurality of characters contains a root substituted for the root which has not been identified; means for third encoding a desired character in the second plurality of characters in response to a second plurality of actuations of keys which corresond to the correct character. | 0.5 |
9,639,628 | 12 | 14 | 12. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive at a social-networking system a request for user comments to be displayed in a user interface with web content of a third-party website distinct from the social-networking system, the request associated with a first user, the third-party website being hosted by a third-party system that is separate from the social-networking system, and the social-networking system comprising social graph information that comprises a plurality of nodes connected by a plurality of edges, wherein each node corresponds to a member of the social-networking system, and each edge represents a relationship between two users who correspond to two nodes connected by the edge; responsive to the request, retrieve from a data store of user comments a plurality of user comments, each of the plurality of user comments being submitted by a respective second user from a plurality of second users, and the data store being maintained by the social-networking system; for each user comment in the plurality of user comments: compute an affinity score based on: (1) social graph information about a relationship between the first user and the respective second user associated with the user comment, and (2) user activities of the first user and the respective second user within an environment provided by the social-networking system, wherein the user activities include interactions by the first user with content or with another user; determine a locality of the respective second user; order the plurality of user comments based on the social-graph information of the first user, the computed affinity scores, and the locality of the respective second user; and provide for display on the third-party website the plurality of user comments based on the ordering of the plurality of user comments. | 12. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive at a social-networking system a request for user comments to be displayed in a user interface with web content of a third-party website distinct from the social-networking system, the request associated with a first user, the third-party website being hosted by a third-party system that is separate from the social-networking system, and the social-networking system comprising social graph information that comprises a plurality of nodes connected by a plurality of edges, wherein each node corresponds to a member of the social-networking system, and each edge represents a relationship between two users who correspond to two nodes connected by the edge; responsive to the request, retrieve from a data store of user comments a plurality of user comments, each of the plurality of user comments being submitted by a respective second user from a plurality of second users, and the data store being maintained by the social-networking system; for each user comment in the plurality of user comments: compute an affinity score based on: (1) social graph information about a relationship between the first user and the respective second user associated with the user comment, and (2) user activities of the first user and the respective second user within an environment provided by the social-networking system, wherein the user activities include interactions by the first user with content or with another user; determine a locality of the respective second user; order the plurality of user comments based on the social-graph information of the first user, the computed affinity scores, and the locality of the respective second user; and provide for display on the third-party website the plurality of user comments based on the ordering of the plurality of user comments. 14. The media of claim 12 , wherein the plurality of user comments are ordered further based on one or more privacy settings. | 0.849034 |
9,009,650 | 1 | 5 | 1. A method for intelligently and efficiently connecting with people and assets involved in projects, the method comprising: generating a first semantic graph for a first project based on resources within said first project, wherein said first semantic graph builds a relationship among entities of said first project; generating a second semantic graph for a second project based on resources within said second project, wherein said second semantic graph builds a relationship among entities of said second project, wherein said second project is a different project from said first project or a different version of said first project; receiving a selection of said first and said second semantic graphs representing different projects or versions of a same project; comparing and merging differences between said first and said second semantic graphs; and generating, by a processor, a third semantic graph that illustrates said differences between said first and said second semantic graphs, wherein said third semantic graph comprises nodes representing said entities of said first and said second projects, wherein said differences comprise one or more of the following: personnel and development processes. | 1. A method for intelligently and efficiently connecting with people and assets involved in projects, the method comprising: generating a first semantic graph for a first project based on resources within said first project, wherein said first semantic graph builds a relationship among entities of said first project; generating a second semantic graph for a second project based on resources within said second project, wherein said second semantic graph builds a relationship among entities of said second project, wherein said second project is a different project from said first project or a different version of said first project; receiving a selection of said first and said second semantic graphs representing different projects or versions of a same project; comparing and merging differences between said first and said second semantic graphs; and generating, by a processor, a third semantic graph that illustrates said differences between said first and said second semantic graphs, wherein said third semantic graph comprises nodes representing said entities of said first and said second projects, wherein said differences comprise one or more of the following: personnel and development processes. 5. The method as recited in claim 1 further comprising: displaying available communication channels and social communities in response to receiving an indication that a cursor is hovering over an identifier of a person associated with a node in said third semantic graph. | 0.684884 |
9,251,225 | 54 | 55 | 54. The computing system of claim 43 , wherein generating the procedural specification includes generating a computer program from the third collection, the computer program including functions or expressions to perform operations corresponding to relational expressions in respective nodes of the third collection. | 54. The computing system of claim 43 , wherein generating the procedural specification includes generating a computer program from the third collection, the computer program including functions or expressions to perform operations corresponding to relational expressions in respective nodes of the third collection. 55. The computing system of claim 54 , wherein the computer program is specified in at least one of the programming languages: Java, C, C++. | 0.5 |
8,868,539 | 12 | 13 | 12. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause performance of: generating one or more query logs that record information about previously received search queries, including, for the previously received search queries, indications of in which specific contexts, of a plurality of search contexts, the previously received search queries have been made over at least a period of time; receiving a search query; determining at least one suggested query, of the previously received search queries, based on the search query; determining, for each specific search context of a plurality of search contexts: a log-based relevance score of the search query to the specific search context, the log-based relevance score being calculated, at least in part, using a count of how many times the search query was made in the specific search context over the period of time, and further using a count of how many times the suggested query was made in the specific search context over the period of time, as recorded in the one or more query logs; wherein each search context of the plurality of search contexts is a different set of searchable information; responsive to receiving the search query, sending an indication, for each specific search context of the plurality of search contexts, of a relative size of the log-based relevance score determined for the specific search context compared to relative sizes of each other log-based relevance score determined for each other search context of the plurality of search contexts. | 12. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause performance of: generating one or more query logs that record information about previously received search queries, including, for the previously received search queries, indications of in which specific contexts, of a plurality of search contexts, the previously received search queries have been made over at least a period of time; receiving a search query; determining at least one suggested query, of the previously received search queries, based on the search query; determining, for each specific search context of a plurality of search contexts: a log-based relevance score of the search query to the specific search context, the log-based relevance score being calculated, at least in part, using a count of how many times the search query was made in the specific search context over the period of time, and further using a count of how many times the suggested query was made in the specific search context over the period of time, as recorded in the one or more query logs; wherein each search context of the plurality of search contexts is a different set of searchable information; responsive to receiving the search query, sending an indication, for each specific search context of the plurality of search contexts, of a relative size of the log-based relevance score determined for the specific search context compared to relative sizes of each other log-based relevance score determined for each other search context of the plurality of search contexts. 13. The one or more non-transitory computer-readable media of claim 12 , wherein the search query is a partial search query, wherein determining the log-based relevance scores and providing the indication are performed prior to receiving input that indicates that said search query represents a complete query. | 0.832432 |
8,731,920 | 1 | 2 | 1. A method performed by a computer processor executing computer program instructions stored on a non-transitory computer-readable medium, the method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. | 1. A method performed by a computer processor executing computer program instructions stored on a non-transitory computer-readable medium, the method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. 2. The method of claim 1 , further comprising: (E) using the document-specific language model in a speech recognition process to recognize the spoken audio stream and thereby to produce a third document. | 0.660535 |
9,652,553 | 9 | 12 | 9. A device for displaying a web page, comprising: at least one processor configured to: pre-process text information to be picture processed in a web page, wherein the pre-processing of the text information comprises: set up display frames, the display frames relating to display positions of the text information; split the text information into text blocks based on the display frames; group the text blocks based on a threshold and a height of at least one text block; combine dimensions of the at least one text block with groups of corresponding text blocks to set up a concatenation of all the text blocks, the dimensions being calculated based on a text style in the at least one text block; and allocate dimensions for a picture that accommodates the text blocks based on the concatenation; create the picture; generate a plurality of position descriptions for corresponding text blocks in the picture; fill the corresponding text blocks into the picture based on the position descriptions of the text blocks; save the filled picture; correspondingly save a call address of the picture and the position description of each text block in the picture as metadata for the web page; and in the event that an access request for the web page is received: invoke the metadata for the web page; load the picture based on the call address in the metadata for the web page; select at least one corresponding text block from the picture based on at least one position description in the metadata for the web page; and display the at least one text block in at least one display position in the web page; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions. | 9. A device for displaying a web page, comprising: at least one processor configured to: pre-process text information to be picture processed in a web page, wherein the pre-processing of the text information comprises: set up display frames, the display frames relating to display positions of the text information; split the text information into text blocks based on the display frames; group the text blocks based on a threshold and a height of at least one text block; combine dimensions of the at least one text block with groups of corresponding text blocks to set up a concatenation of all the text blocks, the dimensions being calculated based on a text style in the at least one text block; and allocate dimensions for a picture that accommodates the text blocks based on the concatenation; create the picture; generate a plurality of position descriptions for corresponding text blocks in the picture; fill the corresponding text blocks into the picture based on the position descriptions of the text blocks; save the filled picture; correspondingly save a call address of the picture and the position description of each text block in the picture as metadata for the web page; and in the event that an access request for the web page is received: invoke the metadata for the web page; load the picture based on the call address in the metadata for the web page; select at least one corresponding text block from the picture based on at least one position description in the metadata for the web page; and display the at least one text block in at least one display position in the web page; and a memory coupled to the at least one processor and configured to provide the at least one processor with instructions. 12. The device as described in claim 9 , wherein: the pre-processing of the text information further comprises: identify a text block with a maximum height; and select a fraction of a height of the text block with the maximum height as the threshold. | 0.657534 |
8,875,043 | 1 | 2 | 1. A computer-implemented method of obtaining criterion-specific feedback for an item, comprising: providing, by a computer system, feedback information for the item, the feedback information comprising one or more statements that correspond to one or more existing criteria relating to the item; providing an add feedback element for providing at least one new criterion for the item; receiving customer input, based at least in part on receipt of an indication that a customer selected the add feedback element, that represents the new criterion the customer wishes to provide for the item and one or more new values for the new criterion by providing the customer the ability to input a new question corresponding to the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; updating the feedback information for the item to include the new question corresponding to the new criterion and the one or more new responses to the new question; providing the updated feedback information to at least one subsequent customer; and providing presentation to the customer of a selected number of statements from the feedback information based at least in part on a detected bias of the customer. | 1. A computer-implemented method of obtaining criterion-specific feedback for an item, comprising: providing, by a computer system, feedback information for the item, the feedback information comprising one or more statements that correspond to one or more existing criteria relating to the item; providing an add feedback element for providing at least one new criterion for the item; receiving customer input, based at least in part on receipt of an indication that a customer selected the add feedback element, that represents the new criterion the customer wishes to provide for the item and one or more new values for the new criterion by providing the customer the ability to input a new question corresponding to the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; updating the feedback information for the item to include the new question corresponding to the new criterion and the one or more new responses to the new question; providing the updated feedback information to at least one subsequent customer; and providing presentation to the customer of a selected number of statements from the feedback information based at least in part on a detected bias of the customer. 2. A computer-implemented method according to claim 1 , further comprising: providing the ability for the customer to specify a statement corresponding to the new question to be included in the feedback information for the item. | 0.68595 |
7,590,536 | 1 | 4 | 1. A computer-implemented method for increasing the accuracy of a voice recognition system, comprising: initiating a voice processing session for a first user, wherein the voice processing session is configured to match a voice pattern derived from one or more words spoken by the first user with entries in a word-usage probability table, based on a probability of the one or more words being spoken by the first user; during the voice processing session initiated for the first user, monitoring for an occurrence of a word-usage anomaly, wherein the word-usage anomaly occurs when an observed usage frequency for a given one or more words differs, by a predetermined magnitude, from an expected frequency recorded in the word-usage probability table for the given one or more words; in response to the occurrence of the word usage anomaly, increasing the expected frequency for the given one or more words in the word-usage probability table, wherein the increased expected frequency for the given one or more words in the word-usage probability table is configured to expire, after a predetermined period of time; transmitting an indication of the observed anomaly to a voice processing session initiated for a second user; and monitoring, by a server, respective voice processing sessions for each of a plurality of users, including at least the first user and the second user, wherein the server is configured to: (i) monitor the occurrence of word-usage anomalies for each of the voice processing sessions, (ii) record anomalies observed by each of the voice processing sessions in a server anomaly table, and (iii) broadcast an indication of a global anomaly to each of the voice processing sessions, wherein the global anomaly comprises an anomaly that is observed independently by at least two of the voice processing sessions. | 1. A computer-implemented method for increasing the accuracy of a voice recognition system, comprising: initiating a voice processing session for a first user, wherein the voice processing session is configured to match a voice pattern derived from one or more words spoken by the first user with entries in a word-usage probability table, based on a probability of the one or more words being spoken by the first user; during the voice processing session initiated for the first user, monitoring for an occurrence of a word-usage anomaly, wherein the word-usage anomaly occurs when an observed usage frequency for a given one or more words differs, by a predetermined magnitude, from an expected frequency recorded in the word-usage probability table for the given one or more words; in response to the occurrence of the word usage anomaly, increasing the expected frequency for the given one or more words in the word-usage probability table, wherein the increased expected frequency for the given one or more words in the word-usage probability table is configured to expire, after a predetermined period of time; transmitting an indication of the observed anomaly to a voice processing session initiated for a second user; and monitoring, by a server, respective voice processing sessions for each of a plurality of users, including at least the first user and the second user, wherein the server is configured to: (i) monitor the occurrence of word-usage anomalies for each of the voice processing sessions, (ii) record anomalies observed by each of the voice processing sessions in a server anomaly table, and (iii) broadcast an indication of a global anomaly to each of the voice processing sessions, wherein the global anomaly comprises an anomaly that is observed independently by at least two of the voice processing sessions. 4. The computer-implemented method of claim 1 , wherein the word-usage probability table is initialized for the second user using at least one indication of a word-usage anomaly observed by the voice processing session of the first user. | 0.754149 |
8,868,592 | 1 | 7 | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. 7. The computer-implemented method of claim 1 , wherein: obtaining the first profile data for the first user comprises obtaining information indicating a first geographical location; obtaining the second profile data for the second users comprises obtaining information that indicates second geographical locations from which the respective search queries were submitted; and determining the similarity scores comprises determining the similarity scores based on distances between the first geographical location and the respective second geographical locations. | 0.546042 |
8,347,391 | 1 | 9 | 1. A computer-implemented method for detecting a network activity of interest, the method comprising: obtaining, by one or more processors, a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; creating, by the one or more processors, a plurality of combined packets from at least a subset of the plurality of TCP packets and IP packets, wherein: a first combined packet of the plurality of combined packets comprises a portion of at least one of the TCP packets and a portion of at least one of the IP packets, and a second combined packet of the plurality of combined packets comprises a portion of at least one of the TCP packets and a portion of at least one of the IP packets, wherein the second combined packet is different from the first combined packet; creating, by the one or more processors, a first sequence by converting bitwise content of at least a portion of the first combined packet into a first plurality of integers, wherein the first sequence includes the first plurality of integers; creating, by the one or more processors, a second sequence by converting bitwise content of at least a portion of the second combined packet into a second plurality of integers, wherein the second sequence includes the second plurality of integers; determining, by the one or more processors, a similarity metric between the first sequence and the second sequence based on a distance function; creating, by the one or more processors, a third sequence based on the similarity metric, wherein the third sequence comprises a third plurality of integers common to the first sequence and the second sequence, in the first order; creating, by the one or more processors, a fourth sequence, wherein the fourth sequence is a meta-expression that: comprises a subset of the third plurality of integers of the third list, in the first order, and corresponds to the presence of the network activity of interest in the network traffic; and storing the meta-expression, wherein the stored meta-expression is used to detect the presence of the network activity of interest. | 1. A computer-implemented method for detecting a network activity of interest, the method comprising: obtaining, by one or more processors, a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; creating, by the one or more processors, a plurality of combined packets from at least a subset of the plurality of TCP packets and IP packets, wherein: a first combined packet of the plurality of combined packets comprises a portion of at least one of the TCP packets and a portion of at least one of the IP packets, and a second combined packet of the plurality of combined packets comprises a portion of at least one of the TCP packets and a portion of at least one of the IP packets, wherein the second combined packet is different from the first combined packet; creating, by the one or more processors, a first sequence by converting bitwise content of at least a portion of the first combined packet into a first plurality of integers, wherein the first sequence includes the first plurality of integers; creating, by the one or more processors, a second sequence by converting bitwise content of at least a portion of the second combined packet into a second plurality of integers, wherein the second sequence includes the second plurality of integers; determining, by the one or more processors, a similarity metric between the first sequence and the second sequence based on a distance function; creating, by the one or more processors, a third sequence based on the similarity metric, wherein the third sequence comprises a third plurality of integers common to the first sequence and the second sequence, in the first order; creating, by the one or more processors, a fourth sequence, wherein the fourth sequence is a meta-expression that: comprises a subset of the third plurality of integers of the third list, in the first order, and corresponds to the presence of the network activity of interest in the network traffic; and storing the meta-expression, wherein the stored meta-expression is used to detect the presence of the network activity of interest. 9. The computer-implemented method of claim 1 , wherein the one or more processors are processors of a first computing device, wherein the stored meta-expression is stored on the first computing device, and the method further comprises: detecting, by the one or more processors of the first computing device, the network activity of interest using the stored meta-expression. | 0.708398 |
9,208,262 | 22 | 25 | 22. A computer-implemented method for providing a graphical representation of a plurality of items in a collaborative innovation environment, the method comprising: initiating a collaborative innovation process with a seed item wherein the seed item includes an idea, a question, an opinion or a statement for which a result is sought, and innovating one or more idea items directly or indirectly in response to the seed item to determine the result for the seed item based on the one or more idea items in the collaborative innovation process, wherein the seed item and the one or more idea items comprise a plurality of items; providing by a processor to a device of a user a list of a plurality of seed items in a graphical user interface; identifying, by the processor, a plurality of items including a seed item selected by the user from the plurality of seed items and a plurality of idea items innovated in response to the selected seed item by a plurality of users in the collaborative innovation environment, each of the plurality of items having an association with at least one other item; transforming, by the processor, the plurality of items into a graphical representation in the graphical user interface, wherein each item of the plurality of items is represented by a shape and the association of each item with the at least one other item is represented by a line between each shape representing each item and each shape representing the at least one of other item, wherein the line between each shape representing each item and each shape representing the at least one other item identifies whether the item was innovated from the at least one other item; transforming, by the processor, the plurality of items into a textual outline representation of the plurality of items; providing, by the processor to a device of a user in the graphical user interface, the graphical representation and the textual outline representation, wherein the graphical representation and the textual outline representation are simultaneously displayed on the device of the user in a graphical display area and a textual outline display area respectively, wherein the graphical representation display area and the textual outline display area are each a responsive display area to each other; responsively, reflecting actions performed in either the graphical representation display area or the textual outline display area in the responsive display area of the other, including: creating an item innovated from one of the plurality of items in the responsive display area of the other in instances when one of the plurality of items is selected and when a selection is received from a user selection made in either the graphical representation display area or the outline display area; receiving, by the processor from the device of the user, a request to search through a set of idea items of the plurality of items, wherein the set of idea items to be searched is determined based on a user selection that indicates whether to search all of the plurality of idea items or to search only a subset of the plurality of idea items that have received a specified rating; moving a user-selected one item of the plurality of items having an association with the at least one other item in the graphical representation to a user-selected destination by: disassociating the user selected one item of the plurality of items from an item it was innovated from; associating the selected one item of the plurality of items with another item based on user input; providing by the processor to the device of the user a preview for display of the graphical representation including the moved user-selected one item of the plurality of items to the destination item; and allowing the user to cancel or confirm the move of the user-selected one item of the plurality of items; wherein in response to a click of a move descendants button in a user interface by the user, including the descendants of the user-selected one item of the plurality of items in the moving of the user-selected one of the plurality of items to the user-selected destination, and including the descendants of the moved user-selected one item of the plurality of items in the preview for display of the graphical representation; in response to a click of a like it button or a click of a don't like it button in the graphical user interface, entering a rating of a selected item in the graphical user interface; in response to a click of an enhance button in the graphical user interface allowing a user to create an item enhancing a selected item in the graphical user interface; in response to a click of an edit button in the graphical user interface allowing a user to edit a selected item in the graphical user interface; and in response to a click of a delete button in the graphical user interface deleting a selected item in the graphical user interface; wherein the graphical user interface includes the like it button, the don't like it button, the enhance button, the edit button and the delete button. | 22. A computer-implemented method for providing a graphical representation of a plurality of items in a collaborative innovation environment, the method comprising: initiating a collaborative innovation process with a seed item wherein the seed item includes an idea, a question, an opinion or a statement for which a result is sought, and innovating one or more idea items directly or indirectly in response to the seed item to determine the result for the seed item based on the one or more idea items in the collaborative innovation process, wherein the seed item and the one or more idea items comprise a plurality of items; providing by a processor to a device of a user a list of a plurality of seed items in a graphical user interface; identifying, by the processor, a plurality of items including a seed item selected by the user from the plurality of seed items and a plurality of idea items innovated in response to the selected seed item by a plurality of users in the collaborative innovation environment, each of the plurality of items having an association with at least one other item; transforming, by the processor, the plurality of items into a graphical representation in the graphical user interface, wherein each item of the plurality of items is represented by a shape and the association of each item with the at least one other item is represented by a line between each shape representing each item and each shape representing the at least one of other item, wherein the line between each shape representing each item and each shape representing the at least one other item identifies whether the item was innovated from the at least one other item; transforming, by the processor, the plurality of items into a textual outline representation of the plurality of items; providing, by the processor to a device of a user in the graphical user interface, the graphical representation and the textual outline representation, wherein the graphical representation and the textual outline representation are simultaneously displayed on the device of the user in a graphical display area and a textual outline display area respectively, wherein the graphical representation display area and the textual outline display area are each a responsive display area to each other; responsively, reflecting actions performed in either the graphical representation display area or the textual outline display area in the responsive display area of the other, including: creating an item innovated from one of the plurality of items in the responsive display area of the other in instances when one of the plurality of items is selected and when a selection is received from a user selection made in either the graphical representation display area or the outline display area; receiving, by the processor from the device of the user, a request to search through a set of idea items of the plurality of items, wherein the set of idea items to be searched is determined based on a user selection that indicates whether to search all of the plurality of idea items or to search only a subset of the plurality of idea items that have received a specified rating; moving a user-selected one item of the plurality of items having an association with the at least one other item in the graphical representation to a user-selected destination by: disassociating the user selected one item of the plurality of items from an item it was innovated from; associating the selected one item of the plurality of items with another item based on user input; providing by the processor to the device of the user a preview for display of the graphical representation including the moved user-selected one item of the plurality of items to the destination item; and allowing the user to cancel or confirm the move of the user-selected one item of the plurality of items; wherein in response to a click of a move descendants button in a user interface by the user, including the descendants of the user-selected one item of the plurality of items in the moving of the user-selected one of the plurality of items to the user-selected destination, and including the descendants of the moved user-selected one item of the plurality of items in the preview for display of the graphical representation; in response to a click of a like it button or a click of a don't like it button in the graphical user interface, entering a rating of a selected item in the graphical user interface; in response to a click of an enhance button in the graphical user interface allowing a user to create an item enhancing a selected item in the graphical user interface; in response to a click of an edit button in the graphical user interface allowing a user to edit a selected item in the graphical user interface; and in response to a click of a delete button in the graphical user interface deleting a selected item in the graphical user interface; wherein the graphical user interface includes the like it button, the don't like it button, the enhance button, the edit button and the delete button. 25. The computer-implemented method of claim 22 wherein a size of each shape is based on a second value of a second metric of each item represented by each shape. | 0.838323 |
8,850,384 | 15 | 17 | 15. The method of claim 14 , wherein the symbol comprises a list of operation candidates associated with the service candidate, the list expanding as operation candidates are being added to the service candidate in the service candidate area. | 15. The method of claim 14 , wherein the symbol comprises a list of operation candidates associated with the service candidate, the list expanding as operation candidates are being added to the service candidate in the service candidate area. 17. The method of claim 15 , wherein the main workspace further illustrates a composition candidate associated with an operation candidate within the service candidate represented in the symbol. | 0.5 |
8,275,772 | 11 | 16 | 11. A system using a model to filter documents according to quality comprising: A) a storage device; B) at least one processor to implement the following steps: C) obtaining from the storage device a first set of documents labeled according to content quality; D) extracting and representing features from the first set of documents; E) modifying the extracted represented features; F) constructing models for labeling documents based on content quality using pattern recognitional algorithms stored in the storage device consisting of the following steps; 1) dividing the first set of documents into N subsets such that the union of all the subsets is the first set of documents; 2) choosing at least one pattern recognition algorithm; a) instantiating a set of parameters for the pattern recognition algorithm; i) processing each of the N subsets comprising the following steps; a′) defining a first subset and defining a second subset mutually exclusive of the first subset; b′) training the pattern recognition algorithm to build a model using the first subset and the parameter set; c′) applying the model to the second subset of documents to obtain labels and scores for each document; d′) evaluating the labels and scores; e′) storing the evaluation measure, set of parameters, and current pattern recognition algorithm; and b) repeating step 2 a ) until all appropriate sets of parameters for the pattern recognition algorithm have been applied; and 3) repeating step 2) until all pattern recognition algorithms have been applied; 4) aggregating the evaluation measures for the N subsets, the pattern recognition algorithms with the set of parameters; 5) selecting the parameter set and pattern recognition algorithm with an aggregate evaluation measure that meets a selection criteria; 6) applying the parameter set and the pattern recognition algorithm identified from step 5) to the first set of documents to build a final model; and G) obtaining a second set of non-labeled documents related to the first set of documents; H) using the final model to label and score the second set of documents according to content quality; and I) displaying the label and/or score of at least one of the previously unlabeled documents. | 11. A system using a model to filter documents according to quality comprising: A) a storage device; B) at least one processor to implement the following steps: C) obtaining from the storage device a first set of documents labeled according to content quality; D) extracting and representing features from the first set of documents; E) modifying the extracted represented features; F) constructing models for labeling documents based on content quality using pattern recognitional algorithms stored in the storage device consisting of the following steps; 1) dividing the first set of documents into N subsets such that the union of all the subsets is the first set of documents; 2) choosing at least one pattern recognition algorithm; a) instantiating a set of parameters for the pattern recognition algorithm; i) processing each of the N subsets comprising the following steps; a′) defining a first subset and defining a second subset mutually exclusive of the first subset; b′) training the pattern recognition algorithm to build a model using the first subset and the parameter set; c′) applying the model to the second subset of documents to obtain labels and scores for each document; d′) evaluating the labels and scores; e′) storing the evaluation measure, set of parameters, and current pattern recognition algorithm; and b) repeating step 2 a ) until all appropriate sets of parameters for the pattern recognition algorithm have been applied; and 3) repeating step 2) until all pattern recognition algorithms have been applied; 4) aggregating the evaluation measures for the N subsets, the pattern recognition algorithms with the set of parameters; 5) selecting the parameter set and pattern recognition algorithm with an aggregate evaluation measure that meets a selection criteria; 6) applying the parameter set and the pattern recognition algorithm identified from step 5) to the first set of documents to build a final model; and G) obtaining a second set of non-labeled documents related to the first set of documents; H) using the final model to label and score the second set of documents according to content quality; and I) displaying the label and/or score of at least one of the previously unlabeled documents. 16. A process according to claim 11 in step C in which the documents are labeled as positive if they match content and quality criteria and labeled as negative if they do not match content and quality criteria. | 0.630282 |
8,145,493 | 14 | 17 | 14. A non-transitory computer-readable recordable medium encoded with computer program instructions that, when executed by a computer, perform a method of establishing a preferred mode of interaction between a user and a multimodal application, the method comprising: evaluating, by the multimodal application operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, a user modal preference, wherein evaluating the user modal preference comprises determining a modal coefficient value based, at least in part, on one or more modes of interaction used by the user in at least one previous interaction with a plurality of voice-enabled and/or non-voice enabled data entry fields presented by the multimodal application and evaluating the user modal preference based, at least in part, on the modal coefficient value; and dynamically configuring multimodal content of the multimodal application in dependence on the user modal preference; wherein the multimodal application comprises a plurality of static markup documents, wherein the plurality of static markup documents comprises documents having different proportions of support for voice mode and non-voice modes; wherein dynamically configuring multimodal content of the multimodal application further comprises selecting among the plurality of static markup documents, in dependence upon the value of the user modal preference, a markup document for presentation to a user as part of the multimodal application. | 14. A non-transitory computer-readable recordable medium encoded with computer program instructions that, when executed by a computer, perform a method of establishing a preferred mode of interaction between a user and a multimodal application, the method comprising: evaluating, by the multimodal application operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, a user modal preference, wherein evaluating the user modal preference comprises determining a modal coefficient value based, at least in part, on one or more modes of interaction used by the user in at least one previous interaction with a plurality of voice-enabled and/or non-voice enabled data entry fields presented by the multimodal application and evaluating the user modal preference based, at least in part, on the modal coefficient value; and dynamically configuring multimodal content of the multimodal application in dependence on the user modal preference; wherein the multimodal application comprises a plurality of static markup documents, wherein the plurality of static markup documents comprises documents having different proportions of support for voice mode and non-voice modes; wherein dynamically configuring multimodal content of the multimodal application further comprises selecting among the plurality of static markup documents, in dependence upon the value of the user modal preference, a markup document for presentation to a user as part of the multimodal application. 17. The computer-readable recordable medium of claim 14 wherein the multimodal application comprises a set of multimodal application markup documents organized in a sequence of presentation, and wherein dynamically configuring multimodal content of the multimodal application further comprises altering the sequence of presentation. | 0.765867 |
7,702,624 | 3 | 4 | 3. The method of claim 2 wherein the identification is performed using a convolution-encoded representation of text contained by the selected document portion. | 3. The method of claim 2 wherein the identification is performed using a convolution-encoded representation of text contained by the selected document portion. 4. The method of claim 3 , further comprising: encoding two selected document portions each into a convolution-encoded representation, the two selected document portions containing text of two different natural languages. | 0.601083 |
10,162,735 | 9 | 10 | 9. A computer system comprising: a memory; and a processing device coupled to the memory to: receive a software testing executable script; append the software testing executable script to a list of executable scripts; identify a test environment comprising a management node and a testable component of a distributed network; establish, over the distributed network, a trusted connection between the management node and the testable component; receive an identifier of the software testing executable script, an identifier of a target for which the management node is to execute the software testing executable script, and a schedule for execution of the software testing executable script, wherein the management node is separate from the target; and execute, in view of the schedule, the identified software testing executable script with respect to the target. | 9. A computer system comprising: a memory; and a processing device coupled to the memory to: receive a software testing executable script; append the software testing executable script to a list of executable scripts; identify a test environment comprising a management node and a testable component of a distributed network; establish, over the distributed network, a trusted connection between the management node and the testable component; receive an identifier of the software testing executable script, an identifier of a target for which the management node is to execute the software testing executable script, and a schedule for execution of the software testing executable script, wherein the management node is separate from the target; and execute, in view of the schedule, the identified software testing executable script with respect to the target. 10. The computer system of claim 9 , wherein the identifier of the target comprises an address of the testable component. | 0.721198 |
9,417,086 | 13 | 16 | 13. A computer system comprising: at least one processor; and memory comprising instructions stored thereon that when executed by at least one processor cause at least one processor to perform acts comprising: receiving a first request to return a first geographic map image corresponding to a geographic map sketch; receiving the sketch in association with the first request, the sketch including a digital image comprising one or more sketched graphical elements; in response to the first request, performing the following: performing, via the computer system, pattern matching of the one or more sketched graphical elements with a geographic map region; generating, via the computer system, a first digital geographic map image of the geographic map region; and returning the first map image of the geographic map region; adding information from the sketch to a database of map data; after generating the first map image, receiving subsequent requests for additional map images; and in response to the subsequent requests for additional map images, accessing the added information from the database and generating additional map images that include the added information from the sketch. | 13. A computer system comprising: at least one processor; and memory comprising instructions stored thereon that when executed by at least one processor cause at least one processor to perform acts comprising: receiving a first request to return a first geographic map image corresponding to a geographic map sketch; receiving the sketch in association with the first request, the sketch including a digital image comprising one or more sketched graphical elements; in response to the first request, performing the following: performing, via the computer system, pattern matching of the one or more sketched graphical elements with a geographic map region; generating, via the computer system, a first digital geographic map image of the geographic map region; and returning the first map image of the geographic map region; adding information from the sketch to a database of map data; after generating the first map image, receiving subsequent requests for additional map images; and in response to the subsequent requests for additional map images, accessing the added information from the database and generating additional map images that include the added information from the sketch. 16. The computer system of claim 13 , wherein the sketch represents a route from a first geographic location to a second geographic location, wherein the map image highlights the route from the first geographic location to the second geographic location, and wherein the acts further include generating directions from the first geographic location to the second geographic location along the route, and wherein the acts further comprise presenting the directions. | 0.624595 |
8,688,436 | 1 | 3 | 1. A method of processing natural language in an apparatus, which comprises steps: providing natural language which is processed by said apparatus to provide electronically encoded data which is representative of said natural language, providing a dictionary data base in memory associated with said apparatus wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers with associated state representation data, and/or function codes, lexically processing said electronically encoded data to access said dictionary data base with said apparatus, providing a natural language plausibility and expectedness processor in said apparatus, utilizing said natural language plausibility and expectedness processor to initiate accessing entries of said dictionary data base which are associated with words of said natural language. | 1. A method of processing natural language in an apparatus, which comprises steps: providing natural language which is processed by said apparatus to provide electronically encoded data which is representative of said natural language, providing a dictionary data base in memory associated with said apparatus wherein said dictionary data base contains a plurality of entries which are comprised of one or more of syntax usage data, associated word sense numbers with associated state representation data, and/or function codes, lexically processing said electronically encoded data to access said dictionary data base with said apparatus, providing a natural language plausibility and expectedness processor in said apparatus, utilizing said natural language plausibility and expectedness processor to initiate accessing entries of said dictionary data base which are associated with words of said natural language. 3. A method of processing as defined in claim 1 comprises steps: providing a natural language output processor in said apparatus, providing a communication, utilizing said natural language output processor to provide output for said communication which is in the form of natural language speech, natural language text, graphical user interfaces with associated natural language, and/or a representation of gestures associated with natural language. | 0.794495 |
9,672,467 | 13 | 14 | 13. The method of claim 1 , further comprising the step of providing at least one of the target personality and conversational personality access to one or more supplemental data sources for selectively increasing the knowledge base of said personality. | 13. The method of claim 1 , further comprising the step of providing at least one of the target personality and conversational personality access to one or more supplemental data sources for selectively increasing the knowledge base of said personality. 14. The method of claim 13 , further comprising the steps of, upon the target personality receiving a conversational input having a response that requires research: transmitting a non-committal response to the communicating entity and continuing the conversation therewith; initiating a second thread for performing the necessary research via the supplemental data sources; and upon concluding the research, interrupting the conversation and transmitting the researched response to the communicating entity. | 0.5 |
8,650,207 | 10 | 11 | 10. The process of claim 5 , wherein the process action of accessing a second expression language, comprise an action of accessing a second expression language that is a combined expression language which performs more than one type of string transformation operation that is different from said first operation. | 10. The process of claim 5 , wherein the process action of accessing a second expression language, comprise an action of accessing a second expression language that is a combined expression language which performs more than one type of string transformation operation that is different from said first operation. 11. The process of claim 10 , wherein the process action of accessing the first expression language associated with string transformations that involve a first operation, comprises accessing a relational table lookup expression language associated with string transformations that involve lookup operations in one or more relational tables, and wherein the process action of accessing the second expression language that is a combined expression language which performs more than one type of string transformation operation, comprises accessing a second expression language that is a combined expression language which performs formatting and rounding operations on numbers as well as syntactic string transformations. | 0.5 |
9,311,391 | 1 | 2 | 1. A method of media content recommendation, comprising: generating a first digital mathematical representation of media contents to associate the media contents with a first plurality of words describing the media contents, comprising defining content text documents describing the media contents by said first plurality of words and processing the first plurality of words to generate a first document-word matrix representing said media contents; generating a second digital mathematical representation of context text documents, different from said content text documents, to associate said context text documents with a second plurality of words, comprising processing the second plurality of words to generate a second document-word matrix representing said context text documents, wherein the context text documents include subjects not connected to the media contents; merging the first and second pluralities of words to create a common plurality of words; processing the first and second digital mathematical representations to generate a common digital mathematical representation of the content and context text documents, based on the common plurality of words, comprising processing the first and second document-word matrices and the common plurality of words to generate a third document-word matrix representing the content and context text documents; and providing media content recommendation by processing the common digital mathematical representation, wherein processing the first and second document-word matrices and the common plurality of words to generate a third document-word matrix comprises: decomposing the first document-word matrix into a product of three first matrices using QR factorisation technique while incorporating modifications of term frequency factors and inverse document frequency factors due to updating of said content and context text documents; decomposing the second document-word matrix into a product of three second matrices using QR factorisation technique while incorporating modifications of term frequency factors and inverse document frequency factors due to updating of said content and context text documents; merging the three first matrices and three second matrices to create a common matrix by concatenating the three first matrices as a first element of the common matrix and the three second matrices as a second element of the common matrix; decomposing the common matrix into a product of three common matrices using QR factorisation technique; and defining the third document-word matrix from said product of the three common matrices. | 1. A method of media content recommendation, comprising: generating a first digital mathematical representation of media contents to associate the media contents with a first plurality of words describing the media contents, comprising defining content text documents describing the media contents by said first plurality of words and processing the first plurality of words to generate a first document-word matrix representing said media contents; generating a second digital mathematical representation of context text documents, different from said content text documents, to associate said context text documents with a second plurality of words, comprising processing the second plurality of words to generate a second document-word matrix representing said context text documents, wherein the context text documents include subjects not connected to the media contents; merging the first and second pluralities of words to create a common plurality of words; processing the first and second digital mathematical representations to generate a common digital mathematical representation of the content and context text documents, based on the common plurality of words, comprising processing the first and second document-word matrices and the common plurality of words to generate a third document-word matrix representing the content and context text documents; and providing media content recommendation by processing the common digital mathematical representation, wherein processing the first and second document-word matrices and the common plurality of words to generate a third document-word matrix comprises: decomposing the first document-word matrix into a product of three first matrices using QR factorisation technique while incorporating modifications of term frequency factors and inverse document frequency factors due to updating of said content and context text documents; decomposing the second document-word matrix into a product of three second matrices using QR factorisation technique while incorporating modifications of term frequency factors and inverse document frequency factors due to updating of said content and context text documents; merging the three first matrices and three second matrices to create a common matrix by concatenating the three first matrices as a first element of the common matrix and the three second matrices as a second element of the common matrix; decomposing the common matrix into a product of three common matrices using QR factorisation technique; and defining the third document-word matrix from said product of the three common matrices. 2. The method of claim 1 , wherein providing media content recommendation comprises: processing the common digital mathematical representation to apply a similarity function to associate a first media content with a second media content; and storing in a database an index linking said first media content to said second media content. | 0.620181 |
8,330,760 | 1 | 4 | 1. A method performed by data processing apparatus, the method comprising: receiving a hinted glyph outline for a glyph to be rendered, the glyph to be rendered being associated with a character of a particular font and at a specified scaled size, the glyph to be rendered having one or more horizontal stems; identifying a darkening amount to be applied to the one or more horizontal stems of the glyph; modifying hints of the one or more horizontal stems of the hinted glyph outline using the identified darkening amount to modify the hinted glyph outline, wherein the modifying includes increasing a spacing between edges of each horizontal stem by twice the darkening amount identified for the respective horizontal stem; and rasterizing the glyph using the modified hinted glyph outline. | 1. A method performed by data processing apparatus, the method comprising: receiving a hinted glyph outline for a glyph to be rendered, the glyph to be rendered being associated with a character of a particular font and at a specified scaled size, the glyph to be rendered having one or more horizontal stems; identifying a darkening amount to be applied to the one or more horizontal stems of the glyph; modifying hints of the one or more horizontal stems of the hinted glyph outline using the identified darkening amount to modify the hinted glyph outline, wherein the modifying includes increasing a spacing between edges of each horizontal stem by twice the darkening amount identified for the respective horizontal stem; and rasterizing the glyph using the modified hinted glyph outline. 4. The method of claim 1 , where modifying horizontal stems includes expanding the spacing between edges of the horizontal stem. | 0.804281 |
4,511,891 | 8 | 9 | 8. A printing system for printing amount information of plural digits comprising: means for introducing amount information represented as a numerical character string; means for determining the order position of each numeral character representing said amount information; means, responsive to the order position of each numerical character determined by said means for determining, for generating non-numerical symbology representative of the order position of said amount information; and means, responsive to said means for generating, for printing said non-numerical symbology representative of said amount information. | 8. A printing system for printing amount information of plural digits comprising: means for introducing amount information represented as a numerical character string; means for determining the order position of each numeral character representing said amount information; means, responsive to the order position of each numerical character determined by said means for determining, for generating non-numerical symbology representative of the order position of said amount information; and means, responsive to said means for generating, for printing said non-numerical symbology representative of said amount information. 9. The printing system of claim 8 wherein said non-numerical symbology consists essentially of alphabetical characters. | 0.5 |
8,849,835 | 1 | 6 | 1. A method comprising: generating, by one or more devices, first scores indicating respective likelihood values that data stored in a first entry in a first database and data stored in second entries in a second database occur in a common document, the second database being separate from the first database, each of the first entry and the second entries including respective fields, and a particular field, of the respective fields, including information regarding a particular attribute of an object being represented by the first entry; identifying, by the one or more devices and based on the first scores, two or more of the second entries in the second database; generating, by the one or more devices, second scores for the two or more of the second entries, the two or more of the second entries including a particular second entry, the second scores including a second score for the particular second entry, the respective fields including first fields in the first entry and second fields in the particular second entry, the first fields including the particular field, and the second score for the particular second entry being generated based on comparing data stored in the first fields in the first entry and data stored in the second fields of the particular second entry; determining, by the one or more devices, that the second score satisfies a threshold; identifying, by the one or more devices, the particular second entry, of the two or more of the second entries, based on determining that the second score satisfies the threshold; and storing, by the one or more devices, information associating the first entry and the particular second entry. | 1. A method comprising: generating, by one or more devices, first scores indicating respective likelihood values that data stored in a first entry in a first database and data stored in second entries in a second database occur in a common document, the second database being separate from the first database, each of the first entry and the second entries including respective fields, and a particular field, of the respective fields, including information regarding a particular attribute of an object being represented by the first entry; identifying, by the one or more devices and based on the first scores, two or more of the second entries in the second database; generating, by the one or more devices, second scores for the two or more of the second entries, the two or more of the second entries including a particular second entry, the second scores including a second score for the particular second entry, the respective fields including first fields in the first entry and second fields in the particular second entry, the first fields including the particular field, and the second score for the particular second entry being generated based on comparing data stored in the first fields in the first entry and data stored in the second fields of the particular second entry; determining, by the one or more devices, that the second score satisfies a threshold; identifying, by the one or more devices, the particular second entry, of the two or more of the second entries, based on determining that the second score satisfies the threshold; and storing, by the one or more devices, information associating the first entry and the particular second entry. 6. The method of claim 1 , where generating the first scores further includes: identifying a particular entry that is included in both the first database and the second database; generating an occurrence count for the particular entry, the occurrence count indicating a quantity of documents, in a plurality of documents, in which data stored in the particular entry occurs; generating a mentions count for the particular entry in the first database and the second database, the mentions count indicating a number of locations in the plurality of documents associated with occurrences of the data stored in the particular entry; and using the occurrence count and the mentions count for the particular entry to generate the first scores. | 0.5 |
9,536,266 | 2 | 4 | 2. The method of claim 1 , further comprising: identifying one or more actions based on one or more of the one or more factual claims, the one or more facts and the confidence score; and transmitting the one or more actions for display in the GUI. | 2. The method of claim 1 , further comprising: identifying one or more actions based on one or more of the one or more factual claims, the one or more facts and the confidence score; and transmitting the one or more actions for display in the GUI. 4. The method of claim 2 , further comprising: receiving user input indicating selection of at least one action of the one or more actions; and in response to receiving the user input, invoking the at least one action. | 0.565737 |
8,396,878 | 32 | 35 | 32. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determine a preliminary category for the video file; based on the preliminary category, generate a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generate an ontology of the plurality of words based on the targeted transcript; rank the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generate one or more automated tags associated with the video file, establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: proximity of words relative to other words, distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. | 32. A non-transitory computer-readable medium having sets of instructions stored thereon which, when executed by a computer, cause the computer to: receive one or more manually generated tags associated with a video file; based at least in part on the one or more manually entered tags, determine a preliminary category for the video file; based on the preliminary category, generate a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generate an ontology of the plurality of words based on the targeted transcript; rank the plurality of words in the ontology based on a plurality of scoring factors; based on the ranking of the plurality of words, generate one or more automated tags associated with the video file, establish a top concepts threshold value; determine that one or more of the rankings of the plurality of words exceeds the top concepts threshold; and associate information about the one or more of the plurality of words with rankings that exceeds the top concepts with the video file to designate the top concepts of the video file, wherein the plurality of scoring factors consists of two or more of: proximity of words relative to other words, distribution of words throughout the targeted transcript of the video file, words related to the plurality of words throughout the targeted transcript of the video file, occurrence age of the related words, information associated with the one or more manually entered tags, vernacular meaning of the plurality of words, or colloquial considerations of the meaning of the plurality of words. 35. The non-transitory computer-readable medium of claim 32 , wherein the sets of instructions when further executed by the computer cause the computer to determine a score for each of the plurality of words, wherein the score includes word frequency, word distribution, and word variety. | 0.674944 |
8,620,657 | 11 | 20 | 11. At least one computer readable medium encoded with at least one program for execution on at least one processor, the program having instructions that, when executed by the at least one processor, perform a method of determining a validity of an identity asserted by a speaker using a voice print associated with a user whose identity the speaker is asserting, the voice print obtained from the user's utterance of at least one enrollment utterance including at least one enrollment word, the method comprising: obtaining a voice signal of the speaker uttering at least one challenge utterance, wherein the at least one challenge utterance includes at least one word that was not in the at least one enrollment utterance; and determining whether the speaker is the user based, at least in part, on the voice signal and the voice print. | 11. At least one computer readable medium encoded with at least one program for execution on at least one processor, the program having instructions that, when executed by the at least one processor, perform a method of determining a validity of an identity asserted by a speaker using a voice print associated with a user whose identity the speaker is asserting, the voice print obtained from the user's utterance of at least one enrollment utterance including at least one enrollment word, the method comprising: obtaining a voice signal of the speaker uttering at least one challenge utterance, wherein the at least one challenge utterance includes at least one word that was not in the at least one enrollment utterance; and determining whether the speaker is the user based, at least in part, on the voice signal and the voice print. 20. The at least one computer readable medium of claim 11 , the method further comprising performing automatic speech recognition on the voice signal of the speaker to verify that the speaker spoke the at least one word in the at least one challenge utterance. | 0.719828 |
7,885,426 | 1 | 4 | 1. A system for assessing copyright fees based on the content being copied, comprising: a processor; a scanning module operable to scan a document comprising at least one page; a content identifying module operable to identify a content on each scanned page of the document and comprising an Optical Character Recognition (OCR) engine operable to extract a stream of text from each scanned page of the document; and a copyright holder identifying module operable to identify a copyright holder of the identified content; wherein the identifying a copyright holder of the identified content comprises: processing the stream of text into contiguous text segments; forming a separate query for each of the contiguous text segments; and searching a copyrighted content database for matching copyrighted content based on the query; wherein the processing the stream of text into contiguous text segments is based on textual coherence determined in accordance with linguistic analysis of the scanned text. | 1. A system for assessing copyright fees based on the content being copied, comprising: a processor; a scanning module operable to scan a document comprising at least one page; a content identifying module operable to identify a content on each scanned page of the document and comprising an Optical Character Recognition (OCR) engine operable to extract a stream of text from each scanned page of the document; and a copyright holder identifying module operable to identify a copyright holder of the identified content; wherein the identifying a copyright holder of the identified content comprises: processing the stream of text into contiguous text segments; forming a separate query for each of the contiguous text segments; and searching a copyrighted content database for matching copyrighted content based on the query; wherein the processing the stream of text into contiguous text segments is based on textual coherence determined in accordance with linguistic analysis of the scanned text. 4. The system of claim 1 wherein the copyright holder identifying module comprises an index of copyrighted information and wherein the copyright holder identifying module is operable to identify the copyright holder of the identified content by searching the index of the copyrighted information using at least a portion of the identified content as a part of a query. | 0.5 |
9,424,559 | 1 | 2 | 1. A method comprising: with a computer, generating a calendar event that is electronically addressed to a plurality of calendar event recipients via a computer network, said calendar event being an event scheduled to occur at a future time for a plurality of participants and recorded in an electronic calendar in a calendaring application executing on said computer, said calendar event recipients receiving an electronic notification of said calendar event via said computer network; with said computer, generating a designation of a subset of the plurality of calendar event recipients as first annotation recipients, such that, with respect to the calendar event, there are both general event recipients and first annotation recipients; and with said computer, associating a first annotation with the calendar event, the first annotation comprising information additional to the calendar event as originally created, the first annotation being addressed to the first annotation recipients such that, with respect to the calendar event, all recipients are sent the electronic notification, but the first annotation is sent only to the designated subset of recipients for that calendar event. | 1. A method comprising: with a computer, generating a calendar event that is electronically addressed to a plurality of calendar event recipients via a computer network, said calendar event being an event scheduled to occur at a future time for a plurality of participants and recorded in an electronic calendar in a calendaring application executing on said computer, said calendar event recipients receiving an electronic notification of said calendar event via said computer network; with said computer, generating a designation of a subset of the plurality of calendar event recipients as first annotation recipients, such that, with respect to the calendar event, there are both general event recipients and first annotation recipients; and with said computer, associating a first annotation with the calendar event, the first annotation comprising information additional to the calendar event as originally created, the first annotation being addressed to the first annotation recipients such that, with respect to the calendar event, all recipients are sent the electronic notification, but the first annotation is sent only to the designated subset of recipients for that calendar event. 2. The method of claim 1 , wherein generating a designation of the subset of the plurality of calendar event recipients as first annotation recipients comprises generating a designation of a predefined group as the first annotation recipients. | 0.593645 |
9,390,152 | 17 | 19 | 17. A computer system comprising: one or more computer-readable storage media having stored thereon computer-executable instructions; one or more processors that, when executing the executable instructions, causes the computing system to have an architecture that dynamically adapts metadata for use with a native data encoding, by performing the following acts: instantiating a metadata reader that accesses one or more portions of metadata in a file containing an object model description of an object model, the metadata comprising metadata represented in an encoding that is expected by a metadata reader configured to read native metadata; the metadata reader determining that at least some of the one or more portions of the accessed metadata are encoded in a non-native encoding; the metadata reader determining one or more metadata modifications required to transform the non-native encoding into native encoding for the at least some of the one or more portions of the accessed metadata; and adapting the accessed portions of metadata from non-native encoding to native encoding according to the determined one or more modifications, such that the native and non-native encodings of the accessed portions of the metadata are contained in the file containing the object model descriptions for the object model, and such that the object model is readable by a native runtime. | 17. A computer system comprising: one or more computer-readable storage media having stored thereon computer-executable instructions; one or more processors that, when executing the executable instructions, causes the computing system to have an architecture that dynamically adapts metadata for use with a native data encoding, by performing the following acts: instantiating a metadata reader that accesses one or more portions of metadata in a file containing an object model description of an object model, the metadata comprising metadata represented in an encoding that is expected by a metadata reader configured to read native metadata; the metadata reader determining that at least some of the one or more portions of the accessed metadata are encoded in a non-native encoding; the metadata reader determining one or more metadata modifications required to transform the non-native encoding into native encoding for the at least some of the one or more portions of the accessed metadata; and adapting the accessed portions of metadata from non-native encoding to native encoding according to the determined one or more modifications, such that the native and non-native encodings of the accessed portions of the metadata are contained in the file containing the object model descriptions for the object model, and such that the object model is readable by a native runtime. 19. The computer system of claim 17 , wherein: the metadata reader determines that a given user is requesting the file containing the native and non-native encodings of the accessed portions of the metadata; and based on the determination that the given user is requesting the file containing the native and non-native encodings of the accessed portions of the metadata, passing the appropriate encoding to the given user. | 0.5 |
8,615,419 | 41 | 42 | 41. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; a categorization component for categorizing the interaction, based on a determined relation of data of the interaction to churning, into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category; an interaction chum score determination component for determining an interaction chum score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories using a formula:
A *(maximal score for a churning category)+ B *((number of churning categories into which the interaction is categorized)/(number of churning categories)*100), wherein A and B are coefficients set by a user and satisfy a condition of A+B=1; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above. | 41. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; a categorization component for categorizing the interaction, based on a determined relation of data of the interaction to churning, into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category; an interaction chum score determination component for determining an interaction chum score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories using a formula:
A *(maximal score for a churning category)+ B *((number of churning categories into which the interaction is categorized)/(number of churning categories)*100), wherein A and B are coefficients set by a user and satisfy a condition of A+B=1; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above. 42. The apparatus according to claim 41 , wherein each category is characterized based on former interactions. | 0.556452 |
8,380,840 | 23 | 35 | 23. A Session Initiation Protocol (SIP) server computer comprising: a first SIP application layer software module, the first SIP application layer software module being executable by the SIP server computer to provide SIP functionality utilizing a first proprietary application; a second SIP application layer software module, the second SIP application layer software module being executable by the SIP server computer to provide SIP functionality utilizing a second proprietary application that is different from the first proprietary application; a call event record module coupled to the first SIP application layer software module and the second SIP application layer software module, the call event record module to: create a call event record, based on the first proprietary application, for each call event, of one or more call events, associated with the SIP server computer; an Extensible Markup Language (XML) processor module coupled to the call event record module, the XML processor module to: generate, for each created call event record, an XML document; create an XML call event file, the XML call event file including each generated call event record, each generated call event record including a tag comprising a string of unparsed data that is bracketed by delimiting punctuation, when creating the XML call event file, the XML processor module being to: generate an XML document type declaration section that includes data identifying one or more relationships associated with the tag included in each generated call event record included in the XML call event file, generate a server information section that includes data associated with the SIP server computer, generate, for each created call event record, a SIP message type section that identifies a type of a message associated with the created call event record, and generate, for each created call event record, an event information section that includes information associated with a processing of the message associated with the created call event record; and a third module, the third module being executable by the SIP server computer to monitor network traffic associated with the SIP server computer based on the XML call event file using a third proprietary application that is different from the first proprietary application and the second proprietary application. | 23. A Session Initiation Protocol (SIP) server computer comprising: a first SIP application layer software module, the first SIP application layer software module being executable by the SIP server computer to provide SIP functionality utilizing a first proprietary application; a second SIP application layer software module, the second SIP application layer software module being executable by the SIP server computer to provide SIP functionality utilizing a second proprietary application that is different from the first proprietary application; a call event record module coupled to the first SIP application layer software module and the second SIP application layer software module, the call event record module to: create a call event record, based on the first proprietary application, for each call event, of one or more call events, associated with the SIP server computer; an Extensible Markup Language (XML) processor module coupled to the call event record module, the XML processor module to: generate, for each created call event record, an XML document; create an XML call event file, the XML call event file including each generated call event record, each generated call event record including a tag comprising a string of unparsed data that is bracketed by delimiting punctuation, when creating the XML call event file, the XML processor module being to: generate an XML document type declaration section that includes data identifying one or more relationships associated with the tag included in each generated call event record included in the XML call event file, generate a server information section that includes data associated with the SIP server computer, generate, for each created call event record, a SIP message type section that identifies a type of a message associated with the created call event record, and generate, for each created call event record, an event information section that includes information associated with a processing of the message associated with the created call event record; and a third module, the third module being executable by the SIP server computer to monitor network traffic associated with the SIP server computer based on the XML call event file using a third proprietary application that is different from the first proprietary application and the second proprietary application. 35. The SIP server computer of claim 23 , where the XML call event file includes a server information tag that identifies an originating server associated with each call event, of the one or more call events, and where the SIP server computer executes the third SIP application layer software module to: determine, based on the XML document type declaration section, that the server information tag identifies the originating server. | 0.5 |
5,568,383 | 1 | 12 | 1. A computer implemented method of transmitting a document in a data processing system having a plurality of workstations from an originator to a recipient, comprising: creating said document in a first workstation of said originator in a first language; translating said document from said first language into a second language at said first workstation and generating information loss for said document accessible by said originator; specifying loss criteria restricting a particular one of a plurality of translations by said originator based on said information loss and combining said loss criteria with said document in said first language; and transmitting said document in said first language with said loss criteria to said recipient at a second workstation in said data processing system for translation into said second language selected by said recipient based on said loss criteria when said second language is not the particular one of said plurality of translations restricted by said originator. | 1. A computer implemented method of transmitting a document in a data processing system having a plurality of workstations from an originator to a recipient, comprising: creating said document in a first workstation of said originator in a first language; translating said document from said first language into a second language at said first workstation and generating information loss for said document accessible by said originator; specifying loss criteria restricting a particular one of a plurality of translations by said originator based on said information loss and combining said loss criteria with said document in said first language; and transmitting said document in said first language with said loss criteria to said recipient at a second workstation in said data processing system for translation into said second language selected by said recipient based on said loss criteria when said second language is not the particular one of said plurality of translations restricted by said originator. 12. A computer implemented method of transmitting a document in a data processing system according to claim 1 wherein said transmitting step includes the step of: transmitting said document in said first language with said loss criteria by said recipient at said second workstation in said data processing system to a second recipient for translation into a third language selected by said second recipient based on said loss criteria when said third language is not the particular one of said plurality of translations restricted by said originator. | 0.539363 |
9,244,706 | 8 | 10 | 8. The method of claim 1 , wherein the plug-in employs an object model exposed by a class generator to provide information about generated classes and interfaces. | 8. The method of claim 1 , wherein the plug-in employs an object model exposed by a class generator to provide information about generated classes and interfaces. 10. The method of claim 8 , wherein the plug-in generates a command shell cmdlet without parsing the schema. | 0.534483 |
8,151,292 | 9 | 11 | 9. The system of claim 1 , wherein the UI allows selection of a portion of the media instance for which at least one of the synchronized data, the reaction data, the aggregated reaction data, and parsed reaction data is viewed. | 9. The system of claim 1 , wherein the UI allows selection of a portion of the media instance for which at least one of the synchronized data, the reaction data, the aggregated reaction data, and parsed reaction data is viewed. 11. The system of claim 9 , wherein the portion includes a period of time. | 0.5 |
9,251,221 | 1 | 6 | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 6. The method of claim 1 , wherein the object-scoring rule variably identifies the numerical contribution to be applied to the score of the object based on a value for a field in one or more particular events that caused the triggering condition to be met, the value for the field derived by applying an extraction rule or regular expression to the portion of machine data in the one or more particular events. | 0.683153 |
7,627,588 | 25 | 26 | 25. A method, comprising: receiving one or more signals that define a plurality of categories associated with a set of data objects; receiving a selection of a category from among the plurality of categories, the category being associated with a subset of objects, the subset being included in the set of objects and including at least one object; receiving a selection of a concept from among a plurality of concepts associated with the category; using a processor to perform multi-dimensional analysis on the concept, the multi-dimensional analysis including determining a strength of presence of the concept in the subset; if the concept is absent from the subset, providing an indication of an absence of the concept from the subset; and outputting to a display device a graphical representation of the strength of presence and the category. | 25. A method, comprising: receiving one or more signals that define a plurality of categories associated with a set of data objects; receiving a selection of a category from among the plurality of categories, the category being associated with a subset of objects, the subset being included in the set of objects and including at least one object; receiving a selection of a concept from among a plurality of concepts associated with the category; using a processor to perform multi-dimensional analysis on the concept, the multi-dimensional analysis including determining a strength of presence of the concept in the subset; if the concept is absent from the subset, providing an indication of an absence of the concept from the subset; and outputting to a display device a graphical representation of the strength of presence and the category. 26. The method of claim 25 , wherein the using a processor to perform multi-dimensional analysis includes one or more of: determining a frequency of occurrence of the concept within the set of objects; determining a normalized frequency of occurrence of the concept within the set of objects; determining a normalized frequency of occurrence of the concept within the subset of objects; determining an electronic path to the location of the subset of objects; determining a characteristic of the subset of objects; and determining a concept type for the concept. | 0.512153 |
9,529,918 | 15 | 16 | 15. The system of claim 13 , wherein the system is further configured to: tokenize the input search query to at least one token to create at least one tokenized query; process the at least one tokenized query by a plurality of engines, wherein each engine of the plurality of engines configured to compute a certainty score that indicates a probability that the at least one tokenized query is mapped to at least one entity, wherein each engine of the plurality of engines is further configured with at least one entity indicating a topic of interest, thereby the plurality of engines are configured with different entities; receive from a set of engines of the plurality of engines their respective entities and computed certainty scores, wherein the set of engines output computed certainty scores above a predefined threshold; and analyze the received certainty scores and the respective entities to determine the search intent. | 15. The system of claim 13 , wherein the system is further configured to: tokenize the input search query to at least one token to create at least one tokenized query; process the at least one tokenized query by a plurality of engines, wherein each engine of the plurality of engines configured to compute a certainty score that indicates a probability that the at least one tokenized query is mapped to at least one entity, wherein each engine of the plurality of engines is further configured with at least one entity indicating a topic of interest, thereby the plurality of engines are configured with different entities; receive from a set of engines of the plurality of engines their respective entities and computed certainty scores, wherein the set of engines output computed certainty scores above a predefined threshold; and analyze the received certainty scores and the respective entities to determine the search intent. 16. The system of claim 15 , wherein the analysis of the received certainty scores and the respective entities includes at least one of: a statistical analysis and a semantic analysis of the received certainty scores and the respective entities to determine which combination of the entities result in a coherent query. | 0.5 |
9,886,946 | 1 | 4 | 1. A computer-implemented method comprising: receiving, by an automated speech recognizer (ASR) system that includes (i) a context selector, (ii) a language model biaser, (iii) an ASR, (iv) a particular language model, and (v) a previously biased language model, audio data corresponding to an utterance of a user; determining, by the context selector of the ASR system, that the user is likely no longer within a particular context that is associated the previously biased language model; in response to determining that the user is likely no longer within a particular context that is associated with the previously biased language model, selecting, by the language model biaser of the ASR system, the particular language model for use in transcribing utterances; after selecting the baseline language model, generating, by the ASR of the ASR system, a transcription of the utterance using the particular language model; and providing a representation of the transcription for output. | 1. A computer-implemented method comprising: receiving, by an automated speech recognizer (ASR) system that includes (i) a context selector, (ii) a language model biaser, (iii) an ASR, (iv) a particular language model, and (v) a previously biased language model, audio data corresponding to an utterance of a user; determining, by the context selector of the ASR system, that the user is likely no longer within a particular context that is associated the previously biased language model; in response to determining that the user is likely no longer within a particular context that is associated with the previously biased language model, selecting, by the language model biaser of the ASR system, the particular language model for use in transcribing utterances; after selecting the baseline language model, generating, by the ASR of the ASR system, a transcription of the utterance using the particular language model; and providing a representation of the transcription for output. 4. The method of claim 1 , wherein determining that the user is likely no longer within the particular context comprises determining that the user is likely in a different context. | 0.621849 |
8,140,526 | 14 | 15 | 14. The method of claim 11 , further comprising: separating the plurality of property names in the object-specific data set into a first group comprising the first property name and a second group comprising the second property name, wherein the property names in the first group have their respective association strength values at or above a predetermined value, wherein the property names in the second group have their respective association strength values below the predetermined value; counting in the document the frequencies of the property names in the first group; and counting in the document the frequencies of the property names in the second group, wherein the relevance score is calculated using the frequencies of the property names in the first group and the frequencies of property names in the second group. | 14. The method of claim 11 , further comprising: separating the plurality of property names in the object-specific data set into a first group comprising the first property name and a second group comprising the second property name, wherein the property names in the first group have their respective association strength values at or above a predetermined value, wherein the property names in the second group have their respective association strength values below the predetermined value; counting in the document the frequencies of the property names in the first group; and counting in the document the frequencies of the property names in the second group, wherein the relevance score is calculated using the frequencies of the property names in the first group and the frequencies of property names in the second group. 15. The method of claim 14 , further comprising: summing the frequencies of the property names in the first group in the document to produce a first sum; and summing the frequencies of property names in the second group in the document to produce a second sum, where the relevance score is calculated using the first sum and the second sum. | 0.5 |
9,070,089 | 13 | 17 | 13. A system comprising: one or more computers configured to perform a method comprising: obtaining a model representation of a predictive model, wherein the model representation is associated with a respective user and expresses a respective predictive model; and selecting a model implementation for the model representation, the model implementation comprising one or more computer programs operable to be executed on one or more computing devices, and the model implementation being selected for the corresponding model representation based on one or more system usage properties associated with the user associated with the corresponding model representation; and causing execution of the selected model implementation. | 13. A system comprising: one or more computers configured to perform a method comprising: obtaining a model representation of a predictive model, wherein the model representation is associated with a respective user and expresses a respective predictive model; and selecting a model implementation for the model representation, the model implementation comprising one or more computer programs operable to be executed on one or more computing devices, and the model implementation being selected for the corresponding model representation based on one or more system usage properties associated with the user associated with the corresponding model representation; and causing execution of the selected model implementation. 17. The system of claim 13 , wherein the method further comprises: selecting a computationally-intensive model implementation for the model representation based on a determination that system resources were previously used during an off-peak time of day. | 0.76306 |
8,458,600 | 8 | 11 | 8. A computer program product for presenting a multi-user mashup session across execution environments, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to, establish a mashup session based, at least in part, on a mashup application and execution environments of participants of the mashup session; maintain state data representative of at least a current view of the mashup session, wherein the computer readable program code being configured to maintain state data representative of at least the current view of the mashup session comprises the computer readable program code being configured to maintain at least one of a history of mashup actions performed in the execution environments that affect a state of the mashup session, a history of requests generated responsive to mashup actions performed in the execution environments during the mashup session, history of requests and corresponding parameter values submitted to the mashup application during the mashup session, one or more recent responses to requests submitted during the mashup session, and data generated by the mashup application responsive to actions performed with the mashup application in the execution environments during the mashup session; and maintain consistent views of the mashup session across the execution environments in accordance with the state data. | 8. A computer program product for presenting a multi-user mashup session across execution environments, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to, establish a mashup session based, at least in part, on a mashup application and execution environments of participants of the mashup session; maintain state data representative of at least a current view of the mashup session, wherein the computer readable program code being configured to maintain state data representative of at least the current view of the mashup session comprises the computer readable program code being configured to maintain at least one of a history of mashup actions performed in the execution environments that affect a state of the mashup session, a history of requests generated responsive to mashup actions performed in the execution environments during the mashup session, history of requests and corresponding parameter values submitted to the mashup application during the mashup session, one or more recent responses to requests submitted during the mashup session, and data generated by the mashup application responsive to actions performed with the mashup application in the execution environments during the mashup session; and maintain consistent views of the mashup session across the execution environments in accordance with the state data. 11. The computer program product of claim 8 , wherein the computer readable program code being configured to maintain consistent views of the mashup session across the execution environments in accordance with the state data comprises the computer readable program code being configured to relay at least one of an indication of an action performed with the mashup application in a first of the execution environments during the mashup session to the other execution environments and an indication of a response to the action performed with the mashup application in the first of the execution environments to the other execution environments, wherein the computer readable program code being configured to maintain state data representative of at least a current view of the mashup session comprises the computer readable program code being configured to update the state data to reflect the action performed with the mashup application in the first of the execution environments. | 0.5 |
8,909,624 | 3 | 4 | 3. The method of claim 1 , further comprising: evaluating the results based on a social network of the user; and evaluating the results based on preferences declared by the user. | 3. The method of claim 1 , further comprising: evaluating the results based on a social network of the user; and evaluating the results based on preferences declared by the user. 4. The method of claim 3 , wherein evaluating the results based on the social network is done in parallel with evaluating the results based on the attributes and in parallel with evaluating the results based on the preferences. | 0.5 |
8,583,683 | 1 | 16 | 1. A computer-implemented method comprising: presenting a user interface to a user to enable the user to select and provide content items and to select privacy settings and/or sharing and publication setting for each content item and/or different types of contents selected and provided via the interface to control interactions of other users of the network related or connected to the user with each content item and/or multiple different types of content; accepting an input provided via selection of the one or more content items and/or one or more types of content via the user interface for the user of the network and receiving via the interface, a content from the user of the network; accepting an input provided via selection of the one or more privacy settings and/or sharing and publication setting via the user interface for the user of the network, the input describing a particular content items and/or type of content to be controlled related to the user and receiving via the interface, a selection of a privacy setting and sharing and publication setting to be associated with the content item and/or one or more types of content from the user, the privacy setting and sharing and publication setting enabling one or more connections and/or set of users and/or determined users and/or subscribers to access the content item; providing or presenting or publishing the content item into one or more communication channels of the network and/or controlling which of the other users are permitted to communicate content to the user and/or to access content and/or one or more types of content of the user via the network based on the input; making the content item accessible to one or more connections and/or set of users and/or determined users and/or subscribers via the communication channel, where accessibility to the one or more connections and/or set of users and/or determined users and/or subscribers is determined by the privacy settings and sharing and publication setting selected by the user; and responsive to receiving a selection and sharing and publication setting to be associated with the content item from locking the content item from being published a communication channel accessible to one or more connections, exclude the content item from the communication channel accessible to the one or more connections. | 1. A computer-implemented method comprising: presenting a user interface to a user to enable the user to select and provide content items and to select privacy settings and/or sharing and publication setting for each content item and/or different types of contents selected and provided via the interface to control interactions of other users of the network related or connected to the user with each content item and/or multiple different types of content; accepting an input provided via selection of the one or more content items and/or one or more types of content via the user interface for the user of the network and receiving via the interface, a content from the user of the network; accepting an input provided via selection of the one or more privacy settings and/or sharing and publication setting via the user interface for the user of the network, the input describing a particular content items and/or type of content to be controlled related to the user and receiving via the interface, a selection of a privacy setting and sharing and publication setting to be associated with the content item and/or one or more types of content from the user, the privacy setting and sharing and publication setting enabling one or more connections and/or set of users and/or determined users and/or subscribers to access the content item; providing or presenting or publishing the content item into one or more communication channels of the network and/or controlling which of the other users are permitted to communicate content to the user and/or to access content and/or one or more types of content of the user via the network based on the input; making the content item accessible to one or more connections and/or set of users and/or determined users and/or subscribers via the communication channel, where accessibility to the one or more connections and/or set of users and/or determined users and/or subscribers is determined by the privacy settings and sharing and publication setting selected by the user; and responsive to receiving a selection and sharing and publication setting to be associated with the content item from locking the content item from being published a communication channel accessible to one or more connections, exclude the content item from the communication channel accessible to the one or more connections. 16. The computer-implemental method of claim 1 , wherein the privacy setting and sharing and publication setting allows the content item as public and searchable by public. | 0.841328 |
9,135,339 | 8 | 12 | 8. A system for invoking an audio hyperlink, the system comprising a computer processor, a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions capable of: providing a user with an option to either enter a first keyword of the user's choice or select a second keyword provided to the user, either the first keyword or the second keyword being configured for use in a speech instruction to invoke the audio hyperlink; storing a plurality of keywords to be included in a grammar, the plurality of keywords comprising either the first keyword or the second keyword; identifying, through an audio anchor element, a predetermined playback time in an audio file pre-designated as having an association with the audio hyperlink; wherein the audio anchor element is a markup language element that identifies the audio file pre-designated as having an association with the audio hyperlink, a Uniform Resource Identifier (‘URI’) identifying a target resource associated with the audio hyperlink, an audio indication of the audio hyperlink, the predetermined playback time in the audio file pre-designated as having an association with the audio hyperlink, and the grammar including the plurality of keywords for speech invocation of a respective plurality of hyperlinks including the audio hyperlink; playing the audio indication of the audio hyperlink at the predetermined playback time; receiving from the user the speech instruction to invoke the audio hyperlink; identifying, through the audio anchor element, the URI associated with the audio hyperlink; and invoking the URI. | 8. A system for invoking an audio hyperlink, the system comprising a computer processor, a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions capable of: providing a user with an option to either enter a first keyword of the user's choice or select a second keyword provided to the user, either the first keyword or the second keyword being configured for use in a speech instruction to invoke the audio hyperlink; storing a plurality of keywords to be included in a grammar, the plurality of keywords comprising either the first keyword or the second keyword; identifying, through an audio anchor element, a predetermined playback time in an audio file pre-designated as having an association with the audio hyperlink; wherein the audio anchor element is a markup language element that identifies the audio file pre-designated as having an association with the audio hyperlink, a Uniform Resource Identifier (‘URI’) identifying a target resource associated with the audio hyperlink, an audio indication of the audio hyperlink, the predetermined playback time in the audio file pre-designated as having an association with the audio hyperlink, and the grammar including the plurality of keywords for speech invocation of a respective plurality of hyperlinks including the audio hyperlink; playing the audio indication of the audio hyperlink at the predetermined playback time; receiving from the user the speech instruction to invoke the audio hyperlink; identifying, through the audio anchor element, the URI associated with the audio hyperlink; and invoking the URI. 12. The system of claim 8 wherein the computer memory also has disposed within it computer program instructions capable of: receiving speech from a user; converting the speech to text; and comparing the text to a grammar. | 0.665152 |
8,077,812 | 15 | 16 | 15. The method as recited in claim 11 , wherein, for step (b), the metric value for the received symbol is based on an error between the received symbol and one of the set of candidates. | 15. The method as recited in claim 11 , wherein, for step (b), the metric value for the received symbol is based on an error between the received symbol and one of the set of candidates. 16. The method as recited in claim 15 , wherein, for step (b), the error is Euclidean distance and the metric value is based on an error metric. | 0.5 |
9,477,643 | 8 | 10 | 8. The method of claim 1 , wherein the inferring by the processor whether the second input from the user is related to the at least one linguistic element associated with the first conversation session includes: identifying by the processor a linguistic element associated with the first conversation session that identifies at least one entity; identifying by the processor a linguistic linking element of the second input; determining by the processor whether the linguistic linking element of the second input is a suitable link to the linguistic element associated with the first conversation session that identifies at least one entity; and upon a condition in which the linguistic linking element of the second input is a suitable link, concluding by the processor that the second input from the user is related to the at least one linguistic element associated with the first conversation session. | 8. The method of claim 1 , wherein the inferring by the processor whether the second input from the user is related to the at least one linguistic element associated with the first conversation session includes: identifying by the processor a linguistic element associated with the first conversation session that identifies at least one entity; identifying by the processor a linguistic linking element of the second input; determining by the processor whether the linguistic linking element of the second input is a suitable link to the linguistic element associated with the first conversation session that identifies at least one entity; and upon a condition in which the linguistic linking element of the second input is a suitable link, concluding by the processor that the second input from the user is related to the at least one linguistic element associated with the first conversation session. 10. The method of claim 8 , wherein the linguistic linking element of the second input is at least one of a pronoun and a syntactic expletive. | 0.605556 |
7,484,185 | 14 | 16 | 14. The method of claim 13 , wherein a first graphical connector graphically connects only the plurality of found occurrences of the specified information element within the multilevel treeview and wherein a second graphical connector graphically connects all of the information elements within the multilevel treeview to indicate the hierarchy. | 14. The method of claim 13 , wherein a first graphical connector graphically connects only the plurality of found occurrences of the specified information element within the multilevel treeview and wherein a second graphical connector graphically connects all of the information elements within the multilevel treeview to indicate the hierarchy. 16. The method of claim 14 , wherein a level of the displayed multilevel treeview of the information hierarchy comprises at least one of the plurality of occurrences of the specified information element and the information elements of the information hierarchy. | 0.668782 |
9,053,152 | 1 | 6 | 1. A computer-implemented method, comprising: identifying a data artifact associated with each search result of at least one received search result; associating each identified data artifact with a module category of a plurality of module categories, the module category associated with a module associated with a module gallery displaying modules that may be associated with an enterprise workspace page associated with an enterprise workspace; injecting the identified artifacts into a content gallery presenting available content associated with a module available to be selected and added to the enterprise workspace page and extending what is displayed in the module gallery to include non-identified artifacts; categorize, by operation of at least one computer, the injected identified artifacts within the content gallery; presenting at least a subset of the injected identified artifacts on the enterprise workspace page; and constructing a context associated with at least one of the enterprise workspace or the enterprise workspace page. | 1. A computer-implemented method, comprising: identifying a data artifact associated with each search result of at least one received search result; associating each identified data artifact with a module category of a plurality of module categories, the module category associated with a module associated with a module gallery displaying modules that may be associated with an enterprise workspace page associated with an enterprise workspace; injecting the identified artifacts into a content gallery presenting available content associated with a module available to be selected and added to the enterprise workspace page and extending what is displayed in the module gallery to include non-identified artifacts; categorize, by operation of at least one computer, the injected identified artifacts within the content gallery; presenting at least a subset of the injected identified artifacts on the enterprise workspace page; and constructing a context associated with at least one of the enterprise workspace or the enterprise workspace page. 6. The computer-implemented method of claim 1 , wherein the subset of the injected identified artifacts is arranged on the enterprise workspace page according to a predefined enterprise workspace page layout. | 0.624549 |
9,454,729 | 14 | 15 | 14. The system of claim 8 , further comprising the one or more processor-based devices configured to: generate the recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values and an application of a probability distribution. | 14. The system of claim 8 , further comprising the one or more processor-based devices configured to: generate the recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values and an application of a probability distribution. 15. The system of claim 14 , further comprising the one or more processor-based devices configured to: generate the recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values and the application of the probability distribution, wherein the application of the probability distribution is tunable by the first user. | 0.5 |
7,774,349 | 7 | 8 | 7. The system of claim 1 , the filter component employs explicit or implicit voting to determine the system settings preferences of disparate users in the community in order to predict the likely or possible settings or profiles for new users of the system. | 7. The system of claim 1 , the filter component employs explicit or implicit voting to determine the system settings preferences of disparate users in the community in order to predict the likely or possible settings or profiles for new users of the system. 8. The system of claim 7 , the filtering component determines votes of an active user in the community of users based on partial information regarding the active user and a set of weights calculated from a user database. | 0.5 |
9,600,533 | 1 | 2 | 1. A method of searching for content objects associated with a search term, the method being executed by a system comprising a processor and a non-transitory computer-readable medium storing instructions that, when executed by the processor, cause the processor to perform the method, the method comprising: performing a first search of a content database, wherein the first search identifies content information included in the content database that includes the first search term; analyzing the content information to generate a plurality of relationship vectors between objects included in the content information; identifying a plurality of sections in the content information; scoring the plurality of sections based on the plurality of relationship vectors; generating an object summary for at least one section of the plurality of sections selected based on a score of the at least one section relative to scores of the other sections of the plurality of sections; determining, based on the object summary, at least one additional search term; and performing a second search for content objects relating to the at least one additional search term. | 1. A method of searching for content objects associated with a search term, the method being executed by a system comprising a processor and a non-transitory computer-readable medium storing instructions that, when executed by the processor, cause the processor to perform the method, the method comprising: performing a first search of a content database, wherein the first search identifies content information included in the content database that includes the first search term; analyzing the content information to generate a plurality of relationship vectors between objects included in the content information; identifying a plurality of sections in the content information; scoring the plurality of sections based on the plurality of relationship vectors; generating an object summary for at least one section of the plurality of sections selected based on a score of the at least one section relative to scores of the other sections of the plurality of sections; determining, based on the object summary, at least one additional search term; and performing a second search for content objects relating to the at least one additional search term. 2. The method of claim 1 , wherein the method further comprises receiving the first search term from a user. | 0.787402 |
8,145,623 | 7 | 8 | 7. The method of claim 1 wherein presenting representative queries further comprises: presenting one or more representative queries in order according to the ranks of their respective clusters, where the one or more representative queries are associated with a common representative category. | 7. The method of claim 1 wherein presenting representative queries further comprises: presenting one or more representative queries in order according to the ranks of their respective clusters, where the one or more representative queries are associated with a common representative category. 8. The method of claim 7 wherein a total number of representative queries associated with the common representative category does not exceed a pre-determined threshold. | 0.5 |
9,183,282 | 9 | 10 | 9. The method of claim 1 , further comprising: presenting, to the user, a recommendation message that is configured to be presented to users of the social networking system having a user attribute matching the generated inferred user attribute. | 9. The method of claim 1 , further comprising: presenting, to the user, a recommendation message that is configured to be presented to users of the social networking system having a user attribute matching the generated inferred user attribute. 10. The method of claim 9 , wherein the recommendation message is an advertisement. | 0.5 |
7,483,891 | 45 | 46 | 45. The method of claim 37 , wherein the ranking step includes calculating overall-relevance scores for the extracted-query units based on the revenue-generation amounts and the relevance scores. | 45. The method of claim 37 , wherein the ranking step includes calculating overall-relevance scores for the extracted-query units based on the revenue-generation amounts and the relevance scores. 46. The method of claim 45 , wherein the comparing step includes comparing an extracted-query unit, having a highest overall-relevance score, with at least one of the query units and the keywords associated with the relevant content. | 0.558712 |
8,024,733 | 54 | 55 | 54. The apparatus of claim 52 , further comprising: at least one online processing client that performs operations using the business function components and the business object components in real time. | 54. The apparatus of claim 52 , further comprising: at least one online processing client that performs operations using the business function components and the business object components in real time. 55. The apparatus of claim 54 , wherein the batch component shares the business function components and the business object components with the at least one online processing client. | 0.542714 |
9,824,683 | 1 | 6 | 1. A computer program product for augmenting training data, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive a training set of sampled audio data including speech of a plurality of source speakers; for each of the plurality of source speakers: convert a feature sequence of a source speaker, of the plurality of source speakers, determined from a plurality of utterances of scripted speech within the training set, to a feature sequence of a respective target speaker under the same scripted speech, wherein the feature sequence of the respective target speaker is added to the training set; train a speaker-dependent acoustic model for the respective target speaker for corresponding speaker-specific acoustic characteristics; and estimate a mapping function between the feature sequence of the source speaker and the speaker-dependent acoustic model of the respective target speaker; and for each of the plurality of source speakers: map each of the utterances from each of the plurality of source speakers in the training set using the mapping function to a plurality of other source speakers of the plurality of source speakers, wherein the mapping is added to the training set to generate augmented training data configured to train an automatic system recognition computer system. | 1. A computer program product for augmenting training data, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive a training set of sampled audio data including speech of a plurality of source speakers; for each of the plurality of source speakers: convert a feature sequence of a source speaker, of the plurality of source speakers, determined from a plurality of utterances of scripted speech within the training set, to a feature sequence of a respective target speaker under the same scripted speech, wherein the feature sequence of the respective target speaker is added to the training set; train a speaker-dependent acoustic model for the respective target speaker for corresponding speaker-specific acoustic characteristics; and estimate a mapping function between the feature sequence of the source speaker and the speaker-dependent acoustic model of the respective target speaker; and for each of the plurality of source speakers: map each of the utterances from each of the plurality of source speakers in the training set using the mapping function to a plurality of other source speakers of the plurality of source speakers, wherein the mapping is added to the training set to generate augmented training data configured to train an automatic system recognition computer system. 6. The computer program product of claim 1 , further comprising a program instructions executable by the processor to cause the processor to select the plurality of other source speakers using a criterion including at least one of vocal tract length, dialect, and signal-to-noise ratio. | 0.5 |
8,316,394 | 32 | 33 | 32. The system of claim 20 , wherein the user equipment is configured to associate the user selected first cell of the mosaic page with interactive features. | 32. The system of claim 20 , wherein the user equipment is configured to associate the user selected first cell of the mosaic page with interactive features. 33. The system of claim 32 , wherein the interactive features are accessed via a remote control device. | 0.801158 |
8,473,317 | 23 | 24 | 23. A non-transitory computer readable medium including program code for providing a message-based interface for performing a service part supply plan, the medium comprising: program code for receiving via a message-based interface derived from a common business object model, where the common business object model includes business objects having relationships that enable derivation of message-based interfaces and message packages, the message-based interface exposing at least one service as defined in a service registry and from a heterogeneous application executing in an environment of computer systems providing message-based services, a first message for querying supply part shortage information associated with a service part supply plan, the shortage information derived from a service part shortage analysis, the first message including a first message package derived from the common business object model and hierarchically organized as: a service part supply plan supply chain management shortage overview by elements query message entity; and at a first hierarchical level of the first message package, a selection package, where the selection package includes, at a second hierarchical level within the first message package, a service part supply plan supply chain management shortage overview by elements entity, and where the service part supply plan supply chain management shortage overview by elements entity includes, at a third hierarchical level within the first message package, a selection by actual result indicator and at least one of a selection by demand planner group code, a selection by service part planning product group code, a selection by ship from location internal identifier (ID), and a selection by ship to location internal ID; program code for processing the first message according to the hierarchical organization of the first message package, where processing the first message includes unpacking the first message package based on the common business object model; and program code for sending a second message to the heterogeneous application responsive to the first message, where the second message includes a second message package derived from the common business object model to provide consistent semantics with the first message package. | 23. A non-transitory computer readable medium including program code for providing a message-based interface for performing a service part supply plan, the medium comprising: program code for receiving via a message-based interface derived from a common business object model, where the common business object model includes business objects having relationships that enable derivation of message-based interfaces and message packages, the message-based interface exposing at least one service as defined in a service registry and from a heterogeneous application executing in an environment of computer systems providing message-based services, a first message for querying supply part shortage information associated with a service part supply plan, the shortage information derived from a service part shortage analysis, the first message including a first message package derived from the common business object model and hierarchically organized as: a service part supply plan supply chain management shortage overview by elements query message entity; and at a first hierarchical level of the first message package, a selection package, where the selection package includes, at a second hierarchical level within the first message package, a service part supply plan supply chain management shortage overview by elements entity, and where the service part supply plan supply chain management shortage overview by elements entity includes, at a third hierarchical level within the first message package, a selection by actual result indicator and at least one of a selection by demand planner group code, a selection by service part planning product group code, a selection by ship from location internal identifier (ID), and a selection by ship to location internal ID; program code for processing the first message according to the hierarchical organization of the first message package, where processing the first message includes unpacking the first message package based on the common business object model; and program code for sending a second message to the heterogeneous application responsive to the first message, where the second message includes a second message package derived from the common business object model to provide consistent semantics with the first message package. 24. The medium of claim 23 , where the service part supply plan supply chain management shortage overview by elements entity includes the selection by demand planner group code, and the selection by demand planner group code includes an inclusion exclusion code, an interval boundary type code, and a lower boundary demand planner group code. | 0.5 |
8,290,977 | 70 | 72 | 70. The method of claim 60 , wherein said determining step includes generating an execution plan for execution of the query. | 70. The method of claim 60 , wherein said determining step includes generating an execution plan for execution of the query. 72. The method of claim 70 , wherein said execution plan includes an operator for executing the XPath built-in function. | 0.67033 |
8,538,790 | 19 | 22 | 19. A computer-implemented method for generating an electronically generated business intelligence report, comprising: generating by a computer system a plurality of category indicators each identifying one predefined business-related category of a plurality of predefined business-related categories, wherein the plurality of predefined business-related categories comprises at least two predefined business-related categories selected from the group consisting of customer service, products, marketing, and sales; and generating by the computer system a plurality of quantitative indicators identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page, wherein: a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating, the collected user comments being assigned to one of the plurality of available ratings based on a subjective assessment of each of the collected user comments; and the subjective assessment comprises a keyword association. | 19. A computer-implemented method for generating an electronically generated business intelligence report, comprising: generating by a computer system a plurality of category indicators each identifying one predefined business-related category of a plurality of predefined business-related categories, wherein the plurality of predefined business-related categories comprises at least two predefined business-related categories selected from the group consisting of customer service, products, marketing, and sales; and generating by the computer system a plurality of quantitative indicators identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page, wherein: a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating, the collected user comments being assigned to one of the plurality of available ratings based on a subjective assessment of each of the collected user comments; and the subjective assessment comprises a keyword association. 22. The method of claim 19 , wherein a quantitative value identified in the report for a particular predefined business-related category comprises the quantity of collected user comments associated with that business-related category. | 0.622581 |
7,711,749 | 1 | 2 | 1. A system for providing an association between a system's meta-tagged data objects and a list of terms, the association indicating which objects are and are not covered by a given policy, comprising: a processor operable to obtain a list of terms and a policy, the policy including one or more of the terms and at least one rule, the at least one rule comprising one or more of: a user category, an action, and a data category, the user category indicating at least one applicable user for the at least one rule, the action specifying at least one application that is either permitted or denied by the at least one rule, the data category indicating a type of data object that is governed by the at least one rule, the processor further operable to identify a plurality of meta-tags used in a system and to build one or more mappings between the terms and the meta-tags, the processor further operable to identify all system data objects in the system having one or more meta-tags and create for each meta-tag of each system data object identified, an association between the system data object and the one or more terms to which the meta-tag is mapped, the association indicating whether the system data object is or is not covered by the policy by determining whether there exists the at least one rule in the policy whose terms for the user category, the action and the data category match terms of the system data objects; and a data store operable to store the association. | 1. A system for providing an association between a system's meta-tagged data objects and a list of terms, the association indicating which objects are and are not covered by a given policy, comprising: a processor operable to obtain a list of terms and a policy, the policy including one or more of the terms and at least one rule, the at least one rule comprising one or more of: a user category, an action, and a data category, the user category indicating at least one applicable user for the at least one rule, the action specifying at least one application that is either permitted or denied by the at least one rule, the data category indicating a type of data object that is governed by the at least one rule, the processor further operable to identify a plurality of meta-tags used in a system and to build one or more mappings between the terms and the meta-tags, the processor further operable to identify all system data objects in the system having one or more meta-tags and create for each meta-tag of each system data object identified, an association between the system data object and the one or more terms to which the meta-tag is mapped, the association indicating whether the system data object is or is not covered by the policy by determining whether there exists the at least one rule in the policy whose terms for the user category, the action and the data category match terms of the system data objects; and a data store operable to store the association. 2. The system of claim 1 , wherein the data store includes memory. | 0.554054 |
7,752,162 | 1 | 2 | 1. A computer-implemented method for analyzing on-line analytical processing (OLAP) data to determine user-relevant information, said method comprising: inputting a set of user preferences expressed in a user preference specification language to a computer, wherein each user preference includes a subset of dimensions, measures, conditions on measures, a drill down specification that specifies a dimension upon which to drill down, and conditions upon which said drill down occurs; generating, by said computer, a set of queries, relevant to said user, based on said set of user preferences, said generating a set of queries, relevant to said user, comprising: generating queries sequentially, said generating queries sequentially comprising: generating a single initial query based on said subset of dimensions, measures, and conditions on measures of each user preference, and further sequentially generating queries based on drilling down according to said drill down specification, while said conditions upon which said drill down occurs are satisfied; or generating a set of queries, one for each combination of cube dimensions that are of interest; determining, by said computer, how often each of said subset of dimensions and said measures, corresponding to said each user preference, is accessed by said user for a query; evaluating, by said computer, each of said queries against said OLAP data to give a query result; determining, by said computer, for each of said evaluated queries, whether said query result is relevant to said user, based on said conditions of said each user preference; if said query result is not relevant, then preventing, by said computer, subsequent queries from being generated for said evaluating, based on said subset of dimensions, said measures, said conditions on measures, and said drill down specification for said each user preference corresponding to said query result that is not relevant; and if said query result is relevant, then adding, by said computer, said query result to relevant query results that are to be outputted; based upon said determination, by said computer, of how often said subset of dimensions and said measures are accessed by said user, and said user selected conditions for tagging said queries and query results as interesting, and for drilling down on a selected dimension, modifying, by said computer, said set of user preferences expressed in said user specification language to include said subset of dimensions and said measures that are often accessed by said user, said user selected condition for tagging said queries and query results as interesting, and said selected condition for drilling down; and outputting, by said computer, said relevant query results to said user. | 1. A computer-implemented method for analyzing on-line analytical processing (OLAP) data to determine user-relevant information, said method comprising: inputting a set of user preferences expressed in a user preference specification language to a computer, wherein each user preference includes a subset of dimensions, measures, conditions on measures, a drill down specification that specifies a dimension upon which to drill down, and conditions upon which said drill down occurs; generating, by said computer, a set of queries, relevant to said user, based on said set of user preferences, said generating a set of queries, relevant to said user, comprising: generating queries sequentially, said generating queries sequentially comprising: generating a single initial query based on said subset of dimensions, measures, and conditions on measures of each user preference, and further sequentially generating queries based on drilling down according to said drill down specification, while said conditions upon which said drill down occurs are satisfied; or generating a set of queries, one for each combination of cube dimensions that are of interest; determining, by said computer, how often each of said subset of dimensions and said measures, corresponding to said each user preference, is accessed by said user for a query; evaluating, by said computer, each of said queries against said OLAP data to give a query result; determining, by said computer, for each of said evaluated queries, whether said query result is relevant to said user, based on said conditions of said each user preference; if said query result is not relevant, then preventing, by said computer, subsequent queries from being generated for said evaluating, based on said subset of dimensions, said measures, said conditions on measures, and said drill down specification for said each user preference corresponding to said query result that is not relevant; and if said query result is relevant, then adding, by said computer, said query result to relevant query results that are to be outputted; based upon said determination, by said computer, of how often said subset of dimensions and said measures are accessed by said user, and said user selected conditions for tagging said queries and query results as interesting, and for drilling down on a selected dimension, modifying, by said computer, said set of user preferences expressed in said user specification language to include said subset of dimensions and said measures that are often accessed by said user, said user selected condition for tagging said queries and query results as interesting, and said selected condition for drilling down; and outputting, by said computer, said relevant query results to said user. 2. The method of claim 1 , wherein said conditions on measures comprise any of Boolean conditions, thresholds for outliers, statistical conditions, trends, and comparisons. | 0.584541 |
8,793,593 | 1 | 15 | 1. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; receiving user interactions on one or more external systems, the user interactions including graph actions performed on a first set of graph objects by users of the social networking system; providing a social content product interface to a viewing user, the social content product interface including selectable links associated with the received user interactions on the one or more external systems, the social content product interface associated with a user profile object on the social networking system and provided for display to users of the social networking system; receiving a selection of a link of the selectable links from the viewing user to perform a graph action on a graph object on an external system associated with a particular user interaction of the received user interactions, the particular user interaction associated with a particular user; sending a request to the external system for the viewing user to perform the graph action on the graph object associated with the particular user interaction, the request including an instruction to the external system to execute user input associated with the graph action on a user device associated with the viewing user; and responsive to the request, receiving an indication from the external system that the user device associated with the viewing user executed the user input associated with the graph action performed on the graph object associated with the particular user interaction, and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. | 1. A method comprising: storing at a social networking system a social graph comprising a plurality of graph objects interconnected by graph actions, the graph actions having graph action types defined by entities external to, and independent from, the social networking system, where each of the graph actions represent a relationship between two or more graph objects and each of the graph action types define the relationship between the two or more graph objects; receiving user interactions on one or more external systems, the user interactions including graph actions performed on a first set of graph objects by users of the social networking system; providing a social content product interface to a viewing user, the social content product interface including selectable links associated with the received user interactions on the one or more external systems, the social content product interface associated with a user profile object on the social networking system and provided for display to users of the social networking system; receiving a selection of a link of the selectable links from the viewing user to perform a graph action on a graph object on an external system associated with a particular user interaction of the received user interactions, the particular user interaction associated with a particular user; sending a request to the external system for the viewing user to perform the graph action on the graph object associated with the particular user interaction, the request including an instruction to the external system to execute user input associated with the graph action on a user device associated with the viewing user; and responsive to the request, receiving an indication from the external system that the user device associated with the viewing user executed the user input associated with the graph action performed on the graph object associated with the particular user interaction, and updating the social graph based on the graph action performed, where the graph action is of a graph action type that was defined by one of the entities external to the social networking system. 15. The method of claim 1 , further comprising: providing for display in the social content product interface recent user interactions from other users connected to a user associated with the social content product interface. | 0.859375 |
10,089,974 | 1 | 4 | 1. A text-to-speech learning system, the system comprising: at least one processor; and at least one storage device, operatively connected to the at least one processor and storing: at least one training corpus comprising a plurality of training pairs that represent a varied vocabulary from one or more speakers, each training pair comprising a speech input and a text input corresponding to the speech input; and instructions that, when executed by the at least processor, cause the at least one processor to perform a method for generating a pronunciation sequence conversion model, the method comprising: for each training pair: selecting a training pair from the at least one training corpus; generating a first pronunciation sequence from the speech input of the training pair; and generating a second pronunciation sequence from the text input of the training pair; determining a pronunciation sequence difference between the first pronunciation sequence and the second pronunciation sequence; and generating a pronunciation sequence conversion model based on a plurality of pronunciation sequence differences, wherein the pronunciation sequence conversion model is configured to synthesize speech by converting a pronunciation sequence generated in response to a received speech input to a target pronunciation sequence that more closely matches a pronunciation sequence extracted from the received speech input. | 1. A text-to-speech learning system, the system comprising: at least one processor; and at least one storage device, operatively connected to the at least one processor and storing: at least one training corpus comprising a plurality of training pairs that represent a varied vocabulary from one or more speakers, each training pair comprising a speech input and a text input corresponding to the speech input; and instructions that, when executed by the at least processor, cause the at least one processor to perform a method for generating a pronunciation sequence conversion model, the method comprising: for each training pair: selecting a training pair from the at least one training corpus; generating a first pronunciation sequence from the speech input of the training pair; and generating a second pronunciation sequence from the text input of the training pair; determining a pronunciation sequence difference between the first pronunciation sequence and the second pronunciation sequence; and generating a pronunciation sequence conversion model based on a plurality of pronunciation sequence differences, wherein the pronunciation sequence conversion model is configured to synthesize speech by converting a pronunciation sequence generated in response to a received speech input to a target pronunciation sequence that more closely matches a pronunciation sequence extracted from the received speech input. 4. The text-to-speech learning system of claim 1 , wherein determining a pronunciation sequence difference between the first pronunciation sequence and the second pronunciation sequence comprises aligning the first pronunciation sequence with the second pronunciation sequence. | 0.772204 |
10,162,904 | 1 | 2 | 1. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of a group consisting of a question and an answer; receive a first user selection indicating a portion of said social network interaction as a question; receive a second user selection indicating a portion of said social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; populate the knowledge element with information about: the portion of the social networking interaction indicated as a question; and the portion of the social networking interaction indicated as an answer; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany said corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of a group consisting of a question and an answer; provide access to information associated with the knowledge element via the knowledge element indicators; and alter said knowledge element in response to a user evaluating or editing said knowledge element. | 1. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of a group consisting of a question and an answer; receive a first user selection indicating a portion of said social network interaction as a question; receive a second user selection indicating a portion of said social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; populate the knowledge element with information about: the portion of the social networking interaction indicated as a question; and the portion of the social networking interaction indicated as an answer; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany said corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of a group consisting of a question and an answer; provide access to information associated with the knowledge element via the knowledge element indicators; and alter said knowledge element in response to a user evaluating or editing said knowledge element. 2. The computer program product of claim 1 , further comprising program instructions that, when executed, cause said processor to categorize said knowledge element. | 0.775342 |
9,594,731 | 5 | 6 | 5. The computer-implemented method of claim 4 , wherein the one or more editing features include: a dialog-based editor configured to one or more of: edit text; and change attributes of the first XML element; a rich-text editor configured to one or more of: edit a text-only XML element via a text-editing interface; and receive a modification to one or more in-line elements within the text-only XML element; a drag and drop editor configured to receive a graphical input including: selection of an element; and dragging the selected element to one of: move the selected element to a new location; and replace an existing element at a specified location; and a template editor configured to one or more of: upon a new XML element being inserted, determining if the new XML element is associated with at least one XML segment; and when the new XML element is associated with at least one XML segment, inserting the at least one XML segment a number of times associated with the new XML element and the at least one XML segment. | 5. The computer-implemented method of claim 4 , wherein the one or more editing features include: a dialog-based editor configured to one or more of: edit text; and change attributes of the first XML element; a rich-text editor configured to one or more of: edit a text-only XML element via a text-editing interface; and receive a modification to one or more in-line elements within the text-only XML element; a drag and drop editor configured to receive a graphical input including: selection of an element; and dragging the selected element to one of: move the selected element to a new location; and replace an existing element at a specified location; and a template editor configured to one or more of: upon a new XML element being inserted, determining if the new XML element is associated with at least one XML segment; and when the new XML element is associated with at least one XML segment, inserting the at least one XML segment a number of times associated with the new XML element and the at least one XML segment. 6. The computer-implemented method of claim 5 , further comprising tracking modifications made to one or more XML elements, including: adding a change attribute to the modified XML element indicating whether the modified XML element has been one of added or deleted; causing the change attribute to be visually displayable in the browser and indicate whether the modified XML element has been one of added or deleted. | 0.5 |
9,740,922 | 52 | 54 | 52. The system of claim 1 , wherein each sensor corresponds to a sensing volume in the SOE, wherein each sensor estimates a pose of an object within the sensing volume. | 52. The system of claim 1 , wherein each sensor corresponds to a sensing volume in the SOE, wherein each sensor estimates a pose of an object within the sensing volume. 54. The system of claim 52 , wherein the sensing volume of each sensor at least partially overlaps with the sensing volume of at least one other sensor of the plurality of sensors, wherein a combined sensing volume of the plurality of sensors is contiguous. | 0.5 |
5,493,658 | 3 | 5 | 3. The tutorial method of claim 2 wherein said comparison step compares user input actions with a lesson control table containing a list of user input action statements. | 3. The tutorial method of claim 2 wherein said comparison step compares user input actions with a lesson control table containing a list of user input action statements. 5. The tutorial method of claim 3 further including the step of dynamically determining a graphical input window handle within said product display window and formatting a selected entry of said lesson control table with the determined position prior to said comparison step. | 0.682448 |
9,643,722 | 1 | 13 | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. | 1. A system comprising; a. a security system; and b. a aerial drone device configured for acquiring content and communicating with the security system including receiving trigger location information from the security system, wherein the aerial drone device is configured to acquire an image of an object based on a database of template targets, including scanning an area and comparing the object in the area with the database of template targets to determine whether to acquire the image of the object, wherein the aerial drone device is configured to determine when to patrol an area by analyzing social networking information and detecting one or more keywords within the social networking information, wherein the one or more keywords are related to a location of the aerial drone device, wherein the aerial drone device includes one or more lights to indicate different situations based on the content acquired by the aerial drone device, wherein the aerial drone device comprises a nested aerial drone device including a first separable aerial drone device and a second separable aerial drone device, wherein each separable aerial drone device is configured to acquire separate information by traveling in different directions. 13. The system of claim 1 wherein the aerial drone device is configured to determine when to patrol an area by analyzing police information and detecting the one or more keywords within the police information, wherein the one or more keywords are related to the location of the aerial drone device. | 0.616967 |
9,183,316 | 11 | 13 | 11. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more devices, cause the one or more devices to: receive, without further interaction by a user of a client, a request for action links that are to be displayed within a document previously requested and received by the client, determine the action links based on information that identifies one or more action services previously defined by the user and that is previously stored in or by the one or more devices, the one or more action services including at least one of one or more email services or one or more social networking services, and the action links providing an opportunity for the user associated with the client to share the document by using one of the one or more action services; generate content that describes the action links; and provide the content to the client for presentation of the document with the content that describes the action links. | 11. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more devices, cause the one or more devices to: receive, without further interaction by a user of a client, a request for action links that are to be displayed within a document previously requested and received by the client, determine the action links based on information that identifies one or more action services previously defined by the user and that is previously stored in or by the one or more devices, the one or more action services including at least one of one or more email services or one or more social networking services, and the action links providing an opportunity for the user associated with the client to share the document by using one of the one or more action services; generate content that describes the action links; and provide the content to the client for presentation of the document with the content that describes the action links. 13. The non-transitory medium of claim 11 , where the content includes hyper-text markup language (HTML) content that includes, for each of the determined action links, a link to a service corresponding to one of the action links. | 0.5 |
7,912,843 | 11 | 12 | 11. The system of claim 9 , wherein the advertisement selector is further configured for: calculating a third content match feature using said set of terms, the third content match feature comprising a translation evaluation feature indicating a degree to which n-grams of the electronic advertisement and the target content match; and processing said third content match feature with the machine learning model, the machine learning model comprising an individual weight for the third content match feature. | 11. The system of claim 9 , wherein the advertisement selector is further configured for: calculating a third content match feature using said set of terms, the third content match feature comprising a translation evaluation feature indicating a degree to which n-grams of the electronic advertisement and the target content match; and processing said third content match feature with the machine learning model, the machine learning model comprising an individual weight for the third content match feature. 12. The system of claim 11 , wherein the third content match feature comprises a BLEU metric or a NIST metric; and an n-gram comprises a bigram, trigram, or 4-gram. | 0.5 |
9,002,877 | 13 | 20 | 13. A system for determining a suitable font for displaying text, comprising: a non-transitory computer-readable storage medium; matrix generating means for generating a two-dimensional link matrix to link a plurality of available fonts for displaying text each identified in the matrix with one or more font attributes identified in the matrix via one or more attribute values identified in the matrix; receiving means for receiving a font match query to determine a suitable font for text to be displayed from the plurality of available fonts including one or more specified attribute-attribute value pairs; and font match determining means for determining a font satisfying the received font match query from the available fonts based on a match between the one or more specified attribute-attribute value pairs and the one or more attribute values of the two-dimensional link matrix to determine which font can correctly display the text wherein the font match determining means is further configured to: retrieve the two-dimensional link matrix for one or more of the attribute-attribute value pairs in the font match query to generate a set of fonts returned results. | 13. A system for determining a suitable font for displaying text, comprising: a non-transitory computer-readable storage medium; matrix generating means for generating a two-dimensional link matrix to link a plurality of available fonts for displaying text each identified in the matrix with one or more font attributes identified in the matrix via one or more attribute values identified in the matrix; receiving means for receiving a font match query to determine a suitable font for text to be displayed from the plurality of available fonts including one or more specified attribute-attribute value pairs; and font match determining means for determining a font satisfying the received font match query from the available fonts based on a match between the one or more specified attribute-attribute value pairs and the one or more attribute values of the two-dimensional link matrix to determine which font can correctly display the text wherein the font match determining means is further configured to: retrieve the two-dimensional link matrix for one or more of the attribute-attribute value pairs in the font match query to generate a set of fonts returned results. 20. The system according to claim 13 , wherein the font match determining means is further configured to: determine a sequence of retrieving the two-dimensional link matrix for the attribute-attribute value pairs in the font match query based on a predetermined weight value of each attribute. | 0.713867 |
7,747,495 | 1 | 13 | 1. A method of doing business by processing a group of documents comprising the steps of: (1) performing optical character recognition from said discrete documents using said device to generate one or more sets of text-based information; (2) classifying at least some of said discrete documents using said sets of text-based information, wherein multiple classification engines are employed and said classifying is based on a consensus of said classification engines; (3) classifying at least some of the discrete documents using Image Based Classification; (4) verifying any of said remaining discrete documents that are not classified in said steps of classifying by employing a Location Diagram with said remaining discrete documents or a portion thereof; (5) collating said at least two of said discrete documents; (6) versioning and sequencing at least two of said discrete documents; (7) locating said fields containing data in said at least two of said discrete documents; (8) extracting data from said fields of said at least two discrete documents to generate extracted data; (9) scrubbing values from said extracted data to generate values therefrom; (10) forming Knowledge Objects; (11) storing said values in a data storage device; (12) forming Business Objects; (13) displaying at least some of said values to a user. | 1. A method of doing business by processing a group of documents comprising the steps of: (1) performing optical character recognition from said discrete documents using said device to generate one or more sets of text-based information; (2) classifying at least some of said discrete documents using said sets of text-based information, wherein multiple classification engines are employed and said classifying is based on a consensus of said classification engines; (3) classifying at least some of the discrete documents using Image Based Classification; (4) verifying any of said remaining discrete documents that are not classified in said steps of classifying by employing a Location Diagram with said remaining discrete documents or a portion thereof; (5) collating said at least two of said discrete documents; (6) versioning and sequencing at least two of said discrete documents; (7) locating said fields containing data in said at least two of said discrete documents; (8) extracting data from said fields of said at least two discrete documents to generate extracted data; (9) scrubbing values from said extracted data to generate values therefrom; (10) forming Knowledge Objects; (11) storing said values in a data storage device; (12) forming Business Objects; (13) displaying at least some of said values to a user. 13. The method of claim 1 , wherein said step of displaying is performed by, or with the assistance of, a computer. | 0.659763 |
8,745,094 | 18 | 32 | 18. A method for tokenization of sensitive strings, the method comprising: receiving a sensitive string of characters; selecting a substring of the sensitive string of characters; forming an intermediate tokenized string of characters, by a processor, by replacing the selected substring of the sensitive string of characters with a first token; selecting a substring of the intermediate tokenized string of characters, the selected substring of the intermediate tokenized string of characters including at least one character replaced by the first token; and forming a final tokenized string of characters, by the processor, by replacing the selected substring of the intermediate tokenized string of characters with a second token, the second token being different from the first token. | 18. A method for tokenization of sensitive strings, the method comprising: receiving a sensitive string of characters; selecting a substring of the sensitive string of characters; forming an intermediate tokenized string of characters, by a processor, by replacing the selected substring of the sensitive string of characters with a first token; selecting a substring of the intermediate tokenized string of characters, the selected substring of the intermediate tokenized string of characters including at least one character replaced by the first token; and forming a final tokenized string of characters, by the processor, by replacing the selected substring of the intermediate tokenized string of characters with a second token, the second token being different from the first token. 32. The method of claim 18 , further comprising modifying the selected substring of the sensitive string of characters prior to replacing the selected substring with a token. | 0.878492 |
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