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9,203,924 | 14 | 20 | 14. A system for recommending audio files to a member of a social network, the system comprising: one or more processors; and a memory comprising instructions stored therein, which when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a representation of a first set of audio files associated with the member; receiving a representation of an ordered list of social networking contacts associated with the member; receiving a representation of one or more second sets of audio files, wherein each second set of audio files is associated with a social networking contact in the ordered list of social networking contacts associated with the member, further wherein the ordered list of social networking contacts is arranged according to a ranking of the social networking contacts; determining a first set of characteristics based on the representation of the first set of audio files; determining one or more second sets of characteristics based on the representation of the one or more second sets of audio files; associating at least a portion of characteristics in the one or more seconds set of characteristics with a likelihood-of-interest, wherein the likelihood-of-interest is based on a position of the associated social networking contact in the ordered list of social networking contacts; and generating a recommendation for at least one new audio file based on the first set of characteristics, the one or more second sets of characteristics, and the likelihood-of-interest associated with characteristics in the one or more second sets of characteristics, wherein the at least one new audio file is not in the first set of audio files, wherein the ordered list of social networking contacts associated with the member comprises one or more predefined collections of social networking contacts associated with the member in a social networking service, and wherein the ordered list of social networking contacts associated with the member comprises users of the social networking service having at least one personal characteristic common to that of the member, the at least one personal characteristic corresponding to user registration information within the social networking service. | 14. A system for recommending audio files to a member of a social network, the system comprising: one or more processors; and a memory comprising instructions stored therein, which when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a representation of a first set of audio files associated with the member; receiving a representation of an ordered list of social networking contacts associated with the member; receiving a representation of one or more second sets of audio files, wherein each second set of audio files is associated with a social networking contact in the ordered list of social networking contacts associated with the member, further wherein the ordered list of social networking contacts is arranged according to a ranking of the social networking contacts; determining a first set of characteristics based on the representation of the first set of audio files; determining one or more second sets of characteristics based on the representation of the one or more second sets of audio files; associating at least a portion of characteristics in the one or more seconds set of characteristics with a likelihood-of-interest, wherein the likelihood-of-interest is based on a position of the associated social networking contact in the ordered list of social networking contacts; and generating a recommendation for at least one new audio file based on the first set of characteristics, the one or more second sets of characteristics, and the likelihood-of-interest associated with characteristics in the one or more second sets of characteristics, wherein the at least one new audio file is not in the first set of audio files, wherein the ordered list of social networking contacts associated with the member comprises one or more predefined collections of social networking contacts associated with the member in a social networking service, and wherein the ordered list of social networking contacts associated with the member comprises users of the social networking service having at least one personal characteristic common to that of the member, the at least one personal characteristic corresponding to user registration information within the social networking service. 20. The system of claim 14 , wherein the first set of characteristics comprises personal characteristics of a speaker in an audio file within the first set of audio files. | 0.658 |
8,989,485 | 9 | 12 | 9. A system for detecting a junction in a received image of a line of text to update a junction list with descriptive data, the system comprising: a memory configured to store processor-executable instructions; and a processor operatively coupled to the memory, wherein the processor is configured to: create a color histogram based on a number of color pixels in the received image of the line of text; detect, based at least in part on the received image of the line of text, a rung in the received image of the line of text; identify a horizontal position of the detected rung in the received image of the line of text; additionally identify a gateway on the color histogram, wherein the identified gateway is associated with the detected rung; and update the junction list with data including a description of the identified gateway. | 9. A system for detecting a junction in a received image of a line of text to update a junction list with descriptive data, the system comprising: a memory configured to store processor-executable instructions; and a processor operatively coupled to the memory, wherein the processor is configured to: create a color histogram based on a number of color pixels in the received image of the line of text; detect, based at least in part on the received image of the line of text, a rung in the received image of the line of text; identify a horizontal position of the detected rung in the received image of the line of text; additionally identify a gateway on the color histogram, wherein the identified gateway is associated with the detected rung; and update the junction list with data including a description of the identified gateway. 12. The system of claim 9 , wherein the horizontal position corresponds to one of three horizontal regions of the received image of the line of text, wherein the three horizontal regions comprise a bottom stripe, a middle stripe, and a top stripe. | 0.502016 |
7,984,032 | 1 | 2 | 1. At least one computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer system, cause the computer system to perform a method comprising: receiving at least one natural language input query; defining at least one term occurrence-level constraint applicable to the input query; identifying at least one fact requested in the input query; instantiating at least one iterator to traverse at least one fact index to identify at least one candidate fact that is responsive to the input query; traversing the iterator through at least a portion of the fact index; receiving at least one candidate fact from the iterator, wherein the candidate fact includes at least one term occurrence; applying the term occurrence-level constraint to the term occurrence; and selecting the candidate fact for inclusion in search results for the input query, based at least in part on applying the term occurrence-level constraint to the term occurrence. | 1. At least one computer-readable storage medium having computer-executable instructions stored thereon which, when executed by a computer system, cause the computer system to perform a method comprising: receiving at least one natural language input query; defining at least one term occurrence-level constraint applicable to the input query; identifying at least one fact requested in the input query; instantiating at least one iterator to traverse at least one fact index to identify at least one candidate fact that is responsive to the input query; traversing the iterator through at least a portion of the fact index; receiving at least one candidate fact from the iterator, wherein the candidate fact includes at least one term occurrence; applying the term occurrence-level constraint to the term occurrence; and selecting the candidate fact for inclusion in search results for the input query, based at least in part on applying the term occurrence-level constraint to the term occurrence. 2. The storage medium of claim 1 , further comprising instructions for defining at least a further term occurrence-level constraints applicable to the input query. | 0.716028 |
9,952,752 | 1 | 6 | 1. A method, comprising: receiving, through a user interface of a social network application presented at a user device and by one or more servers, an indication that a user recommended content displayed the user interface, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the user interface, requesting, by the one or more servers, user interaction data indicative of the user recommendation of content displayed in the user interface; receiving, by the one or more servers, user interaction data that includes an action taken by the user, a time corresponding to the action taken, and a content identifier identifying the content the user recommended; mapping, by the one or more servers, at least one annotation specifying the action taken to the different portions of the recommended content; and distributing, by the one or more servers and based on the mapping, the recommended content through a social network with the at least one annotation at a presentation location corresponding to at least one content component of the recommended content. | 1. A method, comprising: receiving, through a user interface of a social network application presented at a user device and by one or more servers, an indication that a user recommended content displayed the user interface, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the user interface, requesting, by the one or more servers, user interaction data indicative of the user recommendation of content displayed in the user interface; receiving, by the one or more servers, user interaction data that includes an action taken by the user, a time corresponding to the action taken, and a content identifier identifying the content the user recommended; mapping, by the one or more servers, at least one annotation specifying the action taken to the different portions of the recommended content; and distributing, by the one or more servers and based on the mapping, the recommended content through a social network with the at least one annotation at a presentation location corresponding to at least one content component of the recommended content. 6. The method of claim 1 , wherein the indication that the user recommended content is an indication that the user selected a user recommendation control displayed in conjunction with the content. | 0.845912 |
8,229,905 | 11 | 15 | 11. A computer-implemented method of operating a document management system using a first token as a physical representation of a case file on a printed medium, the computer-implemented method comprising: using a computer system to perform the steps of: printing, on the printed medium, the first token that is the physical representation of the case file, the first token comprising a visual representation of the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; receiving a selection of one of the first plurality of links included in the printed token; retrieving an electronic version of the one of the first plurality of documents associated with the selected link; and providing the electronic version of the one of the first plurality of documents. | 11. A computer-implemented method of operating a document management system using a first token as a physical representation of a case file on a printed medium, the computer-implemented method comprising: using a computer system to perform the steps of: printing, on the printed medium, the first token that is the physical representation of the case file, the first token comprising a visual representation of the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; receiving a selection of one of the first plurality of links included in the printed token; retrieving an electronic version of the one of the first plurality of documents associated with the selected link; and providing the electronic version of the one of the first plurality of documents. 15. The method of claim 11 further comprising browsing a set of electronic files associated with the case file, the set including the one of the first plurality of documents. | 0.640496 |
8,997,041 | 12 | 18 | 12. A script management server being connected to a user terminal and managing script codes, the script management server including a plurality of computing devices capable of distributed processing, the plurality of devices comprising: an active script database designating unit designating an active script database by providing the user terminal with a plurality of original script lists; a plurality of script databases being classified according to script version, each of the plurality of script databases storing original script codes and user-specific script codes; a meta database storing the plurality of original script lists associated with the plurality of script databases and user-specific script list; and a database updating unit storing identifiers of the user terminal and the designated active script database in the meta database and, if a script code in the active script database is updated through the user terminal, updating the script list and script codes of the corresponding user stored respectively in the meta database and the designated active script database, wherein the database updating unit, if the script code is updated through the user terminal, updates a new version of script for the corresponding script in the plurality of script databases. | 12. A script management server being connected to a user terminal and managing script codes, the script management server including a plurality of computing devices capable of distributed processing, the plurality of devices comprising: an active script database designating unit designating an active script database by providing the user terminal with a plurality of original script lists; a plurality of script databases being classified according to script version, each of the plurality of script databases storing original script codes and user-specific script codes; a meta database storing the plurality of original script lists associated with the plurality of script databases and user-specific script list; and a database updating unit storing identifiers of the user terminal and the designated active script database in the meta database and, if a script code in the active script database is updated through the user terminal, updating the script list and script codes of the corresponding user stored respectively in the meta database and the designated active script database, wherein the database updating unit, if the script code is updated through the user terminal, updates a new version of script for the corresponding script in the plurality of script databases. 18. The script management server of claim 12 , wherein the database updating unit, if addition of a particular script is requested by the user terminal, adds the particular script to the active script database. | 0.603774 |
8,782,046 | 15 | 17 | 15. The computer implemented method of claim 14 , further comprising: predicting an expected volume of the at least trend at a given time; simultaneously tracking an actual volume of the at least trend; and computing a surprise factor to determine a general direction of the at least trend using a grading function. | 15. The computer implemented method of claim 14 , further comprising: predicting an expected volume of the at least trend at a given time; simultaneously tracking an actual volume of the at least trend; and computing a surprise factor to determine a general direction of the at least trend using a grading function. 17. The computer implemented method of claim 15 , further comprises: constantly tracking the volume of one term taxonomy over a predefined time frame to determine when the at least trend changes direction. | 0.54646 |
7,599,829 | 11 | 12 | 11. The system of claim 9 wherein the data to be searched is a contact list. | 11. The system of claim 9 wherein the data to be searched is a contact list. 12. The system of claim 11 wherein the received partial character is associated with a name stored in the contact list. | 0.5 |
9,002,867 | 14 | 26 | 14. A system comprising: one or more computers configured to perform operations, the operations comprising: receiving a query and a current version of a document; receiving quality of result data for a plurality of versions of the document and the query, the quality of result data specifying a respective version-specific quality of result statistic for each of the versions of the document with respect to the query; calculating a weight for the version-specific quality of result statistics corresponding to each version of the document, wherein the weight for a particular version of the document is determined at least in part on an estimate of a difference between the particular version and the current version of the document, and wherein calculating the weight for a particular version of the document comprises: obtaining a representation of the particular version of the document, wherein the representation is a first time distribution of shingles, calculating a difference score by comparing the first time distribution of shingles representing the particular version of the document to a second time distribution of shingles representing the current version of the document, wherein each shingle is a contiguous subsequence of one or more tokens in the document, and wherein each shingle is associated with a particular time that the shingle is first observed in a version of the document such that a distribution of the times associated with the shingles in a version of the document corresponds to the representation of the version of the document, and using the difference score to calculate a corresponding weight for the particular version of the document; determining a weighted overall quality of result statistic for the document with respect to the query, wherein determining the weighted overall quality of result statistic comprises weighting each version-specific quality of result statistic with the calculated weight and combining the weighted version-specific quality of result statistics; and associating the weighted overall quality of result statistic with the document. | 14. A system comprising: one or more computers configured to perform operations, the operations comprising: receiving a query and a current version of a document; receiving quality of result data for a plurality of versions of the document and the query, the quality of result data specifying a respective version-specific quality of result statistic for each of the versions of the document with respect to the query; calculating a weight for the version-specific quality of result statistics corresponding to each version of the document, wherein the weight for a particular version of the document is determined at least in part on an estimate of a difference between the particular version and the current version of the document, and wherein calculating the weight for a particular version of the document comprises: obtaining a representation of the particular version of the document, wherein the representation is a first time distribution of shingles, calculating a difference score by comparing the first time distribution of shingles representing the particular version of the document to a second time distribution of shingles representing the current version of the document, wherein each shingle is a contiguous subsequence of one or more tokens in the document, and wherein each shingle is associated with a particular time that the shingle is first observed in a version of the document such that a distribution of the times associated with the shingles in a version of the document corresponds to the representation of the version of the document, and using the difference score to calculate a corresponding weight for the particular version of the document; determining a weighted overall quality of result statistic for the document with respect to the query, wherein determining the weighted overall quality of result statistic comprises weighting each version-specific quality of result statistic with the calculated weight and combining the weighted version-specific quality of result statistics; and associating the weighted overall quality of result statistic with the document. 26. The system of claim 14 , wherein calculating the weight further comprises calculating a number of times the document has changed as compared to a reference version of the document or an amount of time the reference version of the document was unchanged. | 0.827748 |
9,158,710 | 14 | 15 | 14. The system of claim 13 , further comprising access logic to limit the instruction from accessing the second page if the effective current page color of the first page and the color of the second page are different. | 14. The system of claim 13 , further comprising access logic to limit the instruction from accessing the second page if the effective current page color of the first page and the color of the second page are different. 15. The system of claim 14 , wherein the access logic is to limit the instruction from accessing the second page by triggering a page fault exception. | 0.5 |
9,130,651 | 1 | 38 | 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. 38. The energy harvesting communication device of claim 1 , wherein said communication apparatus further configured with at least a signal amplifier, wherein the communication apparatus further comprising at least one of: a variable gain module; social network platform; video recognition platform; voice over text platform; text to voice enabled and/or conversion platform; TDMA platform; WCDMA platform; CDMA platform; TDMB platform; digital and/or analog and/or GSM platform; GPS platform; GPRS platform; TIHW platform; MFSCD platform; frequency authentication platform; multiple input/output platform; EDGSM platform; EDMA platform; OFDM platform; OFDMA platform; Wi-Fi platform; Wi-Max platform; wireless library platform; educational module; touch screen sensory platform; phone book; electronic book; electronic reader; dictionary; calendar; calculator; Internet service applications; energy generating apparatus; gaming apparatus; multiple paths switching antenna; Internet service connectivity operable for global roaming. | 0.710718 |
6,058,166 | 1 | 7 | 1. A method for playing prompts during execution of a call flow of a network application, comprising the steps of: storing a plurality of subsets of prompt definitions associated with a particular language, each subset containing prompt definitions for prompts to be played during the call low, one of said subsets being designated as a base subset; designating, at a point in the call flow, one of said subsets of prompt definitions, other than the base subset, as an alternate subset; and thereafter, in response to a request to play a particular prompt, first searching the alternate subset to determine whether it contains a prompt definition for the requested prompt, and if so, playing the prompt according to the prompt definition in the alternate subset, but if the alternate subset does not contain a prompt definition for the requested prompt, then searching the base subset for a prompt definition for the requested prompt and playing the prompt according to the prompt definition in the base subset. | 1. A method for playing prompts during execution of a call flow of a network application, comprising the steps of: storing a plurality of subsets of prompt definitions associated with a particular language, each subset containing prompt definitions for prompts to be played during the call low, one of said subsets being designated as a base subset; designating, at a point in the call flow, one of said subsets of prompt definitions, other than the base subset, as an alternate subset; and thereafter, in response to a request to play a particular prompt, first searching the alternate subset to determine whether it contains a prompt definition for the requested prompt, and if so, playing the prompt according to the prompt definition in the alternate subset, but if the alternate subset does not contain a prompt definition for the requested prompt, then searching the base subset for a prompt definition for the requested prompt and playing the prompt according to the prompt definition in the base subset. 7. The method recited in claim 1 wherein at least one of the prompt definitions in one of the subsets other than the base subset comprises a modified form of a corresponding prompt definition in the base subset. | 0.732234 |
7,584,221 | 15 | 16 | 15. A system comprising: a processor; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured for: determining fields of the document, wherein each field includes a contextual section of the document based on the document structure; determining a field weight for each of the determined fields, wherein the field weight corresponds to a number of times for replicating the content of each of the determined fields; replicating the content of each of the determined fields the number of times indicated by the field weight for each of the determined fields, wherein the replicated content of each field is concatenated into a field set for each of the determined fields; combining each concatenated field set for each field of the document to generate a virtual document including each concatenated field set for each field of the document; indexing the virtual document to produce a virtual document statistics; and computing the field-weighted score from the virtual document index based on the query. | 15. A system comprising: a processor; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured for: determining fields of the document, wherein each field includes a contextual section of the document based on the document structure; determining a field weight for each of the determined fields, wherein the field weight corresponds to a number of times for replicating the content of each of the determined fields; replicating the content of each of the determined fields the number of times indicated by the field weight for each of the determined fields, wherein the replicated content of each field is concatenated into a field set for each of the determined fields; combining each concatenated field set for each field of the document to generate a virtual document including each concatenated field set for each field of the document; indexing the virtual document to produce a virtual document statistics; and computing the field-weighted score from the virtual document index based on the query. 16. The system of claim 15 wherein the query is associated with a search and the field-weighted score represents a level of relevance of the document to the query. | 0.716028 |
9,710,450 | 1 | 9 | 1. A method comprising: determining that tokens have been incorrectly separated due to an incorrect Natural Language Processing (NLP) operation on a corpus; and recombining, as a part of correcting the incorrect NLP operation, the incorrectly separated tokens, the recombining comprising: determining whether a token from an ordered set of tokens is present in a dictionary, the dictionary being related to the corpus from which the ordered set of tokens is extracted; determining whether a compounding threshold has been reached, wherein the compounding threshold limits a number of tokens that can be agglutinated to form a compound token; agglutinating using a processor and a memory, responsive to the token not being present in the dictionary, and responsive to the compounding threshold not having been reached, the token with a next adjacent token in the ordered set of tokens to form the compound token; determining whether the compound token is present in the dictionary; assigning a weight to the compound token responsive to the compound token being present in the dictionary; computing a confidence rating of the compound token, the confidence rating being a function of the weight; and using the compound token and the confidence rating in performing an NLP operation on the corpus. | 1. A method comprising: determining that tokens have been incorrectly separated due to an incorrect Natural Language Processing (NLP) operation on a corpus; and recombining, as a part of correcting the incorrect NLP operation, the incorrectly separated tokens, the recombining comprising: determining whether a token from an ordered set of tokens is present in a dictionary, the dictionary being related to the corpus from which the ordered set of tokens is extracted; determining whether a compounding threshold has been reached, wherein the compounding threshold limits a number of tokens that can be agglutinated to form a compound token; agglutinating using a processor and a memory, responsive to the token not being present in the dictionary, and responsive to the compounding threshold not having been reached, the token with a next adjacent token in the ordered set of tokens to form the compound token; determining whether the compound token is present in the dictionary; assigning a weight to the compound token responsive to the compound token being present in the dictionary; computing a confidence rating of the compound token, the confidence rating being a function of the weight; and using the compound token and the confidence rating in performing an NLP operation on the corpus. 9. The method of claim 1 , further comprising: ordering tokens in the ordered set of tokens such that a first token precedes the token in the ordered set of tokens responsive to a first word corresponding to the first token preceding a second word corresponding to the token in a corpus, and a third token follows the token in the ordered set of tokens responsive to a third word corresponding to the third token following a second word corresponding to the token in the corpus. | 0.618211 |
9,679,380 | 2 | 3 | 2. The method according to claim 1 , wherein the metric comprises values corresponding to magnitudes of the emotions conveyed. | 2. The method according to claim 1 , wherein the metric comprises values corresponding to magnitudes of the emotions conveyed. 3. The method according to claim 2 , wherein the specified emotion change comprises a magnitude of change. | 0.653595 |
8,315,878 | 1 | 4 | 1. A computer-implemented method comprising: receiving a contact list from a wireless communication device; receiving, at a first server computer, a voice command recorded via the wireless communication device; initiating a speech recognition process that identifies the voice command, the speech recognition process using the contact list to assist in automatic translation of the voice command; in response to determining a type of voice command, transferring the voice command to a second server computer that processes the voice command; constructing an application command based on the voice command; and transmitting the application command to the wireless communication device, the application command including instructions that cause a corresponding application on the wireless communication device to execute the application command. | 1. A computer-implemented method comprising: receiving a contact list from a wireless communication device; receiving, at a first server computer, a voice command recorded via the wireless communication device; initiating a speech recognition process that identifies the voice command, the speech recognition process using the contact list to assist in automatic translation of the voice command; in response to determining a type of voice command, transferring the voice command to a second server computer that processes the voice command; constructing an application command based on the voice command; and transmitting the application command to the wireless communication device, the application command including instructions that cause a corresponding application on the wireless communication device to execute the application command. 4. The computer-implemented method of claim 1 , wherein determining the type of voice command include identifying that the type of voice command includes confidential information, and, in response, the transferring the voice command to an additional server computer designated for receiving confidential information. | 0.804455 |
9,953,640 | 10 | 14 | 10. A computer-implemented method of recognizing speech for a medical response environment, the method comprising: operating one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters being operated to apply filter processes to the raw audio data to generate the set of processed audio data, wherein the one or more filters comprise at least one filter appropriate for the medical response environment; operating a translator to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and in response to receiving the set of translation results, automatically trigger a decision controller to select the text data that corresponds to the raw audio data, wherein the decision controller is operable to: identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold, determine whether the identified at least one translation result comprises more than one translation result; in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and generate an output signal associated with the selection by the decision controller. | 10. A computer-implemented method of recognizing speech for a medical response environment, the method comprising: operating one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters being operated to apply filter processes to the raw audio data to generate the set of processed audio data, wherein the one or more filters comprise at least one filter appropriate for the medical response environment; operating a translator to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and in response to receiving the set of translation results, automatically trigger a decision controller to select the text data that corresponds to the raw audio data, wherein the decision controller is operable to: identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold, determine whether the identified at least one translation result comprises more than one translation result; in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and generate an output signal associated with the selection by the decision controller. 14. The computer-implemented method of claim 10 further comprises selecting the text data associated with a highest occurrence frequency as the text data that corresponds to the raw audio data. | 0.843598 |
9,311,278 | 1 | 10 | 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. 10. The method of claim 1 , further comprising: displaying a palette on the graphical user interface, the palette containing representations of available graphical elements that can be added as sub-elements to a selected graphical element. | 0.612013 |
9,734,142 | 1 | 2 | 1. A method for identifying a most likely source language of a snippet, comprising: receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups; determining two or more possible source languages for the snippet; generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor. | 1. A method for identifying a most likely source language of a snippet, comprising: receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups; determining two or more possible source languages for the snippet; generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor. 2. The method of claim 1 , wherein the least one of the two or more translations of the snippet comprises multiple translations, each with a common specified translation source language; wherein computing accuracy scores includes computing a combined accuracy score for the multiple translations, each with a common specified translation source language, wherein computing each combined accuracy score is performed by combining individual accuracy scores corresponding to each of the multiple translations that have a common specified translation source language; and wherein producing the confidence factor for the common specified translation source language is based on the combined accuracy score for the multiple translations each with that common specified translation source language. | 0.5 |
9,514,119 | 1 | 3 | 1. A method comprising: determining that an electronic document includes a first phrase that is at least similar to a first phrase of a plurality of phrases in a database and a second phrase that is at least similar to a second phrase of a plurality of phrases in the database, wherein the electronic document includes content contributed by a plurality of contributors; determining that a first contributor of the plurality of contributors is associated with the first phrase in the electronic document and a second contributor of the plurality of contributors is associated with the second phrase in the electronic document; determining that the first phrase identifies a first text effect in the electronic document and that the second phrase identifies a second text effect in the electronic document; determining that metadata of the electronic document indicates that first content of the electronic document comprises the first text effect and that second content of the electronic document comprises the second text effect; creating a first mapping between the first contributor and the first text effect and a second mapping between the second contributor and the second text effect after determining that the metadata of the electronic document indicates that the first content comprises the first text effect and the second content comprises the second text effect; determining a first location in the electronic document of the first content and a second location in the electronic document of the second content; associating the first location with the first mapping and the second location with the second mapping; supplying the first mapping and the second mapping for presenting of the electronic document; and modifying the electronic document to include an indication of the first contributor at the first location and an indication of the second contributor at the second location. | 1. A method comprising: determining that an electronic document includes a first phrase that is at least similar to a first phrase of a plurality of phrases in a database and a second phrase that is at least similar to a second phrase of a plurality of phrases in the database, wherein the electronic document includes content contributed by a plurality of contributors; determining that a first contributor of the plurality of contributors is associated with the first phrase in the electronic document and a second contributor of the plurality of contributors is associated with the second phrase in the electronic document; determining that the first phrase identifies a first text effect in the electronic document and that the second phrase identifies a second text effect in the electronic document; determining that metadata of the electronic document indicates that first content of the electronic document comprises the first text effect and that second content of the electronic document comprises the second text effect; creating a first mapping between the first contributor and the first text effect and a second mapping between the second contributor and the second text effect after determining that the metadata of the electronic document indicates that the first content comprises the first text effect and the second content comprises the second text effect; determining a first location in the electronic document of the first content and a second location in the electronic document of the second content; associating the first location with the first mapping and the second location with the second mapping; supplying the first mapping and the second mapping for presenting of the electronic document; and modifying the electronic document to include an indication of the first contributor at the first location and an indication of the second contributor at the second location. 3. The method of claim 1 , wherein the supplying the first mapping and the second mapping comprises supplying the first mapping and the second mapping to an accessibility device. | 0.563725 |
6,028,604 | 8 | 11 | 8. A method of previewing menu options including the steps of: storing a list of menu options corresponding to functions; storing a description of said menu options; receiving a first user input indicating a user's designation of one of said menu options: determining which of said menu options is currently designated by said user; retrieving said description of said currently selected menu option; providing the description to said user, wherein said description is stored apart from said function and wherein said designated menu option remains viewable while said description is provided to said user; receiving a second user input indicating said user's selection of said one of said menu options; and executing said menu option. | 8. A method of previewing menu options including the steps of: storing a list of menu options corresponding to functions; storing a description of said menu options; receiving a first user input indicating a user's designation of one of said menu options: determining which of said menu options is currently designated by said user; retrieving said description of said currently selected menu option; providing the description to said user, wherein said description is stored apart from said function and wherein said designated menu option remains viewable while said description is provided to said user; receiving a second user input indicating said user's selection of said one of said menu options; and executing said menu option. 11. The method according to claim 8, wherein said description includes sound files. | 0.803318 |
9,484,021 | 6 | 7 | 6. The method of claim 5 , further comprising: sending, to a device, an indication of the first hypothesis and second hypothesis; and receiving, from the device, an indication of selection of the first hypothesis. | 6. The method of claim 5 , further comprising: sending, to a device, an indication of the first hypothesis and second hypothesis; and receiving, from the device, an indication of selection of the first hypothesis. 7. The method of claim 6 , further comprising: processing text of the first hypothesis to identify a search query; executing the search query to determine search results; and sending the search results to the device. | 0.5 |
8,364,631 | 23 | 25 | 23. A computer program product for converting a first version of a database to a second version, the computer program product being embodied in a computer readable storage device and comprising computer instructions for: determining the database version of the first version of the database based on a key obtained by taking a hash of the database schema of the database in the first version; determining available translation steps; selecting a translation path from the first version of the database to the second version of the database, wherein the translation path includes a sequence of two or more translation steps that are a subset of the available translation steps, wherein the selected translation steps comprise a first selected translation step and a second selected translation step; and executing the selected translation steps in the translation path, wherein executing comprises: using the first selected translation step to convert the first version of the database to a third version of the database; and using the second selected translation step to convert the third version of the database to the second version of the database, wherein each of the first version of the database, the second version of the database, and the third version of the database is associated with a fully migrated version of the database, wherein the selecting of the translation path includes selecting one translation path from a plurality of translation paths based on either a shortest path or a first path, the third version of the database being different from each other for each of the translation paths. | 23. A computer program product for converting a first version of a database to a second version, the computer program product being embodied in a computer readable storage device and comprising computer instructions for: determining the database version of the first version of the database based on a key obtained by taking a hash of the database schema of the database in the first version; determining available translation steps; selecting a translation path from the first version of the database to the second version of the database, wherein the translation path includes a sequence of two or more translation steps that are a subset of the available translation steps, wherein the selected translation steps comprise a first selected translation step and a second selected translation step; and executing the selected translation steps in the translation path, wherein executing comprises: using the first selected translation step to convert the first version of the database to a third version of the database; and using the second selected translation step to convert the third version of the database to the second version of the database, wherein each of the first version of the database, the second version of the database, and the third version of the database is associated with a fully migrated version of the database, wherein the selecting of the translation path includes selecting one translation path from a plurality of translation paths based on either a shortest path or a first path, the third version of the database being different from each other for each of the translation paths. 25. A computer program product as recited in claim 23 , wherein the second version is a new version of the database. | 0.718447 |
8,620,958 | 1 | 4 | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. 4. The processor-implemented method of claim 1 , wherein the specific subject-matter for a particular data store in the data structure overlaps a subject-matter of another data store in the data structure. | 0.730263 |
8,738,363 | 1 | 16 | 1. A method for extraction of suggestions for improvement comprising: providing a structured terminology for a topic, the structured terminology including a set of semantic classes, each of a plurality of the semantic classes including a finite set of terms; providing a thesaurus of terms relating to suggestions of improvement; receiving a corpus of text documents, each document comprising a text string in a natural language; labeling text elements in the text strings which are instances of terms in the structured terminology with the corresponding semantic class; labeling text elements in the text strings which are instances of terms in the thesaurus; with a processor, applying a set of patterns to the labeled text strings to identify suggestions of improvement expressions, the patterns each defining a syntactic relation between text elements, the patterns including: for each of the semantic classes in the set, at least one pattern which specifies a syntactic relation in which one of the text elements in the relation is labeled as an instance of the semantic class, and wherein at least one of the patterns specifies a syntactic relation in which one of the text elements in the relation is labeled as an instance of one of the terms in the thesaurus; and outputting a set of suggestions for improvements based on the identified suggestions of improvement expressions. | 1. A method for extraction of suggestions for improvement comprising: providing a structured terminology for a topic, the structured terminology including a set of semantic classes, each of a plurality of the semantic classes including a finite set of terms; providing a thesaurus of terms relating to suggestions of improvement; receiving a corpus of text documents, each document comprising a text string in a natural language; labeling text elements in the text strings which are instances of terms in the structured terminology with the corresponding semantic class; labeling text elements in the text strings which are instances of terms in the thesaurus; with a processor, applying a set of patterns to the labeled text strings to identify suggestions of improvement expressions, the patterns each defining a syntactic relation between text elements, the patterns including: for each of the semantic classes in the set, at least one pattern which specifies a syntactic relation in which one of the text elements in the relation is labeled as an instance of the semantic class, and wherein at least one of the patterns specifies a syntactic relation in which one of the text elements in the relation is labeled as an instance of one of the terms in the thesaurus; and outputting a set of suggestions for improvements based on the identified suggestions of improvement expressions. 16. The method of claim 1 , wherein all the terms in a majority of the classes in the structured terminology are nouns or noun phrases. | 0.968502 |
10,152,209 | 4 | 6 | 4. The computer usable program product of claim 1 , further comprising: computer usable code for analyzing a user preference, wherein the user preference is used in a second threshold number of data in the first subset; computer usable code for concluding, for the first area in each data in the subset, that the user preference causes the sensitivity to reduce to below the level of sensitivity; and computer usable code for constructing, responsive to the concluding, a second instruction for the UI design tool, the second instruction causing the UI design tool to move a UI element in the future UI design to a second area when the future UI design is used with the user preference. | 4. The computer usable program product of claim 1 , further comprising: computer usable code for analyzing a user preference, wherein the user preference is used in a second threshold number of data in the first subset; computer usable code for concluding, for the first area in each data in the subset, that the user preference causes the sensitivity to reduce to below the level of sensitivity; and computer usable code for constructing, responsive to the concluding, a second instruction for the UI design tool, the second instruction causing the UI design tool to move a UI element in the future UI design to a second area when the future UI design is used with the user preference. 6. The computer usable program product of claim 4 , wherein the user preference is a handedness of a user of the future UI design. | 0.784053 |
7,921,184 | 1 | 7 | 1. In a network device, a method for responding to a request for a dynamically generated object from a plurality of clients, the method comprising the steps of: receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; transmitting, by the cache manager, the first request to the originating server; receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and flushing, by the cache manager, the dynamically generated object from the transmission buffer, responsive to completion of transmission of the dynamically generated object to the first client and the second client. | 1. In a network device, a method for responding to a request for a dynamically generated object from a plurality of clients, the method comprising the steps of: receiving, by a cache manager operating on a network device, from a first client a first request for a dynamically generated object from an originating server; transmitting, by the cache manager, the first request to the originating server; receiving, by the cache manager, the response to the first request from the originating server, the response comprising the dynamically generated object; initiating transmission, by the cache manager, of the dynamically generated object to the first client in response to the first request, the dynamically generated object stored in a transmission buffer of a network stack of the network device while waiting to be transmitted; receiving, by the cache manager, from a second client a second request for the dynamically generated object prior to completing transmission of the response to the first request of the first client; determining, by the cache manager, that the dynamically generated object is currently in the transmission buffer of the network stack of the network device; transmitting, by the cache manager and responsive to the determination that the dynamically generated object is currently in the transmission buffer, the dynamically generated object to the second client from the transmission buffer in response to the second request; and flushing, by the cache manager, the dynamically generated object from the transmission buffer, responsive to completion of transmission of the dynamically generated object to the first client and the second client. 7. The method of claim 1 , comprising determining the second request is for the dynamically generated object of the first request via an object determinant associated with the second request. | 0.762438 |
9,946,751 | 25 | 26 | 25. A system for improving a query in a multi-tenant database system that is to be performed in the context of a tenant-specific filter on a tenant identifier, the system comprising: a processor; a network interface; and a computer-readable medium tangibly embodied with instructions capable of configuring the processor to: receive at a network interface of a server an original query, wherein the original query is associated with data within a database as identified by the tenant identifier, and wherein the database includes at least a first index and a second index, further wherein the database stores data for multiple tenants that are unrelated organizations and have different database schemas, the data corresponding to each tenant having tenant-specific characteristics; retrieve, using a processor of the server, metadata associated with the data, wherein at least a portion of the data is stored in a common table within the database system; determine, using the processor, a tenant-selective query syntax by analyzing at least metadata generated from tenant-specific characteristics; analyze, using the processor, metadata generated from information about the organization to which the original query corresponds; and generate, using the processor, an improved query using the query syntax, wherein the improved query is based at least in part upon the original query and a result of a join between a first number of rows associated with the first index and a second number of rows associated with the second index and the analysis of the metadata. | 25. A system for improving a query in a multi-tenant database system that is to be performed in the context of a tenant-specific filter on a tenant identifier, the system comprising: a processor; a network interface; and a computer-readable medium tangibly embodied with instructions capable of configuring the processor to: receive at a network interface of a server an original query, wherein the original query is associated with data within a database as identified by the tenant identifier, and wherein the database includes at least a first index and a second index, further wherein the database stores data for multiple tenants that are unrelated organizations and have different database schemas, the data corresponding to each tenant having tenant-specific characteristics; retrieve, using a processor of the server, metadata associated with the data, wherein at least a portion of the data is stored in a common table within the database system; determine, using the processor, a tenant-selective query syntax by analyzing at least metadata generated from tenant-specific characteristics; analyze, using the processor, metadata generated from information about the organization to which the original query corresponds; and generate, using the processor, an improved query using the query syntax, wherein the improved query is based at least in part upon the original query and a result of a join between a first number of rows associated with the first index and a second number of rows associated with the second index and the analysis of the metadata. 26. The system of claim 25 , wherein the computer-readable medium is tangibly embodied with further instructions to: receiving information identifying the user; retrieving, using the processor, metadata about the user; and wherein determining, using the processor, comprises analyzing at least one of the group consisting of metadata generated from information about the user, metadata generated from information about the tenant, and metadata generated from the data accessible by the tenant. | 0.5 |
8,539,348 | 1 | 3 | 1. A method of enabling input into an electronic device that comprises a plurality of input members having a number of characters assigned thereto, and a memory having stored therein a plurality of words and a plurality of word frames, each word frame having associated therewith at least a first word comprising a plurality of characters that include a sequential plurality of characters that are all assigned to a particular input member, each word frame being representative of the at least first word and comprising, in place of the sequential plurality of characters of the at least first word, a contracted portion that is representative of any nonzero quantity of the characters assigned to the particular input member, the method comprising: detecting as an input a plurality of input member selections; identifying in the memory one or more words that correspond with the input for at least partial inclusion in an output set; identifying in the memory a particular word frame that corresponds with the input; adding to the output set at least a portion of at least a first word associated with the particular word frame; and outputting at least a portion of the output set. | 1. A method of enabling input into an electronic device that comprises a plurality of input members having a number of characters assigned thereto, and a memory having stored therein a plurality of words and a plurality of word frames, each word frame having associated therewith at least a first word comprising a plurality of characters that include a sequential plurality of characters that are all assigned to a particular input member, each word frame being representative of the at least first word and comprising, in place of the sequential plurality of characters of the at least first word, a contracted portion that is representative of any nonzero quantity of the characters assigned to the particular input member, the method comprising: detecting as an input a plurality of input member selections; identifying in the memory one or more words that correspond with the input for at least partial inclusion in an output set; identifying in the memory a particular word frame that corresponds with the input; adding to the output set at least a portion of at least a first word associated with the particular word frame; and outputting at least a portion of the output set. 3. The method of claim 1 , wherein at least some of the plurality of word frames further comprise a root portion preceding the contracted portion, the root portion comprising the characters of the at least first word associated with the word frame that precede the sequential plurality of characters, and further comprising as at least a portion of the identifying of the particular word frame, making a determination that a portion of the input that precedes any quantity of sequential selections of the particular input member corresponds with a root portion of the particular word frame except for at most one discrepancy therebetween. | 0.5 |
8,019,709 | 15 | 16 | 15. The method of claim 13 , further comprising: determining a number of node records of said node vector after said replacing; and determining a content index as said resulting state corresponding to a number of node records equal to one. | 15. The method of claim 13 , further comprising: determining a number of node records of said node vector after said replacing; and determining a content index as said resulting state corresponding to a number of node records equal to one. 16. The method of claim 15 , further comprising performing a specified editing action relevant to said content according to a value of said content index. | 0.5 |
9,519,917 | 1 | 3 | 1. A method comprising: displaying a document that includes a script and a program, the program, comprising of a programming language and being executable to initiate an analysis that identifies a word in the document as a contextual keyword of the document, the script, comprising of a scripting language and being executable to highlight any contextual keywords identified in the document; by execution, at a client machine, of the program included within the document, initiating the analysis in response to the program sending a request to a server machine; by execution, at the client machine, of the program included within the document, performing the analysis by: determining an occurrence frequency of the word in the document; determining that the word is among a group of most frequently occurring words in the document, the group of most frequently occurring words having a predefined size; identifying an ad category with a highest probability of containing the word based on the word being among the group of most frequently occurring words in the document; comparing the word in the document with words contained in the ad category; and identifying the word in the document as the contextual keyword of the document that is being displayed; selecting an ad from a publication system and from a further ad category that includes the highest number of ads related to the contextual keyword of the document that is being displayed, the selecting of the ad being performed by a processor of the server machine; by execution of the script included within the document, highlighting the word identified as the contextual keyword of the document that is being displayed; detecting, at the client machine, a mouseover event over the word that is highlighted in the document that is being displayed; and displaying, at the client machine, the ad within a tooltip window over the document in response to the detecting of the mouseover event over the word highlighted in the document that is being displayed. | 1. A method comprising: displaying a document that includes a script and a program, the program, comprising of a programming language and being executable to initiate an analysis that identifies a word in the document as a contextual keyword of the document, the script, comprising of a scripting language and being executable to highlight any contextual keywords identified in the document; by execution, at a client machine, of the program included within the document, initiating the analysis in response to the program sending a request to a server machine; by execution, at the client machine, of the program included within the document, performing the analysis by: determining an occurrence frequency of the word in the document; determining that the word is among a group of most frequently occurring words in the document, the group of most frequently occurring words having a predefined size; identifying an ad category with a highest probability of containing the word based on the word being among the group of most frequently occurring words in the document; comparing the word in the document with words contained in the ad category; and identifying the word in the document as the contextual keyword of the document that is being displayed; selecting an ad from a publication system and from a further ad category that includes the highest number of ads related to the contextual keyword of the document that is being displayed, the selecting of the ad being performed by a processor of the server machine; by execution of the script included within the document, highlighting the word identified as the contextual keyword of the document that is being displayed; detecting, at the client machine, a mouseover event over the word that is highlighted in the document that is being displayed; and displaying, at the client machine, the ad within a tooltip window over the document in response to the detecting of the mouseover event over the word highlighted in the document that is being displayed. 3. The method of claim 1 , wherein: the analysis of the document includes detecting a language of the document. | 0.900538 |
9,537,674 | 16 | 18 | 16. A non-transitory computer readable storage medium as defined in claim 15 , wherein the output data defines a graphical is environment in which the visualization structures move. | 16. A non-transitory computer readable storage medium as defined in claim 15 , wherein the output data defines a graphical is environment in which the visualization structures move. 18. A non-transitory computer readable storage medium as defined in claim 16 , wherein the visualization structures move and simulate a physical effect. | 0.5 |
7,788,134 | 1 | 6 | 1. A computer-implemented method of displaying items that are available for commercial transaction, the method comprising: under control of one or more computer systems configured with executable instructions, analyzing data associated with items for consumption to identify any geographic locations associated with each of the items; associating geographic attributes with the items for consumption corresponding to the identified geographic locations; receiving an indication of a particular geographic location from a user; identifying, based at least in part on the particular geographic location, one or more of the items for display; providing for display a geographic representation of the particular location on which information representative of an identified item of said items is positioned and displayed based on at least one of the geographic locations for the identified item; and offering for consumption the identified item from a merchant, said merchant being independent of the particular geographic location. | 1. A computer-implemented method of displaying items that are available for commercial transaction, the method comprising: under control of one or more computer systems configured with executable instructions, analyzing data associated with items for consumption to identify any geographic locations associated with each of the items; associating geographic attributes with the items for consumption corresponding to the identified geographic locations; receiving an indication of a particular geographic location from a user; identifying, based at least in part on the particular geographic location, one or more of the items for display; providing for display a geographic representation of the particular location on which information representative of an identified item of said items is positioned and displayed based on at least one of the geographic locations for the identified item; and offering for consumption the identified item from a merchant, said merchant being independent of the particular geographic location. 6. The method of claim 1 , wherein analyzing data associated with items includes analyzing content of the items and identifying a geographic attribute in the content. | 0.798544 |
7,657,434 | 1 | 3 | 1. A computer-implemented method for interpreting a frame definition, the frame definition comprising at least one data field and at least one goal, to control a dialog with a user, the method comprising: receiving information input from the user; updating frame data associated with the frame definition dependent upon the information input from the user; determining that at least one goal of the frame definition is activated, wherein a goal is activated when at least one field referred to inside the goal has been modified; selecting a goal that has been determined to be activated; if the selected activated goal is satisfied: evaluating final rules of the frame definition; and completing the interpretation of the frame definition; and if the selected activated goal is not satisfied: selecting an unfilled data field in the goal; and generating an output to the user using information in the frame definition that is associated with the selected unfilled data field. | 1. A computer-implemented method for interpreting a frame definition, the frame definition comprising at least one data field and at least one goal, to control a dialog with a user, the method comprising: receiving information input from the user; updating frame data associated with the frame definition dependent upon the information input from the user; determining that at least one goal of the frame definition is activated, wherein a goal is activated when at least one field referred to inside the goal has been modified; selecting a goal that has been determined to be activated; if the selected activated goal is satisfied: evaluating final rules of the frame definition; and completing the interpretation of the frame definition; and if the selected activated goal is not satisfied: selecting an unfilled data field in the goal; and generating an output to the user using information in the frame definition that is associated with the selected unfilled data field. 3. A method in accordance with claim 1 wherein generating an output to the user using information in the frame definition that is associated with the selected unfilled data field comprises generating a prompt associated with the selected unfilled data field. | 0.522222 |
9,087,049 | 1 | 4 | 1. A method for translating natural language text, comprising: receiving at least one multimedia element including a first natural language text; generating metadata representing the first natural language text; generating at least one signature for the at least one multimedia element; determining the context of the at least one multimedia element respective of the signature; and searching for a multimedia content element (MMCE) corresponding to the received at least one multimedia element that includes a second natural language text, wherein the search is performed using the at least one signature, the context and metadata generated for the at least input text in a first natural language respective of the context, wherein the second natural language text is a translated text of the first natural language text. | 1. A method for translating natural language text, comprising: receiving at least one multimedia element including a first natural language text; generating metadata representing the first natural language text; generating at least one signature for the at least one multimedia element; determining the context of the at least one multimedia element respective of the signature; and searching for a multimedia content element (MMCE) corresponding to the received at least one multimedia element that includes a second natural language text, wherein the search is performed using the at least one signature, the context and metadata generated for the at least input text in a first natural language respective of the context, wherein the second natural language text is a translated text of the first natural language text. 4. The method of claim 1 , wherein the metadata includes at least one of: identifiers of the first language text, amount of words in the first language text, letters in the first language text, phonemic information, and appearance of the text. | 0.710024 |
8,280,734 | 12 | 15 | 12. An apparatus for titling recordable audio comprising: an input module to receive audio representative of a title during a title acquisition mode and to receive a body of a recording during a recording mode, wherein the apparatus is configurable in an auto-titling mode in which the recording mode is automatically commenced a predetermined time after the title acquisition mode is commenced; a speech to text converter to convert the audio into textual characters representing the title, wherein the textual characters represent a lingual translation of the audio; and memory to store the body of the recording and the title. | 12. An apparatus for titling recordable audio comprising: an input module to receive audio representative of a title during a title acquisition mode and to receive a body of a recording during a recording mode, wherein the apparatus is configurable in an auto-titling mode in which the recording mode is automatically commenced a predetermined time after the title acquisition mode is commenced; a speech to text converter to convert the audio into textual characters representing the title, wherein the textual characters represent a lingual translation of the audio; and memory to store the body of the recording and the title. 15. The apparatus of claim 12 , further comprising a text to speech converter to provide an audio indicator of the text representing the title. | 0.791545 |
6,014,559 | 25 | 26 | 25. A system for delivering a voice mail notification to a subscriber of a voice mail system to indicate that a voice mail message is waiting in a subscriber mailbox comprising a voice mail system having a plurality of different subscriber mailboxes in which voice mail messages are stored, and including means for generating a respective voice mail notification for each stored voice mail message, the voice mail notification having a calling number of the calling party that left the voice mail message in the voice mail system, a name of the calling party, if known, and an index of the voice mail messages waiting in the subscriber mailbox, and a cellular phone network in communication with the voice mail system for receiving generated voice mail notifications from the voice mail system and forwarding the voice mail notifications to a respective subscriber mail box of a private base station used by a respective subscriber without subscriber intervention. | 25. A system for delivering a voice mail notification to a subscriber of a voice mail system to indicate that a voice mail message is waiting in a subscriber mailbox comprising a voice mail system having a plurality of different subscriber mailboxes in which voice mail messages are stored, and including means for generating a respective voice mail notification for each stored voice mail message, the voice mail notification having a calling number of the calling party that left the voice mail message in the voice mail system, a name of the calling party, if known, and an index of the voice mail messages waiting in the subscriber mailbox, and a cellular phone network in communication with the voice mail system for receiving generated voice mail notifications from the voice mail system and forwarding the voice mail notifications to a respective subscriber mail box of a private base station used by a respective subscriber without subscriber intervention. 26. The system according to claim 25 wherein said private base station includes a speaker through which a retrieval voice mail message is played. | 0.684783 |
10,084,805 | 24 | 25 | 24. The non-transitory computer-readable storage medium of claim 23 , comprising instructions that when executed cause the processing circuitry to generate indicators for entities committing scenario violations based on applying the scenario rules, each indicator to indicate an entity committed a scenario violation. | 24. The non-transitory computer-readable storage medium of claim 23 , comprising instructions that when executed cause the processing circuitry to generate indicators for entities committing scenario violations based on applying the scenario rules, each indicator to indicate an entity committed a scenario violation. 25. The non-transitory computer-readable storage medium of claim 24 , comprising instructions that when executed cause the processing circuitry to: pass each indicator for each of the scenario clusters through a statistical model to determine the predictive ability values for the scenario clusters, each indicator to indicate whether a scenario cluster is triggered to predict the targeted behavior, rank each of the scenario clusters based on the predictive ability values by relative significance, and remove scenario clusters having predictive ability values below the predictive threshold. | 0.5 |
9,330,075 | 1 | 2 | 1. A method for identifying garbage template article, comprising: extracting, by a processor, a feature from an eligible microblog article to generate an article feature, wherein the article feature comprises at least a punctuation feature, a topic feature, a bracket feature, a link feature and an account name feature; acquiring, by the processor, a garbage template list which comprises garbage template feature, the garbage template feature being an article feature whose frequency reaches a preset threshold, and the way to extract the garbage template feature being the same as the way to extract the article feature; and identifying, by the processor, the microblog article as a garbage template article when the article feature is the same as the garbage template feature in the garbage template list, wherein the eligible microblog article is a microblog article which is in an original form and contains link and picture, and before extracting a feature, by the processor, from an eligible microblog article, the method further comprises: removing, by the processor, numbers and letters from the eligible microblog article, and removing the contents in various brackets from the microblog article while retaining the brackets; wherein extracting, by the processor, a feature from the eligible microblog article comprises: segmenting, by the processor, the eligible microblog article with punctuations to generate segment numbers in order; extracting, by the processor, the punctuation of each segment, using the extracted punctuations to constitute a string, and generating the punctuation feature; extracting, by the processor, the topic and the corresponding segment number of the segment which has a topic for each segment, using the extracted topics and segment numbers to constitute a string, and generating the topic feature; extracting, by the processor, the segment number and the corresponding type of brackets of the segment which has brackets for each segment, using the extracted segment numbers and type of brackets to constitute a string, and generating the bracket feature; generating, by the processor, a sequence as the link feature according to whether there is a link in each segment; and generating, by the processor, a sequence as the account name feature according to whether there is an account name identity in each segment. | 1. A method for identifying garbage template article, comprising: extracting, by a processor, a feature from an eligible microblog article to generate an article feature, wherein the article feature comprises at least a punctuation feature, a topic feature, a bracket feature, a link feature and an account name feature; acquiring, by the processor, a garbage template list which comprises garbage template feature, the garbage template feature being an article feature whose frequency reaches a preset threshold, and the way to extract the garbage template feature being the same as the way to extract the article feature; and identifying, by the processor, the microblog article as a garbage template article when the article feature is the same as the garbage template feature in the garbage template list, wherein the eligible microblog article is a microblog article which is in an original form and contains link and picture, and before extracting a feature, by the processor, from an eligible microblog article, the method further comprises: removing, by the processor, numbers and letters from the eligible microblog article, and removing the contents in various brackets from the microblog article while retaining the brackets; wherein extracting, by the processor, a feature from the eligible microblog article comprises: segmenting, by the processor, the eligible microblog article with punctuations to generate segment numbers in order; extracting, by the processor, the punctuation of each segment, using the extracted punctuations to constitute a string, and generating the punctuation feature; extracting, by the processor, the topic and the corresponding segment number of the segment which has a topic for each segment, using the extracted topics and segment numbers to constitute a string, and generating the topic feature; extracting, by the processor, the segment number and the corresponding type of brackets of the segment which has brackets for each segment, using the extracted segment numbers and type of brackets to constitute a string, and generating the bracket feature; generating, by the processor, a sequence as the link feature according to whether there is a link in each segment; and generating, by the processor, a sequence as the account name feature according to whether there is an account name identity in each segment. 2. The method according to claim 1 , wherein the article feature further comprises a content feature, and extracting, by the processor, a feature from the eligible microblog article further comprises: concatenating, by the processor, the remainder of each segment, resulted from removing all of the punctuation, topic, bracket, link and account name identity from each segment, sequentially together to generate the content feature. | 0.554639 |
8,271,260 | 1 | 4 | 1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; receiving translations of text phrases from members of the social network, the text phrases comprising content displayed in a social networking system; providing content to a particular member, the content including a text phrase in a first language; responsive to receiving a request from the particular member to translate the text phrase from the first language to a second language: selecting, by a computer system, a translation of the text phrase from a set of translations of the text phrase in the second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for the particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the member requesting the translation. | 1. A computer implemented method comprising: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; receiving translations of text phrases from members of the social network, the text phrases comprising content displayed in a social networking system; providing content to a particular member, the content including a text phrase in a first language; responsive to receiving a request from the particular member to translate the text phrase from the first language to a second language: selecting, by a computer system, a translation of the text phrase from a set of translations of the text phrase in the second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for the particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the member requesting the translation. 4. The method of claim 1 , wherein the text phrase comprises a portion of a social networking system infrastructure. | 0.880412 |
8,359,202 | 1 | 6 | 1. A computer implemented method, comprising: displaying a sequence of words on a user interface rendered on a display device; applying, by one or more computers, in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associating, by the one or more computers, a first character having an associated first voice model to the first portion of words in the sequence of words; and associating, by the one or more computers, a second, different character having an associated second, different voice model to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. | 1. A computer implemented method, comprising: displaying a sequence of words on a user interface rendered on a display device; applying, by one or more computers, in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associating, by the one or more computers, a first character having an associated first voice model to the first portion of words in the sequence of words; and associating, by the one or more computers, a second, different character having an associated second, different voice model to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. 6. The method of claim 1 , further comprising generating an audible output corresponding to the words in the sequence of words using a text-to-speech application. | 0.787402 |
9,406,078 | 16 | 25 | 16. A system for processing natural language utterances that include requests and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions, the computer program instructions comprising at least a conversational language processor configured to interpret a natural language utterance, which relates to a request, based on words or phrases recognized from the natural language utterance, the computer program instructions which when executed cause the one or more physical processors to: in response to receipt of the natural language utterance, provide the natural language utterance as an input to a speech recognition engine; in response to receipt of the words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine, provide the words or phrases as an input to the conversational language processor; interpret the natural language utterance, at the conversational language processor, based on the recognized words or phrases; determine the request based on the interpretation of the natural language utterance; determine a context for the natural language utterance based at least on the recognized words or phrases; select an advertisement based at least on the determined context; provide the selected advertisement via an output device coupled to the conversational language processor; obtain a response to the request; provide the response to the request; in response to receipt of a second natural language utterance, provide the second natural language utterance as an input to the speech recognition engine; in response to receipt of a second set of words or phrases, recognized from the second natural language utterance, as a second output of the speech recognition engine, provide the second set of words or phrases as a second input to the conversational language processor; interpret the second natural language utterance at the conversational language processor based on the recognized second set of words or phrases and the determined context; and determine a second request, related to the advertisement, based on the interpretation of the second natural language utterance; and obtaining and providing a second response to the second request. | 16. A system for processing natural language utterances that include requests and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions, the computer program instructions comprising at least a conversational language processor configured to interpret a natural language utterance, which relates to a request, based on words or phrases recognized from the natural language utterance, the computer program instructions which when executed cause the one or more physical processors to: in response to receipt of the natural language utterance, provide the natural language utterance as an input to a speech recognition engine; in response to receipt of the words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine, provide the words or phrases as an input to the conversational language processor; interpret the natural language utterance, at the conversational language processor, based on the recognized words or phrases; determine the request based on the interpretation of the natural language utterance; determine a context for the natural language utterance based at least on the recognized words or phrases; select an advertisement based at least on the determined context; provide the selected advertisement via an output device coupled to the conversational language processor; obtain a response to the request; provide the response to the request; in response to receipt of a second natural language utterance, provide the second natural language utterance as an input to the speech recognition engine; in response to receipt of a second set of words or phrases, recognized from the second natural language utterance, as a second output of the speech recognition engine, provide the second set of words or phrases as a second input to the conversational language processor; interpret the second natural language utterance at the conversational language processor based on the recognized second set of words or phrases and the determined context; and determine a second request, related to the advertisement, based on the interpretation of the second natural language utterance; and obtaining and providing a second response to the second request. 25. The system of claim 16 , wherein to obtain the response, the one or more physical processors are further programmed to: (i) service the request and determine the response, or (ii) provide the request to a remote device and receive the response from the remote device. | 0.546823 |
8,832,655 | 27 | 29 | 27. The computer-readable storage medium of claim 26 , wherein building at least one weighted term document matrix comprises: building two weighted term document matrices, based on two different classifications of semantic anchors; and wherein using LSI comprises: using LSI on each weighted term document matrix to produce two matrices of application vectors; and wherein calculating the cosine comprises: calculating the cosine between a first application vector and a second application vector, wherein each of the first and second application vectors is found within one of the two matrices of application vectors; and calculating the cosine between a third application vector and a fourth application vector, wherein each of the third and fourth application vectors is found within the other of the two matrices of application vectors, wherein the third application vector corresponds to the first application, and wherein the fourth application corresponds to the second application; and combining the two calculated cosine values into one new value. | 27. The computer-readable storage medium of claim 26 , wherein building at least one weighted term document matrix comprises: building two weighted term document matrices, based on two different classifications of semantic anchors; and wherein using LSI comprises: using LSI on each weighted term document matrix to produce two matrices of application vectors; and wherein calculating the cosine comprises: calculating the cosine between a first application vector and a second application vector, wherein each of the first and second application vectors is found within one of the two matrices of application vectors; and calculating the cosine between a third application vector and a fourth application vector, wherein each of the third and fourth application vectors is found within the other of the two matrices of application vectors, wherein the third application vector corresponds to the first application, and wherein the fourth application corresponds to the second application; and combining the two calculated cosine values into one new value. 29. The computer-readable storage medium of claim 27 , wherein the semantic anchors comprise Application Programming Interface (API) calls. | 0.5 |
6,026,395 | 7 | 11 | 7. A method performed by a computing system during a proceeding in which a transcript representative of spoken words is generated in real-time, the method comprising: generating a transcript in real time; storing the transcript; accepting, during generation of the transcript, a user input representative of a first search request; identifying at least a portion of the stored transcript corresponding to the first search request; and displaying, during generation of the transcript, the at least a portion of the transcript identified. | 7. A method performed by a computing system during a proceeding in which a transcript representative of spoken words is generated in real-time, the method comprising: generating a transcript in real time; storing the transcript; accepting, during generation of the transcript, a user input representative of a first search request; identifying at least a portion of the stored transcript corresponding to the first search request; and displaying, during generation of the transcript, the at least a portion of the transcript identified. 11. The method claim 7 further comprising screening words of high occurrence during the identifying. | 0.74359 |
8,315,484 | 29 | 54 | 29. A system for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein this at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the system comprises: a system component using an Internet search engine with search arguments established according to a search strategy comprising: a) the system component provides initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) the system component compares the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminate the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non-existing, and the word with this spelling alternative is discarded from further investigations, and continue with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modify the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) the system component is processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative. | 29. A system for resolving contradicting output data from an Optical Character Recognition (OCR) system, wherein the output data comprises at least one word with at least one uncertainly recognized character, wherein the at least one uncertainly recognized character is reported in the output data together with probable alternatives for the at least one uncertainly recognized character, and the words wherein this at least one uncertainly recognized character has been encountered in an image of a text being processed by the OCR system, the system comprises: a system component using an Internet search engine with search arguments established according to a search strategy comprising: a) the system component provides initial search arguments by forming spelling alternatives for the words comprising the at least one uncertainly recognized character by substituting the at least one uncertainly recognized character with the reported probable alternatives for the at least one character, one by one, and in possible combinations in each encountered word, or by removing a character, thereby forming a plurality of spelling alternatives, and then measuring and recording number of hits for search results of each respective spelling alternative that has been formed in this manner, b) the system component compares the measured number of hits for each of the spelling alternatives with an upper predefined relative threshold level and a lower predefined relative threshold level, wherein each of the respective comparisons of the plurality of measurements falls into one of three possible outcomes: i) if the measurement of a spelling alternative is above the predefined relative upper threshold level, the corresponding spelling alternative for this measurement is the correct spelling alternative for the word, and terminate the Internet search, ii) if the measurement of a spelling alternative is below the lower predefined relative threshold level, the corresponding spelling alternative for this measurement is deemed non-existing, and the word with this spelling alternative is discarded from further investigations, and continue with other spelling alternatives that has been formed as search arguments for the Internet search engine, iii) if the measurement of a spelling alternative falls between the upper relative threshold level and the lower relative threshold level, exit the Internet search engine and modify the search strategy providing further search arguments as a combination of members of the remaining spelling alternatives and other words encountered in the document, other character alternatives for the at least one uncertainly recognized character, phrases, adapting the upper relative threshold level, adapting the lower relative threshold level, and/or other information related to the output data from the OCR system, before continuing using the search strategy providing further measurements and comparisons for resolving the contradicting output data, c) the system component is processing step b) a number of predefined times, or until there is only one spelling alternative left, whatever occurs first, providing an iteration amongst a plurality of different search arguments used in the search strategy before terminating step b), and using the remaining spelling alternative having the highest measurement above the upper relative threshold level as the correct spelling alternative. 54. The system according to claim 29 , wherein a merit function is used to define a measurement for the number of hits as: totscore ( i ) = aCRS word ( i ) + b # hits i max ( # hits j ) j ≠ i wherein a+b=1, CRS word (i) is a character score value from the OCR process related to the spelling of alternative i, max(#hits j ) j≠i is the total measured number of hits for all spelling of alternatives not including the spelling alternative for i. | 0.808714 |
9,275,139 | 12 | 13 | 12. A system to search audio data, comprising: a receiver configured to receive audio data representing speech; a receiver configured to receive a search query related to the audio data; a processor configured to compile the search query into a hierarchy of scored speech recognition sub-searches; an audio search engine operating in an audio domain configured to search the audio data for speech identified by one or more of the sub-searches to produce hits; and a processor configured to combine the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M of N function inputs exceed a predetermined threshold value, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score. | 12. A system to search audio data, comprising: a receiver configured to receive audio data representing speech; a receiver configured to receive a search query related to the audio data; a processor configured to compile the search query into a hierarchy of scored speech recognition sub-searches; an audio search engine operating in an audio domain configured to search the audio data for speech identified by one or more of the sub-searches to produce hits; and a processor configured to combine the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M of N function inputs exceed a predetermined threshold value, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score. 13. The system of claim 12 , wherein the high score is produced by applying a transform function to at least one of N function inputs. | 0.559211 |
9,922,351 | 6 | 8 | 6. The computer-implemented method of claim 1 , the pre-determined criteria comprising: a first pre-determined minimum number of feedback providing users at the first location that provided feedback suggesting how the presented screen content selected by the feedback providing users at the first location should be modified, and a second pre-determined minimum number of feedback providing users at the second location that provided feedback suggesting how the presented screen content selected by the feedback providing users at the second location should be modified. | 6. The computer-implemented method of claim 1 , the pre-determined criteria comprising: a first pre-determined minimum number of feedback providing users at the first location that provided feedback suggesting how the presented screen content selected by the feedback providing users at the first location should be modified, and a second pre-determined minimum number of feedback providing users at the second location that provided feedback suggesting how the presented screen content selected by the feedback providing users at the second location should be modified. 8. The computer-implemented method of claim 6 , wherein the first pre-determined minimum number is different from the second pre-determined minimum number. | 0.5 |
9,922,032 | 3 | 4 | 3. The method of claim 1 further comprising adding, via the knowledge base aggregator computer, the instances of the co-occurrence of the two or more features to the feature co-occurrence database along with metadata pertaining to the instance. | 3. The method of claim 1 further comprising adding, via the knowledge base aggregator computer, the instances of the co-occurrence of the two or more features to the feature co-occurrence database along with metadata pertaining to the instance. 4. The method of claim 3 wherein the metadata is selected from the group consisting of feature type, document identifier, document corpus identifier, distance in text between co-occurring features, and a confidence score. | 0.5 |
8,838,653 | 5 | 6 | 5. The method of claim 1 , wherein an object-oriented data model construct, from the plurality of object-oriented data model constructs, is a particular object-oriented package definition; wherein the one or more YANG data model statements includes a particular YANG module statement; and wherein translating the first data to the second data comprises translating the particular object-oriented package definition to the particular YANG module statement. | 5. The method of claim 1 , wherein an object-oriented data model construct, from the plurality of object-oriented data model constructs, is a particular object-oriented package definition; wherein the one or more YANG data model statements includes a particular YANG module statement; and wherein translating the first data to the second data comprises translating the particular object-oriented package definition to the particular YANG module statement. 6. The method of claim 5 , wherein the particular object-oriented package definition comprises a name for the particular object-oriented package, and wherein translating the particular object-oriented package definition to the particular YANG module statement comprises deriving the argument to the particular YANG module statement from the name for the particular object-oriented package. | 0.5 |
9,639,898 | 11 | 15 | 11. A computer-implemented method, comprising: extracting, by at least a processor of a computer, tax related data from a tax transaction database that stores respective records describing respective tax return forms filed by respective taxpayers, where each record includes values in tax return fields describing a taxpayer who filed the tax return form, further where the tax return fields include tax return lines; transforming and storing, by at least the processor, the extracted tax related data in a tax data warehouse that includes fact tables and dimension tables by populating a fact table with i) values in the tax return form lines and ii) a form type identifier that identifies a type of the tax return form, where populating the fact table with values according to tax return form lines improves a granularity of analysis that can be performed using the tax data warehouse as compared to the tax transaction database; where the tax data warehouse includes a dimension table that has i) a row for each tax form type and ii) columns storing contextual information about tax return form lines; generating and storing, by at least the processor, a plurality of key performance indicator (KPI) queries where each KPI query includes a different combination of tax metrics from the tax transaction database and one or more query elements associated with a criteria from the tax metrics; generating, by at least the processor, a plurality of materialized views where each materialized view corresponds to one of the plurality of KPI queries and stores aggregated key performance indicator (KPI) values for the corresponding KPI query; storing, by at least the processor, the plurality of materialized views in the tax data warehouse; generating and displaying, by at least the processor, an interface that displays one or more of the plurality of KPI queries for selection; and in response to a first KPI query being selected from the interface, causing the first KPI query to be executed on at least a first materialized view from the plurality of materialized views that corresponds to the first KPI query to return results corresponding to the first KPI query. | 11. A computer-implemented method, comprising: extracting, by at least a processor of a computer, tax related data from a tax transaction database that stores respective records describing respective tax return forms filed by respective taxpayers, where each record includes values in tax return fields describing a taxpayer who filed the tax return form, further where the tax return fields include tax return lines; transforming and storing, by at least the processor, the extracted tax related data in a tax data warehouse that includes fact tables and dimension tables by populating a fact table with i) values in the tax return form lines and ii) a form type identifier that identifies a type of the tax return form, where populating the fact table with values according to tax return form lines improves a granularity of analysis that can be performed using the tax data warehouse as compared to the tax transaction database; where the tax data warehouse includes a dimension table that has i) a row for each tax form type and ii) columns storing contextual information about tax return form lines; generating and storing, by at least the processor, a plurality of key performance indicator (KPI) queries where each KPI query includes a different combination of tax metrics from the tax transaction database and one or more query elements associated with a criteria from the tax metrics; generating, by at least the processor, a plurality of materialized views where each materialized view corresponds to one of the plurality of KPI queries and stores aggregated key performance indicator (KPI) values for the corresponding KPI query; storing, by at least the processor, the plurality of materialized views in the tax data warehouse; generating and displaying, by at least the processor, an interface that displays one or more of the plurality of KPI queries for selection; and in response to a first KPI query being selected from the interface, causing the first KPI query to be executed on at least a first materialized view from the plurality of materialized views that corresponds to the first KPI query to return results corresponding to the first KPI query. 15. The computer-implemented method of claim 11 , further comprising providing one or more reports, where a report comprises a set of KPI queries that, when executed, return KPI query results according to a predetermined format. | 0.586957 |
9,373,330 | 3 | 9 | 3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker. | 3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker. 9. The method of claim 3 , wherein determining if the set of speech utterances corresponds to one or any of the number of speakers known to the computer system includes comparing the score computed to a threshold. | 0.880605 |
8,572,511 | 1 | 11 | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. 11. The non-transitory computer readable medium of claim 1 , wherein the new search query is a Boolean search query that includes AND, OR, and NOT functions. | 0.829348 |
10,158,639 | 9 | 12 | 9. The non-transitory, tangible computer-readable medium of claim 8 , wherein the instructions to generate a redacted credit report template from among the plurality of redacted credit report templates comprises instructions that, when executed by the processor, cause the processor to: open an unredacted credit report, which contains personal information and is formatted in portable document format (PDF), via a first software application; remove the personal information contained in the unredacted credit report via the first software application to generate a redacted credit report in PDF; save the redacted credit report in PDF via the first software application; open the redacted credit report in PDF with a second software application, the second software application being associated with word processing functionality, wherein upon opening the redacted credit report with the second software application, the second software application causes the redacted credit report in PDF to be reflowed and formatted into an editable word processing file; and edit and save the redacted credit report with the second software application to generate the redacted credit report template. | 9. The non-transitory, tangible computer-readable medium of claim 8 , wherein the instructions to generate a redacted credit report template from among the plurality of redacted credit report templates comprises instructions that, when executed by the processor, cause the processor to: open an unredacted credit report, which contains personal information and is formatted in portable document format (PDF), via a first software application; remove the personal information contained in the unredacted credit report via the first software application to generate a redacted credit report in PDF; save the redacted credit report in PDF via the first software application; open the redacted credit report in PDF with a second software application, the second software application being associated with word processing functionality, wherein upon opening the redacted credit report with the second software application, the second software application causes the redacted credit report in PDF to be reflowed and formatted into an editable word processing file; and edit and save the redacted credit report with the second software application to generate the redacted credit report template. 12. The non-transitory, tangible computer-readable medium of claim 9 , further storing machine readable instructions that, when executed by a processor, cause the processor to: compare the content included in portions of the sent email messages as specified by the detection rule to content included in each of the plurality of credit report templates; calculate, for each comparison made between the content included in portions of the sent email messages and content included in each of the plurality of credit report templates, an initial document exposure score; flag a sent email message from among the sent email messages as a potentially safe sent email message when none of the comparisons between content included in the portions of the sent email message and content included in each of the plurality of credit report templates yields an initial document exposure score below the minimum document exposure threshold; calculate a secondary document exposure score based upon a presence of one or more keywords and form fields associated with credit reports contained in the content included in portions of the potentially safe sent email message; and when the secondary document exposure score exceeds a detection threshold, re-routing the potentially safe sent email message within the local organization to prevent the potentially safe sent email message from being routed outside of the organization as addressed. | 0.5 |
9,275,411 | 9 | 12 | 9. A voice action system comprising: at least one computing device operably coupled to at least one memory and configured to: receive a plurality of electronic voice action bids from a plurality of advertisers that each represent, an offer for modifying the voice action system to include a voice action associated with an electronic voice action bid of the plurality of electronic voice action bids, wherein the voice action comprises a triggering phrase and an action; select, based on a predetermined criteria, one or more electronic voice action bids from among the plurality of electronic voice action bids; modify data associated with the voice action system to include the voice action for each of the selected one or more electronic voice action bids, wherein the voice action system performs the action associated with the respective voice action when voice input received from a user corresponds to the triggering phrase associated with the respective voice action; and set a parameter in a voice action language model database to increase a likelihood that the voice action system determines that the voice input received from the user corresponds to the triggering phrase of the selected one or more electronic voice action bids; and a memory having the voice action language model database stored therein that includes words that the voice action system is configured to recognize as being associated with a triggering phrase of one or more voice actions, wherein at least one voice action bid comprises an offer to modify the voice action system to include a voice action grammar associated with the voice action bid, wherein the voice action grammar comprises a plurality of voice actions, and wherein, for each of the at least one voice action bids having a voice action grammar associated therewith that is selected, the at least one computing device is configured to modify the voice action system to include the plurality of voice actions associated with the voice action grammar. | 9. A voice action system comprising: at least one computing device operably coupled to at least one memory and configured to: receive a plurality of electronic voice action bids from a plurality of advertisers that each represent, an offer for modifying the voice action system to include a voice action associated with an electronic voice action bid of the plurality of electronic voice action bids, wherein the voice action comprises a triggering phrase and an action; select, based on a predetermined criteria, one or more electronic voice action bids from among the plurality of electronic voice action bids; modify data associated with the voice action system to include the voice action for each of the selected one or more electronic voice action bids, wherein the voice action system performs the action associated with the respective voice action when voice input received from a user corresponds to the triggering phrase associated with the respective voice action; and set a parameter in a voice action language model database to increase a likelihood that the voice action system determines that the voice input received from the user corresponds to the triggering phrase of the selected one or more electronic voice action bids; and a memory having the voice action language model database stored therein that includes words that the voice action system is configured to recognize as being associated with a triggering phrase of one or more voice actions, wherein at least one voice action bid comprises an offer to modify the voice action system to include a voice action grammar associated with the voice action bid, wherein the voice action grammar comprises a plurality of voice actions, and wherein, for each of the at least one voice action bids having a voice action grammar associated therewith that is selected, the at least one computing device is configured to modify the voice action system to include the plurality of voice actions associated with the voice action grammar. 12. The voice action system of claim 9 , wherein the action associated with at least one of the voice actions of the electronic voice action bids comprises displaying a particular website in a browser application. | 0.871687 |
8,140,547 | 9 | 10 | 9. The system as claimed in claim 8 wherein the instructions further include instructions to: in response to the existence of an order comparison between the scope L 0 and the scope L 1 , performing: generate a context reference in the context M 0 and the context M 1 , replace a name of the data definition N 0 to generate a variable, n 0 , of the context M 0 ; and refer to a variable, n 1 , of the context M 1 from the context M 0 . | 9. The system as claimed in claim 8 wherein the instructions further include instructions to: in response to the existence of an order comparison between the scope L 0 and the scope L 1 , performing: generate a context reference in the context M 0 and the context M 1 , replace a name of the data definition N 0 to generate a variable, n 0 , of the context M 0 ; and refer to a variable, n 1 , of the context M 1 from the context M 0 . 10. The system as claimed in claim 9 wherein a high-order scope in the context reference in the context M 0 and the context M 1 is a parent, and a low-order scope in the context references in the context M 0 and the context M 1 is a child. | 0.5 |
9,965,272 | 1 | 3 | 1. A system for monitoring software project development, the system comprising: a communication interface that receives, via one or more networks, information included in communications regarding the project development; a processor and memory that are integrated to: identify from the information a plurality of user stories for completion during development and a plurality of resources associated with each of the plurality of user stories; estimate a priority of each of the plurality of user stories; assign a value to each of the plurality of user stories, the assigned value representing an amount of effort needed to complete the respective user story; provide a threshold based on the resources and development based on the assigned value based on the organizational priorities of the development; monitor the burndown of each of the plurality of user stories, estimated priority and assigned value in the memory as ones of the plurality of user stories are completed as compared to the provided threshold; calibrate a difference in the assigned value of each of the plurality of user stories using a central calibration within an organization; and update a product backlog of user stories with the user story's associated calibrated assigned value and adjust resources associated with each of the plurality of user stories in the product backlog; and a display device for displaying the status of the project development based on a plurality of user stories remaining in the product backlog as compared to a plurality of completed user stories. | 1. A system for monitoring software project development, the system comprising: a communication interface that receives, via one or more networks, information included in communications regarding the project development; a processor and memory that are integrated to: identify from the information a plurality of user stories for completion during development and a plurality of resources associated with each of the plurality of user stories; estimate a priority of each of the plurality of user stories; assign a value to each of the plurality of user stories, the assigned value representing an amount of effort needed to complete the respective user story; provide a threshold based on the resources and development based on the assigned value based on the organizational priorities of the development; monitor the burndown of each of the plurality of user stories, estimated priority and assigned value in the memory as ones of the plurality of user stories are completed as compared to the provided threshold; calibrate a difference in the assigned value of each of the plurality of user stories using a central calibration within an organization; and update a product backlog of user stories with the user story's associated calibrated assigned value and adjust resources associated with each of the plurality of user stories in the product backlog; and a display device for displaying the status of the project development based on a plurality of user stories remaining in the product backlog as compared to a plurality of completed user stories. 3. The system of claim 1 wherein the value is one of a numerical sequence. | 0.807292 |
8,788,991 | 36 | 37 | 36. The system of claim 35 , wherein operations to group states of the automaton together in a group instance based on a number of unused first instances include operations to: determine a maximum matching for the graph. | 36. The system of claim 35 , wherein operations to group states of the automaton together in a group instance based on a number of unused first instances include operations to: determine a maximum matching for the graph. 37. The system of claim 36 , wherein operations to group states of the automaton together in a group instance based on a number of unused first instances include operations to: pair each set of states of the automaton corresponding to a matching vertices; and map each state of the automaton that corresponds to an unmatched vertex to a GOT instance wherein one SME instance in the GOT instance is to be unused. | 0.5 |
9,853,818 | 26 | 28 | 26. The system as recited in claim 24 , wherein each of the plurality of policies of the signature authority is indicated by a policy identifier. | 26. The system as recited in claim 24 , wherein each of the plurality of policies of the signature authority is indicated by a policy identifier. 28. The system as recited in claim 26 , wherein a signature field of the to be signed electronic document includes a policy identifier entry into which the signature authority places the policy identifier under which the signature authority operated. | 0.5 |
8,645,914 | 1 | 3 | 1. A method comprising: allowing software code associated with one or more of a plurality of programming building blocks to be concurrently edited and executed within a programming environment, including: receiving, by a conversational programming agent of the programming environment, (i) information regarding the plurality of programming building blocks and (ii) information indicative of a current situation relating to the plurality of programming building blocks; and evaluating, by the conversational programming agent, the plurality of programming building blocks based on the current situation; facilitating detection of one or more logical errors in one or more of the plurality of programming building blocks by proactively providing, by the conversational programming agent, semantic feedback regarding those of the plurality of programming building blocks to which the current situation is relevant to an end user based on the evaluating; wherein the semantic feedback includes a plurality of colored annotations of different colors to one or more visual representations of one or more of the plurality of programming building blocks; and wherein the conversational programming agent is implemented in one or more processors and one or more computer-readable media of one or more computer systems, the one or more computer-readable media having instructions tangibly embodied therein that are executable by the one or more processors. | 1. A method comprising: allowing software code associated with one or more of a plurality of programming building blocks to be concurrently edited and executed within a programming environment, including: receiving, by a conversational programming agent of the programming environment, (i) information regarding the plurality of programming building blocks and (ii) information indicative of a current situation relating to the plurality of programming building blocks; and evaluating, by the conversational programming agent, the plurality of programming building blocks based on the current situation; facilitating detection of one or more logical errors in one or more of the plurality of programming building blocks by proactively providing, by the conversational programming agent, semantic feedback regarding those of the plurality of programming building blocks to which the current situation is relevant to an end user based on the evaluating; wherein the semantic feedback includes a plurality of colored annotations of different colors to one or more visual representations of one or more of the plurality of programming building blocks; and wherein the conversational programming agent is implemented in one or more processors and one or more computer-readable media of one or more computer systems, the one or more computer-readable media having instructions tangibly embodied therein that are executable by the one or more processors. 3. The method of claim 1 , wherein the plurality of programming building blocks include operational programming building blocks. | 0.902883 |
10,013,480 | 9 | 13 | 9. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: identify a first plurality of buckets and assigning each message of a plurality of messages to one or more buckets of the first plurality based on topics of the plurality of messages, each of the one or more buckets having one or more assigned messages; create a conversation graph comprising a plurality of nodes, each node corresponding to a bucket of the first plurality corresponding to a topic, and a plurality of directed edges, each directed edge connecting two buckets of the first plurality and indicating a transition direction from one bucket to the other bucket, the transition direction representing at least one transition of a plurality of transitions between the two buckets; define one or more domains of interaction, each domain of interaction comprising a second plurality of buckets from the first plurality of buckets connected by the directed edges and representing a type of social resource exchange; and assign each message of the plurality to at least one of the one or more domains of interaction, the assigning identifying at least one type of social resource exchange for each message. | 9. A system comprising: at least one computing device comprising one or more processors to execute and memory to store instructions to: identify a first plurality of buckets and assigning each message of a plurality of messages to one or more buckets of the first plurality based on topics of the plurality of messages, each of the one or more buckets having one or more assigned messages; create a conversation graph comprising a plurality of nodes, each node corresponding to a bucket of the first plurality corresponding to a topic, and a plurality of directed edges, each directed edge connecting two buckets of the first plurality and indicating a transition direction from one bucket to the other bucket, the transition direction representing at least one transition of a plurality of transitions between the two buckets; define one or more domains of interaction, each domain of interaction comprising a second plurality of buckets from the first plurality of buckets connected by the directed edges and representing a type of social resource exchange; and assign each message of the plurality to at least one of the one or more domains of interaction, the assigning identifying at least one type of social resource exchange for each message. 13. The system of claim 9 , at least one edge of the plurality representing more than one transition of the plurality and more than one pair of users of the plurality. | 0.781414 |
8,249,870 | 1 | 9 | 1. A method for providing semi-automatic speech transcription, comprising: (a) receiving audio by an automatic speech detection component; (b) automatically detecting speech in the audio by the automatic speech detection component, wherein the automatically detecting comprises (b1) partitioning the audio into a plurality of frames; (b2) classifying each of the plurality of frames as speech or non-speech based on the feature vector corresponding to each frame; and (b3) grouping the plurality of frames into a plurality of speech segments based on the classifications, wherein the grouping comprises, for a sequence of classifications, switching or not switching the speech or non-speech classification in the sequence based on a comparison of a cost for switching the classification with a cost for not switching the classification; (c) providing by the automatic speech detection component the detected speech as the plurality of speech segments to a transcription tool; (d) providing by the transcription tool each of the plurality of speech segments to a user via a transcription interface; and (e) receiving by the transcription tool via the transcription interface an indication for each of the plurality of speech segments from the user, wherein the indication comprises a transcription of the speech segment or an indication of non-speech for the speech segments. | 1. A method for providing semi-automatic speech transcription, comprising: (a) receiving audio by an automatic speech detection component; (b) automatically detecting speech in the audio by the automatic speech detection component, wherein the automatically detecting comprises (b1) partitioning the audio into a plurality of frames; (b2) classifying each of the plurality of frames as speech or non-speech based on the feature vector corresponding to each frame; and (b3) grouping the plurality of frames into a plurality of speech segments based on the classifications, wherein the grouping comprises, for a sequence of classifications, switching or not switching the speech or non-speech classification in the sequence based on a comparison of a cost for switching the classification with a cost for not switching the classification; (c) providing by the automatic speech detection component the detected speech as the plurality of speech segments to a transcription tool; (d) providing by the transcription tool each of the plurality of speech segments to a user via a transcription interface; and (e) receiving by the transcription tool via the transcription interface an indication for each of the plurality of speech segments from the user, wherein the indication comprises a transcription of the speech segment or an indication of non-speech for the speech segments. 9. The method of claim 1 , wherein the indication further comprises an indication that the speech segment cannot be transcribed. | 0.893864 |
8,522,283 | 1 | 8 | 1. A computer-implemented method comprising: receiving, by a portable computing device, a spoken query from a user of the portable computing device; determining that the spoken query is classified as a television-related query; submitting, by the portable computing device to a remote server system, a digital recording of the spoken query and data indicating that the spoken query is classified as a television-related query; receiving, at the portable computing device from the remote server system, a transcription of the spoken query; and automatically transmitting the transcription of the spoken query from the portable computing device to a television system, wherein the television system is programmed to modify the transcription of the spoken query received from the remote server system via the portable computing device, to submit the modified transcription of the spoken query received from the remote server system via the portable computing device as a search query to a remote search engine, and to display to the user media-related results that are determined to be responsive to the search query. | 1. A computer-implemented method comprising: receiving, by a portable computing device, a spoken query from a user of the portable computing device; determining that the spoken query is classified as a television-related query; submitting, by the portable computing device to a remote server system, a digital recording of the spoken query and data indicating that the spoken query is classified as a television-related query; receiving, at the portable computing device from the remote server system, a transcription of the spoken query; and automatically transmitting the transcription of the spoken query from the portable computing device to a television system, wherein the television system is programmed to modify the transcription of the spoken query received from the remote server system via the portable computing device, to submit the modified transcription of the spoken query received from the remote server system via the portable computing device as a search query to a remote search engine, and to display to the user media-related results that are determined to be responsive to the search query. 8. The computer-implemented method of claim 1 , wherein the media-related results identify different broadcasts of a particular item of media content. | 0.826389 |
9,842,090 | 1 | 8 | 1. A computer-implemented method comprising: receiving a path expression to be evaluated on an encoded XML data source, wherein the encoded XML data source is defined by an XML schema, wherein the path expression comprises path expression steps, each path expression step of said path expression steps specifying at least a characteristic of an element or an element attribute, wherein the encoded XML data source comprises an encoded representation of a particular element encoded within said encoded XML data source; prior to evaluating the encoded XML data source, compiling the path expression, thereby forming a compiled path expression, wherein the compiled path expression comprises a representation of a path expression step of the path expression, said representation of a path expression step of the path expression including said encoded representation of a particular element; wherein the compiled path expression also comprises a parsing instruction associated with the representation of the path expression step of the path expression; wherein compiling the path expression comprises: based on analyzing the XML schema, determining a portion of the encoded XML data source that cannot match the path expression step, and generating the parsing instruction to skip said portion of the encoded XML data source; evaluating the compiled path expression on the encoded XML data source, wherein evaluating the compiled path expression includes skipping a portion of the encoded XML data source, based on the parsing instruction, without evaluating whether said portion of the encoded XML data source matches against the path expression step; and generating a result based on the evaluation of the path expression. | 1. A computer-implemented method comprising: receiving a path expression to be evaluated on an encoded XML data source, wherein the encoded XML data source is defined by an XML schema, wherein the path expression comprises path expression steps, each path expression step of said path expression steps specifying at least a characteristic of an element or an element attribute, wherein the encoded XML data source comprises an encoded representation of a particular element encoded within said encoded XML data source; prior to evaluating the encoded XML data source, compiling the path expression, thereby forming a compiled path expression, wherein the compiled path expression comprises a representation of a path expression step of the path expression, said representation of a path expression step of the path expression including said encoded representation of a particular element; wherein the compiled path expression also comprises a parsing instruction associated with the representation of the path expression step of the path expression; wherein compiling the path expression comprises: based on analyzing the XML schema, determining a portion of the encoded XML data source that cannot match the path expression step, and generating the parsing instruction to skip said portion of the encoded XML data source; evaluating the compiled path expression on the encoded XML data source, wherein evaluating the compiled path expression includes skipping a portion of the encoded XML data source, based on the parsing instruction, without evaluating whether said portion of the encoded XML data source matches against the path expression step; and generating a result based on the evaluation of the path expression. 8. The method of claim 1 , wherein evaluating the compiled path expression comprises sending the parsing instruction to an XML parser. | 0.743295 |
8,914,758 | 1 | 21 | 1. A computer-implemented method for verification analysis comprising: obtaining a word-level data flow graph and obtaining a bit-level data flow graph; searching the bit-level data flow graph to find partial-product encoding; removing redundancy from the bit-level data flow graph; checking the word-level data flow graph and the bit-level data flow graph for input correspondence; and performing, one or more processors, equivalence checking using the bit-level data flow graph and the word-level data flow graph. | 1. A computer-implemented method for verification analysis comprising: obtaining a word-level data flow graph and obtaining a bit-level data flow graph; searching the bit-level data flow graph to find partial-product encoding; removing redundancy from the bit-level data flow graph; checking the word-level data flow graph and the bit-level data flow graph for input correspondence; and performing, one or more processors, equivalence checking using the bit-level data flow graph and the word-level data flow graph. 21. The method of claim 1 wherein the word-level data flow graph is based on a C, C++, SystemC, or RTL representation. | 0.63354 |
8,244,529 | 3 | 4 | 3. The method for multi-pass echo residue detection of claim 2 , further comprising: determining whether a duration of the unrecognizable audio data not containing a user speech input is at least a predetermined duration, and when the unrecognizable audio data not containing a user speech input is at least the predetermined duration, extracting the predetermined duration of the unrecognizable audio data not containing a user speech input for further analysis. | 3. The method for multi-pass echo residue detection of claim 2 , further comprising: determining whether a duration of the unrecognizable audio data not containing a user speech input is at least a predetermined duration, and when the unrecognizable audio data not containing a user speech input is at least the predetermined duration, extracting the predetermined duration of the unrecognizable audio data not containing a user speech input for further analysis. 4. The method for multi-pass echo residue detection of claim 3 , further comprising: ending the further analysis when the unrecognizable audio data not containing a user speech input is not at least the predetermined duration. | 0.5 |
8,280,601 | 13 | 17 | 13. A system for classifying a driver's driving style of a vehicle, said system comprising: a plurality of vehicle sensors providing sensor measurement signals; a maneuver identification processor responsive to the sensor signals from the plurality of vehicle sensors, said maneuver identification processor identifying different characteristic maneuvers of the vehicle and providing maneuver identifier signals identifying the characteristic maneuvers; a style characterization processor responsive to the maneuver identifier signals and the sensor measurement signals, said style characterization processor classifying driving style based on the identifier and sensor signals and providing driving style classification signals that identify the type of driver driving the vehicle; and a plurality of combiners that combine the classification signals for different maneuvers, where the plurality of combiners includes a first combiner that combines the style classification signals for multiple maneuvers that are of the same type, and a second combiner that combines style classification signals from the first combiner for different types of maneuvers. | 13. A system for classifying a driver's driving style of a vehicle, said system comprising: a plurality of vehicle sensors providing sensor measurement signals; a maneuver identification processor responsive to the sensor signals from the plurality of vehicle sensors, said maneuver identification processor identifying different characteristic maneuvers of the vehicle and providing maneuver identifier signals identifying the characteristic maneuvers; a style characterization processor responsive to the maneuver identifier signals and the sensor measurement signals, said style characterization processor classifying driving style based on the identifier and sensor signals and providing driving style classification signals that identify the type of driver driving the vehicle; and a plurality of combiners that combine the classification signals for different maneuvers, where the plurality of combiners includes a first combiner that combines the style classification signals for multiple maneuvers that are of the same type, and a second combiner that combines style classification signals from the first combiner for different types of maneuvers. 17. The system according to claim 13 wherein the classifiers use discriminant features to classify the driving style. | 0.865207 |
10,049,147 | 8 | 10 | 8. The method according to claim 1 , wherein before the obtaining of the constituent information of the designated document, the method further comprising: obtaining the designated document which comprises the at least one multimedia resource; parsing the designated document to obtain the at least one multimedia resource; saving the at least one multimedia resource to generate the constituent information of the designated document. | 8. The method according to claim 1 , wherein before the obtaining of the constituent information of the designated document, the method further comprising: obtaining the designated document which comprises the at least one multimedia resource; parsing the designated document to obtain the at least one multimedia resource; saving the at least one multimedia resource to generate the constituent information of the designated document. 10. The method according to claim 8 , wherein the obtaining of the designated document comprising at least one of: generating the designated document according to the at least one multimedia resource; or receiving the designated document uploaded by the terminal; or obtaining the designated document corresponding to a designated web link according to the designated web link; or obtaining the designated document sent by a contact. | 0.560852 |
6,157,905 | 1 | 8 | 1. For a text string of data values representing text in an unknown distinguished language in accordance with an unknown distinguished character set that associates character glyphs with particular data values of a range, a method in a computer system for identifying the distinguished language of the text using the text string of data values, the method comprising the steps of: applying a plurality-to-one reductive mapping of the text string of data values to generate a plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values, wherein data values of the plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values have a range smaller than the range of data values in the text string representing text in the unknown distinguished language; generating a statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterizing the text of data values; for each of a plurality of languages: retrieving a plurality-to-one reductively mapped statistical model that models the language in terms of the statistical occurrence of particular data values in plurality-to-one reductively mapped representative samples of text in the language, and comparing the retrieved plurality-to-one reductively mapped statistical model to the statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterized the text string of data values; and identifying as the distinguished language the language among the plurality of whose model representing the language via the plurality-to-one reductive mapping compares most favorably to the statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values. | 1. For a text string of data values representing text in an unknown distinguished language in accordance with an unknown distinguished character set that associates character glyphs with particular data values of a range, a method in a computer system for identifying the distinguished language of the text using the text string of data values, the method comprising the steps of: applying a plurality-to-one reductive mapping of the text string of data values to generate a plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values, wherein data values of the plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values have a range smaller than the range of data values in the text string representing text in the unknown distinguished language; generating a statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterizing the text of data values; for each of a plurality of languages: retrieving a plurality-to-one reductively mapped statistical model that models the language in terms of the statistical occurrence of particular data values in plurality-to-one reductively mapped representative samples of text in the language, and comparing the retrieved plurality-to-one reductively mapped statistical model to the statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterized the text string of data values; and identifying as the distinguished language the language among the plurality of whose model representing the language via the plurality-to-one reductive mapping compares most favorably to the statistical analysis of the plurality-to-one reductively mapped transformed string of data values characterizing the text string of data values. 8. The method of claim 1 wherein the plurality-to-one reductive mapping comprises: mapping upper and lower case letters of the English alphabet to a set of twenty-six different values; mapping extended characters to a single same value; and mapping upper numerals and punctuation to a single same value. | 0.61054 |
7,711,548 | 1 | 2 | 1. A computer-implemented method for enabling persistent storage of textual data in multiple languages, concurrently, in a single database instance, and retrieval for presentation of that data in a language appropriate for a specified locale, the method comprising the steps of: a computer capturing a piece of data in a first language in a database structure in a computer readable storage media; a computer translating the piece of data into a plurality of additional languages, each of said first language and said additional languages being associated with a specified locale, said locale being identified by a combination of a specified language and a specified geographic region; a computer storing the piece of data in the first language and all of said additional languages in one text table instance in the database structure in the computer readable storage media, for retrieval and presentation in any of a group of supported languages, said one text table instance including a plurality of rows, said storing including the step of storing in each row of the text table a unique combination of language and country codes, and storing in each row of the text table a copy of the data item, in a respective one of the first and additional languages, as determined by said unique combination of languages and country codes in said each row; and a computer providing said piece of data to a user computer in one of said pre-translated, stored languages by (i) identifying a locale of the user computer based on a combination of a given language and a given geographic region for the user computer, (ii) using the locale of the user computer, as identified by the combination of the given language and the given geographic region, to identify one of the languages stored in the one text table instance and retrieving from the one text table instance the pre-stored piece of data in the identified one of the languages, and (iii) displaying on the user computer the retrieved piece of data in the identified one of the languages; and performing the capturing, translating and storing steps, a plurality of times to obtain a plurality of groups of translations for a group of data items, including storing each group of translations in a respective one text table, providing each of the text tables with a respective one text Group ID, and storing all of the text Group IDs in a text Group Table. | 1. A computer-implemented method for enabling persistent storage of textual data in multiple languages, concurrently, in a single database instance, and retrieval for presentation of that data in a language appropriate for a specified locale, the method comprising the steps of: a computer capturing a piece of data in a first language in a database structure in a computer readable storage media; a computer translating the piece of data into a plurality of additional languages, each of said first language and said additional languages being associated with a specified locale, said locale being identified by a combination of a specified language and a specified geographic region; a computer storing the piece of data in the first language and all of said additional languages in one text table instance in the database structure in the computer readable storage media, for retrieval and presentation in any of a group of supported languages, said one text table instance including a plurality of rows, said storing including the step of storing in each row of the text table a unique combination of language and country codes, and storing in each row of the text table a copy of the data item, in a respective one of the first and additional languages, as determined by said unique combination of languages and country codes in said each row; and a computer providing said piece of data to a user computer in one of said pre-translated, stored languages by (i) identifying a locale of the user computer based on a combination of a given language and a given geographic region for the user computer, (ii) using the locale of the user computer, as identified by the combination of the given language and the given geographic region, to identify one of the languages stored in the one text table instance and retrieving from the one text table instance the pre-stored piece of data in the identified one of the languages, and (iii) displaying on the user computer the retrieved piece of data in the identified one of the languages; and performing the capturing, translating and storing steps, a plurality of times to obtain a plurality of groups of translations for a group of data items, including storing each group of translations in a respective one text table, providing each of the text tables with a respective one text Group ID, and storing all of the text Group IDs in a text Group Table. 2. A method according to claim 1 , for use with an application program multi-language support, and wherein the piece of data is captured and maintained through use of said application program. | 0.8125 |
10,055,416 | 1 | 4 | 1. A computer-implemented method for content-related file handling in a hierarchical storage environment, comprising: initiating a new document notification process in response to receipt of a new document, the new document notification process comprising: evaluating enhanced metadata of the new document via a relationship analyzing process to produce a priority list defining a likelihood of possible access, wherein the enhanced metadata includes a set of keywords and/or references from within the new document, wherein the enhanced metadata includes user file access history information and/or a user search history information, wherein the relationship analyzing process uses the access history information and/or a user search history in the enhanced metadata with the set of keywords and/or references to produce the priority list; and storing the new document in a storage tier of a hierarchical storage environment according to the priority list. | 1. A computer-implemented method for content-related file handling in a hierarchical storage environment, comprising: initiating a new document notification process in response to receipt of a new document, the new document notification process comprising: evaluating enhanced metadata of the new document via a relationship analyzing process to produce a priority list defining a likelihood of possible access, wherein the enhanced metadata includes a set of keywords and/or references from within the new document, wherein the enhanced metadata includes user file access history information and/or a user search history information, wherein the relationship analyzing process uses the access history information and/or a user search history in the enhanced metadata with the set of keywords and/or references to produce the priority list; and storing the new document in a storage tier of a hierarchical storage environment according to the priority list. 4. The method according to claim 1 , wherein the enhanced metadata includes the set of references, wherein the set of references comprises references selected from the group consisting of: references from a references section, hyperlinks, and titles of referenced documents. | 0.722672 |
9,064,493 | 11 | 12 | 11. The apparatus of claim 9 , wherein: the at least one alternative recognition result comprises a second recognition result; the method further comprises semantically interpreting each of the first recognition result and the second recognition result to determine at least one first fact expressed in the first recognition result and at least one second fact expressed in the second recognition result; and the determining whether the meaning of the first recognition result differs from the meaning of the at least one alternative recognition result comprises determining whether there is a difference between the at least one first fact and the at least one second fact. | 11. The apparatus of claim 9 , wherein: the at least one alternative recognition result comprises a second recognition result; the method further comprises semantically interpreting each of the first recognition result and the second recognition result to determine at least one first fact expressed in the first recognition result and at least one second fact expressed in the second recognition result; and the determining whether the meaning of the first recognition result differs from the meaning of the at least one alternative recognition result comprises determining whether there is a difference between the at least one first fact and the at least one second fact. 12. The apparatus of claim 11 , wherein: the at least one first fact comprises a fact having a fact type that is marked as significant; and the determining whether there is a difference between the at least one first fact and the at least one second fact comprises determining whether the at least one second fact comprises the fact having the fact type marked as significant. | 0.5 |
4,128,737 | 36 | 37 | 36. An electronic device for phonetically synthesizing human speech comprising: a vocal source adapted to produce a voiced excitation signal; a fricative source adapted to produce an unvoiced excitation signal; input means responsive to the receipt of input data identifying a desired sequence of phonemes to produce a plurality of control signals representing the parameters defining the phonemes identified by said input data including a first control signal for controlling the amplitude of said voiced excitation signal and a second control signal for controlling the amplitude of said unvoiced excitation signal; vocal tract means responsive to said voiced and unvoiced excitation signals and said control signals to produce an audio output comprised of said desired sequence of phonemes integrated into intelligible human speech; and amplitude control means for varying the relative overall amplitude of said audio output by modulating a preselected signal characteristic of said first and second control signals. | 36. An electronic device for phonetically synthesizing human speech comprising: a vocal source adapted to produce a voiced excitation signal; a fricative source adapted to produce an unvoiced excitation signal; input means responsive to the receipt of input data identifying a desired sequence of phonemes to produce a plurality of control signals representing the parameters defining the phonemes identified by said input data including a first control signal for controlling the amplitude of said voiced excitation signal and a second control signal for controlling the amplitude of said unvoiced excitation signal; vocal tract means responsive to said voiced and unvoiced excitation signals and said control signals to produce an audio output comprised of said desired sequence of phonemes integrated into intelligible human speech; and amplitude control means for varying the relative overall amplitude of said audio output by modulating a preselected signal characteristic of said first and second control signals. 37. The speech synthesizer of claim 36 wherein said amplitude control means is responsive to predetermined input data to vary the relative overall amplitude of said audio output while preserving the relative amplitude variations in said voiced and unvoiced excitation signals that occur from phoneme to phoneme under the control of said first and second control signals respectively, by continuously modulating said preselected signal characteristic of said first and second control signals by a certain percentage. | 0.5 |
9,710,225 | 8 | 9 | 8. The computerized information and display apparatus of claim 7 , wherein the at least one matching entry comprises the entity or organization, and the selection of the at least digital image data based at least in part on the at least one matching entry comprises selection of digital image data based at least on stored digital code data associated with data relating to the entity or organization. | 8. The computerized information and display apparatus of claim 7 , wherein the at least one matching entry comprises the entity or organization, and the selection of the at least digital image data based at least in part on the at least one matching entry comprises selection of digital image data based at least on stored digital code data associated with data relating to the entity or organization. 9. The computerized information and display apparatus of claim 8 , wherein the stored digital code data associated with data relating to the entity or organization comprises a data structure comprising: (i) a plurality of data bits indicative of the industry or business type; and (ii) a plurality of data bits indicative of a sub-specialization within the industry or business type. | 0.5 |
7,814,147 | 19 | 22 | 19. A system comprising: a first computer; a web browser operably installed on the first computer; a web page accessible to the first computer via the web browser; a second computer different from the first computer; a web browser readable code component accessible to the second computer, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. | 19. A system comprising: a first computer; a web browser operably installed on the first computer; a web page accessible to the first computer via the web browser; a second computer different from the first computer; a web browser readable code component accessible to the second computer, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. 22. The system as claimed in claim 19 wherein the content of the portion of the web page changed upon execution of the web browser readable code component includes a video clip. | 0.592166 |
7,770,110 | 18 | 19 | 18. A computer-implemented method for transforming an XML file into an add-in function for use in a spreadsheet application comprising: scanning an add-in XML file for an instruction; determining an interface XML file to be exposed by the instruction; accepting the interface XML file from a COM server; determining if the instruction comprises a function qualifier; wherein the function qualifier modifies a function specification in the interface XML file; applying the function qualifier to the function specification; converting the function specification to an intermediate function; determining if the instruction comprises an implementation specifier for the function specification, wherein the implementation specifier overrides the default implementation of the interface XML file; determining the implementation specifier for the add-in function if the instruction does not comprise an implementation specifier; applying an implementation specifier to the intermediate function; converting the intermediate function to an add-in function; and transmitting the add-in function to the spreadsheet application for processing. | 18. A computer-implemented method for transforming an XML file into an add-in function for use in a spreadsheet application comprising: scanning an add-in XML file for an instruction; determining an interface XML file to be exposed by the instruction; accepting the interface XML file from a COM server; determining if the instruction comprises a function qualifier; wherein the function qualifier modifies a function specification in the interface XML file; applying the function qualifier to the function specification; converting the function specification to an intermediate function; determining if the instruction comprises an implementation specifier for the function specification, wherein the implementation specifier overrides the default implementation of the interface XML file; determining the implementation specifier for the add-in function if the instruction does not comprise an implementation specifier; applying an implementation specifier to the intermediate function; converting the intermediate function to an add-in function; and transmitting the add-in function to the spreadsheet application for processing. 19. The computer-implemented method of claim 18 , wherein applying the function qualifier to the function specification further comprises the steps of: generating an empty form intermediate function; accepting a function modifier from the instruction in the add-in XML file; determining if the function modifier comprises instructions to modify a name of the add-in function; setting a name of the form intermediate function based on the instructions in the function modifier based on a positive determination; transferring at least one parameter of the function from the interface XML file to the form intermediate function; determining if the instruction in the add-in XML file comprises additional parameters to be included in the form intermediate function; adding the additional parameters from the instruction to the form intermediate function if the instruction comprises additional parameters; and adding the a function summary, function description, and function return-value from the function specification to the form intermediate function thereby creating the intermediate function. | 0.5 |
9,313,223 | 11 | 12 | 11. The system of claim 10 , wherein the tokens represent a string of characters or equivalent in bytes. | 11. The system of claim 10 , wherein the tokens represent a string of characters or equivalent in bytes. 12. The system of claim 11 , wherein the tokens are categorized according to rules as a symbol. | 0.5 |
8,897,495 | 13 | 16 | 13. A computer readable storage device for tracking a user, the computer readable storage medium having stored thereon computer executable instructions that, when executed on a computer, cause the computer to perform operations comprising: receiving a depth image; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user. | 13. A computer readable storage device for tracking a user, the computer readable storage medium having stored thereon computer executable instructions that, when executed on a computer, cause the computer to perform operations comprising: receiving a depth image; identifying an estimated location or position of a part of the user in the depth image; adjusting a model of the user based on the estimated location or position of the part of the user; and in response to a failure to identify a location or position of the part of the user in a second depth image, associating the part of the user with a portion of the second depth image based on a location or position of a default position of the part of the user. 16. The computer readable storage device of claim 13 , wherein the model comprises: a skeletal model having joints and bones. | 0.734043 |
8,255,215 | 1 | 2 | 1. A method, carried out by use of a keyword locating apparatus for locating a keyword contained in a recognition target speech, comprising: by extracting feature parameters from frames constituting the recognition target speech, forming a feature parameter vector sequence that represents the recognition target speech; by normalizing of the feature parameter vector sequence with use of a codebook containing a plurality of codebook vectors, obtaining a feature trace of the recognition target speech in a vector space; and specifying the position of a keyword by matching prestored keyword template traces with the feature trace, wherein the normalizing step includes the step of obtaining the feature trace by extracting representative feature parameter vectors from the feature parameter vector sequence, and the step of extracting the representative feature parameter vectors includes the steps of: searching the codebook for codebook vectors that are closest to the feature parameter vectors; indicating the feature parameter vectors with use of numbers of the codebook vectors thus found; and obtaining the feature trace by combining feature parameter vectors represented by continuously identical codebook vectors. | 1. A method, carried out by use of a keyword locating apparatus for locating a keyword contained in a recognition target speech, comprising: by extracting feature parameters from frames constituting the recognition target speech, forming a feature parameter vector sequence that represents the recognition target speech; by normalizing of the feature parameter vector sequence with use of a codebook containing a plurality of codebook vectors, obtaining a feature trace of the recognition target speech in a vector space; and specifying the position of a keyword by matching prestored keyword template traces with the feature trace, wherein the normalizing step includes the step of obtaining the feature trace by extracting representative feature parameter vectors from the feature parameter vector sequence, and the step of extracting the representative feature parameter vectors includes the steps of: searching the codebook for codebook vectors that are closest to the feature parameter vectors; indicating the feature parameter vectors with use of numbers of the codebook vectors thus found; and obtaining the feature trace by combining feature parameter vectors represented by continuously identical codebook vectors. 2. The method as set forth in claim 1 , wherein the matching step includes the steps of: by using each of the keyword template traces, sequentially calculating, with respect to each trace frame, distances between (i) template feature vectors that represent the keyword template trace and (ii) the representative feature parameter vectors that represent the feature trace, the trace frame representing the feature trace on a time axis; specifying a minimum value of the distances; and specifying, as the position of the keyword, a position that a keyword template trace corresponding to the minimum value occupies in the vector space. | 0.5 |
9,727,594 | 5 | 6 | 5. A system that determines whether or not to access stored data, comprising: a general purpose computing device; a computer program comprising program modules executable by the general purpose computing device, wherein the computing device is directed by the program modules of the computer program to, create an adaptive range filter structured as a trie wherein: each node of the trie represents a particular region of a domain of data and a root node represents the entire domain indexed, a parent node fully contains the regions of its children nodes in the trie, leaves of the trie contain occupied bits indicating whether tuples in the data exist in that particular region; process a query using the trie-structured adaptive range filter by inspecting all leaf nodes that overlap with the query; if the occupied bit of one of the leaf nodes is set then processing the query on the data set, otherwise deducing that the data set contains no relevant data for the query. | 5. A system that determines whether or not to access stored data, comprising: a general purpose computing device; a computer program comprising program modules executable by the general purpose computing device, wherein the computing device is directed by the program modules of the computer program to, create an adaptive range filter structured as a trie wherein: each node of the trie represents a particular region of a domain of data and a root node represents the entire domain indexed, a parent node fully contains the regions of its children nodes in the trie, leaves of the trie contain occupied bits indicating whether tuples in the data exist in that particular region; process a query using the trie-structured adaptive range filter by inspecting all leaf nodes that overlap with the query; if the occupied bit of one of the leaf nodes is set then processing the query on the data set, otherwise deducing that the data set contains no relevant data for the query. 6. The system of claim 5 , further comprising modules to: partition the data into a cold set of data that is infrequently accessed and a hot set of data that is frequently accessed; store the cold set of data in external memory of a computing device; store in main memory of the computing device the adaptive range filter that contains a compact summary of the contents of an external index for the cold set of data. | 0.5 |
8,606,788 | 5 | 8 | 5. The system of claim 4 , further comprising: a token determination engine configured to determine a respective plurality of item tokens associated with each respective one of the plurality of item character strings, wherein the correlated segment engine is configured to determine a correlation value associated with each one of the tokens, based on determining a correlation of the each one of the tokens with the brand character string associated with the brand partition set that includes the item associated with the item character string that includes the each one of the tokens. | 5. The system of claim 4 , further comprising: a token determination engine configured to determine a respective plurality of item tokens associated with each respective one of the plurality of item character strings, wherein the correlated segment engine is configured to determine a correlation value associated with each one of the tokens, based on determining a correlation of the each one of the tokens with the brand character string associated with the brand partition set that includes the item associated with the item character string that includes the each one of the tokens. 8. The system of claim 5 , wherein: the hierarchy generator is configured to generate the dictionary hierarchy based on obtaining atomic token sequences based on the obtained correlated segments, updating a tree structure based on the obtained atomic sequences, and assigning an attribute value to the tree structure. | 0.709707 |
8,452,653 | 26 | 27 | 26. The computer-readable medium of claim 25 further comprising: sliding the TRM through a TRM reader when paying for goods, services, and entertainment. | 26. The computer-readable medium of claim 25 further comprising: sliding the TRM through a TRM reader when paying for goods, services, and entertainment. 27. The computer-readable medium of claim 26 wherein transferring comprises: transferring the activity data over the network to the profiler responsive to sliding. | 0.767806 |
9,805,101 | 7 | 11 | 7. A computer-implemented method, comprising: receiving a stream of data from a log of browsing activity of a user account; organizing the stream of data in a sequential and nested data structure; defining a relational and a sequential operator that both operate in parallel on the sequential and nested data structure; receiving a query related to the stream of data; splitting a collection of tuples from the stream of data into a plurality of substream of data without splitting the individual tuples; processing, using a hardware processor of a machine, the query on the plurality of substreams across a plurality of nodes of the collection of tuples by operating the relational operator on the nested data structure of a tuple from the collection of tuples in parallel with operating the sequential operator on the sequential data structure of the tuple from the collection of tuples, wherein each respective individual tuple comprises an instance of one of: a search activity by the user account, a bid activity by the user account and a view item activity by the user account, the operators comprising an input operator, an output operator, a relational operator, and a pattern query, the input operator configured to load session logs corresponding to a date range, the output operator configured to save session logs in a storage device, the relational operator configured to operate on the sequential and nested data structure based on relation conditions and extract sub-sequences, the pattern query configured to operate on the sequential and nested data structure to identify sub-sequences that match an event pattern, the event pattern modeled as tuples and defined as a template that matches a set of contiguous events, the event pattern comprising respective instances of search activity that generated no results, the template describing order dependencies in the event pattern, data parameter conditions defining selection criteria for events, and context conditions identifying how events from a start of an event pattern and an end of an event pattern are broken into each pattern part. | 7. A computer-implemented method, comprising: receiving a stream of data from a log of browsing activity of a user account; organizing the stream of data in a sequential and nested data structure; defining a relational and a sequential operator that both operate in parallel on the sequential and nested data structure; receiving a query related to the stream of data; splitting a collection of tuples from the stream of data into a plurality of substream of data without splitting the individual tuples; processing, using a hardware processor of a machine, the query on the plurality of substreams across a plurality of nodes of the collection of tuples by operating the relational operator on the nested data structure of a tuple from the collection of tuples in parallel with operating the sequential operator on the sequential data structure of the tuple from the collection of tuples, wherein each respective individual tuple comprises an instance of one of: a search activity by the user account, a bid activity by the user account and a view item activity by the user account, the operators comprising an input operator, an output operator, a relational operator, and a pattern query, the input operator configured to load session logs corresponding to a date range, the output operator configured to save session logs in a storage device, the relational operator configured to operate on the sequential and nested data structure based on relation conditions and extract sub-sequences, the pattern query configured to operate on the sequential and nested data structure to identify sub-sequences that match an event pattern, the event pattern modeled as tuples and defined as a template that matches a set of contiguous events, the event pattern comprising respective instances of search activity that generated no results, the template describing order dependencies in the event pattern, data parameter conditions defining selection criteria for events, and context conditions identifying how events from a start of an event pattern and an end of an event pattern are broken into each pattern part. 11. The computer-implemented method of claim 7 wherein a substream of data comprises a nestled tuple, wherein the stream of data is grouped into subsequences, wherein the parallel implementation module is configured to perform a sequence operation on the subsequences in parallel without splitting the subsequences. | 0.519817 |
9,483,519 | 16 | 20 | 16. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a corpus of information to process; retrieve a set of author profiles associated with the corpus of information; present a user interface that comprises the set of author profiles, through which a user input is received specifying a user selection of at least one user selected author profile in the set of author profiles; generate a content profile for a portion of content of the corpus of information; compare the content profile to the set of author profiles to generate an association of the content profile with at least one author profile in the set of author profiles; and control a processing operation of the natural language processing (NLP) system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, wherein the processing operation is an ingestion operation that ingests portions of content from the corpus of information, wherein controlling the processing operation of the NLP system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, comprises: ingesting first content, associated with a first user selected author profile having an associated first user specified priority value associated with the first user selected author profile, from the corpus into the NLP system and performing an NLP operation on the first content; and ingesting second content, associated with a second user selected author profile having an associated second user specified priority value associated with the second user selected author profile, after ingesting the first content and performing the NLP operation on the first content, and performing the NLP operation on the second content, wherein the first user specified priority value indicates a higher priority associated with the first user selected author profile than the second user specified priority value. | 16. A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a corpus of information to process; retrieve a set of author profiles associated with the corpus of information; present a user interface that comprises the set of author profiles, through which a user input is received specifying a user selection of at least one user selected author profile in the set of author profiles; generate a content profile for a portion of content of the corpus of information; compare the content profile to the set of author profiles to generate an association of the content profile with at least one author profile in the set of author profiles; and control a processing operation of the natural language processing (NLP) system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, wherein the processing operation is an ingestion operation that ingests portions of content from the corpus of information, wherein controlling the processing operation of the NLP system based on the association of the content profile with the at least one author profile and a determined level of correspondence of the at least one author profile with the at least one user selected author profile, comprises: ingesting first content, associated with a first user selected author profile having an associated first user specified priority value associated with the first user selected author profile, from the corpus into the NLP system and performing an NLP operation on the first content; and ingesting second content, associated with a second user selected author profile having an associated second user specified priority value associated with the second user selected author profile, after ingesting the first content and performing the NLP operation on the first content, and performing the NLP operation on the second content, wherein the first user specified priority value indicates a higher priority associated with the first user selected author profile than the second user specified priority value. 20. The computer program product of claim 16 , wherein each author profile in the set of author profiles specifies characteristics of either a particular individual author or a group of authors having at least one similar characteristic. | 0.763944 |
8,245,136 | 5 | 6 | 5. A method for inserting text into a graphics file, the method comprising: populating a database with records that include text content and a text attribute; from a graphical programming environment, querying the database to select records that include text meeting the query criteria; inserting the text from the returned records into a graphics file and recording a relationship between the inserted text and the related record; querying the database, which includes at least one table of text records with each of the text records being associated with the same graphic file, using a text verification component that compares text in the graphic file with corresponding text in the repository, based on the relationship, for discrepancies between the text already inserted in the graphics file and the text content of the related record; and in response to detecting a discrepancy, replacing the already inserted text with the present text from the related record. | 5. A method for inserting text into a graphics file, the method comprising: populating a database with records that include text content and a text attribute; from a graphical programming environment, querying the database to select records that include text meeting the query criteria; inserting the text from the returned records into a graphics file and recording a relationship between the inserted text and the related record; querying the database, which includes at least one table of text records with each of the text records being associated with the same graphic file, using a text verification component that compares text in the graphic file with corresponding text in the repository, based on the relationship, for discrepancies between the text already inserted in the graphics file and the text content of the related record; and in response to detecting a discrepancy, replacing the already inserted text with the present text from the related record. 6. The method of claim 5 comprising the step of verifying the text in the graphics file by comparing text in the graphics file with text in one or more corresponding database records. | 0.5 |
9,984,165 | 13 | 20 | 13. A system comprising: at least one processor; and program code configured to be executed by the at least one processor to cause the at least one processor to: maintain a plurality of pre-computed priced travel recommendations, each pre-computed priced travel recommendation having been previously computed based on underlying data obtained from a primary data source at a time that the pre-computed priced travel recommendation was computed; associate each pre-computed priced travel recommendation with a corresponding confidence factor that indicates a probability that the associated pre-computed priced travel recommendation is still valid, the pre-computed priced travel recommendation being valid if the underlying data in the primary data source has not changed in a time period passed since the time that the pre-computed priced travel recommendation was computed and being invalid if the underlying data in the primary data source has changed in the time period; receive a travel query from a client indicating at least one travel search criterion; identify, from the plurality of pre-computed priced travel recommendations, a set of pre-computed priced travel recommendations that comply with the at least one travel search criterion; evaluate the confidence factors associated with the identified set of pre-computed priced travel recommendations; validate the pre-computed priced travel recommendations for which the confidence factor is greater than a given threshold by querying the primary data source for valid database query results; and return to the client the set of pre-computed priced travel recommendations and the validated priced travel recommendations associated with confidence factors greater than the given threshold in a response to the travel query, wherein the probability the underlying data used to compute a respective pre-computed priced travel recommendation has changed increases as a function of a duration of the time period, and the response to the travel query is returned by sending a first message conveying the set of pre-computed priced travel recommendations and a second message conveying the validated priced travel recommendations associated with confidence factors greater than the given threshold. | 13. A system comprising: at least one processor; and program code configured to be executed by the at least one processor to cause the at least one processor to: maintain a plurality of pre-computed priced travel recommendations, each pre-computed priced travel recommendation having been previously computed based on underlying data obtained from a primary data source at a time that the pre-computed priced travel recommendation was computed; associate each pre-computed priced travel recommendation with a corresponding confidence factor that indicates a probability that the associated pre-computed priced travel recommendation is still valid, the pre-computed priced travel recommendation being valid if the underlying data in the primary data source has not changed in a time period passed since the time that the pre-computed priced travel recommendation was computed and being invalid if the underlying data in the primary data source has changed in the time period; receive a travel query from a client indicating at least one travel search criterion; identify, from the plurality of pre-computed priced travel recommendations, a set of pre-computed priced travel recommendations that comply with the at least one travel search criterion; evaluate the confidence factors associated with the identified set of pre-computed priced travel recommendations; validate the pre-computed priced travel recommendations for which the confidence factor is greater than a given threshold by querying the primary data source for valid database query results; and return to the client the set of pre-computed priced travel recommendations and the validated priced travel recommendations associated with confidence factors greater than the given threshold in a response to the travel query, wherein the probability the underlying data used to compute a respective pre-computed priced travel recommendation has changed increases as a function of a duration of the time period, and the response to the travel query is returned by sending a first message conveying the set of pre-computed priced travel recommendations and a second message conveying the validated priced travel recommendations associated with confidence factors greater than the given threshold. 20. The system of claim 13 wherein the first message is subdivided into first atomic messages each conveying a single identified pre-computed priced travel recommendation, the second message is subdivided into second atomic messages each conveying a single validated priced travel recommendation, and the first and second atomic messages are sent in an incremental manner. | 0.588496 |
8,930,305 | 12 | 15 | 12. The computer implemented method of claim 8 wherein the original data is shared and reused across applications and community boundaries. | 12. The computer implemented method of claim 8 wherein the original data is shared and reused across applications and community boundaries. 15. The method of claim 12 wherein the data source comprises field data in association with data mined from at least one of the following; data associated with regulatory agencies, customer feedback regarding automobiles, customer feedback regarding automotive parts, customer feedback regarding automotive services. | 0.5 |
8,606,582 | 1 | 4 | 1. A computer-implemented method for processing language input in a system that includes a mobile computer, the mobile computer including a microphone and a display and a non-voice input device operable by a user, the method comprising operations of: responsive to the mobile computing device receiving via the microphone voice input comprising multiple discrete utterances from a user; the mobile computing device displaying an initial N-best list of words corresponding to each of the utterances recognized by speech recognition operations, the operation of displaying each initial N-best list of words further considering context of the corresponding utterance with respect to words of N-best lists corresponding to others of the received utterances; for each of said utterances, the mobile computing device visually displaying a best word from the initial N-best list of words corresponding to said utterance; responsive to implied or explicit user selection of one of the displayed best words, said selected word being from a given N-best list of words corresponding to a given utterance, the mobile computing device displaying additional words from the given initial N-best list of words; during said presentation of the additional words, the mobile computing device receiving via the non-voice input device an input from a user, and responsive to said user input, said presentation of the additional words is constrained to exclude words of the given initial N-best list that are inconsistent with the non-voice input; and responsive to said presentation of the additional words being constrained to a resultant word, displaying the resultant word instead of the selected word. | 1. A computer-implemented method for processing language input in a system that includes a mobile computer, the mobile computer including a microphone and a display and a non-voice input device operable by a user, the method comprising operations of: responsive to the mobile computing device receiving via the microphone voice input comprising multiple discrete utterances from a user; the mobile computing device displaying an initial N-best list of words corresponding to each of the utterances recognized by speech recognition operations, the operation of displaying each initial N-best list of words further considering context of the corresponding utterance with respect to words of N-best lists corresponding to others of the received utterances; for each of said utterances, the mobile computing device visually displaying a best word from the initial N-best list of words corresponding to said utterance; responsive to implied or explicit user selection of one of the displayed best words, said selected word being from a given N-best list of words corresponding to a given utterance, the mobile computing device displaying additional words from the given initial N-best list of words; during said presentation of the additional words, the mobile computing device receiving via the non-voice input device an input from a user, and responsive to said user input, said presentation of the additional words is constrained to exclude words of the given initial N-best list that are inconsistent with the non-voice input; and responsive to said presentation of the additional words being constrained to a resultant word, displaying the resultant word instead of the selected word. 4. The method of claim 1 , said speech recognition operations further comprising operations of: converting the voice input into a digital sequence of vectors; and matching the vectors to potential phonemes and matching the phonemes against a lexicon model and a language model. | 0.673349 |
8,762,906 | 17 | 23 | 17. A system for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, comprising: a non-transitory computer accessible medium having stored thereupon a computer program code for implementing the multi-domain digital or mixed signal verification and low power simulation of the electronic circuit design; at least one processor that is to execute the computer program code to: identify one or more schematics of the electronic circuit design; generate one or more one or more net or terminal sets or one or more overriding net or terminal sets for the one or more schematics of the electronic circuit design by referencing a power data file for the electronic circuit design, wherein the power data file for the electronic circuit design includes a specification of one or more power-saving techniques and data or information for power intent for at least a portion of the electronic circuit design to provide portability of the power intent across multiple electronic circuit design tools; and perform verification or simulation of the electronic circuit design by using at least the one or more net or terminal sets or the one or more overriding net or terminal sets. | 17. A system for implementing multi-power domain digital or mixed-signal verification and low power simulation of an electronic circuit design, comprising: a non-transitory computer accessible medium having stored thereupon a computer program code for implementing the multi-domain digital or mixed signal verification and low power simulation of the electronic circuit design; at least one processor that is to execute the computer program code to: identify one or more schematics of the electronic circuit design; generate one or more one or more net or terminal sets or one or more overriding net or terminal sets for the one or more schematics of the electronic circuit design by referencing a power data file for the electronic circuit design, wherein the power data file for the electronic circuit design includes a specification of one or more power-saving techniques and data or information for power intent for at least a portion of the electronic circuit design to provide portability of the power intent across multiple electronic circuit design tools; and perform verification or simulation of the electronic circuit design by using at least the one or more net or terminal sets or the one or more overriding net or terminal sets. 23. The system of claim 17 , wherein the at least one processor that is to generate the one or more net or terminal sets or the one or more overriding net or terminal sets by referencing the power data file is further to: specify or cause to specify a net or terminal expression in a power or ground tap schematic; and specify a net or terminal set at a hierarchical level. | 0.552758 |
8,452,822 | 1 | 6 | 1. A method implemented by a computing device, the method comprising: receiving, by the computing device and from a content provider device, a file with a custom name; extracting, by the computing device, a digital fingerprint from a content sample of the file with the custom name; generating, by the computing device and based on the digital fingerprint, a universal file name for the file with the custom name; associating, by the computing device, the universal file name with the custom name; determining, by the computing device, that the universal file name is associated with a previously-stored file, where the previously-stored file is identical to the file with the custom name; discarding, by the computing device, the file with the custom name; and associating, by the computing device, the custom name with the universal file name. | 1. A method implemented by a computing device, the method comprising: receiving, by the computing device and from a content provider device, a file with a custom name; extracting, by the computing device, a digital fingerprint from a content sample of the file with the custom name; generating, by the computing device and based on the digital fingerprint, a universal file name for the file with the custom name; associating, by the computing device, the universal file name with the custom name; determining, by the computing device, that the universal file name is associated with a previously-stored file, where the previously-stored file is identical to the file with the custom name; discarding, by the computing device, the file with the custom name; and associating, by the computing device, the custom name with the universal file name. 6. The method of claim 1 , where the file with a custom name is a personal media file and where the custom name is a name selected by a user of the content provider device. | 0.808036 |
10,133,723 | 1 | 9 | 1. A computer system comprised of at least one computer and at least one data storage device for determining the relative geneology of a predetermined set of versions of a document data files stored on the system, said system comprising: an extraction module adapted by logic to extract a set of at least one RSID values from each of the predetermined set of document versions, construct generate and store in computer memory a data structure that encodes the geneology of the predetermined set of document versions; a logic module adapted by logic to select at least one pair of RSID sets comprised of a first RSID set and a second RSID set corresponding to at least one selected pair of versions of the document associated with the corresponding at least one pair of selected RSID sets, and apply at least one of a predetermined set of logic rules to the selected pair of RSID sets said logic rules being at least one of: (i) testing whether the pair of RSID sets are identical; (ii) testing whether any of the RSID values in the first set are the same as any RSID values in the second set; (iii) testing whether all of the RSID values in the first set are a proper subset of the RSID values of the second set; or (iv) testing whether neither the first set of RSID values is a subset of the second set of RSID values nor the second set of RSID values are subset of the first set of RSID values, and to update the stored data structure with an identifier entry for one of the versions in the corresponding at least one pair of versions referring to its genealogical relation to the other version. | 1. A computer system comprised of at least one computer and at least one data storage device for determining the relative geneology of a predetermined set of versions of a document data files stored on the system, said system comprising: an extraction module adapted by logic to extract a set of at least one RSID values from each of the predetermined set of document versions, construct generate and store in computer memory a data structure that encodes the geneology of the predetermined set of document versions; a logic module adapted by logic to select at least one pair of RSID sets comprised of a first RSID set and a second RSID set corresponding to at least one selected pair of versions of the document associated with the corresponding at least one pair of selected RSID sets, and apply at least one of a predetermined set of logic rules to the selected pair of RSID sets said logic rules being at least one of: (i) testing whether the pair of RSID sets are identical; (ii) testing whether any of the RSID values in the first set are the same as any RSID values in the second set; (iii) testing whether all of the RSID values in the first set are a proper subset of the RSID values of the second set; or (iv) testing whether neither the first set of RSID values is a subset of the second set of RSID values nor the second set of RSID values are subset of the first set of RSID values, and to update the stored data structure with an identifier entry for one of the versions in the corresponding at least one pair of versions referring to its genealogical relation to the other version. 9. The system of claim 1 where the logic module is further adapted by logic to determine potential parentage by checking whether the extracted pair of RSID sets of a first pair of document versions is a proper subset of the extracted RSID values of a second pair of document versions. | 0.686534 |
8,296,153 | 20 | 26 | 20. A method of providing information to a user of a computerized apparatus, the method comprising: receiving via a network link a digitized representation of a speech input, the representation generated via a speech recognition apparatus of the computerized apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the representation, identifying a location associated with the organization or entity; and selecting and causing provision of a graphical or visual representation of the location via the network link, the graphical or visual representation being configured for display on a display device of the computerized apparatus and to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and causing display of advertising content selected based at least in part on the industry or occupation of the organization or entity. | 20. A method of providing information to a user of a computerized apparatus, the method comprising: receiving via a network link a digitized representation of a speech input, the representation generated via a speech recognition apparatus of the computerized apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the representation, identifying a location associated with the organization or entity; and selecting and causing provision of a graphical or visual representation of the location via the network link, the graphical or visual representation being configured for display on a display device of the computerized apparatus and to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and causing display of advertising content selected based at least in part on the industry or occupation of the organization or entity. 26. The method of claim 20 , further comprising causing display of advertising for at least one organization or entity which is geographically proximate to the organization or entity at the location. | 0.790526 |
9,594,872 | 1 | 2 | 1. A method for implementing an interface terminology in a longitudinal electronic medical record, the interface terminology comprising concepts and descriptions, a description being an alternative way to express a concept, the method comprising: storing a plurality of concepts in a first table a database; storing a plurality of descriptions in a second table in the database; storing in a third table in the database linking information that links each description in the second table to a respective concept in the first table; storing an external code set in a fourth table in the database, the external code set comprising a plurality of external codes; and mapping an external code to a respective concept via a directed graph structure linking each external code in the fourth table to the respective concept in the first table; wherein said plurality of concepts provide a unique terminology for a user and can be added, updated, deleted, and merged; wherein multiple of said plurality of descriptions may link to one of said plurality of concepts; wherein said plurality of descriptions include terms used by both clinicians and patients; wherein, for each concept, one of said plurality of descriptions is a preferred description for the linked concept and one of said plurality of descriptions is a preferred consumer term for the linked concept; wherein multiple of said plurality of external codes may map to one of said plurality of concepts; wherein said method for implementing an interface terminology serves the ends of capturing clinician's intent, driving financial aspects including billing, and driving analytical functions; creating a longitudinal electronic medical record by: generating a first instance of a plurality of data objects during a first encounter, said plurality of data objects comprising data elements further comprising a first instance identifier and temporal identifiers; linking a data object in said first instance to a summarization reference with a pointer, where the plurality of data objects and the summarization reference are related as part of a directed graph data structure; creating an additional instance of a plurality of data objects during a later encounter, said additional instance of a plurality of data objects comprising data elements further comprising an additional instance identifier and temporal identifier; and providing continuity for said plurality of data objects of said first instance over time by tracking a relationship between said data object of said first instance and a data object of said additional instance; tagging elements within a domain within the longitudinal electronic medical record with one or more of said plurality of descriptions; and displaying the preferred descriptions and the preferred consumer term. | 1. A method for implementing an interface terminology in a longitudinal electronic medical record, the interface terminology comprising concepts and descriptions, a description being an alternative way to express a concept, the method comprising: storing a plurality of concepts in a first table a database; storing a plurality of descriptions in a second table in the database; storing in a third table in the database linking information that links each description in the second table to a respective concept in the first table; storing an external code set in a fourth table in the database, the external code set comprising a plurality of external codes; and mapping an external code to a respective concept via a directed graph structure linking each external code in the fourth table to the respective concept in the first table; wherein said plurality of concepts provide a unique terminology for a user and can be added, updated, deleted, and merged; wherein multiple of said plurality of descriptions may link to one of said plurality of concepts; wherein said plurality of descriptions include terms used by both clinicians and patients; wherein, for each concept, one of said plurality of descriptions is a preferred description for the linked concept and one of said plurality of descriptions is a preferred consumer term for the linked concept; wherein multiple of said plurality of external codes may map to one of said plurality of concepts; wherein said method for implementing an interface terminology serves the ends of capturing clinician's intent, driving financial aspects including billing, and driving analytical functions; creating a longitudinal electronic medical record by: generating a first instance of a plurality of data objects during a first encounter, said plurality of data objects comprising data elements further comprising a first instance identifier and temporal identifiers; linking a data object in said first instance to a summarization reference with a pointer, where the plurality of data objects and the summarization reference are related as part of a directed graph data structure; creating an additional instance of a plurality of data objects during a later encounter, said additional instance of a plurality of data objects comprising data elements further comprising an additional instance identifier and temporal identifier; and providing continuity for said plurality of data objects of said first instance over time by tracking a relationship between said data object of said first instance and a data object of said additional instance; tagging elements within a domain within the longitudinal electronic medical record with one or more of said plurality of descriptions; and displaying the preferred descriptions and the preferred consumer term. 2. The method according to claim 1 , wherein the external code set is an administrative terminology. | 0.759615 |
9,788,215 | 14 | 16 | 14. A system, comprising: a communication interface device; and a processor of a first entity configured to: store in a data store for each of a plurality of entities an entity image data comprising metadata about an entity of the plurality of entities, wherein the data store is configured to create and support an organically changing schema, and provides a mechanism to propagate changes to the schema or data; discover a second entity to help achieve an objective, wherein the second entity is a cloud-based entity; connect to a processor of the second entity via the communication interface device; use a meta-language to exchange with the second processor of the second entity via the communication interface a description of the objective to aggregate data from the second entity and descriptive information associated with the second entity, wherein the descriptive information includes an identification of a proprietary data access interface associated with the second entity, wherein the proprietary data access interface associated with the second entity is different than a proprietary data access interface associated with the first entity, wherein a bridge separate from the processor of the first entity and the processor of the second entity is configured to receive the meta-language exchanged with the processor of the second entity and to use an internal standard meta-language to enable the processor of the second entity with the proprietary data access interface to understand the description of the objective; negotiate with the second entity using the meta-language, including by exchanging one or more proposals with the processor of the entity via the communication interface to form a contract, the contract indicates how data will be aggregated from the second entity; receive an indication of a need to recruit a third entity to help achieve the objective; recruit the third entity to help achieve the objective, through a process that includes one or more of the following: discovery, connection, description, negotiation, configuration, initiation of operation, maintenance of operation, and discontinuation of operation; and in the event the contract is formed, perform a self-configuration in accordance with the contract; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions. | 14. A system, comprising: a communication interface device; and a processor of a first entity configured to: store in a data store for each of a plurality of entities an entity image data comprising metadata about an entity of the plurality of entities, wherein the data store is configured to create and support an organically changing schema, and provides a mechanism to propagate changes to the schema or data; discover a second entity to help achieve an objective, wherein the second entity is a cloud-based entity; connect to a processor of the second entity via the communication interface device; use a meta-language to exchange with the second processor of the second entity via the communication interface a description of the objective to aggregate data from the second entity and descriptive information associated with the second entity, wherein the descriptive information includes an identification of a proprietary data access interface associated with the second entity, wherein the proprietary data access interface associated with the second entity is different than a proprietary data access interface associated with the first entity, wherein a bridge separate from the processor of the first entity and the processor of the second entity is configured to receive the meta-language exchanged with the processor of the second entity and to use an internal standard meta-language to enable the processor of the second entity with the proprietary data access interface to understand the description of the objective; negotiate with the second entity using the meta-language, including by exchanging one or more proposals with the processor of the entity via the communication interface to form a contract, the contract indicates how data will be aggregated from the second entity; receive an indication of a need to recruit a third entity to help achieve the objective; recruit the third entity to help achieve the objective, through a process that includes one or more of the following: discovery, connection, description, negotiation, configuration, initiation of operation, maintenance of operation, and discontinuation of operation; and in the event the contract is formed, perform a self-configuration in accordance with the contract; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions. 16. The system of claim 14 , wherein the processor is further configured to negotiate with the third entity a contract to replace the second entity in helping to achieve the objective. | 0.610169 |
9,947,320 | 11 | 19 | 11. A computerized apparatus having a processor, the processor being adapted to perform steps comprising: receiving at least one audio interaction; decoding speech within the at least one audio interaction; indexing the decoded speech so as to obtain at least one indexed audio interaction; receiving a text representing a script; automatically extracting at least two key terms from the script, comprising: discarding irrelevant terms; determining a recognizability score for a word in the script based on a recognizability of a phoneme combination in the word; determining a uniqueness score for the word in the script; combining the recognizability score and the uniqueness score into a word score; and determining that the word is a key term, subject to the word score exceeding a threshold; automatically generating a query representing the script, comprising: receiving at least one constraint related to a number of words difference between two key terms of the at least two key terms; determining spotted key terms of the at least two key terms that appear in the at least one indexed audio interaction; determining at least one complied constraint from the at least one received constraint; and determining a relevance score for the at least one indexed audio interaction, based on the spotted key terms and the at least one complied constraint; and using the relevance score to determine compliance of the at least one audio interaction with the script. | 11. A computerized apparatus having a processor, the processor being adapted to perform steps comprising: receiving at least one audio interaction; decoding speech within the at least one audio interaction; indexing the decoded speech so as to obtain at least one indexed audio interaction; receiving a text representing a script; automatically extracting at least two key terms from the script, comprising: discarding irrelevant terms; determining a recognizability score for a word in the script based on a recognizability of a phoneme combination in the word; determining a uniqueness score for the word in the script; combining the recognizability score and the uniqueness score into a word score; and determining that the word is a key term, subject to the word score exceeding a threshold; automatically generating a query representing the script, comprising: receiving at least one constraint related to a number of words difference between two key terms of the at least two key terms; determining spotted key terms of the at least two key terms that appear in the at least one indexed audio interaction; determining at least one complied constraint from the at least one received constraint; and determining a relevance score for the at least one indexed audio interaction, based on the spotted key terms and the at least one complied constraint; and using the relevance score to determine compliance of the at least one audio interaction with the script. 19. The computerized apparatus of claim 11 , wherein the processor is further adapted to perform steps comprising sending a list of the at least one audio interactions that do not comply with the script to a user interface. | 0.826324 |
7,716,161 | 3 | 4 | 3. A computer implemented method for determining if an advertisement is relevant to a target document, the method comprising: identifying targeting information for the advertisement; identifying a set of one or more topics of the target document by analyzing the content of the target document; comparing the targeting information to the set of one or more topics to determine if a match exists; determining that the advertisement is relevant to the target document if the match exists; making a serving determination using the determination of whether or not the advertisement is relevant to the target document; and controlling serving of the advertisement for presentation to a requestor via a client device using the serving determination, wherein the advertisement belongs to an advertiser, wherein the targeting information includes a set of one or more topics previously provided from the advertiser, wherein analyzing the content comprises identifying a set of one or more topics by calculating weighted terms for the target document based on text within the target document, and wherein the set of one or more topics contains those of the weighted terms whose weight exceeds a defined threshold. | 3. A computer implemented method for determining if an advertisement is relevant to a target document, the method comprising: identifying targeting information for the advertisement; identifying a set of one or more topics of the target document by analyzing the content of the target document; comparing the targeting information to the set of one or more topics to determine if a match exists; determining that the advertisement is relevant to the target document if the match exists; making a serving determination using the determination of whether or not the advertisement is relevant to the target document; and controlling serving of the advertisement for presentation to a requestor via a client device using the serving determination, wherein the advertisement belongs to an advertiser, wherein the targeting information includes a set of one or more topics previously provided from the advertiser, wherein analyzing the content comprises identifying a set of one or more topics by calculating weighted terms for the target document based on text within the target document, and wherein the set of one or more topics contains those of the weighted terms whose weight exceeds a defined threshold. 4. The computer implemented method of claim 3 , wherein identifying targeting information comprises generating a list of topics by analyzing content of the advertisement. | 0.731861 |
6,088,731 | 1 | 27 | 1. In a computer system having a processor, a memory unit, an input device and an output device, a method for collecting site information from an Internet site, said method comprising computer implemented steps of: executing an intelligent assistant process on said computer system; establishing communication with said Internet site; detecting an intelligent assistant tag in said Internet site, said intelligent assistant tag containing embedded information; authorizing said computer system to collect said site information from said Internet site when said embedded information corresponds to a plug-in process of said intelligent assistant; collecting said site information from said Internet site; and altering said intelligent assistant process based on said site information. | 1. In a computer system having a processor, a memory unit, an input device and an output device, a method for collecting site information from an Internet site, said method comprising computer implemented steps of: executing an intelligent assistant process on said computer system; establishing communication with said Internet site; detecting an intelligent assistant tag in said Internet site, said intelligent assistant tag containing embedded information; authorizing said computer system to collect said site information from said Internet site when said embedded information corresponds to a plug-in process of said intelligent assistant; collecting said site information from said Internet site; and altering said intelligent assistant process based on said site information. 27. The method of claim 1 further comprising the step of a user of said Internet site communicating with said intelligent assistant process via a mouse gesture. | 0.685039 |
8,566,509 | 16 | 17 | 16. The logic circuit of claim 10 , wherein said method further comprises processing, by said VMI FSM, a packet header token using an input/output (I/O) protocol on an adapter specified by an InfiniBand architecture, wherein said processing said packet header token includes: a port receiving a data packet that includes a payload and a packet header; storing said payload in a payload buffer; inserting said packet header in a second field of said packet header token, wherein said packet header token is said first input token, and wherein said second field of said packet header token is said second field of said first input token; extracting a queue pair (QP) number from said packet header, wherein said QP number identifies a QP that specifies a network connection in said InfiniBand architecture; storing said QP number in a first field of said packet header token, wherein said first field of said packet header token is said first field of said first input token, wherein said receiving said first input token includes receiving said packet header token from said port and at said VMI FSM. | 16. The logic circuit of claim 10 , wherein said method further comprises processing, by said VMI FSM, a packet header token using an input/output (I/O) protocol on an adapter specified by an InfiniBand architecture, wherein said processing said packet header token includes: a port receiving a data packet that includes a payload and a packet header; storing said payload in a payload buffer; inserting said packet header in a second field of said packet header token, wherein said packet header token is said first input token, and wherein said second field of said packet header token is said second field of said first input token; extracting a queue pair (QP) number from said packet header, wherein said QP number identifies a QP that specifies a network connection in said InfiniBand architecture; storing said QP number in a first field of said packet header token, wherein said first field of said packet header token is said first field of said first input token, wherein said receiving said first input token includes receiving said packet header token from said port and at said VMI FSM. 17. The logic circuit of claim 16 , wherein said method further comprises: determining a transport mode of said network connection specified by said QP is a reliable connect transport mode (RC) or a reliable datagram transport mode (RD); determining a packet sequence number (PSN) included in said packet header token is equal to an expected PSN (ePSN) included in said fetched context; and in response to said determining said transport mode of said QP is said RC or said RD and in response to said determining said PSN is equal to said ePSN, sending an acknowledgment to said port. | 0.5 |
9,836,290 | 1 | 7 | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a reduced size runtime which resides in the memory and is executable with the logical processor, the reduced size runtime functioning as a replacement for a larger runtime R, the reduced size runtime occupying less nonvolatile storage space than the larger runtime R as a result of containing less metadata than the larger runtime R, wherein metadata includes one or more of the following: a type name, a type member name, a type layout for garbage collection purposes, or a type member layout for garbage collection purposes; and at least one of the following dynamic support structures in the memory and outside of the reduced size runtime: a mapping between metadata and at least one native code runtime artifact; a mapping between runtime type descriptions, each runtime type description including at least one of the following: a list of implemented interfaces for a type which is in an execution scope of a compiled computer program, or a garbage collection layout for a type which is in an execution scope of the compiled computer program; or at least one piece of code which upon execution supports a reflection invocation of an artifact of the compiled computer program. | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; a reduced size runtime which resides in the memory and is executable with the logical processor, the reduced size runtime functioning as a replacement for a larger runtime R, the reduced size runtime occupying less nonvolatile storage space than the larger runtime R as a result of containing less metadata than the larger runtime R, wherein metadata includes one or more of the following: a type name, a type member name, a type layout for garbage collection purposes, or a type member layout for garbage collection purposes; and at least one of the following dynamic support structures in the memory and outside of the reduced size runtime: a mapping between metadata and at least one native code runtime artifact; a mapping between runtime type descriptions, each runtime type description including at least one of the following: a list of implemented interfaces for a type which is in an execution scope of a compiled computer program, or a garbage collection layout for a type which is in an execution scope of the compiled computer program; or at least one piece of code which upon execution supports a reflection invocation of an artifact of the compiled computer program. 7. The system of claim 1 , further comprising at least one of the following items built with metadata in the system which resides outside the reduced size runtime: a garbage collection descriptor for a type; or a garbage collection code for reclaiming memory used by a type. | 0.713987 |
8,245,204 | 3 | 4 | 3. The system of claim 1 , wherein said supplemental symbol-type dictionary further comprises conditional constraints for said plurality of parameter data types. | 3. The system of claim 1 , wherein said supplemental symbol-type dictionary further comprises conditional constraints for said plurality of parameter data types. 4. The system of claim 3 , wherein said conditional constraints comprise an immediate directive that invokes a built-in function. | 0.5 |
8,935,274 | 15 | 20 | 15. An apparatus, comprising: memory element configured to store data; a processor operable to execute instructions associated with the data; a network sensor configured to: receive data propagating in a network environment; identify in real time a first user who generated the data and a second user who consumed the data; evaluate one or more fields in the data, wherein the evaluating includes searching and filtering for nouns and noun phrases; and a central engine configured to interface with the memory element, the processor, and the network sensor, the central engine being configured to: identify selected terms within the nouns and noun phrases, wherein the selected terms correspond to one or more topics, wherein the selected terms are tagged with respective expertise tags; associate the first user and the second user with the expertise tags and add the selected terms to a first personal vocabulary of the first user and a second personal vocabulary of the second user, wherein the first personal vocabulary is associated with expertise of the first user in the one or more topics and the second personal vocabulary is associated with expertise of the second user in the one or more topics, wherein the selected terms are assigned a higher weight in the first personal vocabulary than in the second personal vocabulary. | 15. An apparatus, comprising: memory element configured to store data; a processor operable to execute instructions associated with the data; a network sensor configured to: receive data propagating in a network environment; identify in real time a first user who generated the data and a second user who consumed the data; evaluate one or more fields in the data, wherein the evaluating includes searching and filtering for nouns and noun phrases; and a central engine configured to interface with the memory element, the processor, and the network sensor, the central engine being configured to: identify selected terms within the nouns and noun phrases, wherein the selected terms correspond to one or more topics, wherein the selected terms are tagged with respective expertise tags; associate the first user and the second user with the expertise tags and add the selected terms to a first personal vocabulary of the first user and a second personal vocabulary of the second user, wherein the first personal vocabulary is associated with expertise of the first user in the one or more topics and the second personal vocabulary is associated with expertise of the second user in the one or more topics, wherein the selected terms are assigned a higher weight in the first personal vocabulary than in the second personal vocabulary. 20. The apparatus of claim 15 , further comprising: a search interface configured to initiate the search query for the particular expertise within a database that includes at least some of the selected words. | 0.691395 |
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