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8,442,771 | 16 | 18 | 16. Data-processing apparatus according to claim 15 , wherein the second selection module is operable to select an identifier from the group of one or more candidate identifiers, or a revised group of candidate identifiers selected from the said group of one or more candidate identifiers, and to assign the selected identifier to an individual mention of a subcellular entity on the basis of a predetermined algorithm or heuristic. | 16. Data-processing apparatus according to claim 15 , wherein the second selection module is operable to select an identifier from the group of one or more candidate identifiers, or a revised group of candidate identifiers selected from the said group of one or more candidate identifiers, and to assign the selected identifier to an individual mention of a subcellular entity on the basis of a predetermined algorithm or heuristic. 18. Data-processing apparatus according to claim 16 , wherein the predetermined algorithm or heuristic which is used by the second selection module to select an identifier from the group of one or more candidate identifiers selects an identifier on the basis of the values of the identifiers. | 0.536508 |
6,014,663 | 15 | 18 | 15. A computer program product having control logic stored therein, said control logic, when executed, enabling a computer to compare text portions, said control logic comprising: first text portion indexing means for enabling the computer to index a first selected non-predefined text portion to generate first index information; second text portion indexing means for enabling the computer to index a second selected non-predefined text portion to generate second index information; and index comparing means for enabling the computer to compare said first and second index information generated by said first and second text portion indexing means. | 15. A computer program product having control logic stored therein, said control logic, when executed, enabling a computer to compare text portions, said control logic comprising: first text portion indexing means for enabling the computer to index a first selected non-predefined text portion to generate first index information; second text portion indexing means for enabling the computer to index a second selected non-predefined text portion to generate second index information; and index comparing means for enabling the computer to compare said first and second index information generated by said first and second text portion indexing means. 18. The computer program product of claim 15, wherein said first text portion indexing means enables the computer to generate a first index table, and said second text portion indexing means enables the computer to generate a second index table. | 0.54461 |
9,563,424 | 8 | 10 | 8. The method of claim 1 , wherein generating the one or more alternative machine language instructions comprises selecting an instruction that halts execution in the second execution mode. | 8. The method of claim 1 , wherein generating the one or more alternative machine language instructions comprises selecting an instruction that halts execution in the second execution mode. 10. The method of claim 8 , wherein selecting an instruction that halts execution in the second execution mode comprises selecting an instruction that writes to an address in non-writeable memory, or an instruction that reads from an address in non-readable memory. | 0.5 |
8,599,419 | 21 | 23 | 21. A method for routing a facsimile, comprising: converting a facsimile to a computer-readable document; identifying one or more keywords in the document; analyzing the document by determining at least one of: a relation of one or more symbols in the document to the one or more keywords, a relation of one or more keywords in the document to the one or more other keywords, a relation of graphic elements to the one or more keywords, a classification of the text of the document as a specific document type, a significance of text of the one or more keywords; determining a facsimile destination based on the analysis; and routing the facsimile to the facsimile destination based on the determination; routing the facsimile to a default destination when no facsimile destination determined based on the analyzing is a viable destination. | 21. A method for routing a facsimile, comprising: converting a facsimile to a computer-readable document; identifying one or more keywords in the document; analyzing the document by determining at least one of: a relation of one or more symbols in the document to the one or more keywords, a relation of one or more keywords in the document to the one or more other keywords, a relation of graphic elements to the one or more keywords, a classification of the text of the document as a specific document type, a significance of text of the one or more keywords; determining a facsimile destination based on the analysis; and routing the facsimile to the facsimile destination based on the determination; routing the facsimile to a default destination when no facsimile destination determined based on the analyzing is a viable destination. 23. A method as recited in claim 21 , wherein the computer-readable document is also routed to the facsimile destination based on the determination. | 0.779104 |
8,473,293 | 1 | 2 | 1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: identifying a candidate term for possible inclusion in a speech recognition dictionary; identifying at least one search query metric associated with the identified candidate term; identifying at least one market data metric associated with the identified candidate term; and generating a candidate term score for the identified candidate term based, at least in part, on a weighted combination of the at least one identified search query metric and the at least one identified market data metric. | 1. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: identifying a candidate term for possible inclusion in a speech recognition dictionary; identifying at least one search query metric associated with the identified candidate term; identifying at least one market data metric associated with the identified candidate term; and generating a candidate term score for the identified candidate term based, at least in part, on a weighted combination of the at least one identified search query metric and the at least one identified market data metric. 2. The system of claim 1 , the operations further comprising: identifying a candidate term score minimum threshold associated with the speech recognition dictionary; and determining whether the generated candidate term score for the identified candidate term meets or exceeds the candidate term score minimum threshold. | 0.70298 |
7,849,186 | 6 | 34 | 6. The method according to claim 1 , wherein said evaluating comprises implementing a similarity criterion for determining whether the real-time conversational media session and the reference data item are similar based upon at least a sequence of significant attributes associated with the real-time conversational media session and a reference data item. | 6. The method according to claim 1 , wherein said evaluating comprises implementing a similarity criterion for determining whether the real-time conversational media session and the reference data item are similar based upon at least a sequence of significant attributes associated with the real-time conversational media session and a reference data item. 34. The method according to claim 6 , wherein said similarity criterion is associated with one or more tolerance values configured to accommodate for one or more of the following: expected packet loss over the network, constant delay between MSCs and delay variation or jitter between MSCs. | 0.594972 |
9,804,687 | 1 | 11 | 1. A digital television comprising: a display unit configured to display a keypad including a plurality of key buttons which are assigned with different alphabet characters, respectively, and a text window; and a controller configured to: receive a first signal selecting a first key button of the plurality of key buttons, display a first alphabet character assigned with the first key button in the text window, and display a first sub key button assigned with a second alphabet character on a region adjacent to the first key button of the keypad, in response to the first signal, the first sub key button partially overlapping a second key button neighboring to the first key button, receive a second signal selecting the first sub key button, and display the second alphabet character next to the first alphabet character in the text window, and display a second sub key button assigned with a third alphabet character on the same region adjacent to the first key button of the keypad, in response to the second signal, the second sub key button partially overlapping the same second key button neighboring to the first key button, wherein the second alphabet character is predicted as a next character of the first alphabet character, and wherein the third alphabet character is predicted as a next character of the first and second alphabet characters. | 1. A digital television comprising: a display unit configured to display a keypad including a plurality of key buttons which are assigned with different alphabet characters, respectively, and a text window; and a controller configured to: receive a first signal selecting a first key button of the plurality of key buttons, display a first alphabet character assigned with the first key button in the text window, and display a first sub key button assigned with a second alphabet character on a region adjacent to the first key button of the keypad, in response to the first signal, the first sub key button partially overlapping a second key button neighboring to the first key button, receive a second signal selecting the first sub key button, and display the second alphabet character next to the first alphabet character in the text window, and display a second sub key button assigned with a third alphabet character on the same region adjacent to the first key button of the keypad, in response to the second signal, the second sub key button partially overlapping the same second key button neighboring to the first key button, wherein the second alphabet character is predicted as a next character of the first alphabet character, and wherein the third alphabet character is predicted as a next character of the first and second alphabet characters. 11. The digital television of claim 1 , wherein the controller is configured to: display the first and second alphabet characters in the text window as a first style, and display the rest of the alphabet characters in the text window as a second style different from the first style. | 0.5 |
7,603,413 | 1 | 12 | 1. A computer program product tangibly embodied in a computer readable medium, the computer program product including instructions that, when executed, facilitate on-line communication among multiple instant messaging identities, the computer program product configured to cause a computer to: detect presence of a target instant messaging identity in a chat room that is accessible over a network of computers to instant messaging identities and who desires interaction with other instant messaging identities who are presently on-line in the chat room; present questions to the target instant messaging identity, at least one of the questions including selectable responses associated with the question; receive, from the target instant messaging identity, responses to the questions; access, from computer-accessible memory, stored responses to the questions, at least one of the stored response having been received from another instant messaging identity and being associated with the other instant messaging identity who provided the response; compare responses received from the target instant messaging identity to the accessed stored responses; identify, based at least in part on results of the comparison, a group of less than all of instant messaging identities who are currently on-line; and use an instant messaging identity representing an instant messaging robot to introduce the identified group of instant messaging identities who are currently on-line to the target instant messaging identity and to introduce the target instant messaging identity to the identified group of instant messaging identities who are currently on-line. | 1. A computer program product tangibly embodied in a computer readable medium, the computer program product including instructions that, when executed, facilitate on-line communication among multiple instant messaging identities, the computer program product configured to cause a computer to: detect presence of a target instant messaging identity in a chat room that is accessible over a network of computers to instant messaging identities and who desires interaction with other instant messaging identities who are presently on-line in the chat room; present questions to the target instant messaging identity, at least one of the questions including selectable responses associated with the question; receive, from the target instant messaging identity, responses to the questions; access, from computer-accessible memory, stored responses to the questions, at least one of the stored response having been received from another instant messaging identity and being associated with the other instant messaging identity who provided the response; compare responses received from the target instant messaging identity to the accessed stored responses; identify, based at least in part on results of the comparison, a group of less than all of instant messaging identities who are currently on-line; and use an instant messaging identity representing an instant messaging robot to introduce the identified group of instant messaging identities who are currently on-line to the target instant messaging identity and to introduce the target instant messaging identity to the identified group of instant messaging identities who are currently on-line. 12. The computer program product of claim 1 further configured to cause the computer to: receive, from the target instant messaging identity in a later communications session, an indication of an instant messaging identity to be invited to the chat room; enable transmission of an invitation to the invited instant message participant, wherein the invitation includes a suggested meeting time and a revise control operable to enable the invited instant messaging identity to indicate a different meeting time; receive an indication of a different meeting time; and communicate the different meeting time to the target instant messaging identity. | 0.5 |
9,015,655 | 13 | 14 | 13. The system of claim 12 , wherein the compiled program, the first diverse program and the second diverse program each provide a given output value in response to a given input value. | 13. The system of claim 12 , wherein the compiled program, the first diverse program and the second diverse program each provide a given output value in response to a given input value. 14. The system of claim 13 , wherein the diversification unit wherein the second diverse program and the compiled program are the same program. | 0.5 |
7,805,455 | 2 | 6 | 2. The method according to claim 1 , including determining whether the event representation provides the cause element of the cause-effect relationship or the effect element of the cause-effect relationship prior to formulating the query. | 2. The method according to claim 1 , including determining whether the event representation provides the cause element of the cause-effect relationship or the effect element of the cause-effect relationship prior to formulating the query. 6. The method according to claim 2 , wherein the problem analysis comprises a root cause analysis and the event representation provides an effect element and the one or more knowledge bases locates one or more cause elements. | 0.519231 |
8,265,382 | 1 | 7 | 1. A method for annotating a printed document having preexisting content, the method comprising: identifying a first copy of the printed document having preexisting content, wherein the first copy of the printed document is printed from a digital document having a corresponding digital version of the preexisting content; storing first handwritten annotations captured from a first smart pen interacting with the first copy of the printed document having the preexisting content; identifying a second copy of the printed document having the preexisting content, wherein the second copy of the printed document is printed from the digital document having the corresponding digital version of the preexisting content; storing second handwritten annotations captured from a second smart pen interacting with the second copy of the printed document having the preexisting content; merging the first handwritten annotations and the second handwritten annotations to generate a collective set of handwritten annotations; associating the collective set of handwritten annotations with the digital version of the preexisting content; storing the first and second captured handwritten annotations in association with the digital version of the preexisting content as an annotated digital document; detecting a background color of a particular area of the annotated digital document, the particular area having at least a portion of the first captured handwritten annotations; and formatting the portion of the first captured handwritten annotations in the particular area of the annotated digital document to have a color selected based on the detected background color. | 1. A method for annotating a printed document having preexisting content, the method comprising: identifying a first copy of the printed document having preexisting content, wherein the first copy of the printed document is printed from a digital document having a corresponding digital version of the preexisting content; storing first handwritten annotations captured from a first smart pen interacting with the first copy of the printed document having the preexisting content; identifying a second copy of the printed document having the preexisting content, wherein the second copy of the printed document is printed from the digital document having the corresponding digital version of the preexisting content; storing second handwritten annotations captured from a second smart pen interacting with the second copy of the printed document having the preexisting content; merging the first handwritten annotations and the second handwritten annotations to generate a collective set of handwritten annotations; associating the collective set of handwritten annotations with the digital version of the preexisting content; storing the first and second captured handwritten annotations in association with the digital version of the preexisting content as an annotated digital document; detecting a background color of a particular area of the annotated digital document, the particular area having at least a portion of the first captured handwritten annotations; and formatting the portion of the first captured handwritten annotations in the particular area of the annotated digital document to have a color selected based on the detected background color. 7. The method of claim 1 , further comprising: capturing a user interaction with a portion of the preexisting content printed on the printed document using the smart pen; capturing audio using the smart pen concurrently with capturing the user interaction; and storing the captured audio in association with the portion of the digital version of the preexisting content based on the user interaction with the preexisting content in the printed document. | 0.5 |
7,962,328 | 20 | 21 | 20. The apparatus of claim 16 , wherein the means for generating comprises means for generating the data structure to include a plurality of fields, wherein each of the plurality of fields represents a corresponding one of the plurality of answers. | 20. The apparatus of claim 16 , wherein the means for generating comprises means for generating the data structure to include a plurality of fields, wherein each of the plurality of fields represents a corresponding one of the plurality of answers. 21. The apparatus of claim 20 , wherein the computer-readable memory comprises a computer-readable memory in a computer including a processor, and wherein the means for generating comprises means for generating the data structure to consist of bits equal in number to a number of bits of a data type native to the processor. | 0.5 |
8,627,272 | 21 | 22 | 21. The system of claim 15 , where the mapping is bidirectional, and where the processor is further to: receive information associated with a change to the first graphical element; and modify the first code portion based on the change to the first graphical element. | 21. The system of claim 15 , where the mapping is bidirectional, and where the processor is further to: receive information associated with a change to the first graphical element; and modify the first code portion based on the change to the first graphical element. 22. The system of claim 21 , where the processor is further to: display a visual indication associated with modifying the first code portion. | 0.781734 |
9,116,989 | 1 | 6 | 1. A method comprising: receiving, via a first display device, a spoken content-based free-form natural language query to search content of a plurality of segments within a media presentation that has been processed for content-based searching, the media presentation comprising a series of slides; displaying, via the first display device, the media presentation, text from a speech recognition process applied to the spoken content-based free-form natural language query, and a scrollable search result set in response to the spoken content-based free-form natural language query, the scrollable search result set comprising a portion of the content of the plurality of segments which is associated with the spoken content-based free-form natural language query, while simultaneously transmitting the media presentation to a second display device for display at the second display device without the text and without the scrollable search result set; receiving, via the first display device, a selection from the scrollable search result set, to yield a selected segment of the plurality of segments, wherein the selection is based on a motion input; and transmitting the selected segment to the second display device for display at the second display device as part of the media presentation. | 1. A method comprising: receiving, via a first display device, a spoken content-based free-form natural language query to search content of a plurality of segments within a media presentation that has been processed for content-based searching, the media presentation comprising a series of slides; displaying, via the first display device, the media presentation, text from a speech recognition process applied to the spoken content-based free-form natural language query, and a scrollable search result set in response to the spoken content-based free-form natural language query, the scrollable search result set comprising a portion of the content of the plurality of segments which is associated with the spoken content-based free-form natural language query, while simultaneously transmitting the media presentation to a second display device for display at the second display device without the text and without the scrollable search result set; receiving, via the first display device, a selection from the scrollable search result set, to yield a selected segment of the plurality of segments, wherein the selection is based on a motion input; and transmitting the selected segment to the second display device for display at the second display device as part of the media presentation. 6. The method of claim 1 , wherein the media presentation is processed by extracting text and using linguistics associated with the text for content-based searching. | 0.5 |
8,972,436 | 8 | 13 | 8. A method, comprising: obtaining a set of text, wherein the set of text includes user-generated content; determining, for the set of text, a numerical value for each of a plurality of objects, the numerical value indicating a likelihood that the corresponding one of the plurality of objects could have generated the set of text, the plurality of objects each representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the set of text were generated from one of the objects, is most likely to have generated the set of text based, at least in part, upon the numerical value that has been determined for each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the set of text; associating the set of text with the identified one of the plurality of objects such that a plurality of sets of text associated with the identified one of the plurality of objects includes the set of text; and aggregating information from at least a portion of the plurality of sets of text. | 8. A method, comprising: obtaining a set of text, wherein the set of text includes user-generated content; determining, for the set of text, a numerical value for each of a plurality of objects, the numerical value indicating a likelihood that the corresponding one of the plurality of objects could have generated the set of text, the plurality of objects each representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the set of text were generated from one of the objects, is most likely to have generated the set of text based, at least in part, upon the numerical value that has been determined for each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the set of text; associating the set of text with the identified one of the plurality of objects such that a plurality of sets of text associated with the identified one of the plurality of objects includes the set of text; and aggregating information from at least a portion of the plurality of sets of text. 13. The method as recited in claim 8 , wherein each of the plurality of objects has a set of one or more parameters including a generic parameter that indicates a probability that a generic word is present in the set of text. | 0.714467 |
8,752,011 | 15 | 17 | 15. The method of claim 14 wherein the keywords include programmer-defined keywords and predefined keywords. | 15. The method of claim 14 wherein the keywords include programmer-defined keywords and predefined keywords. 17. The method of claim 15 wherein the predefined keywords identify different kinds of programming patterns, widgets, and customization mechanisms. | 0.834459 |
9,460,715 | 13 | 20 | 13. A method comprising: under control of one or more computing devices configured with executable instructions, receiving a first audio signal generated by a microphone of a device residing in an environment; identifying, from the audio signal, a voice command uttered by a user in the environment; causing the device to perform a first operation specified by the voice command; identifying, from a subsequent audio signal generated by the microphone of the device, subsequent speech uttered within the environment at least partly while the device performs the first operation, the subsequent speech requesting that the device perform a second operation related to the first operation; determining whether that the user uttered the subsequent speech or whether that another user in the environment uttered the subsequent speech; interpreting the subsequent speech as a valid voice command at least partly in response to determining that the user uttered the subsequent speech; and refraining from interpreting the subsequent speech as a valid voice command at least partly in response to determining that another user in the environment uttered the subsequent speech. | 13. A method comprising: under control of one or more computing devices configured with executable instructions, receiving a first audio signal generated by a microphone of a device residing in an environment; identifying, from the audio signal, a voice command uttered by a user in the environment; causing the device to perform a first operation specified by the voice command; identifying, from a subsequent audio signal generated by the microphone of the device, subsequent speech uttered within the environment at least partly while the device performs the first operation, the subsequent speech requesting that the device perform a second operation related to the first operation; determining whether that the user uttered the subsequent speech or whether that another user in the environment uttered the subsequent speech; interpreting the subsequent speech as a valid voice command at least partly in response to determining that the user uttered the subsequent speech; and refraining from interpreting the subsequent speech as a valid voice command at least partly in response to determining that another user in the environment uttered the subsequent speech. 20. A method as recited in claim 13 , wherein the attempting comprises comparing past voice commands uttered by the user to one or more characteristics associated with the subsequent speech. | 0.640152 |
7,610,315 | 14 | 15 | 14. The system of claim 11 , further comprising: a document genre ontology used for document genre classification, the document genre ontology comprising a hierarchical knowledge structure containing a vocabulary of terms and concepts, and inference chains representing interrelationships between the vocabulary terms and concepts; an application program interface (API) configured to provide the document control component with access to selected elements in an inference chain in the document genre ontology; wherein the document control component comprises a policy ontology component configured to recommend the at least one document control policy and including an interface through which a policy management component accesses the at least one document control policy for application to the document. | 14. The system of claim 11 , further comprising: a document genre ontology used for document genre classification, the document genre ontology comprising a hierarchical knowledge structure containing a vocabulary of terms and concepts, and inference chains representing interrelationships between the vocabulary terms and concepts; an application program interface (API) configured to provide the document control component with access to selected elements in an inference chain in the document genre ontology; wherein the document control component comprises a policy ontology component configured to recommend the at least one document control policy and including an interface through which a policy management component accesses the at least one document control policy for application to the document. 15. The system of claim 14 , wherein the policy management component comprises a policy server. | 0.5 |
7,681,147 | 12 | 15 | 12. A system to determine probable meanings of words input as search query terms, comprising: a networked server to receive an input of at least one search query word; a processor coupled with the networked server to analyze the inputted word and to determine a probable meaning of the word in accordance with a prior probability of probable meanings of the word and a context frequency probability of probable meanings of the word, wherein the prior probability comprises a probability that the word refers to a predetermined meaning irregardless of a query context in which the word is used, which prior probability is derived from previous analysis of documents containing the word, wherein the processor: estimates an expected final probability for the at least one word given the prior probability of the at least one word; derives an inverse combine function that uses the prior probability and the expected final probability to determine the context frequency probability of the at least one word; and uses a combine mathematical function to combine the prior probability and the context frequency probability to produce a final probability of the probable meaning of the at least one search query word; and a memory coupled with the processor to store the prior probabilities and the context frequency probabilities of probable meanings of previously-inputted words; wherein the processor generates search results listings in accordance with the final probability of the probable meaning of the word for presentation to a user. | 12. A system to determine probable meanings of words input as search query terms, comprising: a networked server to receive an input of at least one search query word; a processor coupled with the networked server to analyze the inputted word and to determine a probable meaning of the word in accordance with a prior probability of probable meanings of the word and a context frequency probability of probable meanings of the word, wherein the prior probability comprises a probability that the word refers to a predetermined meaning irregardless of a query context in which the word is used, which prior probability is derived from previous analysis of documents containing the word, wherein the processor: estimates an expected final probability for the at least one word given the prior probability of the at least one word; derives an inverse combine function that uses the prior probability and the expected final probability to determine the context frequency probability of the at least one word; and uses a combine mathematical function to combine the prior probability and the context frequency probability to produce a final probability of the probable meaning of the at least one search query word; and a memory coupled with the processor to store the prior probabilities and the context frequency probabilities of probable meanings of previously-inputted words; wherein the processor generates search results listings in accordance with the final probability of the probable meaning of the word for presentation to a user. 15. The system of claim 12 , wherein a meaning of the word comprises a geographic location. | 0.912835 |
9,009,153 | 16 | 20 | 16. A non-transitory computer-readable storage medium on which is encoded executable program code, the program code comprising: program code for determining a collection of named entity terms within a data store coupled to a computer of a user, a named entity term having an associated weight indicating a likelihood that the named entity term is included in a named entity; program code for identifying an event comprising a user interaction with an article on the computer; program code for identifying a plurality of named entity terms associated with the event; program code for identifying, from the collection, the weight associated with each of the plurality of named entity terms; program code for automatically creating an implicit search query responsive to identifying the weight associated with each of the plurality of named entity terms, the implicit query based at least in part on the plurality of named entity terms and the associated weights, the implicit search query based on a first named entity term with an associated weight indicating a higher likelihood that the first named entity term is a named entity more than on a second named entity term with an associated weight indicating a lower likelihood that the second named entity term is a named entity; program code for generating, from the computer, a plurality of search results relevant to the implicit search query; and program code for providing for display the retrieved plurality of search results. | 16. A non-transitory computer-readable storage medium on which is encoded executable program code, the program code comprising: program code for determining a collection of named entity terms within a data store coupled to a computer of a user, a named entity term having an associated weight indicating a likelihood that the named entity term is included in a named entity; program code for identifying an event comprising a user interaction with an article on the computer; program code for identifying a plurality of named entity terms associated with the event; program code for identifying, from the collection, the weight associated with each of the plurality of named entity terms; program code for automatically creating an implicit search query responsive to identifying the weight associated with each of the plurality of named entity terms, the implicit query based at least in part on the plurality of named entity terms and the associated weights, the implicit search query based on a first named entity term with an associated weight indicating a higher likelihood that the first named entity term is a named entity more than on a second named entity term with an associated weight indicating a lower likelihood that the second named entity term is a named entity; program code for generating, from the computer, a plurality of search results relevant to the implicit search query; and program code for providing for display the retrieved plurality of search results. 20. The computer-readable medium of claim 16 , wherein program code for determining the collection of named entity terms comprises program code for analyzing an email data store. | 0.671587 |
9,424,612 | 11 | 14 | 11. The computer-implemented method of claim 1 , wherein the first account is associated with the first category-specific reputation score in a first category and a second category-specific reputation score in a second category. | 11. The computer-implemented method of claim 1 , wherein the first account is associated with the first category-specific reputation score in a first category and a second category-specific reputation score in a second category. 14. The computer-implemented method of claim 11 , wherein said identifying the new user activity includes determining that the new user activity is not associated with the second category; and responsive to determining that the new user activity is not associated with the second category, leaving the second category-specific reputation score unchanged. | 0.5 |
9,875,739 | 8 | 13 | 8. A non-transitory computer-readable medium having stored thereon a sequence of instructions that when executed by a computing system causes, the computing system to perform the steps comprising: obtaining a digital audio file; splitting the digital audio file into a plurality of frames; segmenting the digital audio file into entropy segments based upon an entropy of each frame; performing a blind diarization to identify a first speaker audio file and a second speaker audio file by clustering the entropy segments into the first speaker audio file and the second speaker audio file, wherein the first speaker audio file only contains audio attributed to the first speaker and the second speaker audio file only contains audio attributed to the second speaker; and identifying one of the first speaker audio file and second speaker audio file as an agent audio file and another of the first speaker audio file and the second speaker audio file as a customer audio file; and transcribing the agent audio file and the customer audio file to produce a diarized transcript. | 8. A non-transitory computer-readable medium having stored thereon a sequence of instructions that when executed by a computing system causes, the computing system to perform the steps comprising: obtaining a digital audio file; splitting the digital audio file into a plurality of frames; segmenting the digital audio file into entropy segments based upon an entropy of each frame; performing a blind diarization to identify a first speaker audio file and a second speaker audio file by clustering the entropy segments into the first speaker audio file and the second speaker audio file, wherein the first speaker audio file only contains audio attributed to the first speaker and the second speaker audio file only contains audio attributed to the second speaker; and identifying one of the first speaker audio file and second speaker audio file as an agent audio file and another of the first speaker audio file and the second speaker audio file as a customer audio file; and transcribing the agent audio file and the customer audio file to produce a diarized transcript. 13. The non-transitory computer-readable medium of claim 8 : wherein transcribing the digital audio file comprises applying an agent model to the digital audio file; and wherein identifying one of the first speaker audio file and the second speaker audio file as the agent audio file, comprises comparing the first speaker audio file and the second speaker audio file to the agent model. | 0.792827 |
9,836,502 | 21 | 24 | 21. A non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform functions for: receiving a selection of one or more identifiers of panel templates among a plurality of identifiers of panel templates, wherein each identifier of the plurality of identifiers is associated with a panel template that includes a query and a format for displaying an associated panel in a dashboard, wherein selecting the one or more identifiers of panel templates comprises: dragging each identifier of the one or more identifiers of panel templates onto a representation of a dashboard in a displayed dashboard-creation page; and dropping each dragged identifier at an associated position in the dashboard-creation page, each associated position being indicative of where the associated panel appears when the dashboard is displayed; in response to selecting an identifier of the one or more identifiers of panel templates: adding a reference to an associated panel template of the selected identifier in the associated panel in the dashboard-creation page; and adding to the dashboard-creation page an indication of the panel associated with the selected identifier; in response to a user action for a particular panel in the dashboard-creation page, executing a query included in a panel template referenced by the particular panel to generate data for display in that particular panel within the dashboard-creation page; and visualizing, within the particular panel within the dashboard-creation page, data resulting from execution of the query in the panel template referenced by the particular panel. | 21. A non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform functions for: receiving a selection of one or more identifiers of panel templates among a plurality of identifiers of panel templates, wherein each identifier of the plurality of identifiers is associated with a panel template that includes a query and a format for displaying an associated panel in a dashboard, wherein selecting the one or more identifiers of panel templates comprises: dragging each identifier of the one or more identifiers of panel templates onto a representation of a dashboard in a displayed dashboard-creation page; and dropping each dragged identifier at an associated position in the dashboard-creation page, each associated position being indicative of where the associated panel appears when the dashboard is displayed; in response to selecting an identifier of the one or more identifiers of panel templates: adding a reference to an associated panel template of the selected identifier in the associated panel in the dashboard-creation page; and adding to the dashboard-creation page an indication of the panel associated with the selected identifier; in response to a user action for a particular panel in the dashboard-creation page, executing a query included in a panel template referenced by the particular panel to generate data for display in that particular panel within the dashboard-creation page; and visualizing, within the particular panel within the dashboard-creation page, data resulting from execution of the query in the panel template referenced by the particular panel. 24. The non-transitory computer-readable medium of claim 21 , wherein the panel templates for a plurality of the panels each include a same definition of a global input that defines an aspect of or constrains the queries in the panel templates. | 0.596026 |
8,108,509 | 5 | 7 | 5. The method according to claim 4 , wherein the altered content data being transmitted for output through speakers coupled to the second computer. | 5. The method according to claim 4 , wherein the altered content data being transmitted for output through speakers coupled to the second computer. 7. The method according to claim 5 , wherein the content data output characteristics are defined by input received by the first computer through a user interface. | 0.652361 |
10,121,064 | 1 | 5 | 1. A behavioral classification system, comprising: a microprocessor; and memory containing a classification application; wherein the classification application directs the microprocessor to: identify at least a primary subject interacting with a secondary subject within a sequence of frames of image data comprising depth information; determine poses for at least the primary subject and the secondary subject within a plurality of frames from the sequence of frames of image data; extract a set of parameters describing the poses and movement of at least the primary and secondary subjects from the plurality of frames from the sequence of frames of image data; and detect a social behavior performed by at least the primary subject and involving at least the secondary subject, wherein the primary subject occludes at least a portion of the secondary subject, using a classifier trained to discriminate between a plurality of social behaviors based upon the set of parameters describing poses and movement of a plurality of subjects extracted from a plurality of frames of image data comprising depth information. | 1. A behavioral classification system, comprising: a microprocessor; and memory containing a classification application; wherein the classification application directs the microprocessor to: identify at least a primary subject interacting with a secondary subject within a sequence of frames of image data comprising depth information; determine poses for at least the primary subject and the secondary subject within a plurality of frames from the sequence of frames of image data; extract a set of parameters describing the poses and movement of at least the primary and secondary subjects from the plurality of frames from the sequence of frames of image data; and detect a social behavior performed by at least the primary subject and involving at least the secondary subject, wherein the primary subject occludes at least a portion of the secondary subject, using a classifier trained to discriminate between a plurality of social behaviors based upon the set of parameters describing poses and movement of a plurality of subjects extracted from a plurality of frames of image data comprising depth information. 5. The behavioral classification system of claim 1 , wherein the classification application further directs the microprocessor to detect occurrence of modified social behavior in at least the primary subject resulting from administration of a pharmaceutical. | 0.808321 |
8,370,144 | 8 | 14 | 8. A method according to claim 6 , wherein the windows are overlapping and the step of segmenting comprises segmenting the audio stream into the overlapping windows. | 8. A method according to claim 6 , wherein the windows are overlapping and the step of segmenting comprises segmenting the audio stream into the overlapping windows. 14. A method according to claim 8 , wherein the second limit is 15 windows. | 0.847561 |
8,301,613 | 3 | 4 | 3. The method of claim 2 , where when no associated resource tickets are found during performance of the fourth search available further comprising performing probing of resources determined from the dependency tree to attempt to generate at least one corresponding resource ticket, and searching on any corresponding resource tickets that are generated for related configuration items. | 3. The method of claim 2 , where when no associated resource tickets are found during performance of the fourth search available further comprising performing probing of resources determined from the dependency tree to attempt to generate at least one corresponding resource ticket, and searching on any corresponding resource tickets that are generated for related configuration items. 4. The method of claim 3 , where the probing is adaptive probing constrained to execute in some predetermined period of time with a restriction on a number of probes that can be executed in parallel. | 0.5 |
9,268,824 | 1 | 7 | 1. An article of manufacture, comprising: a computer readable medium; and instructions stored in the computer readable medium which, when executed by one or more computers, cause the one or more computers to perform operations comprising: obtaining data representing entities, each entity being a query, a document, a session of queries, a time, or a domain of a document; identifying a plurality of pairs of entities from a subset of the entities from search history data, where each pair is either: (1) (i) a query paired with (ii) another query, a document, a session of queries, or a time, or (2) (i) a document paired with (ii) a session of queries, or (3) two documents paired with each other, and where the plurality of pairs of entities comprise a first pair of entities that is a first document paired with a first session of queries and a second pair of entities that is a second session of queries paired with a second document; generating, for each pair of entities, using the search history data, a respective directed relationship having a respective strength value and connecting a first entity of the pair to a second entity of the pair; and determining, for any two entities that are directly or indirectly connected through directed relationships, a relevance score from strength values of the directed relationships connecting the two entities. | 1. An article of manufacture, comprising: a computer readable medium; and instructions stored in the computer readable medium which, when executed by one or more computers, cause the one or more computers to perform operations comprising: obtaining data representing entities, each entity being a query, a document, a session of queries, a time, or a domain of a document; identifying a plurality of pairs of entities from a subset of the entities from search history data, where each pair is either: (1) (i) a query paired with (ii) another query, a document, a session of queries, or a time, or (2) (i) a document paired with (ii) a session of queries, or (3) two documents paired with each other, and where the plurality of pairs of entities comprise a first pair of entities that is a first document paired with a first session of queries and a second pair of entities that is a second session of queries paired with a second document; generating, for each pair of entities, using the search history data, a respective directed relationship having a respective strength value and connecting a first entity of the pair to a second entity of the pair; and determining, for any two entities that are directly or indirectly connected through directed relationships, a relevance score from strength values of the directed relationships connecting the two entities. 7. The article of manufacture of claim 1 , the plurality of pairs of entities comprises a first pair of entities, a first entity of the pair being a first document connected to a second entity of the pair being a second distinct document, and wherein the strength value of the directed relationship from the first document to the second is based on whether the first document includes an anchor pointing to the second document. | 0.644167 |
7,660,793 | 48 | 49 | 48. The system of claim 37 wherein the processor is configured to execute API software to handle the received query. | 48. The system of claim 37 wherein the processor is configured to execute API software to handle the received query. 49. The system of claim 48 wherein the API software comprises relational engine software and coprocessor interface software, wherein the relational engine software is configured to invoke the coprocessor interface software upon encountering the received another query portion, and wherein the coprocessor interface software is configured to invoke the coprocessor to handle the received another query portion. | 0.5 |
8,713,078 | 10 | 11 | 10. The computer-implemented method of claim 1 , further comprising: selecting one of the sub-topics identified; collecting a plurality of keywords related to the sub-topic selected, the keywords being collected using at least one dynamic data source; identifying one or more sub-topics of the sub-topic selected using the keywords collected; and building a sub-topic node in the taxonomy of topics, the sub-topic node including a subtopic identifier for the sub-topic selected, a child node identifier for the sub-topic of the sub-topic selected, and a keyword section for one or more of the keywords collected for the sub-topic selected, wherein the collecting, identifying, and building steps are repeated to build a customized taxonomy of topics having a plurality of nodes in a hierarchical structure. | 10. The computer-implemented method of claim 1 , further comprising: selecting one of the sub-topics identified; collecting a plurality of keywords related to the sub-topic selected, the keywords being collected using at least one dynamic data source; identifying one or more sub-topics of the sub-topic selected using the keywords collected; and building a sub-topic node in the taxonomy of topics, the sub-topic node including a subtopic identifier for the sub-topic selected, a child node identifier for the sub-topic of the sub-topic selected, and a keyword section for one or more of the keywords collected for the sub-topic selected, wherein the collecting, identifying, and building steps are repeated to build a customized taxonomy of topics having a plurality of nodes in a hierarchical structure. 11. The computer-implemented method of claim 10 , the method further comprising: retrieving keywords associated with a second topic and ranks assigned to the keywords from the taxonomy of topics; identifying a plurality of videos associated with each keyword associated with the second topic; and calculating a video-keyword rank for each video associated with each keyword based on a relevancy of the video to the keyword. | 0.790179 |
9,535,906 | 7 | 8 | 7. The device of claim 1 , further comprising a location detector to determine a geographic location of the mobile electronic device, wherein the translator application causes the touch sensitive screen to display a graphic that prompts a user of the mobile electronic device to select any one of a plurality of languages to which the entered word or phrase of the first language can be translated by the translator, the plurality of languages being offered by the translator based on the determined geographic location of the mobile electronic device. | 7. The device of claim 1 , further comprising a location detector to determine a geographic location of the mobile electronic device, wherein the translator application causes the touch sensitive screen to display a graphic that prompts a user of the mobile electronic device to select any one of a plurality of languages to which the entered word or phrase of the first language can be translated by the translator, the plurality of languages being offered by the translator based on the determined geographic location of the mobile electronic device. 8. The device of claim 7 , wherein the translator application causes the graphic to be displayed when the detection component detects the change in the physical orientation of the mobile electronic device from the first orientation to the second orientation. | 0.5 |
9,215,207 | 7 | 8 | 7. The method of monitoring an electronic communication according to claim 6 , wherein: the step of electronically sampling the electronic communication comprises filtering to determine untrusted communication data from trusted communication data. | 7. The method of monitoring an electronic communication according to claim 6 , wherein: the step of electronically sampling the electronic communication comprises filtering to determine untrusted communication data from trusted communication data. 8. The method as claimed in claim 7 further comprising preconditioning the untrusted communication data so as to provide a set of expressions, and wherein the step of preconditioning comprises expanding each expression such that common alternative expressions are included in the set of expressions. | 0.5 |
8,276,063 | 9 | 13 | 9. A modeling system comprising: a processor having a memory; a program module stored in said memory, wherein said program module includes instructions for: receiving by a software module at least one web-based language import/export file containing information specifying parameters of the product to be manufactured; determining if the import/export file is valid in response to tags in the import/export file being correctly configured; determining if the import/export file includes a configuration element identifying an import configuration file; loading a configuration file, the configuration file being one of the identified import configuration file or a default configuration file, and setting variables and tags in the configuration file; comparing each element in the import/export file to part configuration elements in the configuration file to determine whether the elements in the import/export file are valid for inputting into a model, and when elements in the import/export file are valid for inputting into a model, then using the import/export file to create a template that is imported into a solid modeling program for modeling the product. | 9. A modeling system comprising: a processor having a memory; a program module stored in said memory, wherein said program module includes instructions for: receiving by a software module at least one web-based language import/export file containing information specifying parameters of the product to be manufactured; determining if the import/export file is valid in response to tags in the import/export file being correctly configured; determining if the import/export file includes a configuration element identifying an import configuration file; loading a configuration file, the configuration file being one of the identified import configuration file or a default configuration file, and setting variables and tags in the configuration file; comparing each element in the import/export file to part configuration elements in the configuration file to determine whether the elements in the import/export file are valid for inputting into a model, and when elements in the import/export file are valid for inputting into a model, then using the import/export file to create a template that is imported into a solid modeling program for modeling the product. 13. The system of claim 9 , further comprising: instructions for providing a configuration file that includes instructions for configuring the variables of a modeling program used to build a model of said product. | 0.5 |
6,098,081 | 1 | 5 | 1. A method of resolving a hyperlink, comprising the following steps: receiving a hyperlinked document from a remote server, the hyperlinked document containing one or more hyperlinks, at least one of the hyperlinks containing a query formulation; in response to selection of said at least one of the hyperlinks by a user, reading a query formulation from the selected hyperlink; querying one or more database servers with the query formulation to locate one or more hyperlink targets that satisfy the query formulation, wherein at least some of the hyperlink targets specify hypermedia documents from servers other than the one or more database servers; retrieving a hypermedia document specified by one of the located hyperlink targets from a server other than the one or more database servers; rendering said retrieved hypermedia document. | 1. A method of resolving a hyperlink, comprising the following steps: receiving a hyperlinked document from a remote server, the hyperlinked document containing one or more hyperlinks, at least one of the hyperlinks containing a query formulation; in response to selection of said at least one of the hyperlinks by a user, reading a query formulation from the selected hyperlink; querying one or more database servers with the query formulation to locate one or more hyperlink targets that satisfy the query formulation, wherein at least some of the hyperlink targets specify hypermedia documents from servers other than the one or more database servers; retrieving a hypermedia document specified by one of the located hyperlink targets from a server other than the one or more database servers; rendering said retrieved hypermedia document. 5. A method as recited in claim 1, further comprising: maintaining a list of bound attributes that are independent of the selected hyperlink; adding search predicates to the query formulation based on said bound attributes. | 0.757609 |
8,767,950 | 7 | 8 | 7. The system of claim 6 , wherein the plurality of input requirements each describes a format for valid device identifiers on the at least one communications network, and the match status reported for each of the plurality of input requirements indicates whether the input string corresponds to the valid device identifier described by the respective input requirement. | 7. The system of claim 6 , wherein the plurality of input requirements each describes a format for valid device identifiers on the at least one communications network, and the match status reported for each of the plurality of input requirements indicates whether the input string corresponds to the valid device identifier described by the respective input requirement. 8. The system of claim 7 , further comprising: an input device connected to the processing device, wherein the input device is configured to receive input and send the given input stream to the processing device. | 0.5 |
7,487,439 | 3 | 6 | 3. The method of claim 1 , further comprising executing the following operation in the data processing device: inserting the constructs into the pre-established DTD to create the annotated DTD. | 3. The method of claim 1 , further comprising executing the following operation in the data processing device: inserting the constructs into the pre-established DTD to create the annotated DTD. 6. The method of claim 3 , further comprising executing the following operation in the data processing device: associating values and/or formulas with the pre-established DTD. | 0.734848 |
9,311,278 | 1 | 2 | 1. A computer-implemented method for providing a visual editor allowing graphical editing of logical expressions in a database expression language, comprising: displaying a graphical user interface; receiving a first user input of a graphical rule logic block on the graphical user interface, wherein the graphical rule logic block represents a high-level definition of a logical expression in plain text for one or more of: a database query, a database rule and a database condition, and wherein the rule logic block includes one or more visual indicators indicating whether the logical expression is usable as is or requires further refinement; receiving a second user input of one or more graphical sub-elements, wherein each individual sub-element is presented as a non-alphanumeric geometric shape and is contained within the rule logic block and represents one of: an operator of a logical expression and an operand of a logical expression, wherein a graphical sub-element representing an operand further includes one or more visual indicators indicating whether the operand is usable as is or requires further refinement; verifying a syntax of the second user input; and providing an alert to the user in response to detecting a syntax error or an inconsistency of the second user input when verifying the syntax. | 1. A computer-implemented method for providing a visual editor allowing graphical editing of logical expressions in a database expression language, comprising: displaying a graphical user interface; receiving a first user input of a graphical rule logic block on the graphical user interface, wherein the graphical rule logic block represents a high-level definition of a logical expression in plain text for one or more of: a database query, a database rule and a database condition, and wherein the rule logic block includes one or more visual indicators indicating whether the logical expression is usable as is or requires further refinement; receiving a second user input of one or more graphical sub-elements, wherein each individual sub-element is presented as a non-alphanumeric geometric shape and is contained within the rule logic block and represents one of: an operator of a logical expression and an operand of a logical expression, wherein a graphical sub-element representing an operand further includes one or more visual indicators indicating whether the operand is usable as is or requires further refinement; verifying a syntax of the second user input; and providing an alert to the user in response to detecting a syntax error or an inconsistency of the second user input when verifying the syntax. 2. The method of claim 1 , wherein the database expression language is one of: a structured query language, a multi dimensional expression language, and a scripting language. | 0.717532 |
7,506,250 | 1 | 15 | 1. A method of processing a paper document, the method comprising: receiving an identification code associated with an identification tag; determining, from a first database storing information associated with a plurality of feature descriptors, electronic information to be associated with the identification code, the determining comprising: obtaining an electronic representation of contents printed on a first paper document; selecting a portion of the obtained electronic representation; locating one or more zones on the selected portion; determining a first feature descriptor based upon at least one zone of the one or more zones on the selected portion, the first feature descriptor being distinct from the identification code; determining a matching feature descriptor from the first database that matches the first feature descriptor; and determining, from the first database, electronic document information associated with the matching feature descriptor; and storing the identification code and the electronic document information associated with the matching feature descriptor in memory, whereby the electronic document information associated with the matching feature descriptor is associated with the identification code and is determinable using the identification code. | 1. A method of processing a paper document, the method comprising: receiving an identification code associated with an identification tag; determining, from a first database storing information associated with a plurality of feature descriptors, electronic information to be associated with the identification code, the determining comprising: obtaining an electronic representation of contents printed on a first paper document; selecting a portion of the obtained electronic representation; locating one or more zones on the selected portion; determining a first feature descriptor based upon at least one zone of the one or more zones on the selected portion, the first feature descriptor being distinct from the identification code; determining a matching feature descriptor from the first database that matches the first feature descriptor; and determining, from the first database, electronic document information associated with the matching feature descriptor; and storing the identification code and the electronic document information associated with the matching feature descriptor in memory, whereby the electronic document information associated with the matching feature descriptor is associated with the identification code and is determinable using the identification code. 15. The method of claim 1 , wherein the location of the one or more zones is the same as selected for extracting feature descriptors stored in the first database. | 0.823913 |
7,966,187 | 12 | 13 | 12. The script compliance method of claim 1 , further comprising performing at least one action based upon at least one result of the evaluating of the at least one voice interaction. | 12. The script compliance method of claim 1 , further comprising performing at least one action based upon at least one result of the evaluating of the at least one voice interaction. 13. The script compliance method of claim 12 , wherein performing at least one action includes transmitting at least one signal to the at least one agent. | 0.552326 |
9,130,651 | 1 | 23 | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. 23. The energy harvesting communication device of claim 1 , wherein said communication apparatus further comprises a case for at least an electronic device, wherein at least a power management module is further associated with the case, and wherein the case further comprises at least one of: a wearable outfit for said communication apparatus; a wearable energy harvesting device; an outfit. | 0.890011 |
8,032,509 | 1 | 17 | 1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement. | 1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement. 17. The computer system of claim 1 , wherein the second query language statement is received in an XQuery format. | 0.865796 |
7,707,012 | 1 | 2 | 1. A method of generating a city model, comprising: receiving a set of roadway segments, the roadway segments corresponding to a plurality of roadways of a city; generating a set of grid points using the set of roadway segments, the grid points corresponding to intersections between the roadway segments; associating a feature model to each subset of the set of grid points, each subset of the set of grid points corresponding to at least a portion of a roadway of the plurality of roadways of the city, the feature model representative of buildings expected to be found along each roadway segment. | 1. A method of generating a city model, comprising: receiving a set of roadway segments, the roadway segments corresponding to a plurality of roadways of a city; generating a set of grid points using the set of roadway segments, the grid points corresponding to intersections between the roadway segments; associating a feature model to each subset of the set of grid points, each subset of the set of grid points corresponding to at least a portion of a roadway of the plurality of roadways of the city, the feature model representative of buildings expected to be found along each roadway segment. 2. The method of claim 1 , further comprising: associating a type to a subset of the set of grid points, the subset corresponding to a roadway from the plurality of roadways; and associating a road profile to the subset of grid points using the type. | 0.55036 |
8,495,571 | 15 | 17 | 15. A computer program product comprising: a non-transitory computer useable medium including a computer readable program for managing engineering revisions; wherein the computer readable program when executed by a computer causes: holding in a data store at least one asset for forming an engineered product; tracking changes made to each asset in a workspace, there being a workspace copy of a subject asset and a data store copy of the subject asset; and automatically displaying at least two separate indications of changes, one of the indications being workspace copy changes and the other indications being data store changes that are juxtaposed together to a user of the workspace: (a) the workspace copy indications are configured to provide indications of changes made to the workspace copy of the subject asset relative to the data store copy of the subject asset, and (b) the data store copy indications are configured to provide indications of changes made by another user to the data store copy of the subject asset relative to the workspace copy of the subject asset, such that the (a) indications of the workspace copy changes are juxtaposed with the and (b) indications of data store copy changes in that they are positioned in close proximity to one another or positioned side by side one another in the certain screen view. | 15. A computer program product comprising: a non-transitory computer useable medium including a computer readable program for managing engineering revisions; wherein the computer readable program when executed by a computer causes: holding in a data store at least one asset for forming an engineered product; tracking changes made to each asset in a workspace, there being a workspace copy of a subject asset and a data store copy of the subject asset; and automatically displaying at least two separate indications of changes, one of the indications being workspace copy changes and the other indications being data store changes that are juxtaposed together to a user of the workspace: (a) the workspace copy indications are configured to provide indications of changes made to the workspace copy of the subject asset relative to the data store copy of the subject asset, and (b) the data store copy indications are configured to provide indications of changes made by another user to the data store copy of the subject asset relative to the workspace copy of the subject asset, such that the (a) indications of the workspace copy changes are juxtaposed with the and (b) indications of data store copy changes in that they are positioned in close proximity to one another or positioned side by side one another in the certain screen view. 17. A computer program product of claim 15 wherein the indications include any one or combination of indicia representing: marked for addition, marked for removal, has conflicts, is locked, is missing, has changes or contains items that have changes, and no changes. | 0.661578 |
8,990,083 | 10 | 11 | 10. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment at a streaming database feeder; ignoring Joint Photographic Experts Group (JPEG) documents from the data; updating tags for each user in the network environment using a user-sub stream created for the user by the streaming database feeder, wherein each user-sub stream includes at least a portion of the data propagating in the network environment, wherein the tags are words and phrases that are associated with each user, wherein the data includes documents and, for at least a portion of the documents in the data, each original document is copied to create an anonymous document and a document that contains selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged, wherein documents that include data in a blacklist are dropped, and wherein the anonymous documents contain a concept field and some of the data in the anonymous documents is selected for the whitelist, and wherein the document that contains selected words does not include the concept field; assigning a weight to the selected words based on at least one characteristic associated with the data; associating the selected words to an individual, wherein the weight for a selected word is higher if the individual propagates the data; and generating a resultant composite of the selected words that are tagged. | 10. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment at a streaming database feeder; ignoring Joint Photographic Experts Group (JPEG) documents from the data; updating tags for each user in the network environment using a user-sub stream created for the user by the streaming database feeder, wherein each user-sub stream includes at least a portion of the data propagating in the network environment, wherein the tags are words and phrases that are associated with each user, wherein the data includes documents and, for at least a portion of the documents in the data, each original document is copied to create an anonymous document and a document that contains selected words within the data based on a whitelist, wherein the whitelist includes a plurality of designated words to be tagged, wherein documents that include data in a blacklist are dropped, and wherein the anonymous documents contain a concept field and some of the data in the anonymous documents is selected for the whitelist, and wherein the document that contains selected words does not include the concept field; assigning a weight to the selected words based on at least one characteristic associated with the data; associating the selected words to an individual, wherein the weight for a selected word is higher if the individual propagates the data; and generating a resultant composite of the selected words that are tagged. 11. The logic of claim 10 , the processor being further operable to perform operations comprising: partitioning the resultant composite amongst a plurality of individuals associated with the data propagating in the network environment; and generating a social graph that identifies a relationship between a selected individual and the plurality of individuals based on a plurality of words exchanged between the selected individual and the plurality of individuals. | 0.5 |
7,562,069 | 29 | 30 | 29. The computer system of claim 21 wherein maintaining a query ontology comprises arranging one or more categories within the query ontology as nodes in a directed acyclic graph. | 29. The computer system of claim 21 wherein maintaining a query ontology comprises arranging one or more categories within the query ontology as nodes in a directed acyclic graph. 30. The computer system of claim 29 wherein identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query comprises identifying multiple categories included in the query ontology that are ancestor or child categories of categories included in the query ontology with which the first portion of the received query is associated. | 0.582046 |
9,460,082 | 18 | 22 | 18. A method for providing annotations for revising a message, comprising: receiving, using a processor of a computer, a message to be sent from a sender to a recipient; receiving selection of a dialect for the sender and a dialect for the recipient; receiving a level of misunderstanding that is acceptable to the recipient; selecting a meaning map associated with the sender based on the dialect for the sender to determine a first context of the message that indicates a first way in which the message is understood; selecting a meaning map associated with the recipient based on the dialect for the recipient to determine a second context of the message that indicates a second way in which the message is understood; parsing the message into sub-constructs; comparing the sub-constructs in the meaning map associated with the sender and the meaning map associated with the recipient to identify words and phrases where there are differences between perceptions of the sender and the recipient; and in response to the comparisons showing that the differences are greater than a threshold that is based on the level of misunderstanding that is acceptable, identifying alternative language for the sub-constructs in the message; and providing annotations for the message to the sender based on the alternative language before the message is sent from the sender to the recipient, wherein the annotations indicate the second context of the message. | 18. A method for providing annotations for revising a message, comprising: receiving, using a processor of a computer, a message to be sent from a sender to a recipient; receiving selection of a dialect for the sender and a dialect for the recipient; receiving a level of misunderstanding that is acceptable to the recipient; selecting a meaning map associated with the sender based on the dialect for the sender to determine a first context of the message that indicates a first way in which the message is understood; selecting a meaning map associated with the recipient based on the dialect for the recipient to determine a second context of the message that indicates a second way in which the message is understood; parsing the message into sub-constructs; comparing the sub-constructs in the meaning map associated with the sender and the meaning map associated with the recipient to identify words and phrases where there are differences between perceptions of the sender and the recipient; and in response to the comparisons showing that the differences are greater than a threshold that is based on the level of misunderstanding that is acceptable, identifying alternative language for the sub-constructs in the message; and providing annotations for the message to the sender based on the alternative language before the message is sent from the sender to the recipient, wherein the annotations indicate the second context of the message. 22. The computer system of claim 18 , further comprising: in response to providing the annotations, receiving changes to the message. | 0.766667 |
7,577,655 | 2 | 9 | 2. The method of claim 1 where the determining includes: determining, by the processor, a plurality of metric values for the news source. | 2. The method of claim 1 where the determining includes: determining, by the processor, a plurality of metric values for the news source. 9. The method of claim 2 where the generating includes: determining, by the processor, for each metric value in the plurality of metric values, a percentile score relative to a highest value for that metric, adding, by the processor, the percentile scores to obtain the quality value. | 0.525084 |
8,788,516 | 15 | 20 | 15. A non-transitory computer-readable medium comprising software, the software when executed by one or more processors operable to perform operations comprising: determining a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating a social object matrix using the determined social interactions; generating a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining text from the social objects of the determined social interactions; generating a term-document matrix (TDM) using the determined text; generating a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating an index using the determined text; and performing a query using the social brain, the semantic brain, and the index. | 15. A non-transitory computer-readable medium comprising software, the software when executed by one or more processors operable to perform operations comprising: determining a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating a social object matrix using the determined social interactions; generating a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining text from the social objects of the determined social interactions; generating a term-document matrix (TDM) using the determined text; generating a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating an index using the determined text; and performing a query using the social brain, the semantic brain, and the index. 20. The non-transitory computer-readable medium of claim 15 , wherein the social object matrix comprises a person-by-social object matrix or a social object-by-person matrix. | 0.884921 |
9,056,256 | 1 | 7 | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. | 1. A method comprising: capturing, using one or more computing devices, actions taken by a user within an online environment; wherein capturing actions includes at least one of: determining which type of items are purchased online by the user; determining which type of computer programs are downloaded and/or used by the user; determining topics reflected in electronic communications of the user; determining topics reflected in items purchased online by the user; determining to which online social communities the user belongs; determining interests reflected in comments made by the user in online social applications; determining persons to whom the user is socially connected in online social applications; capturing how an avatar of the user interacts with one or more other characters in the online environment; randomly inserting questions that relate to play personality with other questions presented to the user within an online game environment; capturing one or more images of the user as the user engages in an activity within the online environment; detecting eye movement of the user as the user engages in an activity within the online environment; detecting pupil size changes of the user as the user engages in an activity within the online environment; or monitoring how the user makes purchases at or interacts with virtual stores or venues; wherein capturing actions further comprises presenting an online assessment that includes a series of questions designed to assess which play type, of a plurality of play types, satisfies the user's need for play; automatically determining a play personality of the user based, at least in part, on the actions of the user that are captured using the one or more computing devices; wherein automatically determining the play personality of the user comprises: estimating a degree to which each of the plurality of play types satisfies the user's need for play; and determining that one or more particular play types, of the plurality of play types, best satisfy the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; storing play personality data that reflects the play personality of the user; and wherein the method is performed by one or more computing devices. 7. The method of claim 1 wherein: capturing actions taken by the user includes determining topics reflected in electronic communications of the user; and automatically determining a play personality of the user is based, at least in part, on the topics reflected in electronic communications of the user. | 0.556851 |
9,378,201 | 1 | 2 | 1. Non-transitory computer storage having stored thereon executable code that directs a computer system to perform a method of automatic text evaluation, the method comprising: detecting whether a particular readability issue exists in text, notwithstanding that the text may be otherwise grammatically correct; scanning for at least one sign that indicates the possible occurrence or absence of the readability issue, the at least one sign comprising the term “that”; and implementing correction logic for correcting the issue, the correction logic specifying a proposed edit, the edit comprising one or some combination of the following: deleting text; adding text; and/or reordering text, wherein scanning for at least one sign further comprises scanning for “that” as a primary sign and scanning for additional signs; and wherein scanning for additional signs comprises scanning for one or some combination of the following: “what”, “who”, “it,” and/or a “to be” verb; the method further comprising: determining if the word immediately preceding “that” is a “to be” verb and if so, determining if the term “it” immediately precedes the “to be” verb and if so, determining if the term “what” or the term “who” immediately precedes “it” and conveying the proposed edit to a user through a computer interface. | 1. Non-transitory computer storage having stored thereon executable code that directs a computer system to perform a method of automatic text evaluation, the method comprising: detecting whether a particular readability issue exists in text, notwithstanding that the text may be otherwise grammatically correct; scanning for at least one sign that indicates the possible occurrence or absence of the readability issue, the at least one sign comprising the term “that”; and implementing correction logic for correcting the issue, the correction logic specifying a proposed edit, the edit comprising one or some combination of the following: deleting text; adding text; and/or reordering text, wherein scanning for at least one sign further comprises scanning for “that” as a primary sign and scanning for additional signs; and wherein scanning for additional signs comprises scanning for one or some combination of the following: “what”, “who”, “it,” and/or a “to be” verb; the method further comprising: determining if the word immediately preceding “that” is a “to be” verb and if so, determining if the term “it” immediately precedes the “to be” verb and if so, determining if the term “what” or the term “who” immediately precedes “it” and conveying the proposed edit to a user through a computer interface. 2. The non-transitory computer storage of claim 1 , wherein, if all the conditions are met, the correction logic comprises specifying the following proposed edit: deleting the term “it”; deleting the “to be” verb; and deleting the term “that”. | 0.508097 |
9,953,176 | 1 | 6 | 1. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of target entities is metadata related to the user activity and requires anonymization; making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; after making the determination: assigning an anonymized identity to the subset of target entities; generating an anonymization identifier for each target entity in the subset of target entities to obtain a plurality of anonymization identifiers each comprising the anonymized identity; and anonymizing user activity, based on the anonymization dictionary previously generated by the computing system by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized activity record. | 1. A method for processing activity records, the method comprising: establishing, by a computing system, an anonymization dictionary based on user activity encountered by the computing system, by: obtaining, by an endpoint agent executing on the computing system, an activity record, wherein the activity record comprises metadata documenting the user activity; generating, by an activity monitoring engine of the computing system that is operatively connected to the endpoint agent, the anonymization dictionary, wherein generating the anonymization dictionary comprises: detecting, in the activity record, a plurality of target entities, wherein each of target entities is metadata related to the user activity and requires anonymization; making a determination that a resource is associated with a subset of the target entities of the plurality of target entities; after making the determination: assigning an anonymized identity to the subset of target entities; generating an anonymization identifier for each target entity in the subset of target entities to obtain a plurality of anonymization identifiers each comprising the anonymized identity; and anonymizing user activity, based on the anonymization dictionary previously generated by the computing system by: processing, by an anonymization engine executing on the computing system, the activity record using the anonymization dictionary to obtain an anonymized activity record, by: replacing, in the activity record, target entities with their corresponding anonymized identifiers, specified in the anonymization dictionary; and storing the anonymized activity record. 6. The method of claim 1 , further comprising: receiving an additional activity record; processing the additional activity record to obtain a second plurality of target entities; making a second determination that the anonymization dictionary does not have an entry to anonymize at least one of the second plurality of target entities; based on the second determination, updating the anonymization dictionary to include at least one additional entry in order to obtain an updated anonymization dictionary; and processing the additional activity record using the updated anonymization dictionary to obtain a second anonymized activity record. | 0.5 |
8,166,161 | 17 | 18 | 17. The apparatus of claim 15 , further comprising: a database configured to store the resultant data in a hashed format. | 17. The apparatus of claim 15 , further comprising: a database configured to store the resultant data in a hashed format. 18. The apparatus of claim 17 , wherein the database is configured to partition the resultant composite amongst a plurality of individuals associated with the data propagating in the network environment. | 0.5 |
8,386,454 | 13 | 15 | 13. A non-transitory computer readable media comprising program code that when executed by a programmable processor causes the processor to perform a method for generating search results, comprising: receiving a search request including at least one search term; accessing a corpus of data relating to web content to determine relevant content for inclusion in a search result set on the basis of the search request; identifying a plurality of semantic object types relating to a plurality of data formats of the web content in the search result set wherein each web content in the search result set is associated with a given one of the plurality of semantic object types, the plurality of semantic object types comprising at least two of a video, an image, and a textual type of web content; selecting a predetermined number of the identified semantic object types based on most occurrences of the identified semantic object types within the search result set; generating an object filter for each of the selected semantic object types; generating a search result output display presenting therein at least a portion of the search result set and a sidebar including active data links for each object filter generated; and toggling the search result output display, therewith filtering display of a subset of the at least a portion of the search result set in response to a selection of a given active data link, the updated search results consisting of web content having a semantic object type associated with the selected active data link. | 13. A non-transitory computer readable media comprising program code that when executed by a programmable processor causes the processor to perform a method for generating search results, comprising: receiving a search request including at least one search term; accessing a corpus of data relating to web content to determine relevant content for inclusion in a search result set on the basis of the search request; identifying a plurality of semantic object types relating to a plurality of data formats of the web content in the search result set wherein each web content in the search result set is associated with a given one of the plurality of semantic object types, the plurality of semantic object types comprising at least two of a video, an image, and a textual type of web content; selecting a predetermined number of the identified semantic object types based on most occurrences of the identified semantic object types within the search result set; generating an object filter for each of the selected semantic object types; generating a search result output display presenting therein at least a portion of the search result set and a sidebar including active data links for each object filter generated; and toggling the search result output display, therewith filtering display of a subset of the at least a portion of the search result set in response to a selection of a given active data link, the updated search results consisting of web content having a semantic object type associated with the selected active data link. 15. The computer readable media of claim 13 , wherein the object filter filters search results based on a single web location content source. | 0.654412 |
8,272,028 | 9 | 10 | 9. A non-transitory computer-readable medium for managing access to electronic documents, the computer-readable medium carrying instructions which, when processed by one or more processors, causes: at a network device, detecting a request to access a particular electronic document stored on the network device; and in response to detecting the request to access the particular electronic document stored on the network device, applying a document retention policy to the particular electronic document by: determining that the particular electronic document belongs to a particular electronic document retention classification from a plurality of electronic document retention classifications, retrieving document retention policy data for the particular electronic document retention classification, wherein the document retention policy data for the particular document retention classification specifies one or more deletion criteria for the particular document retention classification, determining whether any of the one or more deletion criteria for the particular electronic document retention classification are satisfied, if any of the one or more deletion criteria for the particular electronic document retention classification are satisfied, then causing the particular electronic document to be deleted, if none of the one or more deletion criteria for the particular electronic document retention classification are satisfied, then applying a document security policy to the particular electronic document by: determining that the particular electronic document belongs to a particular document security classification from the plurality of document security classifications, retrieving document security policy data for the particular document security classification, wherein the document security policy data for the particular document security classification specifies one or more access criteria for the particular document security classification, determining, based upon the one or more access criteria for the particular document security classification and one or more attributes of a user associated with the request to access the particular electronic document, whether the user is authorized to access the particular electronic document, and if the user is not authorized to access the particular electronic document, then preventing access to the particular electronic document. | 9. A non-transitory computer-readable medium for managing access to electronic documents, the computer-readable medium carrying instructions which, when processed by one or more processors, causes: at a network device, detecting a request to access a particular electronic document stored on the network device; and in response to detecting the request to access the particular electronic document stored on the network device, applying a document retention policy to the particular electronic document by: determining that the particular electronic document belongs to a particular electronic document retention classification from a plurality of electronic document retention classifications, retrieving document retention policy data for the particular electronic document retention classification, wherein the document retention policy data for the particular document retention classification specifies one or more deletion criteria for the particular document retention classification, determining whether any of the one or more deletion criteria for the particular electronic document retention classification are satisfied, if any of the one or more deletion criteria for the particular electronic document retention classification are satisfied, then causing the particular electronic document to be deleted, if none of the one or more deletion criteria for the particular electronic document retention classification are satisfied, then applying a document security policy to the particular electronic document by: determining that the particular electronic document belongs to a particular document security classification from the plurality of document security classifications, retrieving document security policy data for the particular document security classification, wherein the document security policy data for the particular document security classification specifies one or more access criteria for the particular document security classification, determining, based upon the one or more access criteria for the particular document security classification and one or more attributes of a user associated with the request to access the particular electronic document, whether the user is authorized to access the particular electronic document, and if the user is not authorized to access the particular electronic document, then preventing access to the particular electronic document. 10. The non-transitory computer-readable medium as recited in claim 9 , wherein: the one or more deletion criteria for the particular electronic document classification include a retention time, determining whether any of the one or more deletion criteria for the particular electronic document retention classification are satisfied includes determining whether the particular electronic document has existed for at least the retention time, and if the particular electronic has existed for at least the retention time, then causing the particular electronic document to be deleted. | 0.613907 |
7,805,710 | 50 | 55 | 50. The storage medium of claim 49 wherein said compatibility detection of cache translations and subject code to be translated is determined by a cache key comparison between a cache key associated with the first portion of the subject code and the second portion of the subject code. | 50. The storage medium of claim 49 wherein said compatibility detection of cache translations and subject code to be translated is determined by a cache key comparison between a cache key associated with the first portion of the subject code and the second portion of the subject code. 55. The storage medium of claim 50 wherein the compatibility detection is determined by computing a cache key data structure corresponding to the subject code to be translated to a plurality of second data structures, each second data structure corresponding to a different set of cached target code instructions. | 0.665598 |
9,576,262 | 16 | 17 | 16. The computer-readable storage medium of claim 15 , the method further comprises automatically retraining the hierarchy of predictive models at a predetermined interval based on accumulated data. | 16. The computer-readable storage medium of claim 15 , the method further comprises automatically retraining the hierarchy of predictive models at a predetermined interval based on accumulated data. 17. The computer-readable storage medium of claim 16 , the method further comprises: evaluating performance of the hierarchy of predictive models; and activating for use one of the predictive models of the hierarchy of predictive models that outperforms a parent predictive model. | 0.5 |
7,711,105 | 1 | 15 | 1. A method of processing a call received by a call center, comprising the steps of: obtaining a call at the call center; automatically identifying at least one of an accent and a language spoken by a caller making the call; directing the call to an appropriate operator at a first level of the call center based on at least one of the automatically identified accent and the automatically identified language; automatically translating speech associated with the call from at least one of the automatically identified accent and the automatically identified language spoken by the caller to at least one of an accent and a language understood by an operator at a second level of the call center; and directing the caller to the operator at the second level after the step of directing the call to an appropriate operator at a first level; wherein the call center comprises tiered levels of assistance comprising the first level providing primary assistance and the second level, providing more intense assistance. | 1. A method of processing a call received by a call center, comprising the steps of: obtaining a call at the call center; automatically identifying at least one of an accent and a language spoken by a caller making the call; directing the call to an appropriate operator at a first level of the call center based on at least one of the automatically identified accent and the automatically identified language; automatically translating speech associated with the call from at least one of the automatically identified accent and the automatically identified language spoken by the caller to at least one of an accent and a language understood by an operator at a second level of the call center; and directing the caller to the operator at the second level after the step of directing the call to an appropriate operator at a first level; wherein the call center comprises tiered levels of assistance comprising the first level providing primary assistance and the second level, providing more intense assistance. 15. The method of claim 1 , wherein the step of automatically identifying at least one of an accent and a language spoken by a caller making the call further comprises, during caller speech, automatically switching to an operator who speaks with one of an accent and a language that matches the caller. | 0.5 |
8,805,670 | 1 | 12 | 1. A method for language translation comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen and the user selects the link, the program code causes the translation window to open on the screen in combination with the primary window; in the translation window, indicating input information in a first language; translating the input information from the first language to information in a second language; in the translation window, displaying the information in the second language; and permitting scrolling of the primary window independently from the translation window. | 1. A method for language translation comprising: providing program code to launch a translation window associated with a primary window; providing a link to the program code, wherein when the primary window is displayed on a screen and the user selects the link, the program code causes the translation window to open on the screen in combination with the primary window; in the translation window, indicating input information in a first language; translating the input information from the first language to information in a second language; in the translation window, displaying the information in the second language; and permitting scrolling of the primary window independently from the translation window. 12. The method of claim 1 wherein the input information in the first language is received in a text box, and before displaying the text box, in the translation window, prompting the user to select a translation language. | 0.670659 |
8,160,977 | 1 | 4 | 1. A computer implemented method for estimating a probability that a future event will occur based on user input, the method comprises: decomposing by one or more computer systems a data input stream to build a first database of precursor data to build at least one predictive model; building by the one or more computer systems at least one model generated by a model building process using the precursor data in the precursor database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; and storing by the one or more computer systems the at least one model in a second database that stores models, with the second database being searchable to permit the at least one model in the second database to be accessed by users; and calculating by the one or more computer systems accuracy of the at least one model against historical data. | 1. A computer implemented method for estimating a probability that a future event will occur based on user input, the method comprises: decomposing by one or more computer systems a data input stream to build a first database of precursor data to build at least one predictive model; building by the one or more computer systems at least one model generated by a model building process using the precursor data in the precursor database, with the at least one model being a model that produces predictions of the likelihood of an event occurring in the future; and storing by the one or more computer systems the at least one model in a second database that stores models, with the second database being searchable to permit the at least one model in the second database to be accessed by users; and calculating by the one or more computer systems accuracy of the at least one model against historical data. 4. The method of claim 1 wherein building the database comprises: retrieving data as data strings from a data source; producing a dataset from the retrieved data strings. | 0.52514 |
9,092,302 | 1 | 3 | 1. A method comprising: at a network connected platform, collecting device version profiles from a plurality of device instances, wherein a device version profile represents a device instance; classifying the device version profiles into a device profile repository; at a network connected platform, receiving a component version query request that includes a query device version profile that is an at least partial device version profile of a first device instance; querying the device profile repository according to the query device version profile of the component version query request and identifying at least one recommended component that is predicted to be compatible with device instances with device version profiles corresponding to the query device version profile; and responding to the query request with the at least one recommended component. | 1. A method comprising: at a network connected platform, collecting device version profiles from a plurality of device instances, wherein a device version profile represents a device instance; classifying the device version profiles into a device profile repository; at a network connected platform, receiving a component version query request that includes a query device version profile that is an at least partial device version profile of a first device instance; querying the device profile repository according to the query device version profile of the component version query request and identifying at least one recommended component that is predicted to be compatible with device instances with device version profiles corresponding to the query device version profile; and responding to the query request with the at least one recommended component. 3. The method of claim 1 , wherein collecting device version profiles from a plurality of device instances comprises collecting carrier information, location information, user configuration information. | 0.587755 |
8,862,505 | 6 | 9 | 6. The method of claim 2 wherein analyzing the searchable information comprises detecting a keyword in the searchable information. | 6. The method of claim 2 wherein analyzing the searchable information comprises detecting a keyword in the searchable information. 9. The method of claim 6 wherein the keyword is automatically determined based on trending information. | 0.712291 |
8,181,224 | 17 | 18 | 17. The computer implemented method of claim 16 , wherein the first action of the user is a read function and the second action of the user is a write function. | 17. The computer implemented method of claim 16 , wherein the first action of the user is a read function and the second action of the user is a write function. 18. The computer implemented method of claim 17 , wherein the target object is a copy, created by the user, of the source object. | 0.5 |
7,698,125 | 11 | 13 | 11. A method as in claim 1 , further comprising, through execution of instructions stored in memory, further processing the set of values to sum weights based on information learned from said tree transducer information and said transducer information. | 11. A method as in claim 1 , further comprising, through execution of instructions stored in memory, further processing the set of values to sum weights based on information learned from said tree transducer information and said transducer information. 13. A method as in claim 11 , wherein said further processing comprises observing counts and determining each time a rule gets used, and increasing a probability of that rule each time the rule gets used. | 0.538462 |
9,544,263 | 1 | 2 | 1. A method for displaying dynamic content from a networked post in a text message, the method performed by a computer system, the method comprising: receiving a text message, the text message displaying dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; displaying the text message to a user; initiating a call to a first server-side script to retrieve the number of likes that the networked post has received, a client-side handler function being associated with the first server-side script; after completion of the first server-side script, executing the client-side handler function to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; displaying a like button for liking the networked post; in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the act of transmitting the indication of the user liking the networked post to the server comprises initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; displaying a comment field for accepting a comment from the user; in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. | 1. A method for displaying dynamic content from a networked post in a text message, the method performed by a computer system, the method comprising: receiving a text message, the text message displaying dynamic content from a networked post, wherein the networked post is accessible on a network at a network location; wherein the networked post includes a photo or video, and the photo or video is displayed in the text message; displaying the text message to a user; initiating a call to a first server-side script to retrieve the number of likes that the networked post has received, a client-side handler function being associated with the first server-side script; after completion of the first server-side script, executing the client-side handler function to process a return value of the first server-side script and cause the display of the number of likes that the networked post has received; displaying a like button for liking the networked post; in response to activation of the like button, transmitting an indication of the user liking the networked post to a server to cause a representation of the user's act of liking the networked post to be displayed with the networked post; wherein the act of transmitting the indication of the user liking the networked post to the server comprises initiating a call to a second server-side script to cause the indication of the user liking the networked post to be stored in a database accessible to the server; displaying one or more comments from one or more other users about the networked post in a comment section associated with the text message; displaying a comment field for accepting a comment from the user; in response to the user submitting a comment via the comment field, initiating a call to a third server-side script to cause text of the user-submitted comment to be stored in the database accessible to the server; in response to submission of a new comment by the user or another user, dynamically updating the display of comments associated with the text message to include the new comment. 2. The method of claim 1 , wherein the text message is a TCP/IP text message. | 0.891854 |
8,332,188 | 1 | 3 | 1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ( x ) = w offset + ∑ i = 0 n w i × f i ( x ) × NL i ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data. | 1. A tangible computer-readable medium having recorded thereon statements and instructions for execution by a computer of a method to generate at least one mathematical expression describing a performance characteristic of a system, the system associated with variables and with pre-determined data related to the performance characteristic of the system, the method comprising steps of: generating at least one initial mathematical expression having a pre-defined canonical form and being a function of the variables, the at least one initial mathematical expression having operators operating on the variables, the operators being selected from a pre-defined group of operators, the at least one initial mathematical expression describing the performance characteristic of the system; wherein, the variables of the system are representable as a vector {right arrow over (x)} and the canonical form of an expression F({right arrow over (x)}) is representable as F ( x ) = w offset + ∑ i = 0 n w i × f i ( x ) × NL i ( x ) , “n” being an integer, w offset , being an offset value, w i being weights, f i (x) including at least one of a polynomial function of the variables and a rational function of the variables, and NL i ({right arrow over (x)}) being a non-linear function of the variables, with NL 0 (x)=1; generating calculated data using the at least one initial mathematical expression; calculating an output of a goal function in accordance with the pre-determined data and the calculated data; determining that the goal function is outside a pre-defined range; and iteratively performing the following steps a-c until an additional output of the goal function is within the pre-defined range: a. modifying at least one input mathematical expression in accordance with a search algorithm to produce at least one modified mathematical expression having the canonical form and being a function of the variables, the search algorithm to search at least the pre-defined group of operators to identify operators with which to modify the at least one input mathematical expression, the at least one input mathematical expression being the at least one initial mathematical expression in a first iteration of steps a-c, the at least one input mathematical expression being the at least one modified mathematical expression in subsequent iterations of steps a-c; b. generating additional calculated data using the at least one modified mathematical expression; and c. calculating the additional output of the goal function based on the additional calculated data and the pre-determined data. 3. The tangible computer-readable medium of claim 1 wherein, the goal function is a multi-objective goal function for minimizing error and for minimizing complexity. | 0.777628 |
9,336,689 | 13 | 15 | 13. A method of providing error correction in a caption-based communication system, the method comprising: receiving, at a first communication device associated with a call assistant within a captioning service, a voice signal during a real-time communication session between a second communication device associated with a hearing-impaired user and a third communication device; receiving, at a second communication device, the voice signal from the first communication device within the remote communication device during the real-time communication session; generating, at the first communication device, a text transcription for the voice signal during the real-time communication session using a speech recognition program; transmitting, from the first communication device to the second communication device, a first block of text of the text transcription; receiving, at the second communication device, the first block of text of the text transcription of the voice signal from the remote captioning service; displaying the first block of text on a second electronic display of the second communication device during the real-time communication session; receiving, through a first input device of the first communication device, corrections corresponding to an error within at least a portion of a text transcription after of the text transcription to the second communication device has already occurred; generating, at the first communication device, a replacement block of text responsive to the corrections; transmitting the replacement block of text from the first communication device to the second communication device as an inline correction for the error with instructions for the second communication device to indicate that the block of text is a correction for the portion of the text transcription to be replaced; receiving, at the second communication device, the replacement block of text from the remote captioning service after the first block of text has been received and displayed by the second electronic display; and displaying the replacement block of text on the second electronic display as an inline correction for the first block of text previously displayed by the second communication device. | 13. A method of providing error correction in a caption-based communication system, the method comprising: receiving, at a first communication device associated with a call assistant within a captioning service, a voice signal during a real-time communication session between a second communication device associated with a hearing-impaired user and a third communication device; receiving, at a second communication device, the voice signal from the first communication device within the remote communication device during the real-time communication session; generating, at the first communication device, a text transcription for the voice signal during the real-time communication session using a speech recognition program; transmitting, from the first communication device to the second communication device, a first block of text of the text transcription; receiving, at the second communication device, the first block of text of the text transcription of the voice signal from the remote captioning service; displaying the first block of text on a second electronic display of the second communication device during the real-time communication session; receiving, through a first input device of the first communication device, corrections corresponding to an error within at least a portion of a text transcription after of the text transcription to the second communication device has already occurred; generating, at the first communication device, a replacement block of text responsive to the corrections; transmitting the replacement block of text from the first communication device to the second communication device as an inline correction for the error with instructions for the second communication device to indicate that the block of text is a correction for the portion of the text transcription to be replaced; receiving, at the second communication device, the replacement block of text from the remote captioning service after the first block of text has been received and displayed by the second electronic display; and displaying the replacement block of text on the second electronic display as an inline correction for the first block of text previously displayed by the second communication device. 15. The method of claim 13 , further comprising displaying the replacement block of text as an inline correction on a first electronic display of the first communication device to be visible to the call assistant during the real-time communication session. | 0.581699 |
9,384,282 | 1 | 3 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. 3. The method of claim 1 wherein searching for the exact match begins searching the source information located in a designated fact checking database, then goes to a broader set of source information, and repeatedly goes to broader sets of source information until a broadest source information set has been exhausted; wherein utilizing pattern matching begins utilizing the source information located in the designated fact checking database, then goes to the broader set of source information, and repeatedly goes to broader sets of source information until the broadest source information set has been exhausted; and wherein the natural language search begins searching the source information located in the designated fact checking database, then goes to the broader set of source information, and repeatedly goes to broader sets of source information until the broadest source information set has been exhausted. | 0.595679 |
9,241,223 | 29 | 37 | 29. A directional filter comprising: a processor; a non-transitory memory including instructions that when executed by the processor cause the directional filter to: determine one or more directional indicator values from composite audible signal data, the composite audible signal data including a respective audible signal data component from each of a plurality of audio sensors; determine a gain function from the one or more directional indicator values, the gain function targeting one or more portions of the composite audible signal data, wherein determining the gain function from the one or more directional indicator values includes determining, for each directional indicator value, a respective component-gain function based on the directional indicator value and a corresponding target value associated with the directional indicator value, and the respective component-gain function includes a distance function of the directional indicator value and the corresponding target value; and filter the composite audible signal data using the gain function in order to produce directionally filtered audible signal data, the directionally filtered audible signal data including one or more portions of the composite audible signal data that have been changed by filtering with the gain function. | 29. A directional filter comprising: a processor; a non-transitory memory including instructions that when executed by the processor cause the directional filter to: determine one or more directional indicator values from composite audible signal data, the composite audible signal data including a respective audible signal data component from each of a plurality of audio sensors; determine a gain function from the one or more directional indicator values, the gain function targeting one or more portions of the composite audible signal data, wherein determining the gain function from the one or more directional indicator values includes determining, for each directional indicator value, a respective component-gain function based on the directional indicator value and a corresponding target value associated with the directional indicator value, and the respective component-gain function includes a distance function of the directional indicator value and the corresponding target value; and filter the composite audible signal data using the gain function in order to produce directionally filtered audible signal data, the directionally filtered audible signal data including one or more portions of the composite audible signal data that have been changed by filtering with the gain function. 37. The directional filter of claim 29 , wherein the non-transitory memory also includes instructions that when executed by the processor cause the directional filter to combine one or more of the respective component-gain functions. | 0.793073 |
8,441,670 | 11 | 12 | 11. A printer for printing data comprising: a. a memory; and b. at least one processor executing a plurality of programmatic instructions wherein, upon execution, said programmatic instructions: i. perform a first analysis of said data to identify a page description language; and ii. if no page description language is identified by said first analysis, perform a plurality of additional processing activities wherein said plurality of additional processing activities is performed concurrent with a second analysis of said data to identify a page description language and wherein if the page description language is identified by said first analysis, said second analysis is not performed. | 11. A printer for printing data comprising: a. a memory; and b. at least one processor executing a plurality of programmatic instructions wherein, upon execution, said programmatic instructions: i. perform a first analysis of said data to identify a page description language; and ii. if no page description language is identified by said first analysis, perform a plurality of additional processing activities wherein said plurality of additional processing activities is performed concurrent with a second analysis of said data to identify a page description language and wherein if the page description language is identified by said first analysis, said second analysis is not performed. 12. The printer of claim 11 wherein if no page description language is identified by said second analysis, the data is printed as ASCII text. | 0.875661 |
8,005,679 | 1 | 5 | 1. A method for operating a global speech user interface (GSUI), comprising: providing a speech input device having a switch, where the GSUI is activated by user activation of the switch; performing speech recognition to transcribe spoken commands into commands acceptable by a communications system; using the transcribed spoken commands to navigate among applications hosted on said communications system; displaying a set of immediate speech feedback overlays including visual cues to guide a user in issuing proper spoken commands where each immediate speech feedback overlay provides non-textual feedback information about a state of said communications system, comprising: (a) checking if a current screen is speech-enabled when said switch is activated; (b) if the current screen is speech-enabled, displaying a first tab signaling that a speech input system is activated; (c) if the current screen is not speech-enabled, displaying a second tab signaling a non speech-enabled alert, said second tab staying on screen for a first interval; (d) if said switch is re-activated, repeating Step(a); (e) if said switch is not deactivated within a second interval, interrupting recognition; (f) if said switch is deactivated after a third interval lapsed but before said second interval in Step (e) lapsed, displaying a third tab signaling that speech recognition is in processing; and (g) if said switch was deactivated before said third interval in Step (f) lapsed, removing any tab on the screen. | 1. A method for operating a global speech user interface (GSUI), comprising: providing a speech input device having a switch, where the GSUI is activated by user activation of the switch; performing speech recognition to transcribe spoken commands into commands acceptable by a communications system; using the transcribed spoken commands to navigate among applications hosted on said communications system; displaying a set of immediate speech feedback overlays including visual cues to guide a user in issuing proper spoken commands where each immediate speech feedback overlay provides non-textual feedback information about a state of said communications system, comprising: (a) checking if a current screen is speech-enabled when said switch is activated; (b) if the current screen is speech-enabled, displaying a first tab signaling that a speech input system is activated; (c) if the current screen is not speech-enabled, displaying a second tab signaling a non speech-enabled alert, said second tab staying on screen for a first interval; (d) if said switch is re-activated, repeating Step(a); (e) if said switch is not deactivated within a second interval, interrupting recognition; (f) if said switch is deactivated after a third interval lapsed but before said second interval in Step (e) lapsed, displaying a third tab signaling that speech recognition is in processing; and (g) if said switch was deactivated before said third interval in Step (f) lapsed, removing any tab on the screen. 5. The method of claim 1 , wherein said first interval in Step (c) is approximately ten seconds. | 0.932489 |
8,516,437 | 11 | 19 | 11. An apparatus comprising: a processor; and a type library manager to use the processor to group a plurality of Extensible Mark-up Language (XML) schema definition (XSD) types, each XSD type being defined in an individual XSD file according to a pre-defined rule, use the processor to bundle the plurality of individual XSD types into a type library, the type library including a type information file to register the individual XSD types in the type library, the type library further including a type dependencies file to register dependencies between the individual XSD types in the same or a different type library, generate Java artifacts from the XSD types, and associate the Java artifacts with corresponding XSD types in the type information file of the type library, the type library manager including a mechanism for importing types from a different type library, when defining derived types or aggregated types. | 11. An apparatus comprising: a processor; and a type library manager to use the processor to group a plurality of Extensible Mark-up Language (XML) schema definition (XSD) types, each XSD type being defined in an individual XSD file according to a pre-defined rule, use the processor to bundle the plurality of individual XSD types into a type library, the type library including a type information file to register the individual XSD types in the type library, the type library further including a type dependencies file to register dependencies between the individual XSD types in the same or a different type library, generate Java artifacts from the XSD types, and associate the Java artifacts with corresponding XSD types in the type information file of the type library, the type library manager including a mechanism for importing types from a different type library, when defining derived types or aggregated types. 19. The apparatus of claim 11 being further configured to inline XSD types from the type library into a WSDL. | 0.785433 |
7,783,672 | 1 | 7 | 1. A computer implemented method of managing group policy related data comprising: providing one or more interfaces to manage group policy related data, the interfaces including two or more selectable group policy objects, the group policy objects comprising at least one of: a collection of files, an object or an attribute located in a network; providing, from a unified view, the ability to view, manage, and search across one or more sites and to copy and import data to the group policy objects; receiving a selection of one of the group policy objects; providing a custom context menu of items related to the selected group policy object, wherein the custom context menu of items is customized based on context for the selected group policy object; receiving a selection of one of the menu items; accessing structured context menu data in a data structure in response to the selection of one of the menu items; providing a custom context menu of commands for the selected one of the menu items based on the structured context menu data, wherein at least one of the commands in the custom context menu of commands is a snap-in supplied command; receiving from the snap-in tool one or more flags for the context menu of commands, wherein at least one of the flags indicates how to display one of the commands in the context menu of commands; and receiving data for one or more items of the context menu of commands from the snap-in tool in a customized result pane area, wherein at least one of the providing the custom context menu of items or the providing the custom context menu of commands comprises: processing a context menu map into a static data structure, the context menu map including macro declarations, the macros declarations including definitions of methods; and calling methods in a base class to operate on the static data structure to generate at least one of the context menu of items or the context menu of commands, for a specific node type, the methods in the base class being generic to a plurality of node types include the specific node type. | 1. A computer implemented method of managing group policy related data comprising: providing one or more interfaces to manage group policy related data, the interfaces including two or more selectable group policy objects, the group policy objects comprising at least one of: a collection of files, an object or an attribute located in a network; providing, from a unified view, the ability to view, manage, and search across one or more sites and to copy and import data to the group policy objects; receiving a selection of one of the group policy objects; providing a custom context menu of items related to the selected group policy object, wherein the custom context menu of items is customized based on context for the selected group policy object; receiving a selection of one of the menu items; accessing structured context menu data in a data structure in response to the selection of one of the menu items; providing a custom context menu of commands for the selected one of the menu items based on the structured context menu data, wherein at least one of the commands in the custom context menu of commands is a snap-in supplied command; receiving from the snap-in tool one or more flags for the context menu of commands, wherein at least one of the flags indicates how to display one of the commands in the context menu of commands; and receiving data for one or more items of the context menu of commands from the snap-in tool in a customized result pane area, wherein at least one of the providing the custom context menu of items or the providing the custom context menu of commands comprises: processing a context menu map into a static data structure, the context menu map including macro declarations, the macros declarations including definitions of methods; and calling methods in a base class to operate on the static data structure to generate at least one of the context menu of items or the context menu of commands, for a specific node type, the methods in the base class being generic to a plurality of node types include the specific node type. 7. The method of claim 1 , further comprising receiving from the snap-in tool one or more command codes for one or more commands of the context menu of commands. | 0.660338 |
9,338,071 | 31 | 33 | 31. A method for conveying locale information for an electronic device, comprising: receiving, from a remote device and via a network interface of at least one network interfaces of an electronic device, a request for active or available locales for the electronic device; sending, to the remote device and via the network interface, a message in a locale profile format including a list of available locales, wherein the message comprises: a version field that indicates a version of schema used to transmit the list of available locales; an active local field that indicates a locale currently being used by the electronic device; and an available locales field that indicates which locales are available for use; and enabling the remote device to write to the version field using a profile field other than a locale profile, wherein enabling the remote device to write to the version field using a profile other than the locale profile comprises: changing a value of the version field to a new value in response to a request to update software command as part of a software update profile used to update code stored in the memory of the electronic device; and updating the schema to a version of the schema corresponding to new value. | 31. A method for conveying locale information for an electronic device, comprising: receiving, from a remote device and via a network interface of at least one network interfaces of an electronic device, a request for active or available locales for the electronic device; sending, to the remote device and via the network interface, a message in a locale profile format including a list of available locales, wherein the message comprises: a version field that indicates a version of schema used to transmit the list of available locales; an active local field that indicates a locale currently being used by the electronic device; and an available locales field that indicates which locales are available for use; and enabling the remote device to write to the version field using a profile field other than a locale profile, wherein enabling the remote device to write to the version field using a profile other than the locale profile comprises: changing a value of the version field to a new value in response to a request to update software command as part of a software update profile used to update code stored in the memory of the electronic device; and updating the schema to a version of the schema corresponding to new value. 33. The method of claim 31 , wherein the active locale field indicates a locale of a plurality of available locales that the electronic device currently employs in communication with the remote device, with users, or with a remote service, wherein the active locale field comprises an active locale field tag including a tag value of 0x0001 that indicates that the following information identifies an active locale for the electronic device. | 0.5 |
7,953,279 | 9 | 16 | 9. In a computing environment, a system comprising an online recognizer implemented by a computer and configured to process an handwritten input to produce first data corresponding to online recognition results, and a combination mechanism implemented by the computer and configured to process the first data and second data to output a final recognition result set, wherein an offline recognizer processes the handwritten input to produce the second data, and wherein the second data corresponds to offline recognition results. | 9. In a computing environment, a system comprising an online recognizer implemented by a computer and configured to process an handwritten input to produce first data corresponding to online recognition results, and a combination mechanism implemented by the computer and configured to process the first data and second data to output a final recognition result set, wherein an offline recognizer processes the handwritten input to produce the second data, and wherein the second data corresponds to offline recognition results. 16. The system of claim 9 wherein the online recognizer produces the first data as radical level data used in constructing a radical graph, wherein the offline recognizer produces the second data as radical level data, and wherein the combination mechanism uses the second data to re-score the radical graph data in the graph, and further comprising a search mechanism that processes paths in the graph to produce the final recognition result set. | 0.5 |
7,813,929 | 13 | 22 | 13. A computer program product in a non-transitory computer readable storage medium for transforming an input sequence of unstructured speech recognition text into output structured document text, the product comprising: program code for performing transformation modeling of a source unstructured speech recognition text to create a most likely word sequence output structured document text, the program code for performing transformation modeling including: program code for providing a probabilistic word substitution model to establish association probabilities indicative of target structured document text correlating with source unstructured speech recognition text; program code for considering a set of candidate sequences of structured document text based on the word substitution model with respect to an input sequence of unstructured speech recognition text; program code for evaluating the likelihood of candidates corresponding to the input sequence of unstructured speech recognition text; program code for determining as an output a most likely sequence of structured document text. | 13. A computer program product in a non-transitory computer readable storage medium for transforming an input sequence of unstructured speech recognition text into output structured document text, the product comprising: program code for performing transformation modeling of a source unstructured speech recognition text to create a most likely word sequence output structured document text, the program code for performing transformation modeling including: program code for providing a probabilistic word substitution model to establish association probabilities indicative of target structured document text correlating with source unstructured speech recognition text; program code for considering a set of candidate sequences of structured document text based on the word substitution model with respect to an input sequence of unstructured speech recognition text; program code for evaluating the likelihood of candidates corresponding to the input sequence of unstructured speech recognition text; program code for determining as an output a most likely sequence of structured document text. 22. A computer program product according to claim 13 , wherein the word substitution model uses a combination of speaker dependent models and speaker independent models. | 0.587805 |
8,429,740 | 3 | 5 | 3. The system of claim 1 , wherein altering said search result so that said first tagged portion is not presented comprises redacting said first tagged portion from the search result. | 3. The system of claim 1 , wherein altering said search result so that said first tagged portion is not presented comprises redacting said first tagged portion from the search result. 5. The system of claim 3 , wherein redacting said first tagged portion comprising modifying the search result so there is no indication the first tagged portion was included in the search result. | 0.5 |
7,707,221 | 8 | 9 | 8. A method comprising: receiving, at a computing device, a metadata request, which comprises a plurality of numeric values retrieved from a media item, as metadata corresponding to the media item; running a first query using the received metadata on first and second metadata sources; responsive to retrieving at least one record from the first query performed in response to the metadata request, transmitting metadata from the retrieved at least one record; and responsive to the metadata request and to extracting no metadata from one of the metadata sources queried in the first query performed in response to the metadata request: forming a second query using additional media identification information as metadata corresponding to the media item, the additional metadata being other than the received metadata; running the second query using the additional metadata, so as to retrieve at least one record from the queried metadata source; and responsive to retrieving at least one record in response to the second query, transmitting metadata from the retrieved at least one record in response to the metadata request; creating, at the computing device, an auxiliary record comprising a mapping between the metadata used in the second query and the metadata used in the first query; and storing the auxiliary record in a linking database that is in communication with the computing device. | 8. A method comprising: receiving, at a computing device, a metadata request, which comprises a plurality of numeric values retrieved from a media item, as metadata corresponding to the media item; running a first query using the received metadata on first and second metadata sources; responsive to retrieving at least one record from the first query performed in response to the metadata request, transmitting metadata from the retrieved at least one record; and responsive to the metadata request and to extracting no metadata from one of the metadata sources queried in the first query performed in response to the metadata request: forming a second query using additional media identification information as metadata corresponding to the media item, the additional metadata being other than the received metadata; running the second query using the additional metadata, so as to retrieve at least one record from the queried metadata source; and responsive to retrieving at least one record in response to the second query, transmitting metadata from the retrieved at least one record in response to the metadata request; creating, at the computing device, an auxiliary record comprising a mapping between the metadata used in the second query and the metadata used in the first query; and storing the auxiliary record in a linking database that is in communication with the computing device. 9. The method of claim 8 , wherein the additional media identification information comprises a bar code. | 0.81362 |
9,081,749 | 2 | 3 | 2. The computer-implemented method of claim 1 and further comprising: receiving configuration inputs indicative of the changes of interest, for which posts are to be generated for the given user; and storing the configuration inputs for the given user. | 2. The computer-implemented method of claim 1 and further comprising: receiving configuration inputs indicative of the changes of interest, for which posts are to be generated for the given user; and storing the configuration inputs for the given user. 3. The computer-implemented method of claim 2 wherein identifying the change made as being a change of interest by comparing the change input to the configuration inputs. | 0.585366 |
8,135,711 | 12 | 13 | 12. The method of claim 11 , further comprising: establishing an actor heartbeat based on an activity level, the activity level differentiated between the modalities of communication. | 12. The method of claim 11 , further comprising: establishing an actor heartbeat based on an activity level, the activity level differentiated between the modalities of communication. 13. The method of claim 12 , further comprising: utilizing the actor heartbeat to identify periods of vacation, illness, or business travel. | 0.585799 |
10,162,893 | 5 | 6 | 5. The system according to claim 4 , wherein the pre-assembled media content added to the electronic media collection runs on the virtual display. | 5. The system according to claim 4 , wherein the pre-assembled media content added to the electronic media collection runs on the virtual display. 6. The system of claim 5 , wherein the pre-assembled media content added to the electronic media collection runs on user-selectable frames of the virtual display. | 0.669388 |
7,519,589 | 32 | 33 | 32. A method to enable improved analysis and use of sociological data, the method of comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; depicting communications between a plurality of actors using communication lines between the actors; and enabling graphical queries based on selecting the communication lines between actors. | 32. A method to enable improved analysis and use of sociological data, the method of comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; depicting communications between a plurality of actors using communication lines between the actors; and enabling graphical queries based on selecting the communication lines between actors. 33. The method of claim 32 , wherein the communications lines identify the communication as in-person, via telephone, via email, via TM, via fax, via pager, via conference call. | 0.644578 |
7,904,429 | 1 | 10 | 1. A method of detecting the inclusion of records in an input string of words comprising: a. pre-processing the records such that at least a portion of the records are represented by a string; said string comprising a plurality of sections wherein each of the said sections (chunks) comprises a pre-defined number of elementary words, in the manner that when a chunk is the first chunk in the chunk representation of a record a “Begin of Record” attribute is assigned to the first chunk and when a chunk is the last chunk in the chunk representation of a record, an “End of Record” attribute is assigned to the last chunk; b. searching said string in the manner that the input string is divided into a plurality of chunks and each of said chunks is searched in the records so that if a searched chunk is found to be present in at least one record, a Partial Match Flag is set according to a logic calculation; and, c. calculating an Incremental Hash Function (IHF) for each input chunk; characterized by that whenever a chunk from the input string is found to be in at least one of the records, and the said chunk is associated with an End of Record and the Partial Match is set for this chunk (End of Record chunk), the difference values between the value of the IHF at that “End of Record” chunk and the value of the IHF at each of the previous chunks of the said string, to which a “Begin of Record” is associated (Begin of Record Chunk), is calculated and compared with all pre-recorded values ΔI, calculated during the pre-processing for each record having the said End of Record chunk as last chunk, and associated to the said End of Record chunk; wherein calculating the Incremental Hash Function (IHF)includes: i. starting with an arbitrary initial value; ii. processing sequentially each chunk of the record; and, iii. calculating the IHF for each of said processed chunks as an arbitrarily first predefined function of the said chunk and the previously calculated IHF value where the said chunk has not been associated with a “Begin of Record” attribute, and as a reversible operation of a second predefined function of the said chunk and the previously calculated IHF value where the said chunk has been associated with a “Begin of Record” attribute; d. calculating a ΔI function for each record as the inverse of the said reversible operation of the IHF value at the last chunk of the record, and the said initial value of the IHF for that record; e. associating to each chunk having an “End of Record” attribute, the values of all ΔI function for all records for which that chunk is the last chunk; f. representing the input string as a string of chunks (input string of chunks); h. processing sequentially each chunk of the said input string of chunks, and for each said chunk setting a Partial Match Flag if the said chunk appears in the said list of chunks and if either the said Chunk has a “Begin of Record” attribute, or the Partial Match Flag was previously set; if said chunk has an “End of Record” attribute, calculating a set of ΔJ function values, each one being the result of the inverse of the said reversible operation of the IHF value at the said chunk of the input string of chunks, and the IHF value obtained immediately before calculating the IHF for a chunk having a “Begin of Record” attribute; and g. asserting a “Probable Match” in case the said chunk has an “End of Record” attribute and at least one of the ΔJ functions from the said set of ΔJ functions equals one of the ΔI functions associated to the said chunk wherein a “Probable Match” indicates a high probability that at least one record is included in the input string. | 1. A method of detecting the inclusion of records in an input string of words comprising: a. pre-processing the records such that at least a portion of the records are represented by a string; said string comprising a plurality of sections wherein each of the said sections (chunks) comprises a pre-defined number of elementary words, in the manner that when a chunk is the first chunk in the chunk representation of a record a “Begin of Record” attribute is assigned to the first chunk and when a chunk is the last chunk in the chunk representation of a record, an “End of Record” attribute is assigned to the last chunk; b. searching said string in the manner that the input string is divided into a plurality of chunks and each of said chunks is searched in the records so that if a searched chunk is found to be present in at least one record, a Partial Match Flag is set according to a logic calculation; and, c. calculating an Incremental Hash Function (IHF) for each input chunk; characterized by that whenever a chunk from the input string is found to be in at least one of the records, and the said chunk is associated with an End of Record and the Partial Match is set for this chunk (End of Record chunk), the difference values between the value of the IHF at that “End of Record” chunk and the value of the IHF at each of the previous chunks of the said string, to which a “Begin of Record” is associated (Begin of Record Chunk), is calculated and compared with all pre-recorded values ΔI, calculated during the pre-processing for each record having the said End of Record chunk as last chunk, and associated to the said End of Record chunk; wherein calculating the Incremental Hash Function (IHF)includes: i. starting with an arbitrary initial value; ii. processing sequentially each chunk of the record; and, iii. calculating the IHF for each of said processed chunks as an arbitrarily first predefined function of the said chunk and the previously calculated IHF value where the said chunk has not been associated with a “Begin of Record” attribute, and as a reversible operation of a second predefined function of the said chunk and the previously calculated IHF value where the said chunk has been associated with a “Begin of Record” attribute; d. calculating a ΔI function for each record as the inverse of the said reversible operation of the IHF value at the last chunk of the record, and the said initial value of the IHF for that record; e. associating to each chunk having an “End of Record” attribute, the values of all ΔI function for all records for which that chunk is the last chunk; f. representing the input string as a string of chunks (input string of chunks); h. processing sequentially each chunk of the said input string of chunks, and for each said chunk setting a Partial Match Flag if the said chunk appears in the said list of chunks and if either the said Chunk has a “Begin of Record” attribute, or the Partial Match Flag was previously set; if said chunk has an “End of Record” attribute, calculating a set of ΔJ function values, each one being the result of the inverse of the said reversible operation of the IHF value at the said chunk of the input string of chunks, and the IHF value obtained immediately before calculating the IHF for a chunk having a “Begin of Record” attribute; and g. asserting a “Probable Match” in case the said chunk has an “End of Record” attribute and at least one of the ΔJ functions from the said set of ΔJ functions equals one of the ΔI functions associated to the said chunk wherein a “Probable Match” indicates a high probability that at least one record is included in the input string. 10. The method of claim 1 , wherein the ΔI function for each record is obtained by calculating the inverse of a reversible operation of the IHF value at the last chunk of the record, and the initial value of the IHF for that record. | 0.859903 |
4,078,319 | 13 | 14 | 13. An apparatus for use in teaching reading, said apparatus including generally planar means lying on a first level and adapted to receive reading material for display thereof in generally upwardly facing relation, optical means for reducing the apparent image sizes of at least portions of said reading material, means for supporting said optical means, means for spacing said supporting means apart from said receiving means and for positioning said supporting means in generally parallel relation to said receiving means, and adjustment means for permitting said supporting means to be moved between a plurality of positions to enable said optical image reducing means to be focused upon said reading material disposed on said receiving means. | 13. An apparatus for use in teaching reading, said apparatus including generally planar means lying on a first level and adapted to receive reading material for display thereof in generally upwardly facing relation, optical means for reducing the apparent image sizes of at least portions of said reading material, means for supporting said optical means, means for spacing said supporting means apart from said receiving means and for positioning said supporting means in generally parallel relation to said receiving means, and adjustment means for permitting said supporting means to be moved between a plurality of positions to enable said optical image reducing means to be focused upon said reading material disposed on said receiving means. 14. An apparatus as defined in claim 13 wherein said supporting means comprises a generally flat sheet of transparent material, whereby said optical means may be supported thereon and moved about the surface of said generally flat sheet for viewing said material at a reduced size, and whereby said reading material is able to be viewed through said sheet to facilitate positioning of said optical means. | 0.5 |
9,928,834 | 8 | 10 | 8. An electronic device comprising a processor and a storage medium in which computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the electronic device to: obtain voice information; obtain at least one voice feature in the voice information by identifying the voice information; generate a voice operation instruction based on the voice information; determine a presentation outcome of multimedia data based on the at least one voice feature and the voice operation instruction, wherein the presentation outcome matches the voice feature; and present the multimedia data based on the presentation outcome, wherein: obtaining the at least one voice feature in the voice information by identifying the voice information includes determining, based on the voice information, an age feature of a first user inputting the voice information, determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes: outputting voice reply information based on the voice operation instruction, and setting a voice speed for the voice reply information to be a first voice speed, and the first voice speed corresponds to the age feature. | 8. An electronic device comprising a processor and a storage medium in which computer program instructions are stored, wherein the computer program instructions, when executed by the processor, cause the electronic device to: obtain voice information; obtain at least one voice feature in the voice information by identifying the voice information; generate a voice operation instruction based on the voice information; determine a presentation outcome of multimedia data based on the at least one voice feature and the voice operation instruction, wherein the presentation outcome matches the voice feature; and present the multimedia data based on the presentation outcome, wherein: obtaining the at least one voice feature in the voice information by identifying the voice information includes determining, based on the voice information, an age feature of a first user inputting the voice information, determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes: outputting voice reply information based on the voice operation instruction, and setting a voice speed for the voice reply information to be a first voice speed, and the first voice speed corresponds to the age feature. 10. The electronic device according to claim 8 , wherein determining the presentation outcome of the multimedia data based on the at least one voice feature and the voice operation instruction includes: generating subtitle information based on the voice operation instruction, and setting a subtitle display parameter for the subtitle information to be a first subtitle display parameter corresponding to the age feature. | 0.64322 |
8,255,221 | 5 | 6 | 5. The method of claim 1 further comprising an initial step of invoking a podcasting application through a user browser interface. | 5. The method of claim 1 further comprising an initial step of invoking a podcasting application through a user browser interface. 6. The method of claim 5 further comprising the step of creating a source of predefined interviewer voices. | 0.609489 |
8,775,365 | 58 | 63 | 58. A system of providing at least one service over a data network comprising: at least one software module comprising instructions, executable by one or more processors, configured, using one or more data processing or computing devices, to create an interactive session environment for obtaining an input from a user; at least one first program comprising instructions, executable by one or more processors, configured to access at least one content, said at least one content is the output of at least one second program comprising instructions, executable by one or more processors, configured to perform: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, a content according to the user's input using one or more partitions of the body of knowledge based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge; and at least one server computer, having at least one processing device, to respond to a user's input over a network. | 58. A system of providing at least one service over a data network comprising: at least one software module comprising instructions, executable by one or more processors, configured, using one or more data processing or computing devices, to create an interactive session environment for obtaining an input from a user; at least one first program comprising instructions, executable by one or more processors, configured to access at least one content, said at least one content is the output of at least one second program comprising instructions, executable by one or more processors, configured to perform: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, a content according to the user's input using one or more partitions of the body of knowledge based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge; and at least one server computer, having at least one processing device, to respond to a user's input over a network. 63. The system of claim 58 , wherein the data network is internet. | 0.882143 |
9,967,265 | 2 | 3 | 2. A computer-implemented method as in claim 1 , wherein the graph structures include nodes and edges connected to a pair of nodes, each node representing an entity, each edge representing an interaction between a pair of entities; wherein deleting each of the set of graph structures includes removing an edge from the relational graph. | 2. A computer-implemented method as in claim 1 , wherein the graph structures include nodes and edges connected to a pair of nodes, each node representing an entity, each edge representing an interaction between a pair of entities; wherein deleting each of the set of graph structures includes removing an edge from the relational graph. 3. A computer-implemented method as in claim 2 , further comprising receiving a set of rules, each of the set of rules specifying a logical condition that, when satisfied by the relational graph, indicates that edges of the relational graph represent interactions that are part of a malicious event; wherein performing the malicious event detection operation on the relational graph includes verifying whether the relational graph satisfies a logical condition specified by the set of rules. | 0.5 |
8,693,043 | 34 | 36 | 34. The computer-readable medium of claim 30 wherein said step of automatically categorizing further comprises applying a manually generated classification rule that eliminates at least one possible categorization sequence. | 34. The computer-readable medium of claim 30 wherein said step of automatically categorizing further comprises applying a manually generated classification rule that eliminates at least one possible categorization sequence. 36. The computer-readable medium of claim 34 wherein said at least one possible categorization sequence comprises two consecutive pages of a first document type known to have a predefined number of pages. | 0.625 |
9,858,548 | 3 | 4 | 3. The system of claim 1 , wherein the processor is further configured to: receive an initial value for the data entry field placed onto the electronic canvas; and add the initial value to the form record. | 3. The system of claim 1 , wherein the processor is further configured to: receive an initial value for the data entry field placed onto the electronic canvas; and add the initial value to the form record. 4. The system of claim 3 , wherein the initial value is any of a numerical value, a binary value, and a check mark status. | 0.5 |
9,066,046 | 25 | 40 | 25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal. | 25. A system for filtering objectionable words comprising: a closed caption analyzer executable by at least one processor and configured to identify a specified text in a closed caption text stream based on a comparison of each word in the closed caption text stream to at least one filter list; a closed caption audiotizer executable by the at least one processor and configured to generate an audio equivalent of the specified text by converting the specified text to a phonetic representation associated with at least one energy value; and an audio stream analyzer executable by the at least one processor and configured to match a portion of an audio signal with the specified text by comparing the at least one energy value of the audio equivalent with an energy of a comparative form of the audio signal involving a total energy of a speech slice and energy of one or more frequency bands of the speech slice, the audio stream analyzer further configured to filter the portion of the audio signal. 40. The system of claim 25 , wherein the phonetic representation is time extended for association with an average duration of a phonetic category in the specified text. | 0.629956 |
9,323,742 | 1 | 10 | 1. A method of providing a semantic data architecture, comprising: providing a data model layer in the semantic data architecture, wherein the data model layer is formed by at least one processor, at least one storage device, at least one memory, and at least one communication interface in combination with a data model application program stored in the at least one storage device, wherein the at least one processor, in conjunction with running the data model application program, is configured to use the at least one storage device, the at least one memory, and the at least one communication interface to selectively receive source data from a source device, process the source data received from the source device based at least in part on pre-defined data types and filtering terms to form semantic data arranged in one or more binary tree structures, and store the semantic data in the at least one storage device; and providing a data filtering layer in the semantic data architecture, wherein the data filtering layer is formed by the at least one processor, the at least one storage device, the at least one memory, and the at least one communication interface in combination with a data filtering application program stored in the at least one storage device, wherein the at least one processor, in conjunction running the data filtering application program, is configured to use the at least one storage device, the at least one memory, and the at least one communication interface to selectively receive at least a portion of the semantic data from the data model layer, process the semantic data received from the data model layer using a reflexive matching operation based at least in part on the filtering terms to filter data through substitution to form filtered data, and store the filtered data in the at least one storage device. | 1. A method of providing a semantic data architecture, comprising: providing a data model layer in the semantic data architecture, wherein the data model layer is formed by at least one processor, at least one storage device, at least one memory, and at least one communication interface in combination with a data model application program stored in the at least one storage device, wherein the at least one processor, in conjunction with running the data model application program, is configured to use the at least one storage device, the at least one memory, and the at least one communication interface to selectively receive source data from a source device, process the source data received from the source device based at least in part on pre-defined data types and filtering terms to form semantic data arranged in one or more binary tree structures, and store the semantic data in the at least one storage device; and providing a data filtering layer in the semantic data architecture, wherein the data filtering layer is formed by the at least one processor, the at least one storage device, the at least one memory, and the at least one communication interface in combination with a data filtering application program stored in the at least one storage device, wherein the at least one processor, in conjunction running the data filtering application program, is configured to use the at least one storage device, the at least one memory, and the at least one communication interface to selectively receive at least a portion of the semantic data from the data model layer, process the semantic data received from the data model layer using a reflexive matching operation based at least in part on the filtering terms to filter data through substitution to form filtered data, and store the filtered data in the at least one storage device. 10. The method of claim 1 , further comprising: providing a backward inference layer in the semantic data architecture, wherein the backward inference layer is formed by the at least one processor, the at least one storage device, the at least one memory, and the at least one communication interface in combination with a backward inference application program stored in the at least one storage device, wherein the at least one processor, in conjunction running the backward inference application program, is configured to use the at least one storage device, the at least one memory, and the at least one communication interface to selectively receive at least a portion of the filtered data from the data filtering layer, process the filtered data received from the data filtering layer using a symmetric matching process to evaluate matching rules and explore solutions to form matching conditions using an iterative strategy, and store the matching conditions in the at least one storage device. | 0.587727 |
9,600,897 | 1 | 4 | 1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets. | 1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets. 4. The system of claim 1 , comprising applying a naive Bayes distance for video segmentation that provides a probabilistic framework to combine a plurality of feature channels. | 0.765957 |
8,374,885 | 12 | 15 | 12. A computer system comprising at least one processor and a nontransitory computer-readable storage medium, the non-transitory computer-readable storage medium storing an executable program which directs the processor in performing a computer-implemented method for automatically assessing credibility of a particular website, the computer-implemented method comprising: classifying the particular website based on subject matter of the particular website, the particular website comprising a plurality of elements that produce a presentation of the website when rendered, each element of the plurality of elements defined by at least one attribute; identifying a set of credibility scoring rules based on the classification of the particular website, said set of credibility scoring rules for computing credibility of the particular website based on encoded preferences of a primary demographic of users for websites of the same classification as the particular website; for each particular element of the plurality of elements, producing a credibility score identifying whether the particular element when rendered for display according to the at least one attribute defined for that particular element increases credibility of the particular website by attracting more visitors to the particular website or decreases credibility of the particular website by discouraging visitors to the particular website, wherein producing the credibility score for a particular element comprises (i) selecting a particular credibility scoring rule from the identified set of credibility scoring rules that quantifies a credibility impact of the particular element and (ii) passing the at least one attribute defined for the particular element to the particular credibility scoring rule in order to generate a credibility score as output; and presenting credibility of the particular website by (i) rendering each particular element of the plurality of elements according to the at least one attribute that is defined for each particular element thereby producing a display of the particular website and (ii) overlaying each particular element with the credibility score that is computed for that particular element. | 12. A computer system comprising at least one processor and a nontransitory computer-readable storage medium, the non-transitory computer-readable storage medium storing an executable program which directs the processor in performing a computer-implemented method for automatically assessing credibility of a particular website, the computer-implemented method comprising: classifying the particular website based on subject matter of the particular website, the particular website comprising a plurality of elements that produce a presentation of the website when rendered, each element of the plurality of elements defined by at least one attribute; identifying a set of credibility scoring rules based on the classification of the particular website, said set of credibility scoring rules for computing credibility of the particular website based on encoded preferences of a primary demographic of users for websites of the same classification as the particular website; for each particular element of the plurality of elements, producing a credibility score identifying whether the particular element when rendered for display according to the at least one attribute defined for that particular element increases credibility of the particular website by attracting more visitors to the particular website or decreases credibility of the particular website by discouraging visitors to the particular website, wherein producing the credibility score for a particular element comprises (i) selecting a particular credibility scoring rule from the identified set of credibility scoring rules that quantifies a credibility impact of the particular element and (ii) passing the at least one attribute defined for the particular element to the particular credibility scoring rule in order to generate a credibility score as output; and presenting credibility of the particular website by (i) rendering each particular element of the plurality of elements according to the at least one attribute that is defined for each particular element thereby producing a display of the particular website and (ii) overlaying each particular element with the credibility score that is computed for that particular element. 15. The computer-implemented method of claim 12 , wherein the action comprises changing the at least one attribute that is defined for the specific element to a system suggested attribute. | 0.578475 |
9,152,704 | 7 | 9 | 7. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning interactions with a plurality of documents; assembling an interest set of documents corresponding to the user-specific information concerning interactions with the plurality of documents, wherein the interactions include a previous view of a document by the user; grouping the documents in the interest set into a plurality of clusters based on a level of similarity between words in the documents; determining a keyword for a cluster of the one or more clusters, the keyword identified based on a plurality of terms identified via natural language understanding and representing the theme of the documents in the cluster, wherein the keyword is not one of the terms identified via natural language understanding; determining a set of eligible documents within the cluster, each identified document including either the keyword representing the theme of the documents or a portion of the terms identified via natural language understanding; constructing from the eligible documents a recommended set of documents for the cluster based on a relevance score of each document in the cluster, wherein the relevance score is based on: the frequency that the keyword or the portion of the terms identified via natural language understanding appears in each document in the set of eligible documents, and a user-defined limit on document age; and providing the recommended set of documents for further interaction. | 7. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for adaptive information recommendation, the method comprising: storing user-specific information in memory, the user-specific information concerning interactions with a plurality of documents; assembling an interest set of documents corresponding to the user-specific information concerning interactions with the plurality of documents, wherein the interactions include a previous view of a document by the user; grouping the documents in the interest set into a plurality of clusters based on a level of similarity between words in the documents; determining a keyword for a cluster of the one or more clusters, the keyword identified based on a plurality of terms identified via natural language understanding and representing the theme of the documents in the cluster, wherein the keyword is not one of the terms identified via natural language understanding; determining a set of eligible documents within the cluster, each identified document including either the keyword representing the theme of the documents or a portion of the terms identified via natural language understanding; constructing from the eligible documents a recommended set of documents for the cluster based on a relevance score of each document in the cluster, wherein the relevance score is based on: the frequency that the keyword or the portion of the terms identified via natural language understanding appears in each document in the set of eligible documents, and a user-defined limit on document age; and providing the recommended set of documents for further interaction. 9. The non-transitory computer-readable storage medium of claim 7 , wherein the interactions include previous e-mail messages sent by the user. | 0.558642 |
9,990,417 | 1 | 3 | 1. A method, comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the user interface represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective subset; the user interface includes a user-selectable input by which the first Boolean query is changed, at least in part, without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. | 1. A method, comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the user interface represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective subset; the user interface includes a user-selectable input by which the first Boolean query is changed, at least in part, without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. 3. The method of claim 1 , wherein forming the second Boolean query comprises: selecting a Boolean operator based on whether the term is a broadening term or a narrowing term; determining a position in the first Boolean query to add the term based on steps for determining an order of operations; and forming an abstract syntax tree representation of the second Boolean query based on both the selected Boolean operator and the determined position. | 0.854734 |
9,070,084 | 2 | 3 | 2. A method of claim 1 , wherein the steps of modifying the base expression, generating a comparison canonical expression and comparing the comparison canonical expression with the modified canonical expression are sequentially repeated, the modification sub-expression including one or more elements and being modified to include a larger number of elements with each repetition, until the comparison canonical expression matches the modified canonical expression. | 2. A method of claim 1 , wherein the steps of modifying the base expression, generating a comparison canonical expression and comparing the comparison canonical expression with the modified canonical expression are sequentially repeated, the modification sub-expression including one or more elements and being modified to include a larger number of elements with each repetition, until the comparison canonical expression matches the modified canonical expression. 3. A method of claim 2 , wherein the modification sub-expression is initially generated from a sub-expression in the canonical expression containing the target update expression segment and having the smallest number of elements. | 0.654079 |
8,145,647 | 1 | 3 | 1. A computer program product for electronically responding to requests for product related data, the computer program product comprising a non-transitory storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for facilitating a method comprising: collecting product related data from feeder systems; organizing the collected product related data into digital libraries within a document management system; receiving a discovery request from legal counsel to identify related documents; searching the product related data for documents; tagging documents identified in the search and placing copies of the documents in a holding queue; and exporting the documents in the holding queue to a litigation support system; wherein when the discovery request is received, a request management module groups requests together hierarchically in response to request group, individual request details, and question; wherein documents are linked to a question to create a relationship between the question and documents; wherein documents contained in the export are maintained and grouped with all exports for that question. | 1. A computer program product for electronically responding to requests for product related data, the computer program product comprising a non-transitory storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for facilitating a method comprising: collecting product related data from feeder systems; organizing the collected product related data into digital libraries within a document management system; receiving a discovery request from legal counsel to identify related documents; searching the product related data for documents; tagging documents identified in the search and placing copies of the documents in a holding queue; and exporting the documents in the holding queue to a litigation support system; wherein when the discovery request is received, a request management module groups requests together hierarchically in response to request group, individual request details, and question; wherein documents are linked to a question to create a relationship between the question and documents; wherein documents contained in the export are maintained and grouped with all exports for that question. 3. The computer program product of claim 1 , further comprising foldering documents into at least one of a source folder, collection folder, and user folder. | 0.5 |
9,928,244 | 1 | 7 | 1. A method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories in which it was classified; receiving a user feedback regarding prioritization of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising, associating one or more concepts with one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. | 1. A method comprising: analyzing an electronic document to generate document identifying data; classifying the electronic document in one or more display categories by applying a classification rule to the document identifying data, wherein the classification of the electronic document represents a prioritization of the electronic document; displaying the classified electronic document in the one of the one or more display categories in which it was classified; receiving a user feedback regarding prioritization of the electronic document; and updating the classification rule based on the feedback from the user, wherein analyzing the electronic document further comprises analyzing the document using semantical analysis of the document comprising, associating one or more concepts with one or more display categories, extracting the one or more concepts from the electronic document, and pattern matching the one or more extracted concepts with the one or more concepts associated with the one or more display categories. 7. The method of claim 1 , further comprising: updating the classification rule based on analysis of electronic documents by an end user. | 0.827889 |
9,978,396 | 1 | 2 | 1. A method for analyzing mobile device usage, the method comprising: creating, by one or more processors, a graph display which is depicting a conversation between at least two parties, wherein the graph display contains: a first set of nodes which represent the at least two or more parties of the conversation, wherein: a node, among the first set of nodes, is associated with a first party of the at least two or more parties of the conversation, and another node, among the first set of nodes, is associated with a second party of the at least two or more parties of the conversation, and a second set of nodes which represent contents of the conversation, wherein: one or more nodes, among the second set of nodes, are associated with a first party of the at least two or more parties of the conversation, and one or more nodes, among the second set of nodes, are associated with a second party of the at least two or more parties of the conversation; receiving, by one or more processors, voice data from the first party and the second party of the at least two parties and encoding the voice data into the second set of nodes of the graph display associated with the first party and the second party, wherein the first party and the second party are represented by the first set of nodes; sending, by the first party the one or more nodes, among the second set of nodes, associated with the first party, to the second party over a virtualized boundary in the graph display, wherein the virtualized boundary separates the first party from the second party; receiving, by the second party, content associated with the sent one or more nodes, among the second set of nodes, over the virtual boundary in the graph display; determining, by one or more processors, whether a plurality of event types have occurred during the conversation by performing analytics on the encoded voice data in the second set of nodes, and wherein the plurality of event types consist of: a first type of event, wherein the first type of event are one or more instances of negative emotional sentiments expressed between the first party and the second party, a second type of event, wherein the second type of event are one or more search queries, wherein the one or more search queries are received by the second party from the first party or the first party from the second party, and a third type of event, wherein the third type of event are one or more divergences from a first topic in the conversation to a second topic in the conversation; in response to determining that the plurality of event types has occurred, generating, by one or more processors, a third set of nodes associated with the plurality of event types, wherein the third set of nodes are transposable across the virtualized boundary; incorporating, by one or more processors, the third set of nodes into the graph display, wherein the third set of nodes consist of: generated text which reduces negative emotional sentiments expressed between the first party and second party responsive to determining the first type of event has occurred, generated text which answers the one or more search queries responsive to determining the second type of event has occurred, and generated text which brings back the conversation back to the first topic from the second topic responsive to determining the third type of event has occurred; and generating, by one or more processors, an automated response system in a call center based on the third set of nodes, wherein the automated response system addresses the negative emotional sentiments and the divergences in the conversations between the at least two parties. | 1. A method for analyzing mobile device usage, the method comprising: creating, by one or more processors, a graph display which is depicting a conversation between at least two parties, wherein the graph display contains: a first set of nodes which represent the at least two or more parties of the conversation, wherein: a node, among the first set of nodes, is associated with a first party of the at least two or more parties of the conversation, and another node, among the first set of nodes, is associated with a second party of the at least two or more parties of the conversation, and a second set of nodes which represent contents of the conversation, wherein: one or more nodes, among the second set of nodes, are associated with a first party of the at least two or more parties of the conversation, and one or more nodes, among the second set of nodes, are associated with a second party of the at least two or more parties of the conversation; receiving, by one or more processors, voice data from the first party and the second party of the at least two parties and encoding the voice data into the second set of nodes of the graph display associated with the first party and the second party, wherein the first party and the second party are represented by the first set of nodes; sending, by the first party the one or more nodes, among the second set of nodes, associated with the first party, to the second party over a virtualized boundary in the graph display, wherein the virtualized boundary separates the first party from the second party; receiving, by the second party, content associated with the sent one or more nodes, among the second set of nodes, over the virtual boundary in the graph display; determining, by one or more processors, whether a plurality of event types have occurred during the conversation by performing analytics on the encoded voice data in the second set of nodes, and wherein the plurality of event types consist of: a first type of event, wherein the first type of event are one or more instances of negative emotional sentiments expressed between the first party and the second party, a second type of event, wherein the second type of event are one or more search queries, wherein the one or more search queries are received by the second party from the first party or the first party from the second party, and a third type of event, wherein the third type of event are one or more divergences from a first topic in the conversation to a second topic in the conversation; in response to determining that the plurality of event types has occurred, generating, by one or more processors, a third set of nodes associated with the plurality of event types, wherein the third set of nodes are transposable across the virtualized boundary; incorporating, by one or more processors, the third set of nodes into the graph display, wherein the third set of nodes consist of: generated text which reduces negative emotional sentiments expressed between the first party and second party responsive to determining the first type of event has occurred, generated text which answers the one or more search queries responsive to determining the second type of event has occurred, and generated text which brings back the conversation back to the first topic from the second topic responsive to determining the third type of event has occurred; and generating, by one or more processors, an automated response system in a call center based on the third set of nodes, wherein the automated response system addresses the negative emotional sentiments and the divergences in the conversations between the at least two parties. 2. The method of claim 1 , further comprising: responsive to receiving one or more external user gestures, generating, by one or more processors, a gesture node to be incorporated into the third set of nodes, wherein the gesture node is transported across the virtualized boundary separating the first party from the second party, and wherein the gesture node contains preconfigured instructions to perform an action. | 0.831174 |
8,799,197 | 1 | 2 | 1. A data processing method for a clinical decision support system, the method comprising: inferring input data having a natural language format based on an Ontology technique to recognize an input rule coming from the input data; inferring storage data having a natural language format and stored in rule database based on the Ontology technique to recognize a storage rule associated with the input rule from the storage data; comparing the input rule to the storage rule using a Self Evolutionary Rule-base algorithm; and updating the storage data stored in the rule database to the input data according to the result of the comparison, wherein each of the input rule and the storage rule is composed of an item and a detail, and in response to a result of comparing indicating that at least one item included in the input rule is a new item that is not identical to an item included in the storage rule, the updating of the storage data comprises adding the input rule including the new item to the rule database. | 1. A data processing method for a clinical decision support system, the method comprising: inferring input data having a natural language format based on an Ontology technique to recognize an input rule coming from the input data; inferring storage data having a natural language format and stored in rule database based on the Ontology technique to recognize a storage rule associated with the input rule from the storage data; comparing the input rule to the storage rule using a Self Evolutionary Rule-base algorithm; and updating the storage data stored in the rule database to the input data according to the result of the comparison, wherein each of the input rule and the storage rule is composed of an item and a detail, and in response to a result of comparing indicating that at least one item included in the input rule is a new item that is not identical to an item included in the storage rule, the updating of the storage data comprises adding the input rule including the new item to the rule database. 2. The data processing method of claim 1 , wherein in response to the result of the comparing indicates that at least one item included in the input rule is identical to an item included in the storage rule and a detail of the item of the input rule is different from a detail of the item of the storage rule, the updating of the storage data comprises substituting the detail of the item of the storage rule by the detail of the item of the input rule. | 0.5 |
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