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9,529,522 | 1 | 4 | 1. A method for enabling gesture-based search, comprising: providing, at a client device during a conversation with a plurality of conversation participants in which a user of the client device is currently participating in real-time, a search interface comprising a concept interface, a content interface adjacent to the concept interface, and a participant interface adjacent to the concept interface and content interface and identifying each of the plurality of conversation participants, the concept interface comprising a plurality of selectable concept tabs displayed in a line within the concept interface and the content interface configured to present content associated with a selected content tab, each selectable concept tab representative of a topic of the conversation identified based on a portion of speech of the conversation and including a visual indicator identifying a conversation participant that spoke the portion of conversation speech based on which the topic of the conversation is identified, wherein the client device comprises a touch-screen display; receiving, at the concept interface, a gesture input associated with adding an additional concept tab, wherein the gesture input comprises a touch input on the touch-screen display dragged in a direction towards the line of concept tabs; presenting, in response to receiving the gesture input, a concept input mechanism configured to allow a user of the client device to enter a concept for the additional concept tab; and in response to receiving a concept for the additional concept tab via the concept input mechanism, displaying the additional concept tab within the concept interface; wherein the content interface displays content associated with the received concept in response to the additional concept tab being selected. | 1. A method for enabling gesture-based search, comprising: providing, at a client device during a conversation with a plurality of conversation participants in which a user of the client device is currently participating in real-time, a search interface comprising a concept interface, a content interface adjacent to the concept interface, and a participant interface adjacent to the concept interface and content interface and identifying each of the plurality of conversation participants, the concept interface comprising a plurality of selectable concept tabs displayed in a line within the concept interface and the content interface configured to present content associated with a selected content tab, each selectable concept tab representative of a topic of the conversation identified based on a portion of speech of the conversation and including a visual indicator identifying a conversation participant that spoke the portion of conversation speech based on which the topic of the conversation is identified, wherein the client device comprises a touch-screen display; receiving, at the concept interface, a gesture input associated with adding an additional concept tab, wherein the gesture input comprises a touch input on the touch-screen display dragged in a direction towards the line of concept tabs; presenting, in response to receiving the gesture input, a concept input mechanism configured to allow a user of the client device to enter a concept for the additional concept tab; and in response to receiving a concept for the additional concept tab via the concept input mechanism, displaying the additional concept tab within the concept interface; wherein the content interface displays content associated with the received concept in response to the additional concept tab being selected. 4. The method of claim 1 , wherein the concept input mechanism is presented in response to the user releasing the touch input. | 0.760456 |
8,805,803 | 4 | 5 | 4. The method of claim 3 , wherein the step of reclassifying the document further comprises the steps of: organizing a plurality of terms in the document into a number of language groups, each of the language groups being defined by a characteristic of a native language of the document, wherein at least one of the terms is considered to be a putative index; searching indices associated with the ground truth documents for occurrences of the putative index; and reclassifying the document as belonging to a classification that includes at least one ground truth document that having at least one occurrence of the putative index. | 4. The method of claim 3 , wherein the step of reclassifying the document further comprises the steps of: organizing a plurality of terms in the document into a number of language groups, each of the language groups being defined by a characteristic of a native language of the document, wherein at least one of the terms is considered to be a putative index; searching indices associated with the ground truth documents for occurrences of the putative index; and reclassifying the document as belonging to a classification that includes at least one ground truth document that having at least one occurrence of the putative index. 5. The method of claim 4 , wherein at least one of language groups is defined by capitalization of the terms. | 0.599265 |
8,751,957 | 14 | 15 | 14. A system for updating a user profile for a television programming recommender, operative to generate recommendations regarding content of programs based on the user profile comprising: a memory for storing computer readable code and said user profile; and a processor operatively coupled to said memory, said processor being configured to; read from said memory said user profile indicating preferences of a user; using an audio/visual device to capture user initiated feedback generated by the user provided in the form of gestural feedback in the form of video information, and/or sounds in the form of audio information, while the user is watching specific television programs; wherein the processor is configured to analyze at least one of audio and video information of said user while viewing or completing viewing of a plurality of television programs at different times to identify predefined behavioral feedback indicating present television program preferences of said user; and update said user profile based on said predefined behavioral feedback; translate the predefined behavioral feedback into a representation indicating a strength of a user's liking or disliking of a specific program being watched; and update said user profile by processing said representation, the audio and/or video information is in the form of auditory or gestural feedback from the user and said feedback is initiated by the said system or initiated by the user and wherein if the occurrence of a predefined event relating to the television program being watched is detected then the feedback which is received for that program is either of a user response to a query which is generated to the user in which case that response is explicit feedback which is used to update the user profile or the feedback received is user initiated feedback which is implicit feedback which is used to update the user profile and the auditory and gestural feedback identified during the watching of the program is analyzed to validate the user's like or dislike of the said television program said predefined behavioral feedback includes, auditory and/or gestural commands mapped to a scale corresponding to respective strengths of said preferences of said user in rating said plurality of television programs viewed. | 14. A system for updating a user profile for a television programming recommender, operative to generate recommendations regarding content of programs based on the user profile comprising: a memory for storing computer readable code and said user profile; and a processor operatively coupled to said memory, said processor being configured to; read from said memory said user profile indicating preferences of a user; using an audio/visual device to capture user initiated feedback generated by the user provided in the form of gestural feedback in the form of video information, and/or sounds in the form of audio information, while the user is watching specific television programs; wherein the processor is configured to analyze at least one of audio and video information of said user while viewing or completing viewing of a plurality of television programs at different times to identify predefined behavioral feedback indicating present television program preferences of said user; and update said user profile based on said predefined behavioral feedback; translate the predefined behavioral feedback into a representation indicating a strength of a user's liking or disliking of a specific program being watched; and update said user profile by processing said representation, the audio and/or video information is in the form of auditory or gestural feedback from the user and said feedback is initiated by the said system or initiated by the user and wherein if the occurrence of a predefined event relating to the television program being watched is detected then the feedback which is received for that program is either of a user response to a query which is generated to the user in which case that response is explicit feedback which is used to update the user profile or the feedback received is user initiated feedback which is implicit feedback which is used to update the user profile and the auditory and gestural feedback identified during the watching of the program is analyzed to validate the user's like or dislike of the said television program said predefined behavioral feedback includes, auditory and/or gestural commands mapped to a scale corresponding to respective strengths of said preferences of said user in rating said plurality of television programs viewed. 15. A system according to claim 14 wherein the system includes an explicit user profile in the memory which is updated with regard to explicit feedback which is received and an implicit user profile in the memory which is updated with regard to implicit feedback which is received. | 0.5 |
8,224,642 | 10 | 13 | 10. The method of claim 1 wherein the parameter set for the impostor profile for the most likely language includes a respective mean and standard deviation characterizing the score distribution for each of the impostor languages in the impostor set for the most likely language. | 10. The method of claim 1 wherein the parameter set for the impostor profile for the most likely language includes a respective mean and standard deviation characterizing the score distribution for each of the impostor languages in the impostor set for the most likely language. 13. The method of claim 10 wherein comparing the document scores for the one or more impostor languages in the impostor set associated with the most likely language to the impostor profile for the most likely language includes: applying a likelihood ratio test to the document score and each impostor language in the impostor set for the most likely language, wherein the likelihood ratio test is applied separately for each impostor language. | 0.5 |
7,620,494 | 1 | 12 | 1. A method for displaying driving directions, the method comprising: accessing data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; selecting a portion of the accessed data that describes a particular maneuver, the particular maneuver including an action and a road; determining a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determining an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and presenting both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver. | 1. A method for displaying driving directions, the method comprising: accessing data that describes at least one maneuver to be executed to traverse a route from an origin to a destination; selecting a portion of the accessed data that describes a particular maneuver, the particular maneuver including an action and a road; determining a road symbol to associate with the particular maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road involved in the particular maneuver; determining an action symbol to associate with the particular maneuver, the action symbol having substantially the same appearance as a road sign used to identify the action to be performed to execute the particular maneuver; and presenting both the road symbol and the action symbol to describe the particular maneuver, such that the road symbol and the action symbol describe the particular maneuver. 12. The method of claim 1 wherein the road symbol comprises an interstate road symbol having substantially the same appearance as an interstate sign used to mark the interstate represented by the interstate road symbol. | 0.5 |
9,042,554 | 25 | 29 | 25. A tangible computer readable storage medium comprising computer readable instructions which, when executed, cause a processor to at least: assign source data to one of a plurality of groups, the source data comprising text data; identify a symbol to be added to the source data based on an assigned group of the source data; and generate encoded data by changing a first text character in the source data to be a second text character that is representative of the symbol and represents a same alphanumeric character or non-alphanumeric symbol as the first text character in the source data. | 25. A tangible computer readable storage medium comprising computer readable instructions which, when executed, cause a processor to at least: assign source data to one of a plurality of groups, the source data comprising text data; identify a symbol to be added to the source data based on an assigned group of the source data; and generate encoded data by changing a first text character in the source data to be a second text character that is representative of the symbol and represents a same alphanumeric character or non-alphanumeric symbol as the first text character in the source data. 29. A tangible computer readable storage medium as defined in claim 25 , wherein the first text character in the source data is a first white space character represented by a first character code and the second text character representative of the symbol is a second white space character represented by a second character code. | 0.5 |
7,617,492 | 17 | 20 | 17. A method for extensible parsing a command line of an application comprising: receiving an option list of allowable options of the application, the option list comprising a first allowable option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving the command line of the application, the command line of the application comprising a first command line option; and parsing the command line to determine if the first command line option matches the first allowable option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. | 17. A method for extensible parsing a command line of an application comprising: receiving an option list of allowable options of the application, the option list comprising a first allowable option, wherein the list of allowable options comprises, for each allowable option, a command line option string, a minimum number of characters that uniquely identify the command line option, a command line option identifier and a parameter having a value indicative of a type of allowable arguments for the command line option string; receiving the command line of the application, the command line of the application comprising a first command line option; and parsing the command line to determine if the first command line option matches the first allowable option of the option list, wherein a success result is returned when it is determined that the first command line option in the command line exactly matches a portion of an option name in the list, a number of characters in the first command line option in the command line being not less than a minimum number of characters of the portion of the option name in the list of allowable options. 20. The method of claim 17 , wherein parsing the command line comprises: determining if the first command line option received from the command line is associated with an argument; determining if the first allowable option of the option list indicates that the argument for the first command line option is required. | 0.5 |
8,708,960 | 1 | 12 | 1. An infusion pump assembly comprising: a reservoir assembly configured to contain an infusible fluid; a motor assembly configured to act upon the reservoir assembly and dispense at least a portion of the infusible fluid contained within the reservoir assembly; processing logic configured to control the motor assembly; wherein the processing logic includes: a primary microprocessor configured to execute one or more primary applications written in a first computer language; and a safety microprocessor configured to execute one or more safety applications written in a second computer language that is different than the first computer language; and a computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: receiving, on the primary microprocessor executing one or more applications written in a first computer language, an initial command processable by the one or more applications written in the first computer language; converting the initial command into a modified command processable by one or more applications written in a second computer language; and providing the modified command to the safety microprocessor executing the one or more applications written in the second computer language. | 1. An infusion pump assembly comprising: a reservoir assembly configured to contain an infusible fluid; a motor assembly configured to act upon the reservoir assembly and dispense at least a portion of the infusible fluid contained within the reservoir assembly; processing logic configured to control the motor assembly; wherein the processing logic includes: a primary microprocessor configured to execute one or more primary applications written in a first computer language; and a safety microprocessor configured to execute one or more safety applications written in a second computer language that is different than the first computer language; and a computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: receiving, on the primary microprocessor executing one or more applications written in a first computer language, an initial command processable by the one or more applications written in the first computer language; converting the initial command into a modified command processable by one or more applications written in a second computer language; and providing the modified command to the safety microprocessor executing the one or more applications written in the second computer language. 12. The infusion pump assembly of claim 1 wherein the primary power supply and the backup power supply are configured to provide electrical energy to an audio system included within the infusion pump assembly. | 0.763575 |
8,166,017 | 17 | 18 | 17. A system comprising: a bookmark database; and one or more processors configured to: identify a user; and synchronize a first set of bookmarks stored for the identified user in the bookmark database, with a second set of bookmarks stored in a client-side browser bookmark list, wherein one or more bookmarks in the first set of bookmarks or the second set of bookmarks are associated with ratings of resources, the resources being identified by the one or more bookmarks, and wherein synchronizing the first set of bookmarks and the second set of bookmarks comprises preserving the ratings associated with the one or more bookmarks. | 17. A system comprising: a bookmark database; and one or more processors configured to: identify a user; and synchronize a first set of bookmarks stored for the identified user in the bookmark database, with a second set of bookmarks stored in a client-side browser bookmark list, wherein one or more bookmarks in the first set of bookmarks or the second set of bookmarks are associated with ratings of resources, the resources being identified by the one or more bookmarks, and wherein synchronizing the first set of bookmarks and the second set of bookmarks comprises preserving the ratings associated with the one or more bookmarks. 18. The system of claim 17 , wherein identifying the user further comprises authenticating the user. | 0.870801 |
7,509,314 | 1 | 2 | 1. A document retrieval system for retrieving a document from a set of documents according to one or more terms received as search conditions submitted by a user, the terms that can be received including both numeric terms, which include numeric values, and non-numeric terms, which do not include numeric values, the document retrieval system comprising: a first processor for generating at least one item of index information for each document in the set of documents, the index information generated for the documents including both numeric term index information and non-numeric term index information, the non-numeric term index information including information about frequency of occurrence of non-numeric terms in the document, the numeric term index information including information about types and numeric values of numeric terms in the document; a memory unit for storing the index information generated by the first processor; a second processor for examining each numeric term received as a search condition, determining its type, and generating numeric search information indicating the type and numeric value of the numeric term; a third processor for using the non-numeric term index information generated by the first processor to calculate, for each document in the set of documents including a non-numeric term received as a search condition, a first numeric quantity having a single numeric value indicating a goodness of fit between the non-numeric term and the document; a fourth processor for using the numeric term index information generated by the first processor and the numeric search information generated by the second processor from a numeric term received as a search condition to calculate, for each document in the set of documents including a numeric term of the same type as the numeric term received as the search condition, by comparing numeric values of the numeric terms, a second numeric quantity having a single numeric value indicating a goodness of fit between the numeric term received as the search condition and the document, closer numeric values indicating better fits; a fifth processor for calculating, for a document in the set of documents, a third numeric quantity indicating a goodness of fit between the document and the one or more terms received as search conditions, the third numeric quantity being calculated from the first and second numeric quantities; and an output unit for sending information for displaying a list of documents from the set of documents to the user according to the third numeric quantity. | 1. A document retrieval system for retrieving a document from a set of documents according to one or more terms received as search conditions submitted by a user, the terms that can be received including both numeric terms, which include numeric values, and non-numeric terms, which do not include numeric values, the document retrieval system comprising: a first processor for generating at least one item of index information for each document in the set of documents, the index information generated for the documents including both numeric term index information and non-numeric term index information, the non-numeric term index information including information about frequency of occurrence of non-numeric terms in the document, the numeric term index information including information about types and numeric values of numeric terms in the document; a memory unit for storing the index information generated by the first processor; a second processor for examining each numeric term received as a search condition, determining its type, and generating numeric search information indicating the type and numeric value of the numeric term; a third processor for using the non-numeric term index information generated by the first processor to calculate, for each document in the set of documents including a non-numeric term received as a search condition, a first numeric quantity having a single numeric value indicating a goodness of fit between the non-numeric term and the document; a fourth processor for using the numeric term index information generated by the first processor and the numeric search information generated by the second processor from a numeric term received as a search condition to calculate, for each document in the set of documents including a numeric term of the same type as the numeric term received as the search condition, by comparing numeric values of the numeric terms, a second numeric quantity having a single numeric value indicating a goodness of fit between the numeric term received as the search condition and the document, closer numeric values indicating better fits; a fifth processor for calculating, for a document in the set of documents, a third numeric quantity indicating a goodness of fit between the document and the one or more terms received as search conditions, the third numeric quantity being calculated from the first and second numeric quantities; and an output unit for sending information for displaying a list of documents from the set of documents to the user according to the third numeric quantity. 2. The document retrieval system of claim 1 , wherein the type of a numeric term indicates the type of quantity represented by the numeric value of the numeric term. | 0.750755 |
9,348,851 | 16 | 17 | 16. The non-transitory computer-readable storage medium of claim 13 , wherein the potential data quality problem is unparsed properties, and said one or more data quality criterion identify objects that have one or more property values including unparsed data. | 16. The non-transitory computer-readable storage medium of claim 13 , wherein the potential data quality problem is unparsed properties, and said one or more data quality criterion identify objects that have one or more property values including unparsed data. 17. The non-transitory computer-readable storage medium of claim 16 , wherein the unparsed data takes on a meaning unintended by a data source providing the unparsed data. | 0.5 |
8,316,001 | 38 | 39 | 38. Apparatus for performing an analysis on data from a web-based search engine, the apparatus comprising: a digital computing device, such device in communication over a network with the web-based search engine, and running a browser application operating in response to a web page having content received from the search engine responsive to a query, the web page including analysis computer code downloaded to the digital computing device from a server, executable by the digital computing device and configured to perform the analysis; such browser application running the analysis computer code, in the web page, that to perform the analysis on the content to produce analysis results; such browser application causing display of the web page and the analysis results in the digital computing device. | 38. Apparatus for performing an analysis on data from a web-based search engine, the apparatus comprising: a digital computing device, such device in communication over a network with the web-based search engine, and running a browser application operating in response to a web page having content received from the search engine responsive to a query, the web page including analysis computer code downloaded to the digital computing device from a server, executable by the digital computing device and configured to perform the analysis; such browser application running the analysis computer code, in the web page, that to perform the analysis on the content to produce analysis results; such browser application causing display of the web page and the analysis results in the digital computing device. 39. Apparatus according to claim 38 , wherein the apparatus is for performing a type of analysis specified when the query is specified, and the browser application is running code that performs the specified type of analysis. | 0.692623 |
9,430,772 | 11 | 14 | 11. A method comprising: receiving, by a processor over a network, an Short Message Service (SMS) message from a user of the client device, the SMS message being directed to another user of another client device, the user and the other user having a defined social connection; analyzing, by the processor, the SMS message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing, by the processor, a copy of the detected question comprised in the received text message; monitoring, by the processor, for a response text message to the detected question from the other user for a timeout time period; intercepting, by the processor, a response SMS from the other user of the other client device if the response text message is received within the timeout time period; refining, by the processor, the detected question from the user by combining at least a portion of the response SMS message to the detected question with at least a portion of the detected question from the user, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing, by the processor, the refined detected question to select a contextual advertisement; modifying, by the processor, the response SMS message to include link information to the contextual advertisement; and providing, by the processor, the modified response SMS message to the mobile device. | 11. A method comprising: receiving, by a processor over a network, an Short Message Service (SMS) message from a user of the client device, the SMS message being directed to another user of another client device, the user and the other user having a defined social connection; analyzing, by the processor, the SMS message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing, by the processor, a copy of the detected question comprised in the received text message; monitoring, by the processor, for a response text message to the detected question from the other user for a timeout time period; intercepting, by the processor, a response SMS from the other user of the other client device if the response text message is received within the timeout time period; refining, by the processor, the detected question from the user by combining at least a portion of the response SMS message to the detected question with at least a portion of the detected question from the user, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing, by the processor, the refined detected question to select a contextual advertisement; modifying, by the processor, the response SMS message to include link information to the contextual advertisement; and providing, by the processor, the modified response SMS message to the mobile device. 14. The method of claim 11 , the timeout time period is based on maintenance of relevancy between the detected question and a prospective response to the detected question. | 0.621145 |
9,817,552 | 1 | 10 | 1. A method including: identifying a first plurality of items based on a search, the identifying including utilizing at least one criterion to perform the search; generating a first transmission including the first plurality of items and a first plurality of selection functions, the first plurality of items respectively being associated with the first plurality of selection functions, the generating utilizing at least one processor; communicating the first transmission over a communications network; receiving a first plurality of selections over the communications network, the first plurality of selections including at least two selections, the at least two selections collectively identifying a first plurality of deleted items as deleted from the first plurality of items, the first plurality of items further including a second plurality of items that are not deleted from the first plurality of items, the receiving utilizing at least one processor; identifying an associated message to be communicated together with the second plurality of items; and communicating the associated message with the second plurality of items as a second transmission over the communications network. | 1. A method including: identifying a first plurality of items based on a search, the identifying including utilizing at least one criterion to perform the search; generating a first transmission including the first plurality of items and a first plurality of selection functions, the first plurality of items respectively being associated with the first plurality of selection functions, the generating utilizing at least one processor; communicating the first transmission over a communications network; receiving a first plurality of selections over the communications network, the first plurality of selections including at least two selections, the at least two selections collectively identifying a first plurality of deleted items as deleted from the first plurality of items, the first plurality of items further including a second plurality of items that are not deleted from the first plurality of items, the receiving utilizing at least one processor; identifying an associated message to be communicated together with the second plurality of items; and communicating the associated message with the second plurality of items as a second transmission over the communications network. 10. The method of claim 1 , wherein the message includes an address of the second user. | 0.816456 |
4,881,197 | 22 | 24 | 22. Apparatus according to claim 20, wherein said first format corresponds to the format used to define at least one of the left and right margins and indentation points for the main body of textual material and wherein said means for defining at least one characteristic includes means for selecting at lest left and right margins to be associated with said first named format. | 22. Apparatus according to claim 20, wherein said first format corresponds to the format used to define at least one of the left and right margins and indentation points for the main body of textual material and wherein said means for defining at least one characteristic includes means for selecting at lest left and right margins to be associated with said first named format. 24. Apparatus according to claim 22 wherein said document includes at least one column of alphanumeric data and wherein said second abstract format name is associated with a format used to define the start and the end of each of said at least one column of alphanumeric data. | 0.5 |
8,190,632 | 5 | 6 | 5. The computer-readable recording medium according to claim 3 , wherein the hierarchy retrieval automaton makes state transition to the subordinate hierarchical node, if an end symbol of the start tag is given when state transition has been made to an end node of the series of nodes. | 5. The computer-readable recording medium according to claim 3 , wherein the hierarchy retrieval automaton makes state transition to the subordinate hierarchical node, if an end symbol of the start tag is given when state transition has been made to an end node of the series of nodes. 6. The computer-readable recording medium according to claim 5 , wherein the hierarchy retrieval automaton has a series of nodes representing the hierarchical name of the subordinate hierarchical node between the node representing the start symbol and the superior hierarchical node, and if a character string is given when state transition has been made to the node representing the start symbol, the hierarchy retrieval automaton makes state transition to the series of nodes until a hit-missing character appears. | 0.5 |
9,946,514 | 13 | 14 | 13. The non-transitory computer readable storage medium of claim 12 , wherein each of the natural language utterance, the extracted one or more entities, the determined intent, the design command, the component of the application being designed, and the workspace are each associated with respective unique identifiers. | 13. The non-transitory computer readable storage medium of claim 12 , wherein each of the natural language utterance, the extracted one or more entities, the determined intent, the design command, the component of the application being designed, and the workspace are each associated with respective unique identifiers. 14. The non-transitory computer readable storage medium of claim 13 , further comprising: distributing the functional instance of the application being designed to at least one test system; receiving session data indicative one or more interactions between a user of a test system and the functional instance of the application; and storing the session data in a workspace data store. | 0.571429 |
9,864,995 | 11 | 12 | 11. The system of claim 8 , wherein the computing system is further configured to modify a contact event interface at the agent communication device based on the user data and the contact need classification. | 11. The system of claim 8 , wherein the computing system is further configured to modify a contact event interface at the agent communication device based on the user data and the contact need classification. 12. The system of claim 11 , wherein to modify the contact event interface the computing system is to present at least a portion of the user data and the contact need classification. | 0.5 |
8,694,529 | 12 | 17 | 12. A computer-implemented method for facilitating a search, comprising: under control of one or more computer systems configured with executable instructions, categorizing at least some of a first plurality of items included in a search result set of items into at least one of a plurality of categories arranged in a category hierarchy having a root category; selecting a second plurality of items from the first plurality of items based at least in part on one or more search terms and independent of categories in the category hierarchy other than the root category; selecting a plurality of refinements from a set of refinements based at least in part on the one or more search terms and a map depicting a plurality of associations between search terms and categories of the category hierarchy, and links between the categories and the set of refinements; receiving a selection of at least one of the plurality of refinements linked to the at least one of a plurality of categories; maintaining a log of a number of times the at least one refinement of the plurality of refinements is selected during searches employing the one or more search terms in one or more time periods; determining a possibly relevant set of categories of the category hierarchy below a distinguished category based at least in part on the log; increasing an associative confidence between at least one of the one or more search terms and a subset of the set of refinements linked to the possibly relevant set of categories based at least in part on the log; determining the subset of the set of refinements linked to the possibly relevant set of categories when the associative confidence at least meets a first sufficiency threshold; providing said subset of the set of refinements for presentation; and constraining subsequent search result sets to a particular distinguished category, based at least on the one or more search terms, when the associative confidence meets at least a sufficiency second threshold. | 12. A computer-implemented method for facilitating a search, comprising: under control of one or more computer systems configured with executable instructions, categorizing at least some of a first plurality of items included in a search result set of items into at least one of a plurality of categories arranged in a category hierarchy having a root category; selecting a second plurality of items from the first plurality of items based at least in part on one or more search terms and independent of categories in the category hierarchy other than the root category; selecting a plurality of refinements from a set of refinements based at least in part on the one or more search terms and a map depicting a plurality of associations between search terms and categories of the category hierarchy, and links between the categories and the set of refinements; receiving a selection of at least one of the plurality of refinements linked to the at least one of a plurality of categories; maintaining a log of a number of times the at least one refinement of the plurality of refinements is selected during searches employing the one or more search terms in one or more time periods; determining a possibly relevant set of categories of the category hierarchy below a distinguished category based at least in part on the log; increasing an associative confidence between at least one of the one or more search terms and a subset of the set of refinements linked to the possibly relevant set of categories based at least in part on the log; determining the subset of the set of refinements linked to the possibly relevant set of categories when the associative confidence at least meets a first sufficiency threshold; providing said subset of the set of refinements for presentation; and constraining subsequent search result sets to a particular distinguished category, based at least on the one or more search terms, when the associative confidence meets at least a sufficiency second threshold. 17. A computer-implemented method according to claim 12 , wherein ordering the plurality of refinements comprises assigning a weight to at least one of the plurality of refinements of the plurality of refinements based at least in part on a distance in the category hierarchy from a root of at least one linked category. | 0.522388 |
8,332,327 | 17 | 18 | 17. The computer-readable storage medium of claim 16 , the apparatus is caused, at least in part, to further perform the following steps: determining whether the legal text element includes a user consent requirement; and in response to determining that the legal text element includes the user consent requirement, prompting a user of the apparatus for consent. | 17. The computer-readable storage medium of claim 16 , the apparatus is caused, at least in part, to further perform the following steps: determining whether the legal text element includes a user consent requirement; and in response to determining that the legal text element includes the user consent requirement, prompting a user of the apparatus for consent. 18. The computer-readable storage medium of claim 17 , the apparatus is caused, at least in part, to further perform the following steps: determining whether the user consents to the legal text; and in response to determining that the user consents to the legal text, transmitting a purchase message to a content provider. | 0.5 |
9,064,339 | 8 | 9 | 8. The method of claim 1 , further comprising: updating the geographical representation by: performing a second search of the contact data to identify a second contact based on the search parameters and based on a second geographical location associated with the source of the request; updating the geographical representation to display on the map a geographical location of the second contact; and generating a notification indicating that the geographical representation has been updated, the notification capable of being displayed at the user interface of the computer system, wherein the second contact was added to the shared contact data of the database service provider by another user at a time after the identification of the first contact. | 8. The method of claim 1 , further comprising: updating the geographical representation by: performing a second search of the contact data to identify a second contact based on the search parameters and based on a second geographical location associated with the source of the request; updating the geographical representation to display on the map a geographical location of the second contact; and generating a notification indicating that the geographical representation has been updated, the notification capable of being displayed at the user interface of the computer system, wherein the second contact was added to the shared contact data of the database service provider by another user at a time after the identification of the first contact. 9. The method of claim 8 , wherein the first and second geographical locations are different. | 0.5 |
8,595,220 | 1 | 7 | 1. A computer-implemented method for sharing summaries indicative of a document, comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity. | 1. A computer-implemented method for sharing summaries indicative of a document, comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity. 7. The computer-implemented method of claim 1 , the receiving feedback from the first distinctly identifiable entity comprising: receiving a link to be inserted into the first summary. | 0.75 |
7,779,004 | 7 | 9 | 7. A system for characterizing a target system, comprising: a characterization application stored in memory; and a processor communicating with the memory, the processor sending a query, the query comprising an ontology of interest that describes and represents a domain of interest, wherein the ontology of interest includes a plurality of nodes, each node of the plurality of nodes related to another node of the plurality of nodes, a predicate, and a scoring algorithm, the predicate describing a membership qualification for a node in the ontology of interest; the processor receiving a response comprising a score generated with the scoring algorithm, the score representing an evaluation of the predicate to metadata associated with the target system and how well the metadata matches the ontology of interest; the processor evaluating the score to characterize the target system, wherein the metadata of the target system is inaccessible to the processor; and wherein the system accepts that the metadata is inaccessible to a sender of the query. | 7. A system for characterizing a target system, comprising: a characterization application stored in memory; and a processor communicating with the memory, the processor sending a query, the query comprising an ontology of interest that describes and represents a domain of interest, wherein the ontology of interest includes a plurality of nodes, each node of the plurality of nodes related to another node of the plurality of nodes, a predicate, and a scoring algorithm, the predicate describing a membership qualification for a node in the ontology of interest; the processor receiving a response comprising a score generated with the scoring algorithm, the score representing an evaluation of the predicate to metadata associated with the target system and how well the metadata matches the ontology of interest; the processor evaluating the score to characterize the target system, wherein the metadata of the target system is inaccessible to the processor; and wherein the system accepts that the metadata is inaccessible to a sender of the query. 9. A system according to claim 7 , wherein the processor sends information that describes what metadata is collected on behalf of a sender of the query. | 0.787709 |
9,047,261 | 14 | 15 | 14. A method according to claim 13 , including overlapping content of the document displayed in the second display area with content of the document displayed in the first display area. | 14. A method according to claim 13 , including overlapping content of the document displayed in the second display area with content of the document displayed in the first display area. 15. A method according to claim 14 , including arranging the content of the at least part of the document displayed in at least one of: the second display area and the first display area to be coincident with each other. | 0.5 |
8,948,789 | 37 | 39 | 37. A computer-readable storage medium containing program instructions, that, when executed by a processor, cause the processor to execute a method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity between a location of the other device at a first time and a location of a mobile device at a second time, the first time and the second time being different, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. | 37. A computer-readable storage medium containing program instructions, that, when executed by a processor, cause the processor to execute a method comprising: accessing low-level context information for each of a plurality of other devices, wherein location information associated with each of the other devices indicates a proximity between a location of the other device at a first time and a location of a mobile device at a second time, the first time and the second time being different, and wherein the low-level context information for each of the other devices is based on data collected by a sensor of the respective other device; aggregating the low-level context information across the plurality of other devices; determining match scores between the aggregated low-level context information and each of the one or more histograms of context data; and transmitting, to the mobile device, a multi-device statistical summary comprising the aggregated low-level context information and the match scores; and the mobile device inferring a context based on the multi-device statistical summary and additional data not included in the multi-device statistical summary. 39. The computer-readable storage medium of claim 37 , wherein the method further comprises identifying a software application from a set of available software applications based on the inferred context. | 0.5 |
8,347,276 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein the unified document is originated by a business person using predetermined labels to mark sections of one or more of the following: sections of the unified document, introductory and guiding text, markup language, and business rule statements. | 2. The computer-implemented method of claim 1 , wherein the unified document is originated by a business person using predetermined labels to mark sections of one or more of the following: sections of the unified document, introductory and guiding text, markup language, and business rule statements. 3. The computer-implemented method of claim 2 , wherein a technical analyst adds first text related to first computer language assertion format and second text related to second computer language assertion format to the unified document, the first computer assertion format to enable evaluation of the business rule statements to true for all correct statements and the second computer assertion format to enable evaluation of the business rules statements to false for all correct statements. | 0.5 |
7,644,052 | 2 | 4 | 2. The method of claim 1 , wherein the calculating comprises calculating information gain for an attribute A in relation to documents S and categories C by which the documents S are grouped, and the calculating the information gain comprises handling separately a subset of the documents S, for which the attribute A is absent, to improve performance with respect to populating sub-concepts in the second ontology. | 2. The method of claim 1 , wherein the calculating comprises calculating information gain for an attribute A in relation to documents S and categories C by which the documents S are grouped, and the calculating the information gain comprises handling separately a subset of the documents S, for which the attribute A is absent, to improve performance with respect to populating sub-concepts in the second ontology. 4. The method of claim 2 , wherein the calculating the information gain comprises calculating a smoothed zero-value information gain (SZVIG) in accordance with an equation: SZVIG β‘ ( A ) = H β‘ ( S ) - 1 C Β· ο S A = 0 ο ο S ο β’ H β‘ ( S A = 0 ) - β v β’ β’ Ξ΅ β’ β’ V A , v β 0 β’ ο S A = v ο ο S ο β’ H β‘ ( S A = v ) ; wherein V A is a set of values v for the attribute A for the documents S, S A=v is a partition of the documents S based on V A , and H(x) is a determined entropy of a set x. | 0.5 |
7,865,394 | 22 | 59 | 22. A system for creating and distributing at least five hundred individualized multimedia messages over a computer network using an email sent simultaneously, comprising: (a) a computer operatively connected to said network and executing a programmed sequence of instructions; (b) a recipient information access routing within said programmed sequence of instructions for accessing data about a given intended recipient with unique recipient information for each of at least five hundred recipients; (c) a content repository containing multimedia elements that may be combined to form individualized messages with computer files comprising at least one of text and graphics files, and further comprising at least one of audio and video files; (d) a content management routine within said programmed sequence of instructions for retrieving selected multimedia content from the content repository, wherein the process of selecting multimedia content is responsive to information content regarding the given recipient accessed by the recipient information access routine; (e) a multimedia engine routine within said programmed sequence of instructions, for packaging the multimedia content as an individualized message for delivery to the given recipient; and (f) a delivery routine within said programmed sequence of instructions for delivering the individualized message to each of the given recipients including sending an email message simultaneously to each of at least five hundred recipients and wherein at least some of said individualized multimedia content for said at least five hundred recipients are different from at least some other of said individualized multimedia content. | 22. A system for creating and distributing at least five hundred individualized multimedia messages over a computer network using an email sent simultaneously, comprising: (a) a computer operatively connected to said network and executing a programmed sequence of instructions; (b) a recipient information access routing within said programmed sequence of instructions for accessing data about a given intended recipient with unique recipient information for each of at least five hundred recipients; (c) a content repository containing multimedia elements that may be combined to form individualized messages with computer files comprising at least one of text and graphics files, and further comprising at least one of audio and video files; (d) a content management routine within said programmed sequence of instructions for retrieving selected multimedia content from the content repository, wherein the process of selecting multimedia content is responsive to information content regarding the given recipient accessed by the recipient information access routine; (e) a multimedia engine routine within said programmed sequence of instructions, for packaging the multimedia content as an individualized message for delivery to the given recipient; and (f) a delivery routine within said programmed sequence of instructions for delivering the individualized message to each of the given recipients including sending an email message simultaneously to each of at least five hundred recipients and wherein at least some of said individualized multimedia content for said at least five hundred recipients are different from at least some other of said individualized multimedia content. 59. A system as recited in claim 22 , wherein there is unique individual information contained within the at least one of audio and video files, and the at least one of text and graphics files and wherein the means for delivering the multimedia media message delivers the multimedia message to the email after one of the recipients opens the email. | 0.573529 |
8,731,944 | 1 | 4 | 1. A method enabling cross linguistic communication through speech and text machine translation, comprising method operations of: receiving a first and a second language selection; receiving an expression in the first language; presenting the expression in the first language for verification; translating the verified expression into an expression in the second language; confirming the meaning of terms within the verified expression in the first language; back-translating the expression in the second language to a back-translated expression in the first language; and verifying the back-translated expression in the first language, wherein at least one method operation is executed through a processor. | 1. A method enabling cross linguistic communication through speech and text machine translation, comprising method operations of: receiving a first and a second language selection; receiving an expression in the first language; presenting the expression in the first language for verification; translating the verified expression into an expression in the second language; confirming the meaning of terms within the verified expression in the first language; back-translating the expression in the second language to a back-translated expression in the first language; and verifying the back-translated expression in the first language, wherein at least one method operation is executed through a processor. 4. The method of claim 1 , wherein the first and the second language selection are received as voice commands. | 0.858247 |
8,606,778 | 15 | 18 | 15. A non-transitory computer-readable medium for storing instructions, the instructions comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to identify a document based on two or more search terms, one or more instructions which, when executed by the at least one processor, cause the at least one processor to form a tree structure based on the document, the tree structure including a plurality of items; one or more instructions which, when executed by the at least one processor, cause the at least one processor to analyze a repetition of one or more tags in the tree structure; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine, based on analyzing the repetition of the one or more tags, that the plurality of items are associated with a list, in the tree structure, the list not being defined by a list tag, the list including a header, and each item, of the plurality of items associated with the list, including a plurality of words that describe the item associated with the list; one or more instructions which, when executed by the at least one processor, cause the at least one processor to annotate the tree structure to indicate that the list is present; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine a metric associated with the two or more search terms in a first manner when the two or more search terms appear in a single item of the plurality of items associated with the list; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine the metric associated with the two or more search terms in a second manner when: a first search term, of the two or more search terms, appears in a first item of the plurality of items associated with the list, and a second search term, of the two or more search terms, appears in a second item of the plurality of items associated with the list, the first manner being different than the second manner; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine the metric associated with the two or more search terms in a third manner when: the first search term appears in the header, and the second search term appears in an item of the plurality of items associated with the list, the third manner being different than the first manner and the second manner; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine a score for the document based on the metric associated with the two or more search terms; and one or more instructions which, when executed by the at least one processor, cause the at least one processor to rank, based on the score, the document with respect to at least one other document. | 15. A non-transitory computer-readable medium for storing instructions, the instructions comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to identify a document based on two or more search terms, one or more instructions which, when executed by the at least one processor, cause the at least one processor to form a tree structure based on the document, the tree structure including a plurality of items; one or more instructions which, when executed by the at least one processor, cause the at least one processor to analyze a repetition of one or more tags in the tree structure; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine, based on analyzing the repetition of the one or more tags, that the plurality of items are associated with a list, in the tree structure, the list not being defined by a list tag, the list including a header, and each item, of the plurality of items associated with the list, including a plurality of words that describe the item associated with the list; one or more instructions which, when executed by the at least one processor, cause the at least one processor to annotate the tree structure to indicate that the list is present; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine a metric associated with the two or more search terms in a first manner when the two or more search terms appear in a single item of the plurality of items associated with the list; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine the metric associated with the two or more search terms in a second manner when: a first search term, of the two or more search terms, appears in a first item of the plurality of items associated with the list, and a second search term, of the two or more search terms, appears in a second item of the plurality of items associated with the list, the first manner being different than the second manner; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine the metric associated with the two or more search terms in a third manner when: the first search term appears in the header, and the second search term appears in an item of the plurality of items associated with the list, the third manner being different than the first manner and the second manner; one or more instructions which, when executed by the at least one processor, cause the at least one processor to determine a score for the document based on the metric associated with the two or more search terms; and one or more instructions which, when executed by the at least one processor, cause the at least one processor to rank, based on the score, the document with respect to at least one other document. 18. The non-transitory computer-readable medium of claim 15 , where the one or more tags include at least one of: a divide tag that divides the document into one or more sections and specifies one or more alignments for the one or more sections; a font tag that specifies a font size for at least a portion of text of the document; a line break tag that specifies one or more line breaks in the document; or a bold tag that specifies bold font text for at least a portion of the text of the document. | 0.521073 |
9,529,901 | 1 | 3 | 1. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the computing device to at least: receive an electronic document from a drafter; apply a language tag value to a language tag of the electronic document via the one or more processors, where the language tag defines a language, and wherein the language tag value is applied based, at least in part, on words used in the electronic document and on an internet protocol address of the drafter; apply a locale tag value to a locale tag of the electronic document via the one or more processors, where the locale tag defines a dialect of the language; and store the electronic document, the language tag value, and the locale tag value in a memory, via the one or more processors, where the language tag and the locale tag are assigned positions in a hierarchy of linguistic tags such that the language tag inherits a linguistic relationship from the locale tag, where the linguistic relationship is between dialects and languages. | 1. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the computing device to at least: receive an electronic document from a drafter; apply a language tag value to a language tag of the electronic document via the one or more processors, where the language tag defines a language, and wherein the language tag value is applied based, at least in part, on words used in the electronic document and on an internet protocol address of the drafter; apply a locale tag value to a locale tag of the electronic document via the one or more processors, where the locale tag defines a dialect of the language; and store the electronic document, the language tag value, and the locale tag value in a memory, via the one or more processors, where the language tag and the locale tag are assigned positions in a hierarchy of linguistic tags such that the language tag inherits a linguistic relationship from the locale tag, where the linguistic relationship is between dialects and languages. 3. The non-transitory computer-readable medium of claim 1 , wherein the instructions further comprise instructions that, when executed by the one or more processors, cause the computing device to apply a global tag value to a global tag that is assigned a position in the hierarchy of linguistic tags. | 0.681818 |
7,660,793 | 42 | 46 | 42. The system of claim 41 wherein the reconfigurable logic device has firmware deployed thereon, the firmware configured to perform the defined searching operation. | 42. The system of claim 41 wherein the reconfigurable logic device has firmware deployed thereon, the firmware configured to perform the defined searching operation. 46. The system of claim 42 wherein the firmware comprises a firmware pipeline, the firmware pipeline being configured to perform a decryption operation prior to the defined searching operation. | 0.507653 |
9,875,494 | 1 | 7 | 1. A computer-implemented method comprising: receiving, by a computing device, verbal input, wherein the verbal input includes natural language; determining an input intent associated with the verbal input, wherein the input intent is associated with an action that can be performed by the computing device, wherein the intent is determined using a dialog context, and wherein the dialog context includes a history of a current dialog session; adding the input intent to a history of intents, wherein the history of intents includes one or more intents from one or more previous dialog sessions, wherein the one or more intents include a transient intent, and wherein a transient intent does not cause the computing device to perform an action; determining an unstated characteristic associated with the history of intents, wherein determining includes identifying a pattern associated with the one or more intents from the history of intents and associating the pattern with the transient intent; modifying the action associated with the input intent, wherein the action is modified using the unstated characteristic; and executing the modified action, wherein the modified action modifies an operation of the computing device, and wherein executing the modified action fulfills the associated input intent. | 1. A computer-implemented method comprising: receiving, by a computing device, verbal input, wherein the verbal input includes natural language; determining an input intent associated with the verbal input, wherein the input intent is associated with an action that can be performed by the computing device, wherein the intent is determined using a dialog context, and wherein the dialog context includes a history of a current dialog session; adding the input intent to a history of intents, wherein the history of intents includes one or more intents from one or more previous dialog sessions, wherein the one or more intents include a transient intent, and wherein a transient intent does not cause the computing device to perform an action; determining an unstated characteristic associated with the history of intents, wherein determining includes identifying a pattern associated with the one or more intents from the history of intents and associating the pattern with the transient intent; modifying the action associated with the input intent, wherein the action is modified using the unstated characteristic; and executing the modified action, wherein the modified action modifies an operation of the computing device, and wherein executing the modified action fulfills the associated input intent. 7. The computer-implemented method of claim 1 , wherein the unstated characteristic is associated with a preference. | 0.842818 |
7,962,490 | 1 | 4 | 1. A method, comprising: analyzing a plurality of rules in a textual rules structure; decomposing the plurality of rules into a plurality of contexts, based on the analysis; storing the plurality of contexts into a table; generating a plurality of concatenated values, each concatenated value comprising one value associated with a context of one of the plurality of contexts joined with one value associated with at least one other context of the one of the plurality of contexts; and storing the plurality of concatenated values in a plurality of filtering tables; wherein the plurality of filtering tables include a light context filtering table storing at least one concatenated value representing a combination of light contexts, a heavy context filtering table storing at last one concatenated value representing a combination of heavy contexts, a heavy and light context filtering table storing at last one concatenated value representing a combination of at least one heavy context and at least one light context, a looping filtering table storing at least one positive context that is utilized for positively filtering values, and not looping filtering table storing at least one negative context that is utilized for negatively filtering values; wherein each of the plurality of contexts is identified as a heavy context or a light context based on a predetermined number of distinct occurrences of data in a data stream; wherein the light context is predetermined to have a fewer number of distinct occurrences in the data than a number of distinct occurrences included in the heavy context; wherein if each context in the plurality of contexts filters a plurality of values, then the plurality of values is serialized into a series of concatenated values. | 1. A method, comprising: analyzing a plurality of rules in a textual rules structure; decomposing the plurality of rules into a plurality of contexts, based on the analysis; storing the plurality of contexts into a table; generating a plurality of concatenated values, each concatenated value comprising one value associated with a context of one of the plurality of contexts joined with one value associated with at least one other context of the one of the plurality of contexts; and storing the plurality of concatenated values in a plurality of filtering tables; wherein the plurality of filtering tables include a light context filtering table storing at least one concatenated value representing a combination of light contexts, a heavy context filtering table storing at last one concatenated value representing a combination of heavy contexts, a heavy and light context filtering table storing at last one concatenated value representing a combination of at least one heavy context and at least one light context, a looping filtering table storing at least one positive context that is utilized for positively filtering values, and not looping filtering table storing at least one negative context that is utilized for negatively filtering values; wherein each of the plurality of contexts is identified as a heavy context or a light context based on a predetermined number of distinct occurrences of data in a data stream; wherein the light context is predetermined to have a fewer number of distinct occurrences in the data than a number of distinct occurrences included in the heavy context; wherein if each context in the plurality of contexts filters a plurality of values, then the plurality of values is serialized into a series of concatenated values. 4. The method of claim 1 , wherein each context may include one of a source address, a source port, a source type, a destination address, a destination port, a destination type, a protocol, a service, a reason, a product, message information, an originating number, a destination number, a time, a date, a timestamp, a duration, a flag, a condition, a session record, and an attack. | 0.5 |
8,170,289 | 18 | 19 | 18. A system for generating a character-by-character alignment between a first and a second character sequence representing text in a source, comprising: a computer processor that is operable to execute a computer program product tangibly embodied in a computer-readable storage medium, the computer program product being operable to cause the computer processor to: align the two character sequences in a hierarchical manner utilizing a plurality of hierarchical levels, wherein the first character sequence is an optical character recognition (OCR) text output of a document, and the second character sequence is a separate electronic version of the document, and wherein: for a first hierarchical level, unique words of the second character sequence are aligned with corresponding words of the first character sequence and unique word anchors for a lower hierarchical level are designated; for each hierarchical level below the first hierarchical level and above a final hierarchical level, the computer program product is operable to cause the computer processor to: parse the two character sequences at a current hierarchical level into character subsequences, align the character subsequences, and designate the character subsequences at the current hierarchical level as anchors, the parsing of the character sequences and aligning of the character subsequences being performed between the anchors generated from an immediately previous hierarchical level if the current hierarchical level is below the first hierarchical level; and for the final hierarchical level, the computer program product is operable to cause the computer processor to: perform character-by-character alignment between the first character sequence and the second character sequence by aligning each character in the first character sequence at the final hierarchical level to each respective character in the second character sequence at the final hierarchical level, each of the characters being between anchors generated from an immediately previous hierarchical level, and identify extra OCR text, the extra OCR text comprising text that is included in the first character sequence and that is not included in the second character sequence, and eliminate the extra OCR text from the OCR text output. | 18. A system for generating a character-by-character alignment between a first and a second character sequence representing text in a source, comprising: a computer processor that is operable to execute a computer program product tangibly embodied in a computer-readable storage medium, the computer program product being operable to cause the computer processor to: align the two character sequences in a hierarchical manner utilizing a plurality of hierarchical levels, wherein the first character sequence is an optical character recognition (OCR) text output of a document, and the second character sequence is a separate electronic version of the document, and wherein: for a first hierarchical level, unique words of the second character sequence are aligned with corresponding words of the first character sequence and unique word anchors for a lower hierarchical level are designated; for each hierarchical level below the first hierarchical level and above a final hierarchical level, the computer program product is operable to cause the computer processor to: parse the two character sequences at a current hierarchical level into character subsequences, align the character subsequences, and designate the character subsequences at the current hierarchical level as anchors, the parsing of the character sequences and aligning of the character subsequences being performed between the anchors generated from an immediately previous hierarchical level if the current hierarchical level is below the first hierarchical level; and for the final hierarchical level, the computer program product is operable to cause the computer processor to: perform character-by-character alignment between the first character sequence and the second character sequence by aligning each character in the first character sequence at the final hierarchical level to each respective character in the second character sequence at the final hierarchical level, each of the characters being between anchors generated from an immediately previous hierarchical level, and identify extra OCR text, the extra OCR text comprising text that is included in the first character sequence and that is not included in the second character sequence, and eliminate the extra OCR text from the OCR text output. 19. The system of claim 18 wherein the hierarchical levels include the first, a second, and the final hierarchical level, and the character subsequences corresponding to the second hierarchical level are words. | 0.846041 |
9,781,540 | 35 | 37 | 35. A system comprising: means for determining, based on a dynamic characteristic of a mobile device of a user, a current device context value of at least one of a plurality of device context parameters; means for receiving, at the mobile device and over a communications network, context information from each client device of a plurality of client devices, wherein each client device corresponds to a different social contact of a plurality of social contacts of the user, wherein the context information received from each client device comprises information relating a social context of the client device of the social contact, and wherein the information relating to the social context of the client device of the social contact relates to historical application usage information of a plurality of applications of the client device of the social contact; means for determining, based on the context information received from each client device of the plurality of social contacts of the user, a current social context value of at least one of a plurality of social context parameters; for each of a plurality of applications previously downloaded and stored on the mobile device, means for calculating an application relevance score as a function of the current device context value and the current social context value; means for identifying at least one of the plurality of applications downloaded to the mobile device as a pinned application; and means for dynamically updating a display of a plurality of application representations on a graphical user interface (GUI) of the mobile device, such that the application representations are arranged according at least to the application relevance scores, each application representation corresponding to one of the plurality of applications downloaded to the mobile device, the arranging comprising removing at least one application representation of the plurality of application representations according to a frequency of use of each of the plurality of application representations, reordering one or more application representations of the plurality of application representations according to the frequency of use of each such application representation, and listing an application representation corresponding to a most recently used application of the plurality of applications downloaded to the mobile device in a user-designated location of the GUI for the most recently used application, wherein the arrangement of the application representation of the pinned application is fixed and is not affected by changes in the application relevance scores. | 35. A system comprising: means for determining, based on a dynamic characteristic of a mobile device of a user, a current device context value of at least one of a plurality of device context parameters; means for receiving, at the mobile device and over a communications network, context information from each client device of a plurality of client devices, wherein each client device corresponds to a different social contact of a plurality of social contacts of the user, wherein the context information received from each client device comprises information relating a social context of the client device of the social contact, and wherein the information relating to the social context of the client device of the social contact relates to historical application usage information of a plurality of applications of the client device of the social contact; means for determining, based on the context information received from each client device of the plurality of social contacts of the user, a current social context value of at least one of a plurality of social context parameters; for each of a plurality of applications previously downloaded and stored on the mobile device, means for calculating an application relevance score as a function of the current device context value and the current social context value; means for identifying at least one of the plurality of applications downloaded to the mobile device as a pinned application; and means for dynamically updating a display of a plurality of application representations on a graphical user interface (GUI) of the mobile device, such that the application representations are arranged according at least to the application relevance scores, each application representation corresponding to one of the plurality of applications downloaded to the mobile device, the arranging comprising removing at least one application representation of the plurality of application representations according to a frequency of use of each of the plurality of application representations, reordering one or more application representations of the plurality of application representations according to the frequency of use of each such application representation, and listing an application representation corresponding to a most recently used application of the plurality of applications downloaded to the mobile device in a user-designated location of the GUI for the most recently used application, wherein the arrangement of the application representation of the pinned application is fixed and is not affected by changes in the application relevance scores. 37. The system of claim 35 , wherein the means for determining the current device context value comprises means for determining the current device context value based on substantially real-time data received from a sensor integrated with the mobile device. | 0.803077 |
8,805,814 | 1 | 8 | 1. A computer system for searching databases and displaying search results, comprising: one or more databases storing information regarding publications, said information comprising author, title, date of publication, abstract, cited references, and citing references data; and one or more Internet servers in communication with said one or more databases; wherein at least one of said one or more Internet servers is in communication with and configured to transmit data to a Web browser application resident on a user's computer, and wherein said data is sufficient to enable said browser to display: (a) a search page that allows said user to input publication search parameters; and (b) a results page comprising: a tabular display of results that allows said user to sort results according to date, relevance, author, source title, and number of citations to each publication, wherein said display of results further comprises an indication of availability of a link allowing said user access to the full text for each respective result and a link to at least one aspect of the publication corresponding to said result, and a listing of subsets of said results, located on screen and separate from said display of results, wherein said listing of subsets comprises a source title subset, a author name subset, a year subset, a document type subset, and a subject area subset, wherein the number of results in each said subset is listed adjacent to each respective subset to allow for at-a-glance evaluation of said results, wherein said subsets are user selectable, and wherein said user may limit said results on said results page to said selected subsets and said user may exclude from said results on said results page said selected subsets; (c) a record page for providing further details of a result, said record page including a reference citing to said result. | 1. A computer system for searching databases and displaying search results, comprising: one or more databases storing information regarding publications, said information comprising author, title, date of publication, abstract, cited references, and citing references data; and one or more Internet servers in communication with said one or more databases; wherein at least one of said one or more Internet servers is in communication with and configured to transmit data to a Web browser application resident on a user's computer, and wherein said data is sufficient to enable said browser to display: (a) a search page that allows said user to input publication search parameters; and (b) a results page comprising: a tabular display of results that allows said user to sort results according to date, relevance, author, source title, and number of citations to each publication, wherein said display of results further comprises an indication of availability of a link allowing said user access to the full text for each respective result and a link to at least one aspect of the publication corresponding to said result, and a listing of subsets of said results, located on screen and separate from said display of results, wherein said listing of subsets comprises a source title subset, a author name subset, a year subset, a document type subset, and a subject area subset, wherein the number of results in each said subset is listed adjacent to each respective subset to allow for at-a-glance evaluation of said results, wherein said subsets are user selectable, and wherein said user may limit said results on said results page to said selected subsets and said user may exclude from said results on said results page said selected subsets; (c) a record page for providing further details of a result, said record page including a reference citing to said result. 8. The computer system of claim 1 , wherein said tabular display of results that allows said user to sort results according to date, relevance, author, source title, and number of citations to each publication allows said user to limit publication titles displayed to publication titles for publications from one or more selected authors. | 0.5 |
7,757,191 | 1 | 19 | 1. A computer-implemented method for race logic analysis on an integrated circuit (IC) design, to aid IC chip designers to detect and correct errors in their circuits and hence produce reliable IC products, the race logic analysis method comprisingβusing a processor to perform one or more of the following steps (a) detecting concurrent invocation of HDL-defined system functions/tasks that may cause one or more static or global signals/registers in the IC to be concurrently assigned or concurrently assigned and referenced, and render indeterminate values for those signals/registers; (b) detecting concurrently execution of βun-relatedβ process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned with different values, and hence render indeterminate values for those signals/registers; (c) detecting concurrently execution of βun-relatedβ process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned and being referenced by different process blocks, and render indeterminate values being read by driven process blocks; (d) detecting, dynamically via an event-driven logic simulation, circular functions/tasks invocation that may cause operation of the IC design to hang (deadlock); (e) detecting user-defined functions/tasks that invoke themselves recursively without termination, and hence render the IC design operation to hang (deadlock); (f) detecting concurrent invocation of HDL-defined functions/tasks that are built-in to HDL-defined inter-process communication (IPC) objects by βun-relatedβ processes, that may render execution order of said βun-relatedβ processes indeterminate, and/or that may process data that are of indeterminate values. | 1. A computer-implemented method for race logic analysis on an integrated circuit (IC) design, to aid IC chip designers to detect and correct errors in their circuits and hence produce reliable IC products, the race logic analysis method comprisingβusing a processor to perform one or more of the following steps (a) detecting concurrent invocation of HDL-defined system functions/tasks that may cause one or more static or global signals/registers in the IC to be concurrently assigned or concurrently assigned and referenced, and render indeterminate values for those signals/registers; (b) detecting concurrently execution of βun-relatedβ process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned with different values, and hence render indeterminate values for those signals/registers; (c) detecting concurrently execution of βun-relatedβ process blocks in the IC design that may cause one or more signals/registers to be concurrently assigned and being referenced by different process blocks, and render indeterminate values being read by driven process blocks; (d) detecting, dynamically via an event-driven logic simulation, circular functions/tasks invocation that may cause operation of the IC design to hang (deadlock); (e) detecting user-defined functions/tasks that invoke themselves recursively without termination, and hence render the IC design operation to hang (deadlock); (f) detecting concurrent invocation of HDL-defined functions/tasks that are built-in to HDL-defined inter-process communication (IPC) objects by βun-relatedβ processes, that may render execution order of said βun-relatedβ processes indeterminate, and/or that may process data that are of indeterminate values. 19. The method of claim 1 , wherein step (f), further comprises: recording, during a dynamic race logic analysis, a simulation time, an IPC semaphore object ID, a semaphore built-in function/task name and a calling process's ID, wherein each time a semaphore built-in function/task is invoked by a process; and if a semaphore object has one or more pairs of its built-in functions/tasks invoked by βunrelatedβ processes at the same simulation time, flagging those processes that are involved in a race logic with respect to the semaphore object, as the execution order of those process pending on the semaphore object is indeterminate. | 0.690244 |
9,055,148 | 16 | 18 | 16. The method of claim 15 , further comprising: applying specific filters for voice and text chat categorization. | 16. The method of claim 15 , further comprising: applying specific filters for voice and text chat categorization. 18. The method of claim 16 , further comprising: providing a priority index to control each of said filters. | 0.843478 |
8,909,573 | 8 | 11 | 8. A computer system comprising: at least one processor; and a memory comprising instructions stored thereon that when executed by the at least one processor cause the at least one processor to perform acts comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more intra-candidate dependent feature scores that are based on dependencies between different terms in the alteration candidate, the intra-candidate dependent feature scores comprising at least one skip bigram score; and using the one or more intra-candidate dependent feature scores to compute a candidate score for the candidate; and determining whether to select the candidate to expand the query, the determination using the candidate score. | 8. A computer system comprising: at least one processor; and a memory comprising instructions stored thereon that when executed by the at least one processor cause the at least one processor to perform acts comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more intra-candidate dependent feature scores that are based on dependencies between different terms in the alteration candidate, the intra-candidate dependent feature scores comprising at least one skip bigram score; and using the one or more intra-candidate dependent feature scores to compute a candidate score for the candidate; and determining whether to select the candidate to expand the query, the determination using the candidate score. 11. The computer system of claim 8 , wherein scoring the alteration candidate further comprises: computing one or more query-dependent feature scores that are based on dependencies to multiple query terms from each of one or more of the alteration terms; and using the one or more query-dependent feature scores to compute the candidate score for the candidate. | 0.5 |
7,685,512 | 16 | 17 | 16. The computer readable medium of claim 15 , wherein said XML entity is a local element declaration and wherein said computer-executable instructions further cause said computing device to: determine an original type of said local element declaration; create a derived type based on said original type; and change the type of said local element declaration from said original type to said derived type. | 16. The computer readable medium of claim 15 , wherein said XML entity is a local element declaration and wherein said computer-executable instructions further cause said computing device to: determine an original type of said local element declaration; create a derived type based on said original type; and change the type of said local element declaration from said original type to said derived type. 17. The computer readable medium of claim 16 , wherein said rendering option further specifies a target namespace for said additional attribute and wherein said computer-executable instructions further cause said computing device to, if said target namespace for said additional attribute is null or the same as a target namespace of said derived type, add to said derived type a local attribute declaration having said specified attribute name and said specified attribute value. | 0.622047 |
8,818,717 | 1 | 4 | 1. A method for increasing route accuracies, the method comprising: recording a waypoint while moving along a route; recording a positional-accuracy measurement for the recorded waypoint; calculating a position accuracy prediction (PAP) parameter for the recorded waypoint based on the recorded positional-accuracy measurement wherein the PAP parameter comprises a first weight value, a first confidence value, and an-a first error distance; and comparing, with a computer processor, the recorded waypoint and the calculated PAP parameter to a corpus waypoint and an associated corpus PAP parameter stored on a computer-based system, wherein the corpus PAP parameter comprises a second weight value, a second confidence value, and a second error distance, and wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the recorded waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus waypoint to provide a second probability distribution circle; and computationally generating a vector line between the recorded waypoint and the corpus waypoint; and determining, with the computer processor, an updated waypoint along the vector line between the recorded waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average. | 1. A method for increasing route accuracies, the method comprising: recording a waypoint while moving along a route; recording a positional-accuracy measurement for the recorded waypoint; calculating a position accuracy prediction (PAP) parameter for the recorded waypoint based on the recorded positional-accuracy measurement wherein the PAP parameter comprises a first weight value, a first confidence value, and an-a first error distance; and comparing, with a computer processor, the recorded waypoint and the calculated PAP parameter to a corpus waypoint and an associated corpus PAP parameter stored on a computer-based system, wherein the corpus PAP parameter comprises a second weight value, a second confidence value, and a second error distance, and wherein the comparing step comprises: calculating a weight average based on the first and second weight values; computationally extending the first error distance from the PAP parameter of the recorded waypoint to provide a first probability distribution circle; computationally extending the second error distance from the PAP parameter of the corpus waypoint to provide a second probability distribution circle; and computationally generating a vector line between the recorded waypoint and the corpus waypoint; and determining, with the computer processor, an updated waypoint along the vector line between the recorded waypoint and the corpus waypoint and within an overlapping area of the first and second probability distribution circles based on the calculated weight average. 4. The method of claim 1 , and further comprising recording environment information for each recorded waypoint, wherein the recorded environment information is selected from the group consisting of humidity, precipitation, temperature, barometric pressure, and combinations thereof, and wherein the PAP parameter is also based on the recorded environment information. | 0.5 |
8,151,183 | 10 | 11 | 10. The computer-readable storage medium of claim 8 , wherein the received file contains structured data; and wherein generating the processable extensible markup language file involves applying an extensible stylesheet language transformation tool. | 10. The computer-readable storage medium of claim 8 , wherein the received file contains structured data; and wherein generating the processable extensible markup language file involves applying an extensible stylesheet language transformation tool. 11. The computer-readable storage medium of claim 10 , wherein applying the extensible stylesheet language transformation tool involves transforming the processable extensible markup language file to one or more of the following files: a DocBook XML file; a LegalXML file; a VoiceXML file; a MathXML file; a WML file; and an XHTML-MP file. | 0.5 |
8,375,067 | 21 | 22 | 21. A system comprising: a plurality of processors; a database; a matching module implemented on one of the plurality of processors connected to the database and to a web server accessible to a job seeker, said matching module determining a matched job for the job seeker by comparing job parameters and job seeker parameters; an individualized data collection module determining job seeker characteristics based on individualized information captured from a user interface instantiated on a job seeker's individual device, wherein the determined job seeker characteristics are incorporated into job seeker parameters utilized by the matching module; a correlation module implemented on one of the plurality of processors communicating with the job matching module and the database, the correlation module comprising: a user activity monitor module implemented on one of the plurality of processors tracking job seeker activity within the system for matching job seekers with potential jobs based on behavior of prior activity for the job seeker; an affinity module implemented on one of the plurality of processors configured to determine affinity metrics between the matched job and other jobs interacted with by other job seekers based on the tracked job seeker activity and determine alternative jobs in addition to the matched job for the job seeker based on the determined affinity metrics; and a filtration module implemented on one of the plurality of processors operably coupled to the affinity module and user activity monitor module receiving preferences from a job seeker to refine correlations made by the matching module and correlation module for consideration by the job seeker, and generating and storing a negative filtration indication associated with a job for excluding the job in instant and subsequent job queries for the job seeker. | 21. A system comprising: a plurality of processors; a database; a matching module implemented on one of the plurality of processors connected to the database and to a web server accessible to a job seeker, said matching module determining a matched job for the job seeker by comparing job parameters and job seeker parameters; an individualized data collection module determining job seeker characteristics based on individualized information captured from a user interface instantiated on a job seeker's individual device, wherein the determined job seeker characteristics are incorporated into job seeker parameters utilized by the matching module; a correlation module implemented on one of the plurality of processors communicating with the job matching module and the database, the correlation module comprising: a user activity monitor module implemented on one of the plurality of processors tracking job seeker activity within the system for matching job seekers with potential jobs based on behavior of prior activity for the job seeker; an affinity module implemented on one of the plurality of processors configured to determine affinity metrics between the matched job and other jobs interacted with by other job seekers based on the tracked job seeker activity and determine alternative jobs in addition to the matched job for the job seeker based on the determined affinity metrics; and a filtration module implemented on one of the plurality of processors operably coupled to the affinity module and user activity monitor module receiving preferences from a job seeker to refine correlations made by the matching module and correlation module for consideration by the job seeker, and generating and storing a negative filtration indication associated with a job for excluding the job in instant and subsequent job queries for the job seeker. 22. The system according to claim 21 wherein the filtration module presents to the job seeker an option to select a matching job to be eliminated from subsequent display to the job seeker. | 0.58952 |
8,051,045 | 18 | 19 | 18. A method comprising: identifying a data record to be archived, the data record comprising a plurality of data record attributes and originally residing in a database; creating an archive record, the archive record comprising a first subset of the plurality of data record attributes, the first subset comprising at least some of the plurality of data record attributes; storing the archive record in a data archive, the data archive being maintained separately from the database; creating a new archive index record, the new archive index record comprising a reference to a location of the archive record in the data archive and a second plurality of attributes of the plurality of data record attributes, the second subset comprising selected attributes from the plurality of data record attributes, the selected attributes being those identified as necessary for access by users of the database; adding the new archive index record to a dictionary-based archive index, the dictionary-based archive index comprising a plurality of archive index records, being stored separately from the database, and comprising a dictionary storing every term used in the plurality of index records; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. | 18. A method comprising: identifying a data record to be archived, the data record comprising a plurality of data record attributes and originally residing in a database; creating an archive record, the archive record comprising a first subset of the plurality of data record attributes, the first subset comprising at least some of the plurality of data record attributes; storing the archive record in a data archive, the data archive being maintained separately from the database; creating a new archive index record, the new archive index record comprising a reference to a location of the archive record in the data archive and a second plurality of attributes of the plurality of data record attributes, the second subset comprising selected attributes from the plurality of data record attributes, the selected attributes being those identified as necessary for access by users of the database; adding the new archive index record to a dictionary-based archive index, the dictionary-based archive index comprising a plurality of archive index records, being stored separately from the database, and comprising a dictionary storing every term used in the plurality of index records; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. 19. The method of claim 18 , wherein the determining whether the attribute value of the plurality of attribute values is required for frequent user read access comprises analyzing data collected from queries run by users on the dictionary-based archive index to determine a frequency with which attributes of the plurality of attributes are accessed. | 0.5 |
7,555,711 | 17 | 18 | 17. A machine for processing an electronic document, comprising computer hardware operable to perform operations comprising: extracting logical blocks from the electronic document including a text block comprising text lines each encompassed by a respective bounding rectangle; receiving the explicit logical blocks; extending edges of ones of the bounding rectangles to at least one boundary without changing layout relationships among the logical blocks in the electronic document; a text layout boundary from extended and unextended edges of the bounding rectangles; and storing a description of the text layout boundary in a machine-readable medium. | 17. A machine for processing an electronic document, comprising computer hardware operable to perform operations comprising: extracting logical blocks from the electronic document including a text block comprising text lines each encompassed by a respective bounding rectangle; receiving the explicit logical blocks; extending edges of ones of the bounding rectangles to at least one boundary without changing layout relationships among the logical blocks in the electronic document; a text layout boundary from extended and unextended edges of the bounding rectangles; and storing a description of the text layout boundary in a machine-readable medium. 18. The machine of claim 17 , wherein the text layout boundary extraction engine is configured to identify at least one boundary to which ones of the bounding rectangles are extendable without changing layout relationships among logical blocks in the electronic document. | 0.5 |
7,996,410 | 1 | 2 | 1. A method, comprising: generating a dictionary comprising (a) one or more transformations of words from singular to plural form and (b) one or more transformations of words from plural to singular form; counting a first number of times that a certain word appears in a set of two or more separate web documents, wherein the certain word is a singular form of the word; counting a second number of times that a transformation of the certain word appears in the set of two or more separate web documents, wherein the transformation of the certain word is a plural form of the certain word; computing a probability by either (a) dividing the second number by the first number or (b) dividing the first number by the second number, removing, from the dictionary, the certain word and the transformation of the certain word in response to determining that the probability is below a particular value; receiving a particular query from a user comprising a plurality of words; based on the particular query, determining whether a particular word in the particular query occurs in the dictionary; selecting from the dictionary a transformation of the particular word; and generating results based on executing a version of the particular query that includes both the particular word and the transformation of the particular word; wherein the method is performed by one or more computing devices. | 1. A method, comprising: generating a dictionary comprising (a) one or more transformations of words from singular to plural form and (b) one or more transformations of words from plural to singular form; counting a first number of times that a certain word appears in a set of two or more separate web documents, wherein the certain word is a singular form of the word; counting a second number of times that a transformation of the certain word appears in the set of two or more separate web documents, wherein the transformation of the certain word is a plural form of the certain word; computing a probability by either (a) dividing the second number by the first number or (b) dividing the first number by the second number, removing, from the dictionary, the certain word and the transformation of the certain word in response to determining that the probability is below a particular value; receiving a particular query from a user comprising a plurality of words; based on the particular query, determining whether a particular word in the particular query occurs in the dictionary; selecting from the dictionary a transformation of the particular word; and generating results based on executing a version of the particular query that includes both the particular word and the transformation of the particular word; wherein the method is performed by one or more computing devices. 2. The method of claim 1 , wherein the dictionary is based upon words used in a certain number of previous most frequent search queries. | 0.880071 |
8,745,094 | 7 | 8 | 7. The method of claim 1 , wherein at least one of the selected substring of the sensitive string of characters and the selected substring of the intermediate tokenized string of characters comprises only numerical characters, and wherein at least one of the first and second tokens comprises alphanumerical characters. | 7. The method of claim 1 , wherein at least one of the selected substring of the sensitive string of characters and the selected substring of the intermediate tokenized string of characters comprises only numerical characters, and wherein at least one of the first and second tokens comprises alphanumerical characters. 8. The method of claim 7 , wherein at least one substring being replaced by a token comprising alphanumerical characters comprises more characters than the corresponding token. | 0.5 |
9,411,710 | 16 | 17 | 16. The computer readable medium of claim 13 wherein each test script comprises a keyword table including a set of the at least some of the identified components of the application. | 16. The computer readable medium of claim 13 wherein each test script comprises a keyword table including a set of the at least some of the identified components of the application. 17. The computer readable medium of claim 16 wherein the search is based on the keyword table associated with each test script. | 0.5 |
9,971,766 | 1 | 6 | 1. A computing device comprising one or more processors and one or more non-transitory storage devices storing instructions that, when executed by the one or more processors, configure the computing device to: receive at least one user query from an input device, wherein the at least one user query includes a user intent and at least one command, the at least one user intent being associated with a set of functions to be carried out by the computing device; derive, using a natural language processing (NLP) engine, the user intent from the user query; identify, using the NLP engine, at least one domain and the at least one command associated with the derived user intent, wherein the NLP engine performs entity extraction on the at least one user query to identify at least one entity associated with the at least one command, wherein the at least one command is associated with the domain; execute the at least one command associated with the user intent, wherein the at least one command is configured to direct the computing device to carry out at least one function selected from the set of functions; and generate output of at least one result of the executed at least one command from at least one component of the computing device. | 1. A computing device comprising one or more processors and one or more non-transitory storage devices storing instructions that, when executed by the one or more processors, configure the computing device to: receive at least one user query from an input device, wherein the at least one user query includes a user intent and at least one command, the at least one user intent being associated with a set of functions to be carried out by the computing device; derive, using a natural language processing (NLP) engine, the user intent from the user query; identify, using the NLP engine, at least one domain and the at least one command associated with the derived user intent, wherein the NLP engine performs entity extraction on the at least one user query to identify at least one entity associated with the at least one command, wherein the at least one command is associated with the domain; execute the at least one command associated with the user intent, wherein the at least one command is configured to direct the computing device to carry out at least one function selected from the set of functions; and generate output of at least one result of the executed at least one command from at least one component of the computing device. 6. The computing device of claim 1 , wherein the at least one command and at least one entity are provided to a services component for identifying at least one service capable of performing the at least one command, and for instructing the at least one service to perform the at least one command, the at least one service configured to return a service result to the services component in response to performing the at least one command. | 0.672156 |
7,840,488 | 1 | 31 | 1. A computer-implemented method for processing plural rights expressions associated with an item for use in a system for controlling use of the item in accordance with the rights expressions, the method comprising: receiving a request to use the item, the item having associated rights expressions governing use of the item; returning one or more rights expressions including one or more conditions that must be satisfied in order to use the item; and processing the returned rights expressions in a manner to facilitate selection of the returned rights expressions in order to use the item in accordance with the selected rights expressions, and including: prioritizing the returned rights expressions based on the one or more conditions of the returned rights expressions, so as to facilitate selection of the returned rights expressions. | 1. A computer-implemented method for processing plural rights expressions associated with an item for use in a system for controlling use of the item in accordance with the rights expressions, the method comprising: receiving a request to use the item, the item having associated rights expressions governing use of the item; returning one or more rights expressions including one or more conditions that must be satisfied in order to use the item; and processing the returned rights expressions in a manner to facilitate selection of the returned rights expressions in order to use the item in accordance with the selected rights expressions, and including: prioritizing the returned rights expressions based on the one or more conditions of the returned rights expressions, so as to facilitate selection of the returned rights expressions. 31. The method of claim 1 , wherein the processing step includes calculating condition term usage costs based on respective terms of the conditions. | 0.793872 |
9,710,455 | 1 | 2 | 1. A sensitive text detecting method comprising: by a server system comprising one or more processors, acquiring, from a user terminal triggered in response to detecting updated text, a feature text string of a currently detected text; detecting the feature text string according to a finite-state machine indicating transitions between states based on information determined by the server system, the transitions enabling the server system to scan the feature text string once, and the information causing the server system to determine frequency of occurrence of each keyword in the feature text string, the finite-state machine being associated with multiple keywords; calculating, for each keyword category of multiple keyword categories, a weight of the keyword category in the text based on the frequency of occurrence of each keyword corresponding to the keyword category and a preset weight of each keyword; and determining that the text is a sensitive text when the weight of at least one keyword category is greater than a preset threshold; wherein the method further comprises: after the determining that the text is a sensitive text, determining, when the weight of at least one keyword category is greater than the preset threshold, a category of the text according to a keyword category that has a greatest weight; determining a sensitive degree of the text by comparing the weight of the keyword category that has the greatest weight with the preset threshold; and outputting, to a reviewer via a display, the sensitive degree of the text. | 1. A sensitive text detecting method comprising: by a server system comprising one or more processors, acquiring, from a user terminal triggered in response to detecting updated text, a feature text string of a currently detected text; detecting the feature text string according to a finite-state machine indicating transitions between states based on information determined by the server system, the transitions enabling the server system to scan the feature text string once, and the information causing the server system to determine frequency of occurrence of each keyword in the feature text string, the finite-state machine being associated with multiple keywords; calculating, for each keyword category of multiple keyword categories, a weight of the keyword category in the text based on the frequency of occurrence of each keyword corresponding to the keyword category and a preset weight of each keyword; and determining that the text is a sensitive text when the weight of at least one keyword category is greater than a preset threshold; wherein the method further comprises: after the determining that the text is a sensitive text, determining, when the weight of at least one keyword category is greater than the preset threshold, a category of the text according to a keyword category that has a greatest weight; determining a sensitive degree of the text by comparing the weight of the keyword category that has the greatest weight with the preset threshold; and outputting, to a reviewer via a display, the sensitive degree of the text. 2. The method according to claim 1 , before the detecting the feature text string according to a finite-state machine, the method further comprising: configuring a keyword list, the keyword list at least comprising multiple keywords, a keyword category of each keyword, and a preset weight of each keyword; determining a common prefix of all keywords in the keyword list; and establishing a tree-like finite-state machine by using the common prefix as a root node, each branch of the tree-like finite-state machine at least comprising one keyword. | 0.5 |
9,386,950 | 10 | 16 | 10. A computer-readable medium comprising a plurality of software instructions that, when executed by at least one network-connected computer-based system, perform a method of determining a user's risk of dyslexia, the instructions comprising: instructions for identifying, based on an input received from an input device of the computer-based system, an age category associated with the user; instructions for generating a plurality of query pages, each query page being generated from data received by the computer-based system from a remote server over a data communications channel and stored in a memory device of the computer-based system, and each query page comprising a plurality of non-verbal answers that are determined based on the identified age category and are selectable by the user; instructions for generating a plurality of auditory queries to be rendered via a speaker of the computer-based system, each auditory query being producible as audible sounds and generated from a sound data file corresponding to a non-verbal query, each auditory query being associated with one or more of the plurality of query pages; instructions for identifying, via the input device of the computer-based system, a plurality of electronic input selections from the user, each electronic input selection identifying a non-verbal answer from a query page; instructions for identifying, via a timer of the computer-based system, timing data associated with the plurality of electronic input selections, the timing data indicating time intervals between the rendering of each of the plurality of auditory queries and the detection of electronic input selections from the user corresponding to each of the auditory queries; instructions for assigning weighted scores to each of the electronic input selections from the user, the weighted scores being determined based on the identified age category and the time intervals, wherein time intervals above a first threshold receive a first weighting factor and time intervals below the first threshold receive a second weighting factor; and instructions for rendering, on the display screen of the computer-based system, an assessment in a graphical user interface, the assessment identifying a risk of dyslexia for the user based on whether the weighted scores exceed a predefined threshold associated with the plurality of query pages. | 10. A computer-readable medium comprising a plurality of software instructions that, when executed by at least one network-connected computer-based system, perform a method of determining a user's risk of dyslexia, the instructions comprising: instructions for identifying, based on an input received from an input device of the computer-based system, an age category associated with the user; instructions for generating a plurality of query pages, each query page being generated from data received by the computer-based system from a remote server over a data communications channel and stored in a memory device of the computer-based system, and each query page comprising a plurality of non-verbal answers that are determined based on the identified age category and are selectable by the user; instructions for generating a plurality of auditory queries to be rendered via a speaker of the computer-based system, each auditory query being producible as audible sounds and generated from a sound data file corresponding to a non-verbal query, each auditory query being associated with one or more of the plurality of query pages; instructions for identifying, via the input device of the computer-based system, a plurality of electronic input selections from the user, each electronic input selection identifying a non-verbal answer from a query page; instructions for identifying, via a timer of the computer-based system, timing data associated with the plurality of electronic input selections, the timing data indicating time intervals between the rendering of each of the plurality of auditory queries and the detection of electronic input selections from the user corresponding to each of the auditory queries; instructions for assigning weighted scores to each of the electronic input selections from the user, the weighted scores being determined based on the identified age category and the time intervals, wherein time intervals above a first threshold receive a first weighting factor and time intervals below the first threshold receive a second weighting factor; and instructions for rendering, on the display screen of the computer-based system, an assessment in a graphical user interface, the assessment identifying a risk of dyslexia for the user based on whether the weighted scores exceed a predefined threshold associated with the plurality of query pages. 16. The computer-readable medium of claim 10 , further comprising instructions for, each time no selection from the user is identified within a second threshold, changing a query page that is being rendered on the display screen of the computer-based system, wherein the second threshold is different from the first threshold. | 0.544693 |
9,060,063 | 1 | 3 | 1. A non-transitory machine-readable medium having stored thereon a set of instructions, which when executed by a server system causes the server system to perform a method, the method comprising: transmitting, by the server system to an end-user computing device via an Internet, a web page configured to indicate an option to receive, from a user, a request via the web page and a browser of the end-user computing device; processing, by the server system, a first indication of a selection of the option; selecting, by the server system, an advisor from a plurality of advisors for indication in an advertisement for the advisor, the selecting based at least in part on a compensation rate of the advisor and a quality score of the advisor; determining, by the server system, a status of the advisor; in response to the selection, transmitting to the end-user computing device the advertisement for the advisor, the advertisement to be visually displayed via the end-user computing device, wherein the advertisement includes: at least one reference selectable by the user to request a real-time communication connection with the advisor, wherein the real-time communication connection is separate from an Internet connection used by the end-user computing device to download the web page; and an indication of the status of the advisor; while the advisor is determined to be currently available for real-time communication, receiving, by the server system, from the end-user computing device a second indication of a user selection of the at least one reference made via the advertisement, the user selection of the at least one reference corresponding to the advisor; and in response to the second indication of the user selection of the at least one reference, establishing a telephonic connection via a central controller of the server system to provide the real-time communication connection requested between the advisor and the user, wherein the establishing the telephonic connection comprises the central controller directing a first transmission to the user, the central controller directing a second transmission to the advisor, and the central controller joining the first transmission and the second transmission, and wherein the telephonic connection is separate from the Internet connection used by the end-user computing device to download the web page. | 1. A non-transitory machine-readable medium having stored thereon a set of instructions, which when executed by a server system causes the server system to perform a method, the method comprising: transmitting, by the server system to an end-user computing device via an Internet, a web page configured to indicate an option to receive, from a user, a request via the web page and a browser of the end-user computing device; processing, by the server system, a first indication of a selection of the option; selecting, by the server system, an advisor from a plurality of advisors for indication in an advertisement for the advisor, the selecting based at least in part on a compensation rate of the advisor and a quality score of the advisor; determining, by the server system, a status of the advisor; in response to the selection, transmitting to the end-user computing device the advertisement for the advisor, the advertisement to be visually displayed via the end-user computing device, wherein the advertisement includes: at least one reference selectable by the user to request a real-time communication connection with the advisor, wherein the real-time communication connection is separate from an Internet connection used by the end-user computing device to download the web page; and an indication of the status of the advisor; while the advisor is determined to be currently available for real-time communication, receiving, by the server system, from the end-user computing device a second indication of a user selection of the at least one reference made via the advertisement, the user selection of the at least one reference corresponding to the advisor; and in response to the second indication of the user selection of the at least one reference, establishing a telephonic connection via a central controller of the server system to provide the real-time communication connection requested between the advisor and the user, wherein the establishing the telephonic connection comprises the central controller directing a first transmission to the user, the central controller directing a second transmission to the advisor, and the central controller joining the first transmission and the second transmission, and wherein the telephonic connection is separate from the Internet connection used by the end-user computing device to download the web page. 3. The medium of claim 1 , wherein the transmitting the advertisement is in response to a search submitted by the user. | 0.868071 |
9,652,717 | 4 | 5 | 4. The method of claim 3 , further comprising: outputting, to a user presenting the case, an indication that supporting evidence for the first candidate answer is not included as part of a response to the case at least in part due to the first attribute. | 4. The method of claim 3 , further comprising: outputting, to a user presenting the case, an indication that supporting evidence for the first candidate answer is not included as part of a response to the case at least in part due to the first attribute. 5. The method of claim 4 , further comprising: excluding a second candidate answer from the set of candidate answers upon determining that at least one of the first attribute and a second attribute preclude returning the second candidate answer as a valid response to the case. | 0.5 |
8,244,720 | 10 | 16 | 10. A method performed by one or more server devices, the method comprising: receiving, by a blog search engine of the one or more server devices, a search query; identifying, by the blog search engine of the one or more server devices, a blog document that is responsive to the search query; generating, by the blog search engine of the one or more server devices, a relevance score for the blog document, the relevance score being based on a relevance of the blog document to the search query; generating, by the blog search engine of the one or more server devices, a quality score for the blog document, the quality score based on quality of the blog document independent of the search query, where the quality score is based on a plurality of indicators that include at least one of one or more positive indicators or one or more negative indicators, where the one or more positive indicators include an indication that the blog document is referenced in a blogroll; where the one or more negative indicators include a location of ads in the blog document; generating, by the blog search engine of the one or more server devices, a ranking score based on the relevance score and the quality score; and providing, by the blog search engine of the one or more server devices, information regarding the blog document based on the ranking score. | 10. A method performed by one or more server devices, the method comprising: receiving, by a blog search engine of the one or more server devices, a search query; identifying, by the blog search engine of the one or more server devices, a blog document that is responsive to the search query; generating, by the blog search engine of the one or more server devices, a relevance score for the blog document, the relevance score being based on a relevance of the blog document to the search query; generating, by the blog search engine of the one or more server devices, a quality score for the blog document, the quality score based on quality of the blog document independent of the search query, where the quality score is based on a plurality of indicators that include at least one of one or more positive indicators or one or more negative indicators, where the one or more positive indicators include an indication that the blog document is referenced in a blogroll; where the one or more negative indicators include a location of ads in the blog document; generating, by the blog search engine of the one or more server devices, a ranking score based on the relevance score and the quality score; and providing, by the blog search engine of the one or more server devices, information regarding the blog document based on the ranking score. 16. The method of claim 10 , where the one or more negative indicators include a size of posts in the blog document. | 0.686486 |
9,524,717 | 11 | 12 | 11. The interface of claim 10 , wherein the interface generates a recording of the voice call for review by an intended recipient and links to the recording for access by an intended recipient. | 11. The interface of claim 10 , wherein the interface generates a recording of the voice call for review by an intended recipient and links to the recording for access by an intended recipient. 12. The interface of claim 11 , wherein the interface appends metadata to the recording but does not append the text data to the recording if the confidence score is below a predetermined threshold. | 0.5 |
8,145,586 | 1 | 2 | 1. An apparatus for digital forensics, comprising: a page file extractor for extracting a page file stored in a target storage medium; a stored-page feature extractor for extracting features of pages stored in the extracted page file; a page classifier for comparing the extracted features of the pages with at least one predetermined classification criterion, and classifying the pages according to the comparison results; and a digital forensics unit for performing digital forensics according to the classified pages, wherein the features of the pages correspond to binary data distribution characteristics according to memory addresses in the pages. | 1. An apparatus for digital forensics, comprising: a page file extractor for extracting a page file stored in a target storage medium; a stored-page feature extractor for extracting features of pages stored in the extracted page file; a page classifier for comparing the extracted features of the pages with at least one predetermined classification criterion, and classifying the pages according to the comparison results; and a digital forensics unit for performing digital forensics according to the classified pages, wherein the features of the pages correspond to binary data distribution characteristics according to memory addresses in the pages. 2. The apparatus of claim 1 , wherein the page file stores virtual memory data in units of pages in a computing environment using a Windows operating system. | 0.655702 |
9,047,368 | 1 | 3 | 1. A computer implemented method for clustering documents around entities associated with an individual user, thereby enabling the individual user to intuitively identify and access the documents, the method comprising the steps of: retrieving multiple documents associated with the individual user from at least one source, by a computer; identifying specific textual elements that occur in the retrieved documents; identifying cluster keys in retrieved documents based on at least identified textual elements, wherein a cluster key comprises an association between a document and a specific entity associated with the individual user, around which to cluster documents associated with the specific entity, comprising: classifying a specific document as being of a type for which names and addresses are likely cluster keys; finding at least one name or addresses in the specific document; for each found name or address, determining whether the found name or address is that of a recipient of the specific document; responsive to determining that the name or address is not that of the recipient of the specific document, identifying the name or address as a cluster key for the specific document; and responsive to determining that the name or address is that of the recipient of the specific document, identifying the name or address as not comprising a cluster key for the specific document; storing retrieved documents, identified cluster keys and associations between them, thereby organizing documents into clusters based on entities associated with the individual user; and providing the individual user with access to the documents according to the clusters into which the documents are organized. | 1. A computer implemented method for clustering documents around entities associated with an individual user, thereby enabling the individual user to intuitively identify and access the documents, the method comprising the steps of: retrieving multiple documents associated with the individual user from at least one source, by a computer; identifying specific textual elements that occur in the retrieved documents; identifying cluster keys in retrieved documents based on at least identified textual elements, wherein a cluster key comprises an association between a document and a specific entity associated with the individual user, around which to cluster documents associated with the specific entity, comprising: classifying a specific document as being of a type for which names and addresses are likely cluster keys; finding at least one name or addresses in the specific document; for each found name or address, determining whether the found name or address is that of a recipient of the specific document; responsive to determining that the name or address is not that of the recipient of the specific document, identifying the name or address as a cluster key for the specific document; and responsive to determining that the name or address is that of the recipient of the specific document, identifying the name or address as not comprising a cluster key for the specific document; storing retrieved documents, identified cluster keys and associations between them, thereby organizing documents into clusters based on entities associated with the individual user; and providing the individual user with access to the documents according to the clusters into which the documents are organized. 3. The method of claim 1 wherein identifying specific textual elements further comprises: performing optical character recognition on an image of text in a document, the document being in an image based format; and identifying textual elements in output of the performed optical character recognition. | 0.608073 |
8,751,215 | 13 | 14 | 13. The computer storage medium of claim 12 further including instructions for performing a step of acquiring user demographic information and comparing each match with the user demographic information to verify the accuracy of the match. | 13. The computer storage medium of claim 12 further including instructions for performing a step of acquiring user demographic information and comparing each match with the user demographic information to verify the accuracy of the match. 14. The computer storage medium of claim 13 wherein each step of assigning includes determining a match between a detected gesture and a sign, and further includes assigning a probability weight to each sign indicating the strength of the match between the gesture and the sign. | 0.5 |
9,203,867 | 12 | 13 | 12. The method of claim 10 , further comprises: providing at least one categorized group of user identity attributes; and determining a privacy preference for each category. | 12. The method of claim 10 , further comprises: providing at least one categorized group of user identity attributes; and determining a privacy preference for each category. 13. The method of claim 12 , further comprises: receiving from the environment the security policy having requirements specifying required attributes; identifying at least one category referencing the required attributes; and the evaluating further includes using the privacy preference of at least one identified category in the evaluation operation. | 0.5 |
4,658,370 | 1 | 34 | 1. A knowledge engineering tool comprising a computer having a stored program and memory for storing a knowledge base, said knowledge base including factual knowledge and judgmental knowledge, said judgmental knowledge including judgmental rules having premises for limiting the conditions in which the rules are applicable and conclusions for indicating the actions to perform when the rules are successfully applied, said factual knowledge including definitions of attributes that can take on values, said judgmental rules including rules having premises referring to attributes and rules concluding values for attributes, means for executing a built-in control procedure including means for interpreting the knowledge base, means for invoking and chaining said rules, and means for terminating the knowledge base search for a value, said knowledge base also including control knowledge supplied by a knowledge engineer to modify the built-in control procedure, and a language interpreter for executing the control knowledge to modify the built-in control procedure, whereby the control knowledge can be separated from the factual knowledge and judgmental knowledge and stored as a distinct portion of the knowledge base. | 1. A knowledge engineering tool comprising a computer having a stored program and memory for storing a knowledge base, said knowledge base including factual knowledge and judgmental knowledge, said judgmental knowledge including judgmental rules having premises for limiting the conditions in which the rules are applicable and conclusions for indicating the actions to perform when the rules are successfully applied, said factual knowledge including definitions of attributes that can take on values, said judgmental rules including rules having premises referring to attributes and rules concluding values for attributes, means for executing a built-in control procedure including means for interpreting the knowledge base, means for invoking and chaining said rules, and means for terminating the knowledge base search for a value, said knowledge base also including control knowledge supplied by a knowledge engineer to modify the built-in control procedure, and a language interpreter for executing the control knowledge to modify the built-in control procedure, whereby the control knowledge can be separated from the factual knowledge and judgmental knowledge and stored as a distinct portion of the knowledge base. 34. A knowledge engineering tool as set forth in claim 1 wherein said control knowledge includes control blocks specifying methods for determining the values of prescribed attributes. | 0.792517 |
7,991,608 | 3 | 5 | 3. An apparatus for multilingual data querying, comprising: circuitry to: receive a base word selected by a user using a user interface; receive one or more parts of speech of the base word selected by the user using the user interface; determine an ontology of the base word in a source language, the word ontology comprising words associated with a part of speech selected by the user if one part of speech is selected by the user, the word ontology comprising words associated with more than one part of speech if more than one part of speech is selected by the user, the word ontology of the base word comprising at least two of a synonym, a homonym, a hypernym and a hyponym of the base word; generate, in the source language, a first set of words comprising the word ontology and a definition of each word in the word ontology; receive a subset of the first set of words selected by the user using the user interface; translate the subset of the first set of words selected by the user from the source language into a second set of words in a target language; translate the second set of words selected by the user from the target language into a third set of words in the source language; receive a subset of the second set of words in the target language selected by the user using the user interface after the user observes the third set of words in the source language; and querying the subset of the second set of words. | 3. An apparatus for multilingual data querying, comprising: circuitry to: receive a base word selected by a user using a user interface; receive one or more parts of speech of the base word selected by the user using the user interface; determine an ontology of the base word in a source language, the word ontology comprising words associated with a part of speech selected by the user if one part of speech is selected by the user, the word ontology comprising words associated with more than one part of speech if more than one part of speech is selected by the user, the word ontology of the base word comprising at least two of a synonym, a homonym, a hypernym and a hyponym of the base word; generate, in the source language, a first set of words comprising the word ontology and a definition of each word in the word ontology; receive a subset of the first set of words selected by the user using the user interface; translate the subset of the first set of words selected by the user from the source language into a second set of words in a target language; translate the second set of words selected by the user from the target language into a third set of words in the source language; receive a subset of the second set of words in the target language selected by the user using the user interface after the user observes the third set of words in the source language; and querying the subset of the second set of words. 5. The apparatus of claim 3 , further comprising circuitry to retrieve data from an indexed database based on the selections from the user. | 0.701717 |
9,373,057 | 11 | 12 | 11. A system for training a neural network that receives an input image and outputs a predetermined number of candidate bounding boxes that each cover a respective portion of the input image at a respective position in the input image and a respective confidence score for each candidate bounding box that represents a likelihood that the candidate bounding box contains an image of an object, the system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a training image and object location data for the training image, wherein the object location data identifies one or more object locations in the training image; providing the training image to the neural network and obtaining bounding box data for the training image from the neural network, wherein the bounding box data comprises data defining a plurality of candidate bounding boxes in the training image and a respective confidence score for each candidate bounding box in the training image; determining an optimal set of assignments using the object location data for the training image and the bounding box data for the training image, wherein the optimal set of assignments assigns a respective candidate bounding box to each of the object locations; and training the neural network on the training image using the optimal set of assignments. | 11. A system for training a neural network that receives an input image and outputs a predetermined number of candidate bounding boxes that each cover a respective portion of the input image at a respective position in the input image and a respective confidence score for each candidate bounding box that represents a likelihood that the candidate bounding box contains an image of an object, the system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a training image and object location data for the training image, wherein the object location data identifies one or more object locations in the training image; providing the training image to the neural network and obtaining bounding box data for the training image from the neural network, wherein the bounding box data comprises data defining a plurality of candidate bounding boxes in the training image and a respective confidence score for each candidate bounding box in the training image; determining an optimal set of assignments using the object location data for the training image and the bounding box data for the training image, wherein the optimal set of assignments assigns a respective candidate bounding box to each of the object locations; and training the neural network on the training image using the optimal set of assignments. 12. The system of claim 11 , wherein determining the optimal set of assignments comprises performing a bipartite matching between the object locations and the candidate bounding boxes to select the optimal set of assignments. | 0.672012 |
8,150,923 | 8 | 9 | 8. The method as recited in claim 2 , wherein the one or more general data fields include: a primary type field defining a format for representing a primary message type corresponding to an electronic message, the primary message type implying a behavior of the electronic message; a participants relationship field defining a format for representing links to message participants, the message participants being associated with the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; a contents relationship field defining a format for representing links to one or more portions of message content, the one or more portions of content corresponding to the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; a sent message folder relationship field defining a format for representing links to one or more message folders that the electronic message, having a primary message type defined in accordance with the primary message type format in the primary type field, should be moved to after being submitted for delivery; and a download state field defining a format for representing download states corresponding to the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; and wherein the act of assigning a primary type to the message item comprises an act of assigning a value to the primary type field. | 8. The method as recited in claim 2 , wherein the one or more general data fields include: a primary type field defining a format for representing a primary message type corresponding to an electronic message, the primary message type implying a behavior of the electronic message; a participants relationship field defining a format for representing links to message participants, the message participants being associated with the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; a contents relationship field defining a format for representing links to one or more portions of message content, the one or more portions of content corresponding to the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; a sent message folder relationship field defining a format for representing links to one or more message folders that the electronic message, having a primary message type defined in accordance with the primary message type format in the primary type field, should be moved to after being submitted for delivery; and a download state field defining a format for representing download states corresponding to the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field; and wherein the act of assigning a primary type to the message item comprises an act of assigning a value to the primary type field. 9. The method as recited in claim 8 , wherein the one or more general data fields also include: a message status field defining a format for representing the status of the electronic message having a primary message type defined in accordance with the primary message type format in the primary type field, the message schema including or referring to a message status schema that defines the format for representing the status of the electronic message. | 0.5 |
9,620,107 | 7 | 9 | 7. A method, comprising: analyzing, using a computer processor, an inspection audio recording for keywords associated with an inspection, by: recording, during the inspection, using the at least one of an inspection tool and an inspection instrument communicatively coupled to the inspection tool, the inspection audio recording, wherein the inspection audio recording comprises audible annotations comprising comments of the inspection from an inspector performing the inspection, the comments comprising data minable keywords related to the inspection; sending, using the at least one of the inspection tool and the inspection instrument, the inspection audio recording to a cloud-based voice recognition service to data mine the inspection audio recording for the keywords; and obtaining, using the at least one of the inspection tool and the inspection instrument, the keywords from the voice recognition service; associating, using the at least one of the inspection tool and the inspection instrument, the keywords as metadata for inspection data acquired in time proximity to the audio recording, by the inspection tool; and storing the inspection data with the associated keywords such that subsequent queries on the keywords may retrieve the inspection data; wherein the inspection tool comprises: a borescope, ultrasound device, radiography equipment, camera, x-ray inspection device, eddy current device, or any combination thereof; and wherein the inspection instrument comprises: a computing device communicatively coupled to the inspection tool. | 7. A method, comprising: analyzing, using a computer processor, an inspection audio recording for keywords associated with an inspection, by: recording, during the inspection, using the at least one of an inspection tool and an inspection instrument communicatively coupled to the inspection tool, the inspection audio recording, wherein the inspection audio recording comprises audible annotations comprising comments of the inspection from an inspector performing the inspection, the comments comprising data minable keywords related to the inspection; sending, using the at least one of the inspection tool and the inspection instrument, the inspection audio recording to a cloud-based voice recognition service to data mine the inspection audio recording for the keywords; and obtaining, using the at least one of the inspection tool and the inspection instrument, the keywords from the voice recognition service; associating, using the at least one of the inspection tool and the inspection instrument, the keywords as metadata for inspection data acquired in time proximity to the audio recording, by the inspection tool; and storing the inspection data with the associated keywords such that subsequent queries on the keywords may retrieve the inspection data; wherein the inspection tool comprises: a borescope, ultrasound device, radiography equipment, camera, x-ray inspection device, eddy current device, or any combination thereof; and wherein the inspection instrument comprises: a computing device communicatively coupled to the inspection tool. 9. The method of claim 7 , wherein the inspection audio recording is analyzed using a jargon dictionary specific to a manufacturer, an object being inspected, an inspection type, a maintenance facility, or any combination thereof. | 0.5 |
8,200,584 | 1 | 4 | 1. A computer-implemented web-based system for advertising and promoting career opportunities, said system including a server computer communicatively coupled to at least one other computer, said server computer including multimedia transmission means, and said server computer providing to said at least one other computer, a computer displayable holistic multimedia overview of the career opportunity and life in the business location so that a job seeker may make an informed decision, said holistic multimedia overview comprising a menu of a plurality of user-selectable sections, in viewing order, said sections presenting multimedia, including streaming video, graphics and text concerning a service area topic and a career topic, the service area topic including multimedia relating to a geographic service area for the career opportunity, local schools, local businesses and local lifestyle attractions, including recreation, entertainment and shopping attractions, and the career topic including multimedia relating to facilities, and streaming video, photographs and testimonials of professionals associated with the business and in the service area and interviews with said professionals said system further comprising a subsystem for creating a posting for a career opportunity, said subsystem including a computer-executable interactive module adapted to request input of multimedia for the job posting, said multimedia including content concerning a geographic service area for the career, photographs of and information about service area leaders and information about service area organizations, said interactive module being further adapted to create the job posting using inputted multimedia, said interactive module being further adapted for network access. | 1. A computer-implemented web-based system for advertising and promoting career opportunities, said system including a server computer communicatively coupled to at least one other computer, said server computer including multimedia transmission means, and said server computer providing to said at least one other computer, a computer displayable holistic multimedia overview of the career opportunity and life in the business location so that a job seeker may make an informed decision, said holistic multimedia overview comprising a menu of a plurality of user-selectable sections, in viewing order, said sections presenting multimedia, including streaming video, graphics and text concerning a service area topic and a career topic, the service area topic including multimedia relating to a geographic service area for the career opportunity, local schools, local businesses and local lifestyle attractions, including recreation, entertainment and shopping attractions, and the career topic including multimedia relating to facilities, and streaming video, photographs and testimonials of professionals associated with the business and in the service area and interviews with said professionals said system further comprising a subsystem for creating a posting for a career opportunity, said subsystem including a computer-executable interactive module adapted to request input of multimedia for the job posting, said multimedia including content concerning a geographic service area for the career, photographs of and information about service area leaders and information about service area organizations, said interactive module being further adapted to create the job posting using inputted multimedia, said interactive module being further adapted for network access. 4. A system according to claim 1 , said sections further presenting multimedia concerning a key personnel topic, the key personnel topic including multimedia relating to personnel relevant to the career opportunity. | 0.911885 |
8,713,586 | 18 | 19 | 18. The computer-readable storage medium of claim 16 , wherein scanning the web page to identify the external code referenced by the web page comprises: scanning the HTML code of the web page; scanning the at least one embedded code block; scanning the at least one import file; and identifying one or more entry points included in at least one of the HTML code, the at least one embedded code block, and the at least one import file. | 18. The computer-readable storage medium of claim 16 , wherein scanning the web page to identify the external code referenced by the web page comprises: scanning the HTML code of the web page; scanning the at least one embedded code block; scanning the at least one import file; and identifying one or more entry points included in at least one of the HTML code, the at least one embedded code block, and the at least one import file. 19. The computer-readable storage medium of claim 18 , wherein the identified one or more entry points comprise at least one of HTML tags that incorporate JAVASCRIPT statements, actions associated with web page elements, or document object model (DOM) events. | 0.5 |
10,102,359 | 9 | 10 | 9. A method comprising: at an electronic device: while the device is in a locked state at a first time, receiving non-voice authentication information from a user; in response to receiving valid authentication information, transitioning the device to an unlocked state; while in the unlocked state, receiving a first speech input from the user; generating a voiceprint based on a voice sample of the first speech input; while the device is in a locked state at a second time, receiving a second speech input, the second speech input including a command associated with a restricted feature of the device; determining a degree of match between the generated voiceprint and the second speech input; and upon determining that the degree of match is above a predetermined threshold, executing the command including invoking the restricted feature of the device, wherein the command is executed while the device is in the locked state, and wherein the command is a request to perform an actin other than unlocking the device. | 9. A method comprising: at an electronic device: while the device is in a locked state at a first time, receiving non-voice authentication information from a user; in response to receiving valid authentication information, transitioning the device to an unlocked state; while in the unlocked state, receiving a first speech input from the user; generating a voiceprint based on a voice sample of the first speech input; while the device is in a locked state at a second time, receiving a second speech input, the second speech input including a command associated with a restricted feature of the device; determining a degree of match between the generated voiceprint and the second speech input; and upon determining that the degree of match is above a predetermined threshold, executing the command including invoking the restricted feature of the device, wherein the command is executed while the device is in the locked state, and wherein the command is a request to perform an actin other than unlocking the device. 10. The method of claim 9 , further comprising: upon determining that the degree of match is not above a predetermined threshold, forgo executing the command. | 0.5 |
7,711,547 | 1 | 3 | 1. A method for associating words and word strings in a language comprising: providing a collection of documents, wherein said collection includes at least one document; receiving from a user a word or word string query to be analyzed; searching, by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning documents containing said words or word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List and creating a Left Anchor List comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in a collection of documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List and creating a Right Anchor List comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency; and ranking results based on the number of different Anchor Lists on which the result appears. | 1. A method for associating words and word strings in a language comprising: providing a collection of documents, wherein said collection includes at least one document; receiving from a user a word or word string query to be analyzed; searching, by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning documents containing said words or word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List and creating a Left Anchor List comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in a collection of documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List and creating a Right Anchor List comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency; and ranking results based on the number of different Anchor Lists on which the result appears. 3. The method of claim 1 , wherein ranking results includes adding a total frequency of each word or word string occurring in said Left Anchor Lists to a total frequency of said word or word string occurring in said Right Anchor Lists, for each word or word string occurring in both the Left Anchor List and the Right Anchor List. | 0.5 |
6,045,277 | 1 | 5 | 1. A tape printing apparatus, comprising: print format-designating means for selecting one kind of print format as a designated print format, from a plurality of kinds of print formats, each print format corresponding to instructions initially stored in a memory; entry means for arranging entered characters to form a character string; print image-forming means for forming print image data by editing said character string based on the instructions for said designated print format; printing means for printing on a recording medium in the form of a tape being fed, based on said print image data, means for arranging said characters of said character string in a direction other than a longitudinal direction of said recording medium in the form of a tape; and changing an orientation of each of said characters in a direction different from an orientation thereof originally set in said character string. | 1. A tape printing apparatus, comprising: print format-designating means for selecting one kind of print format as a designated print format, from a plurality of kinds of print formats, each print format corresponding to instructions initially stored in a memory; entry means for arranging entered characters to form a character string; print image-forming means for forming print image data by editing said character string based on the instructions for said designated print format; printing means for printing on a recording medium in the form of a tape being fed, based on said print image data, means for arranging said characters of said character string in a direction other than a longitudinal direction of said recording medium in the form of a tape; and changing an orientation of each of said characters in a direction different from an orientation thereof originally set in said character string. 5. A tape printing apparatus according to claim 1, wherein said plurality of print formats include a portrait horizontal writing print format, and wherein when said portrait horizontal writing print format is selected as said designated print format, said print image-forming means forms said print image data by making a lateral direction of character image data corresponding to said each character of said character string in agreement with a direction corresponding to a transverse direction of said recording medium in the form of a tape, and arranging said character image data in said transverse direction of said recording medium in the form of a tape. | 0.641694 |
9,372,844 | 1 | 3 | 1. A computer implemented method for displaying on a display surface an automatically generated graphical display using a symbolic annotation language, the method comprising: analyzing a business process flow genus to form an alphabet of a compact symbolic language representing a plurality of semantics from a number of symbols, wherein the analyzing comprises determining a representative set of process flow description attributes; capturing a business process flow using one or more symbols of the number of symbols, the business process flow being a species of the business process flow genus, wherein capturing the business process flow using the one or more symbols of the number of symbols comprises mapping the representative set of process flow description attributes into the compact symbolic language while observing a constraint and analyzing characteristics of the business process flow, the business process flow being a species of the business process flow genus; testing the captured business process flow using a schematic of the business process flow; mapping the one or more symbols of the number of symbols to a plurality of constructs of a markup language, one or more constructs of the plurality of constructs to be rendered in a graphical display, wherein mapping the one or more symbols of the number of symbols to the plurality of constructs of the markup language comprises mapping the one or more symbols of the compact symbolic language to a plurality of instances of schematic symbols, mapping the plurality of instances of schematic symbols to the plurality of constructs of the markup language, and mapping the plurality of constructs of the markup language to a plurality of computer-automated processes; and automatically generating and displaying, on a display surface, the business process flow in a graphical user interface using the symbolic annotation language wherein displaying the business process flow is based on the plurality of computer-automated processes. | 1. A computer implemented method for displaying on a display surface an automatically generated graphical display using a symbolic annotation language, the method comprising: analyzing a business process flow genus to form an alphabet of a compact symbolic language representing a plurality of semantics from a number of symbols, wherein the analyzing comprises determining a representative set of process flow description attributes; capturing a business process flow using one or more symbols of the number of symbols, the business process flow being a species of the business process flow genus, wherein capturing the business process flow using the one or more symbols of the number of symbols comprises mapping the representative set of process flow description attributes into the compact symbolic language while observing a constraint and analyzing characteristics of the business process flow, the business process flow being a species of the business process flow genus; testing the captured business process flow using a schematic of the business process flow; mapping the one or more symbols of the number of symbols to a plurality of constructs of a markup language, one or more constructs of the plurality of constructs to be rendered in a graphical display, wherein mapping the one or more symbols of the number of symbols to the plurality of constructs of the markup language comprises mapping the one or more symbols of the compact symbolic language to a plurality of instances of schematic symbols, mapping the plurality of instances of schematic symbols to the plurality of constructs of the markup language, and mapping the plurality of constructs of the markup language to a plurality of computer-automated processes; and automatically generating and displaying, on a display surface, the business process flow in a graphical user interface using the symbolic annotation language wherein displaying the business process flow is based on the plurality of computer-automated processes. 3. The method of claim 1 , wherein the compact symbolic language comprises only combinations of UNICODE characters. | 0.775391 |
8,275,785 | 1 | 9 | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. 9. The method of claim 1 , wherein said code, when executed, includes information from network browser cookies as a search parameter. | 0.581761 |
7,490,099 | 12 | 13 | 12. One or more computer readable media storing computer executable instructions to perform a method for performing rapid application development, said method comprising: a) creating a data dependency path based on a data model representing units of meaning and their relationships, by; analyzing the data model stored to identify a data view of the data model, said data model comprising a propositional structure representing a grammar having a plurality of parts of speech, said propositional structure having 28 predefined data relations comprising identifiers, modifiers, and descriptors related using predefined logical operators; automatically creating the data dependency path based on the identified data view; and storing data identifying the data dependency path; and b) creating an input/output user interface based on the data dependency path. | 12. One or more computer readable media storing computer executable instructions to perform a method for performing rapid application development, said method comprising: a) creating a data dependency path based on a data model representing units of meaning and their relationships, by; analyzing the data model stored to identify a data view of the data model, said data model comprising a propositional structure representing a grammar having a plurality of parts of speech, said propositional structure having 28 predefined data relations comprising identifiers, modifiers, and descriptors related using predefined logical operators; automatically creating the data dependency path based on the identified data view; and storing data identifying the data dependency path; and b) creating an input/output user interface based on the data dependency path. 13. The computer readable media of claim 12 , wherein step b) comprises: receiving user input selecting the data dependency path; receiving user input selecting a plurality of data items within the data dependency path; and generating the user interface comprising the selected plurality of data items. | 0.5 |
9,014,479 | 1 | 2 | 1. An image processing system that determines an orientation for a text-containing region of an image, the image processing system comprising: one or more processors; one or more electronic memories; one or more mass-storage devices; an orientation-marker pattern set stored in one or more of the one or more electronic data storage devices, wherein the orientation-marker pattern set comprises two or more patterns corresponding to two or more considered orientations of one or more orientation-marker characters; and computer instructions stored in the one or more electronic data storage devices that control the image processing system to receive an image with a text-containing region, store a representation of the text-containing region in one or more of the one or more electronic memories, identify one or more text-character images within the text-containing region that match an orientation-marker pattern from the orientation-marker pattern set, and determine an orientation for the text-containing region from the orientations of the one or more text-character images that match the orientation-marker pattern. | 1. An image processing system that determines an orientation for a text-containing region of an image, the image processing system comprising: one or more processors; one or more electronic memories; one or more mass-storage devices; an orientation-marker pattern set stored in one or more of the one or more electronic data storage devices, wherein the orientation-marker pattern set comprises two or more patterns corresponding to two or more considered orientations of one or more orientation-marker characters; and computer instructions stored in the one or more electronic data storage devices that control the image processing system to receive an image with a text-containing region, store a representation of the text-containing region in one or more of the one or more electronic memories, identify one or more text-character images within the text-containing region that match an orientation-marker pattern from the orientation-marker pattern set, and determine an orientation for the text-containing region from the orientations of the one or more text-character images that match the orientation-marker pattern. 2. The image processing system of claim 1 wherein the number of orientation-marker patterns in the orientation-marker-pattern set is less than 10% of the total number of patterns used to represent text symbols. | 0.883073 |
8,521,581 | 1 | 7 | 1. A computer-implemented method comprising: transmitting, by a computer and to a device, a first SMS message for an advertisement, the first SMS message comprising text outlining navigation instructions for retrieval of one or more text content options available for delivery to the device, each navigation instruction including a corresponding text response for transmission from the device to the computer for requesting delivery of one of the one or more text content options, each text response corresponding to one of the text content options, each text content option being associated with the advertisement; receiving, by the computer, a response from the device, the response comprising a second SMS message that includes a text response that corresponds to a selected navigation instruction; selecting, by the computer, a first text message from among text messages based upon the text response included in the second SMS message, each of the text messages comprising text content associated with one of the one or more text content options, the first text message including text content associated with the text content option that corresponds to the text response included in the second SMS message; and transmitting, by the computer, a third SMS message to the device, the third SMS message including the text content included in the first text message. | 1. A computer-implemented method comprising: transmitting, by a computer and to a device, a first SMS message for an advertisement, the first SMS message comprising text outlining navigation instructions for retrieval of one or more text content options available for delivery to the device, each navigation instruction including a corresponding text response for transmission from the device to the computer for requesting delivery of one of the one or more text content options, each text response corresponding to one of the text content options, each text content option being associated with the advertisement; receiving, by the computer, a response from the device, the response comprising a second SMS message that includes a text response that corresponds to a selected navigation instruction; selecting, by the computer, a first text message from among text messages based upon the text response included in the second SMS message, each of the text messages comprising text content associated with one of the one or more text content options, the first text message including text content associated with the text content option that corresponds to the text response included in the second SMS message; and transmitting, by the computer, a third SMS message to the device, the third SMS message including the text content included in the first text message. 7. The method of claim 1 , further comprising: storing a path associated with the device to a stored path data store based upon each text message served to the device; retrieving stored paths from a data store; and transmitting statistics associated with stored paths to an advertiser. | 0.628906 |
9,430,495 | 16 | 18 | 16. The computer program product of claim 15 , wherein generate the score for the entry from the plurality of entries comprises: align terms in the entry with terms in the additional entry; compare each term in the entry with a corresponding aligned term in the additional entry; determine a cost associated with each term in the entry based at least in part on a difference between the term in the entry and the corresponding aligned term in the additional entry; generate a modified cost for one or more terms identified as trending terms by discounting a cost associated with a term identified as a trending term; and generate the score based at least in part on the costs and the modified costs. | 16. The computer program product of claim 15 , wherein generate the score for the entry from the plurality of entries comprises: align terms in the entry with terms in the additional entry; compare each term in the entry with a corresponding aligned term in the additional entry; determine a cost associated with each term in the entry based at least in part on a difference between the term in the entry and the corresponding aligned term in the additional entry; generate a modified cost for one or more terms identified as trending terms by discounting a cost associated with a term identified as a trending term; and generate the score based at least in part on the costs and the modified costs. 18. The computer program product of claim 16 , wherein determine the cost associated with each term in the entry based at least in part on the difference between the term in the entry and the corresponding aligned term in the additional entry comprises: associate a weight with each term in the entry based at least in part on a global frequency associated with a term in the entry and a local frequency associated with the term in the entry; associate a weight with each term in the additional entry based at least in part on a global frequency associated with a term in the additional entry and a local frequency associated with the term in the additional entry; and determine a cost associated one or more terms in the entry differing from one or more entries in the additional entry based at least in part on the weights associated with terms in the entry and weights associated with terms in the additional entry. | 0.5 |
9,830,311 | 7 | 8 | 7. A computing device comprising: at least one processor; and memory configured to store instructions that, when executed, cause the at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; receive a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determine, based at least in part on both physical cost values from a spatial model, and lexical cost values from a language model at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determine, based at least in part on the at least one predicted current word that is the previous word, at least one predicted next word that follows the at least one predicted current word; and output, for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. | 7. A computing device comprising: at least one processor; and memory configured to store instructions that, when executed, cause the at least one processor to: output, for display, a graphical keyboard comprising a plurality of keys; receive a plurality of indications of input, each respective indication of input from the plurality of indications of input corresponding to a respective location of the graphical keyboard; and for each respective indication of input from the plurality of indications of input, incrementally: determine, based at least in part on both physical cost values from a spatial model, and lexical cost values from a language model at least one predicted current word based on a set of characters that correspond to the plurality of indications of input, wherein the spatial model comprises at least one respective distribution of touch points that corresponds to at least one respective key of the graphical keyboard, and wherein the at least one predicted current word is determined based on a physical cost value from the spatial model that is modified by a lexical cost value from the language model, the physical cost value representing a first likelihood that the plurality of indications of input correspond to the set of characters, and the lexical cost value representing a second likelihood that the set of characters are included in any word in a lexicon of the language model; determine, based at least in part on the at least one predicted current word that is the previous word, at least one predicted next word that follows the at least one predicted current word; and output, for display, the at least one predicted current word and the at least one predicted next word as a soft commit word in a text entry area of a graphical user interface by at least: outputting, for display in a first visual style, characters of the at least one predicted current word and the at least one predicted next word that are from the set of characters that correspond to the plurality of indications of input; and outputting, for display in a second visual style that is different than the first visual style, characters of the at least one predicted current word and the at least one predicted next word that are not from the set of characters that correspond to the plurality of indications of input. 8. The computing device of claim 7 , wherein the instructions, when executed, further cause the at least one processor to determine a plurality of sets of one or more predicted current words, each respective set of one or more predicted current words from the plurality of sets of one or more predicted current words being based on a respective set of characters that correspond to the plurality of indications of input. | 0.549356 |
10,146,773 | 1 | 9 | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. | 1. A method using one or more computer processors, comprising: providing, using the one or more computer processors, a first message in a first language to a first transformation module in a sequence of computer-implemented transformation modules, each transformation module comprising executable instructions configured to be executed by the one or more computer processors for performing message transformation operations, wherein each subsequent transformation module in the sequence accepts, as input, an output of a preceding transformation module in the sequence and provides, as output, a respective transformed message, wherein at least one transformation module in the sequence identifies at least a portion of the output of the at least one transformation module as not to be transformed by subsequent transformation modules in the sequence, and wherein the output of a final transformation module in the sequence comprises a transformed message in the first language; and querying, using the one or more computer processors, a computer data store for a translation of the transformed message in a second language. 9. The method of claim 1 , wherein one or more transformation modules (i) identify a profane word or phrase in the first message and (ii) replace the profane word or phrase with a non-profane word or phrase or remove the profane word or phrase. | 0.504065 |
7,877,410 | 1 | 3 | 1. A system for providing private inference control, comprising: at least a central processing unit; and at least a memory coupled to the central processing unit; the system further comprising: a query count and a secure database comprising a plurality of records with each record comprising a plurality of attributes, wherein a set of the attributes form one or more inference channels; a regular data structure comprising a set of ciphertext keys, which each relate to one such attribute and record in the secure database; a query processor to choose a seed for a pseudorandom function and a secret key for non-malleable encryption; a query generator to specify a query by providing indices identifying one such record and attribute and a secure function evaluation circuit to execute a secure function evaluation dependent upon the inference channels, the seed, the secret key, the query count, and the set of ciphertext keys, wherein an output from the secure function evaluation comprises the pseudorandom function and an updated set of ciphertext keys subject to sum-consistency of the set of ciphertext keys and a non-inference enabling query; a table of entries formed by combining each of the attributes for each of the records of the database with an output from the pseudorandom function as applied to the seed and the indices, wherein the entry from the table corresponding to the indices is provided. | 1. A system for providing private inference control, comprising: at least a central processing unit; and at least a memory coupled to the central processing unit; the system further comprising: a query count and a secure database comprising a plurality of records with each record comprising a plurality of attributes, wherein a set of the attributes form one or more inference channels; a regular data structure comprising a set of ciphertext keys, which each relate to one such attribute and record in the secure database; a query processor to choose a seed for a pseudorandom function and a secret key for non-malleable encryption; a query generator to specify a query by providing indices identifying one such record and attribute and a secure function evaluation circuit to execute a secure function evaluation dependent upon the inference channels, the seed, the secret key, the query count, and the set of ciphertext keys, wherein an output from the secure function evaluation comprises the pseudorandom function and an updated set of ciphertext keys subject to sum-consistency of the set of ciphertext keys and a non-inference enabling query; a table of entries formed by combining each of the attributes for each of the records of the database with an output from the pseudorandom function as applied to the seed and the indices, wherein the entry from the table corresponding to the indices is provided. 3. A system according to claim 1 , further comprising: a set of reject counts, wherein a further output is generated from the secure function evaluation comprising the reject counts. | 0.705502 |
8,983,997 | 1 | 9 | 1. An information processing apparatus comprising: a setting unit that sets a search character string; a searching unit that searches information including the set search character string; and a determining unit that extracts a co-occurrence character string candidate group among all partial character strings appearing in a plurality of pieces of the information obtained as a search result, wherein the determining unit determines a co-occurrence character string from the co-occurrence character string candidate group, wherein the setting unit sets one or more contrast character strings to characterize the search character string, wherein the one or more contrast character strings is in contrast with the search character string, and wherein the determining unit determines the co-occurrence character string, on the basis of the comparison result of the appearance frequency of each co-occurrence character string candidate forming the co-occurrence character string candidate, group in the information including the search character string and the appearance frequency of each co-occurrence character string candidate in information including the contrast character string. | 1. An information processing apparatus comprising: a setting unit that sets a search character string; a searching unit that searches information including the set search character string; and a determining unit that extracts a co-occurrence character string candidate group among all partial character strings appearing in a plurality of pieces of the information obtained as a search result, wherein the determining unit determines a co-occurrence character string from the co-occurrence character string candidate group, wherein the setting unit sets one or more contrast character strings to characterize the search character string, wherein the one or more contrast character strings is in contrast with the search character string, and wherein the determining unit determines the co-occurrence character string, on the basis of the comparison result of the appearance frequency of each co-occurrence character string candidate forming the co-occurrence character string candidate, group in the information including the search character string and the appearance frequency of each co-occurrence character string candidate in information including the contrast character string. 9. The information processing apparatus according to claim 1 , wherein the determining unit determines the co-occurrence character string from the co-occurrence character string candidate group on the basis of the extracted co-occurrence character string candidate group and kinds of characters used in characters before and after the co-occurrence character string candidate group. | 0.55787 |
7,668,873 | 1 | 6 | 1. A computer-implemented method for generating an accessible metadata store in a source document, the method comprising: generating a source document on a source application, wherein the source document includes surface view data that is exposed on a presentation layer when the source document is rendered and metadata that is unexposed on the presentation layer when the source document is rendered; structuring the metadata of the source document into a mark-up language (ML) document; storing the ML document that includes the metadata of the source document in the metadata store separate from the surface view data of the source document, wherein the metadata store and the surface view data are stored in the source document; attaching an ML schema file to the ML document that includes the metadata of the source document, wherein the ML schema file is stored in the metadata store of the source document; exposing application programming interfaces (APIs) to the metadata store, wherein the APIs provide other applications having application types different than the source application access to the ML document that includes the metadata of the source document via object models of the other applications, wherein the exposed APIs for the metadata store permit the other applications to: load the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, monitor modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, modify the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, when a modification of the metadata is received at the metadata store, receive a change notification from the metadata store of a modification to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, and undo modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data. | 1. A computer-implemented method for generating an accessible metadata store in a source document, the method comprising: generating a source document on a source application, wherein the source document includes surface view data that is exposed on a presentation layer when the source document is rendered and metadata that is unexposed on the presentation layer when the source document is rendered; structuring the metadata of the source document into a mark-up language (ML) document; storing the ML document that includes the metadata of the source document in the metadata store separate from the surface view data of the source document, wherein the metadata store and the surface view data are stored in the source document; attaching an ML schema file to the ML document that includes the metadata of the source document, wherein the ML schema file is stored in the metadata store of the source document; exposing application programming interfaces (APIs) to the metadata store, wherein the APIs provide other applications having application types different than the source application access to the ML document that includes the metadata of the source document via object models of the other applications, wherein the exposed APIs for the metadata store permit the other applications to: load the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, monitor modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, modify the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, when a modification of the metadata is received at the metadata store, receive a change notification from the metadata store of a modification to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, and undo modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data. 6. The computer-implemented method of claim 1 , wherein the exposed APIs permit other applications to simultaneously: load the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, monitor modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, modify the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, when a modification of the metadata is received at the metadata store receive a change notification from the metadata store of a modification to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data, and undo modifications to the metadata, stored in the metadata store that is stored in the source document, independent of the surface view data. | 0.5 |
8,255,813 | 14 | 15 | 14. The computer system of claim 12 , wherein the task controller is configured to bypass the temporary storage by committing the current business object state to the database. | 14. The computer system of claim 12 , wherein the task controller is configured to bypass the temporary storage by committing the current business object state to the database. 15. The computer system of claim 14 , wherein the task controller is further configured to perform the bypass while maintaining another business object state of the business object in the temporary storage. | 0.5 |
8,386,262 | 15 | 20 | 15. A computer-readable storage device having instructions stored which, when executed on a computing device, perform a method comprising: partitioning a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; generating a semantic representation using the dialog act and the object; and recursively extending the semantic representation by qualifying the object in each of the independent clauses. | 15. A computer-readable storage device having instructions stored which, when executed on a computing device, perform a method comprising: partitioning a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; generating a semantic representation using the dialog act and the object; and recursively extending the semantic representation by qualifying the object in each of the independent clauses. 20. The computer-readable storage device of claim 15 , wherein generating the semantic representation further comprises identifying relationships between the dialog act and the object. | 0.751351 |
9,792,355 | 8 | 9 | 8. A non-transitory, machine-readable medium that stores instructions, which, when performed by a machine, cause the machine to perform operations comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the identified metamodel semantic network. | 8. A non-transitory, machine-readable medium that stores instructions, which, when performed by a machine, cause the machine to perform operations comprising: accessing a first document; identifying one or more terms from a metamodel semantic network; identifying one or more terms from the metamodel semantic network that are also found in the first document, wherein the identification of the one or more terms from the metamodel semantic network comprises: identifying a user that created the first document; retrieving context information associated with the user; identifying business functional data associated with the context information; identifying, from a number of domains, the domain associated with the business functional data, each domain from the number of domains including a different grouping of terms; and selecting terms that are associated with the identified domain for the analysis; identifying a weighted frequency of occurrence in the first document for each of the one or more identified terms, each weighted frequency of occurrence being a count of occurrences of the corresponding term in the first document multiplied by a weight based on a length of the first document; and searching for another document having one or more weighted frequencies of occurrences that are within a predefined range of a corresponding weighted frequency of occurrence of the corresponding term in the first document, the other document having been previously analyzed using terms from the identified metamodel semantic network. 9. The non-transitory, machine-readable medium of claim 8 , wherein the operation of searching the other document comprises comparing each of the identified weighted frequencies of occurrences with the corresponding weighted frequency of occurrence. | 0.606013 |
8,490,196 | 1 | 7 | 1. A method for extending automated penetration testing of a target network comprising, the steps of: a. computing a scenario, wherein the step of computing the scenario comprises the steps of i. translating a workspace having at least one target computer in the target network, to a planning definition language; ii. translating penetration modules available in a penetration testing framework to the planning definition language; and iii. defining a goal in the target network and translating the goal into the planning definition language; b. building a knowledge database with information regarding the target network, properties of hosts in the network, parameters and running history of modules in the penetration testing framework; and c. running an attack plan solver module, wherein the attack plan solver module performs the steps of: i. running an attack planner using the scenario as input, to produce at least one attack plan that achieves the goal; and ii. executing actions defined in the at least one attack plan against the target network from the penetration testing framework. | 1. A method for extending automated penetration testing of a target network comprising, the steps of: a. computing a scenario, wherein the step of computing the scenario comprises the steps of i. translating a workspace having at least one target computer in the target network, to a planning definition language; ii. translating penetration modules available in a penetration testing framework to the planning definition language; and iii. defining a goal in the target network and translating the goal into the planning definition language; b. building a knowledge database with information regarding the target network, properties of hosts in the network, parameters and running history of modules in the penetration testing framework; and c. running an attack plan solver module, wherein the attack plan solver module performs the steps of: i. running an attack planner using the scenario as input, to produce at least one attack plan that achieves the goal; and ii. executing actions defined in the at least one attack plan against the target network from the penetration testing framework. 7. The method of claim 1 wherein an end user defines the goal to be achieved by the system. | 0.923401 |
8,539,359 | 39 | 53 | 39. The machine system of claim 26 and further comprising: an automated transmitter that transmits a plurality of Current Focus indicating records (CFi records) to a network indicating relatively recent, focus-related activities or focus-related states of the first user, where the transmitted CFi records include: a report indicating one or more particular machine usage activities of the first user, and a report indicating one or more biometric or mental states of the first user. | 39. The machine system of claim 26 and further comprising: an automated transmitter that transmits a plurality of Current Focus indicating records (CFi records) to a network indicating relatively recent, focus-related activities or focus-related states of the first user, where the transmitted CFi records include: a report indicating one or more particular machine usage activities of the first user, and a report indicating one or more biometric or mental states of the first user. 53. The machine system of claim 39 wherein at least one of the transmitted CFi records includes: an indication of situational settings surrounding a location of at least of one of the first user or of a portion of the machine system that sensed a physical attribute from which the indicated one or more particular machine usage activities of the first user or one or more biometric or mental states of the first user were derived. | 0.893617 |
5,561,446 | 14 | 17 | 14. A method according to claim 11, wherein: said plurality of digitally stored forms are standard medical forms for patient diagnoses, procedures, services, laboratory tests, and prescriptions. | 14. A method according to claim 11, wherein: said plurality of digitally stored forms are standard medical forms for patient diagnoses, procedures, services, laboratory tests, and prescriptions. 17. A method according to claim 14, wherein: said reference code includes an identification of a particular human being. | 0.5 |
9,026,425 | 21 | 22 | 21. A translation system adapted to a domain of interest comprising: memory which stores: a bilingual probability for each of a set of biphrases estimated on an associated out-of-domain parallel corpus comprising source and target strings, each biphrase comprising a text fragment in the source language and a text fragment in a target language; and a monolingual probability for each of a set of text fragments estimated on an associated in-domain monolingual corpus, each of the text fragments occurring in at least one of the biphrases in the set of biphrases; memory which stores: a candidate translation generator for generating a set of candidate translations of a source text string, the source string comprising a sequence of source words in a source language, each candidate translation comprising a sequence of target words in a target language; a translation evaluation component for identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: the respective bilingual probabilities for the source and target text fragments of the source text string and candidate translation, and the respective monolingual probabilities for text fragments of at least one of the source text string and candidate translation, the domain adapted feature comprising at least one domain adapted lexical feature selected from: lex β‘ ( s _ β t _ ) = β i = 1 n β’ β’ 1 ο { j β ( i , j ) β a } ο β’ β ( i , j ) β a β’ w out β‘ ( t j β s i ) β’ w in β‘ ( s i ) β k β’ w out β‘ ( t j β s k ) β’ w in β‘ ( s k ) ; ( 9 ) and lex β‘ ( t _ β s _ ) = β j = 1 n β’ β’ 1 ο { i β ( i , j ) β a } ο β’ β ( i , j ) β a β’ w out β‘ ( s i β t j ) β’ w in β‘ ( t j ) β l β’ w out β‘ ( s i β t l ) β’ w in β‘ ( t l ) ; ( 10 ) and a processor which executes the instructions. | 21. A translation system adapted to a domain of interest comprising: memory which stores: a bilingual probability for each of a set of biphrases estimated on an associated out-of-domain parallel corpus comprising source and target strings, each biphrase comprising a text fragment in the source language and a text fragment in a target language; and a monolingual probability for each of a set of text fragments estimated on an associated in-domain monolingual corpus, each of the text fragments occurring in at least one of the biphrases in the set of biphrases; memory which stores: a candidate translation generator for generating a set of candidate translations of a source text string, the source string comprising a sequence of source words in a source language, each candidate translation comprising a sequence of target words in a target language; a translation evaluation component for identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: the respective bilingual probabilities for the source and target text fragments of the source text string and candidate translation, and the respective monolingual probabilities for text fragments of at least one of the source text string and candidate translation, the domain adapted feature comprising at least one domain adapted lexical feature selected from: lex β‘ ( s _ β t _ ) = β i = 1 n β’ β’ 1 ο { j β ( i , j ) β a } ο β’ β ( i , j ) β a β’ w out β‘ ( t j β s i ) β’ w in β‘ ( s i ) β k β’ w out β‘ ( t j β s k ) β’ w in β‘ ( s k ) ; ( 9 ) and lex β‘ ( t _ β s _ ) = β j = 1 n β’ β’ 1 ο { i β ( i , j ) β a } ο β’ β ( i , j ) β a β’ w out β‘ ( s i β t j ) β’ w in β‘ ( t j ) β l β’ w out β‘ ( s i β t l ) β’ w in β‘ ( t l ) ; ( 10 ) and a processor which executes the instructions. 22. The system of claim 21 , further comprising an in domain language model stored in memory, the translation evaluation component identifying an optimal translation based also on the language model. | 0.5 |
9,171,478 | 17 | 18 | 17. The apparatus of claim 16 , wherein capturing the history of performance and correctness metrics further comprises: recording performance characteristics for each of the plurality of algorithms; and generating a performance profile for each of the plurality of algorithms for each question category. | 17. The apparatus of claim 16 , wherein capturing the history of performance and correctness metrics further comprises: recording performance characteristics for each of the plurality of algorithms; and generating a performance profile for each of the plurality of algorithms for each question category. 18. The apparatus of claim 17 , wherein the performance characteristics comprise heap sizes, CPU utilization, memory usage, the execution time of an algorithm, file input and output access, or write speeds. | 0.5 |
7,593,575 | 1 | 3 | 1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. | 1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. 3. The method of claim 1 , wherein at least one writing profile representation is obtained from a valid document. | 0.78839 |
9,460,068 | 3 | 4 | 3. The system of claim 2 , wherein the operations further comprise creating a paragraph using an input device, a gesture or both an input device and a gesture, thereby, adding space between the digital media files in a form of a new paragraph. | 3. The system of claim 2 , wherein the operations further comprise creating a paragraph using an input device, a gesture or both an input device and a gesture, thereby, adding space between the digital media files in a form of a new paragraph. 4. The system of claim 3 , wherein creating the paragraph includes adding space in the NMO environment for a headline. | 0.68617 |
8,595,697 | 7 | 9 | 7. A computer program product comprising a computer usable storage medium storing computer usable program code for configuring a test plan for serialization, the computer program product comprising: computer usable program code for selecting a template of the test plan through a graphical user interface of a test plan markup generation module executing in memory by a processor of a host computer; computer usable program code for extracting a table of contents from the selected template, the table of contents including at least one reference to at least one test case; computer usable program code for transforming at least one portion of the table of contents including the at least one test case into a markup language representation of the selected template of the test plan computer usable program code for retrieving a revision level for the selected template; and, computer usable program code for inserting the retrieved revision level into the markup language representation. | 7. A computer program product comprising a computer usable storage medium storing computer usable program code for configuring a test plan for serialization, the computer program product comprising: computer usable program code for selecting a template of the test plan through a graphical user interface of a test plan markup generation module executing in memory by a processor of a host computer; computer usable program code for extracting a table of contents from the selected template, the table of contents including at least one reference to at least one test case; computer usable program code for transforming at least one portion of the table of contents including the at least one test case into a markup language representation of the selected template of the test plan computer usable program code for retrieving a revision level for the selected template; and, computer usable program code for inserting the retrieved revision level into the markup language representation. 9. The computer program product of claim 7 , further comprising computer usable program code for serializing the markup language representation of the selected template for transmission over a computer communications network. | 0.747191 |
8,301,633 | 3 | 4 | 3. The method of claim 2 , further comprising: obtaining a semantic representation of the information passage, the semantic representation of the information passage comprising one or more semantic the substructures, each semantic substructure comprising at least one predicate-argument relation; generating the semantic index token from at least one of the semantic substructures; and generating the semantic index key term including the semantic index token. | 3. The method of claim 2 , further comprising: obtaining a semantic representation of the information passage, the semantic representation of the information passage comprising one or more semantic the substructures, each semantic substructure comprising at least one predicate-argument relation; generating the semantic index token from at least one of the semantic substructures; and generating the semantic index key term including the semantic index token. 4. The method of claim 3 , further comprising: obtaining a semantic representation of the search query, the semantic representation of the search query comprising one or more semantic substructures, wherein each semantic substructure comprises at least one predicate-argument relation; generating the semantic query token based upon at least one of the semantic substructures for the search query; and generating the semantic query key term comprising at least one semantic query token. | 0.5 |
8,224,912 | 1 | 14 | 1. A method to use dynamically prioritized electronic communications to establish and analyze organization social network maps, the method comprising the steps of: selecting a dynamically prioritized electronic communication dataset based on network boundaries and contextual framework; establishing a one-way trusted relationship score between an electronic communication recipient and sender; establishing a one-way trusted relationship score between an electronic communication sender and recipient; establishing a two-way trusted relationship score between two communicating entities; establishing an atomic unit of entities based on a decreasing order of at least one of the one-way trusted relationship score and the two-way trusted relationship score; establishing a social network based on arranging atomic units and entities based on one or more of an electronic communication prioritization score, a trusted relationship score, and an electronic communication productivity and collaboration metric; establishing top trusted entities for a given keyword or a set of keywords; establishing a secondary trusted network of entities for at least one of the top trusted entities based on the given keyword or the set of keywords; and wherein the entities are electronic communication senders and electronic communication recipients. | 1. A method to use dynamically prioritized electronic communications to establish and analyze organization social network maps, the method comprising the steps of: selecting a dynamically prioritized electronic communication dataset based on network boundaries and contextual framework; establishing a one-way trusted relationship score between an electronic communication recipient and sender; establishing a one-way trusted relationship score between an electronic communication sender and recipient; establishing a two-way trusted relationship score between two communicating entities; establishing an atomic unit of entities based on a decreasing order of at least one of the one-way trusted relationship score and the two-way trusted relationship score; establishing a social network based on arranging atomic units and entities based on one or more of an electronic communication prioritization score, a trusted relationship score, and an electronic communication productivity and collaboration metric; establishing top trusted entities for a given keyword or a set of keywords; establishing a secondary trusted network of entities for at least one of the top trusted entities based on the given keyword or the set of keywords; and wherein the entities are electronic communication senders and electronic communication recipients. 14. The method of claim 1 , further including the step of plotting the social network map, wherein a Y-axis is the prioritization score, an X-axis is a size of a bubble (minimum to maximum) established based on at least one of a trust relationship score (two-way or one-way), an electronic communication productivity metric, and an electronic communication collaboration metric. | 0.644068 |
9,703,792 | 10 | 11 | 10. The method of claim 1 , wherein the data files are multi-media content including at least one of an audio, a video, a still image, or a text. | 10. The method of claim 1 , wherein the data files are multi-media content including at least one of an audio, a video, a still image, or a text. 11. The method of claim 10 , wherein the plurality of formats of the data files include at least two of (a) Microsoft Word files, (b) Microsoft Excel files, (c) Microsoft PowerPoint files, (d) JPG files, (e) PDF files, (f) MOV files, (g) Keynotes files, (h) GIF files, (i) BMP files, or (j) TXT files. | 0.5 |
6,052,680 | 9 | 10 | 9. The program storage device of claim 5 wherein the step of determining a relevance value of the input with respect to each of the first and second decision systems includes sub-steps of: i) forming a first vector in m-dimensional space based on words contained in the input, ii) forming a second vector in m-dimensional space based on words associated with the first decision system; iii) forming a third vector in m-dimensional space based on words associated with the second decision system; iv) determining a relevance value of the input with respect to the first decision system based on a distance between the first and second vectors; and v) determining a relevance value of the input with respect to the second decision system based on a distance between the first and third vectors. | 9. The program storage device of claim 5 wherein the step of determining a relevance value of the input with respect to each of the first and second decision systems includes sub-steps of: i) forming a first vector in m-dimensional space based on words contained in the input, ii) forming a second vector in m-dimensional space based on words associated with the first decision system; iii) forming a third vector in m-dimensional space based on words associated with the second decision system; iv) determining a relevance value of the input with respect to the first decision system based on a distance between the first and second vectors; and v) determining a relevance value of the input with respect to the second decision system based on a distance between the first and third vectors. 10. The program storage device of claim 9 wherein the distance between the first and second vectors and the distance between the first and third vectors are cosine distances. | 0.5 |
4,616,327 | 1 | 5 | 1. An apparatus for producing a personalized drawing of a user within preprinted background material comprising: a means for recording a plurality of factors affecting the user's appearence; a means for selecting at least two predesigned visual features most fitting to the user from a plurality of predesigned visual features in accordance with the plurality of factors affecting the user's appearance; a means for automatically controlling a plotter to draw the at least two predesigned visual features most fitting to the user within the preprinted background material to produce a continuous and personalized drawing of the user. | 1. An apparatus for producing a personalized drawing of a user within preprinted background material comprising: a means for recording a plurality of factors affecting the user's appearence; a means for selecting at least two predesigned visual features most fitting to the user from a plurality of predesigned visual features in accordance with the plurality of factors affecting the user's appearance; a means for automatically controlling a plotter to draw the at least two predesigned visual features most fitting to the user within the preprinted background material to produce a continuous and personalized drawing of the user. 5. The apparatus in accordance with claim 1 further including: a means for recording a favorite pastime of the user; a means for selecting a predesigned action background material in accordance with the recorded favorite pastime of the user; and, a means for automatically controlling the plotter to draw the selected predesigned action background material and incorporating the at least two visual features most fitting to the user within the selected predesigned action background material to produce a continuous and personalized drawing of the user acting out his/her favorite pastime. | 0.5 |
7,584,458 | 10 | 13 | 10. In a computer system comprising a computer, a method of annotating computer program code stored on a computer-readable medium, wherein the computer program code is operable to cause computer execution to perform according to instructions in the computer program code, the method comprising: inserting, by the computer, an annotation at a first value having a first value type in the computer program code; wherein the annotation comprises a first instance of a keyword, the first instance of the keyword indicating that the first value satisfies all usability properties necessary to allow a first function to rely on the first value, wherein other instances of the keyword identical to the first instance are operable to indicate that other values having different respective value types satisfy all usability properties necessary to allow functions to rely on the respective other values, wherein use of the keyword associates a pre-determined set of usability properties with a value type, and wherein the usability properties depend on the value type. | 10. In a computer system comprising a computer, a method of annotating computer program code stored on a computer-readable medium, wherein the computer program code is operable to cause computer execution to perform according to instructions in the computer program code, the method comprising: inserting, by the computer, an annotation at a first value having a first value type in the computer program code; wherein the annotation comprises a first instance of a keyword, the first instance of the keyword indicating that the first value satisfies all usability properties necessary to allow a first function to rely on the first value, wherein other instances of the keyword identical to the first instance are operable to indicate that other values having different respective value types satisfy all usability properties necessary to allow functions to rely on the respective other values, wherein use of the keyword associates a pre-determined set of usability properties with a value type, and wherein the usability properties depend on the value type. 13. The method of claim 10 wherein the first value is a pointer, wherein an object pointed to by the pointer has one or more readable elements, the one or more readable elements of the object each having usability properties sufficient to allow the first function to rely on the one or more readable elements. | 0.5 |
9,065,830 | 12 | 16 | 12. A system for recording media for a contact center comprising: a first processor; a first memory, wherein the first memory has stored thereon instructions that, when executed by the first processor, cause the first processor to: receive media exchanged between first and second communication devices during a telephony call, the media being received by the recording system over a wide area network; bridge a media path between the first and second communication devices; and replicate media exchanged in the media path for storing the replicated media in the mass storage device; and a second processor coupled to the first processor; and a second memory, wherein the second memory has stored thereon instructions that, when executed by the second processor, cause the second processor to: capture metadata associated with the call; and store the captured metadata in association with the stored media, wherein a routing point coupled to the first processor over the wide area network is configured to receive a request for the telephony call from the first communication device and determine whether the telephony call is to be recorded, and in response to determining that the telephony call is to be recorded, the routing point is configured to establish a first call path between the routing point and the first processor, and in response to determining that the telephony call is not to be recorded, the routing point is configured to establish a second call path between the routing point and the second communication device without establishing the first call path. | 12. A system for recording media for a contact center comprising: a first processor; a first memory, wherein the first memory has stored thereon instructions that, when executed by the first processor, cause the first processor to: receive media exchanged between first and second communication devices during a telephony call, the media being received by the recording system over a wide area network; bridge a media path between the first and second communication devices; and replicate media exchanged in the media path for storing the replicated media in the mass storage device; and a second processor coupled to the first processor; and a second memory, wherein the second memory has stored thereon instructions that, when executed by the second processor, cause the second processor to: capture metadata associated with the call; and store the captured metadata in association with the stored media, wherein a routing point coupled to the first processor over the wide area network is configured to receive a request for the telephony call from the first communication device and determine whether the telephony call is to be recorded, and in response to determining that the telephony call is to be recorded, the routing point is configured to establish a first call path between the routing point and the first processor, and in response to determining that the telephony call is not to be recorded, the routing point is configured to establish a second call path between the routing point and the second communication device without establishing the first call path. 16. The system of claim 12 , wherein the metadata includes a word uttered during the call. | 0.84589 |
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