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8,156,129 | 1 | 7 | 1. A method comprising the following computer-executable acts: analyzing a relationship between a first query and a second query based at least in part upon search results previously selected by users, wherein the search results previously selected by the users were presented to the users in response to submission of the first query and/or the second query to a search engine, wherein analyzing the relationship between the first query and the second query comprises: accessing a data repository that comprises a computer-implemented bipartite graph that includes a first set of nodes and a second set of nodes, wherein the first set of nodes represents queries and the second set of nodes represents URLs, wherein the first set of nodes includes a first node that is representative of the first query and a second node that is representative of the second query, and wherein the graph further comprises edges that are weighted to indicate relationships between queries and URLs; initiating a random walk at the first node; and determining a number of steps in the random walk until the second node is reached in the random walk, wherein a step is from a node in the first set of nodes to another node in the first set of nodes; determining whether the first query is substantially similar to the second query based at least in part upon the number of steps in the random walk until the second node is reached in the random walk; and generating correlation data that correlates the first query and the second query if the first query and second query are determined to be substantially similar. | 1. A method comprising the following computer-executable acts: analyzing a relationship between a first query and a second query based at least in part upon search results previously selected by users, wherein the search results previously selected by the users were presented to the users in response to submission of the first query and/or the second query to a search engine, wherein analyzing the relationship between the first query and the second query comprises: accessing a data repository that comprises a computer-implemented bipartite graph that includes a first set of nodes and a second set of nodes, wherein the first set of nodes represents queries and the second set of nodes represents URLs, wherein the first set of nodes includes a first node that is representative of the first query and a second node that is representative of the second query, and wherein the graph further comprises edges that are weighted to indicate relationships between queries and URLs; initiating a random walk at the first node; and determining a number of steps in the random walk until the second node is reached in the random walk, wherein a step is from a node in the first set of nodes to another node in the first set of nodes; determining whether the first query is substantially similar to the second query based at least in part upon the number of steps in the random walk until the second node is reached in the random walk; and generating correlation data that correlates the first query and the second query if the first query and second query are determined to be substantially similar. 7. The method of claim 1 , further comprising: receiving the first query from a user for execution against contents of a data repository; determining that the first query is substantially similar to the second query; and outputting a search result to the user that is based at least in part upon the second query. | 0.715455 |
9,697,827 | 6 | 24 | 6. A computer-implemented method, comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving an utterance; generating an input finite state transducer (FST) comprising sequences of subword units organized into input FST paths, wherein a path of the input FST paths corresponds to a speech recognition hypothesis of a plurality of speech recognition hypotheses that are based on the received utterance; obtaining a grammar of utterances, wherein each utterance of the grammar of utterances comprises a sequence of subword units; generating, using the grammar of utterances, an utterance FST comprising sequences of subword units organized into utterance FST paths, wherein a path of the utterance FST paths corresponds to a command; generating an output FST using the input FST and the utterance FST, wherein the output FST comprises a first path indicative of a difference between a first path of the input FST paths and a first path of the utterance FST paths, and a second path indicative of a difference between the first path of the input FST paths and a second path of the utterance FST paths; computing a first difference score using the first path of the output FST; computing a second difference score using the second path of the output FST; and determining a first command representative of the received utterance based at least in part on the first difference score and the second difference score. | 6. A computer-implemented method, comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving an utterance; generating an input finite state transducer (FST) comprising sequences of subword units organized into input FST paths, wherein a path of the input FST paths corresponds to a speech recognition hypothesis of a plurality of speech recognition hypotheses that are based on the received utterance; obtaining a grammar of utterances, wherein each utterance of the grammar of utterances comprises a sequence of subword units; generating, using the grammar of utterances, an utterance FST comprising sequences of subword units organized into utterance FST paths, wherein a path of the utterance FST paths corresponds to a command; generating an output FST using the input FST and the utterance FST, wherein the output FST comprises a first path indicative of a difference between a first path of the input FST paths and a first path of the utterance FST paths, and a second path indicative of a difference between the first path of the input FST paths and a second path of the utterance FST paths; computing a first difference score using the first path of the output FST; computing a second difference score using the second path of the output FST; and determining a first command representative of the received utterance based at least in part on the first difference score and the second difference score. 24. The method of claim 6 , wherein the determining the first command is further based at least in part on at least one of: historical user data, a user preference, availability of hardware, availability of a file, or a capability of a computing device to process the first command. | 0.73743 |
8,775,409 | 28 | 39 | 28. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. | 28. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. 39. The system of claim 28 , wherein the category popularity score used for determining the cluster score is based on a total volume of web traffic related to the representative category, an increase in total volume of web traffic related to the representative category, a number of clusters associated with the representative category, or a number of search queries in a plurality of clusters associated with the representative category. | 0.510067 |
8,666,757 | 5 | 9 | 5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. | 5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. 9. The computer-implemented method according to claim 5 , wherein summary variables comprise one of the data extracted across the primary level, the data extracted within the driving elements, the data extracted across the intermediary level, the data extracted within the groups, the data extracted across the aggregate level, and the data extracted within the categories. | 0.5 |
9,298,703 | 1 | 10 | 1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. | 1. A system comprising: means for selecting, from a data store, a word or phrase associated with a failure to translate a message from a first language to a second language; means for selecting a person from whom to solicit user feedback for the translation failure; means for generating a query to request user feedback from the person; means for offering an incentive to the person; means for receiving the user feedback, the user feedback potentially assisting to translate the word or phrase; and means for rewarding the person with the incentive wherein the incentive is determined based on a complexity of the word or phrase or an importance of the word or phrase. 10. The system of claim 1 , wherein the query comprises a set of preselected definitions from which the person can choose a definition for the word or phrase. | 0.666667 |
5,379,366 | 35 | 36 | 35. The method for representing information in a computer system according to claim 34, wherein said patterns in said relationships are comprised of recurring correlations in values of fundamental relationships in Project library records, and recurring correlations in values of user relationships in records of the Project and Component libraries. | 35. The method for representing information in a computer system according to claim 34, wherein said patterns in said relationships are comprised of recurring correlations in values of fundamental relationships in Project library records, and recurring correlations in values of user relationships in records of the Project and Component libraries. 36. The method for representing information in a computer system according to claim 35, wherein patterns recognized in Project library records are stored in the component record represented by the URN stored in the type fundamental relationship of said project records or in a parent record of said component record, and wherein patterns recognized in Component library records are stored in the component record in which said recognized patterns are first identified or in a parent record of said component record; the characterization of the relationship storing the recognized pattern being designated as a system concept. | 0.5 |
9,459,995 | 11 | 12 | 11. The method of claim 8 , wherein the second set of markup-language statements includes respective test definitions for the tests, and wherein for a rule of the collection of rules, a test definition of the respective test definitions includes references to multiple ones of the interconnected components and their attributes, and two or more distinct conditions one or more of which are to be satisfied by the multiple ones of the interconnected components for the computing system to comply with the rule. | 11. The method of claim 8 , wherein the second set of markup-language statements includes respective test definitions for the tests, and wherein for a rule of the collection of rules, a test definition of the respective test definitions includes references to multiple ones of the interconnected components and their attributes, and two or more distinct conditions one or more of which are to be satisfied by the multiple ones of the interconnected components for the computing system to comply with the rule. 12. The method of claim 11 , wherein the multiple ones of the interconnected components include different types of hardware components. | 0.5 |
9,582,591 | 12 | 14 | 12. A system, comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving user input that is indicative of a first research document, the first research document is authored by an author and has a publication date, the publication date indicative of a date upon which the first research document was published, wherein a second research document comprises a sentence that includes a citation to the first research document, the second research document has a publication date that is subsequent to the publication date of the first research document; and in response to receipt of the user input, generating a graphical summary of the first research document, the graphical summary comprising portions of sentences included in research documents having publication dates that are subsequent to the publication date of the first research document, the portions of the sentences comprising a portion of the sentence in the second research document that includes the citation to the first research document. | 12. A system, comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving user input that is indicative of a first research document, the first research document is authored by an author and has a publication date, the publication date indicative of a date upon which the first research document was published, wherein a second research document comprises a sentence that includes a citation to the first research document, the second research document has a publication date that is subsequent to the publication date of the first research document; and in response to receipt of the user input, generating a graphical summary of the first research document, the graphical summary comprising portions of sentences included in research documents having publication dates that are subsequent to the publication date of the first research document, the portions of the sentences comprising a portion of the sentence in the second research document that includes the citation to the first research document. 14. The system of claim 12 , the acts further comprising locating the sentence in the second research document that includes the citation to the first research document. | 0.73676 |
9,788,796 | 1 | 3 | 1. A system for adaptive interpretation of ECG waveforms, the system comprising: a processor; a cluster database of existing ECG datasets organized into clusters, wherein each existing ECG dataset includes an existing ECG waveform with at least one corresponding existing feature and existing interpretation, and wherein the clusters are existing ECG datasets having a common existing feature; a user interface; and a cluster training module executable by the processor to: receive a new ECG waveform and a feature extracted from the new ECG waveform; select a cluster interpretation module based on the feature, wherein the cluster interpretation module is trained on one of the clusters from the cluster database; process the new ECG waveform and/or the feature to provide a cluster interpretation output; display the cluster interpretation output on the user interface; receive clinician input via the user interface accepting or rejecting the cluster interpretation output; and create a new cluster based on the extracted feature when the clinician input rejects the cluster interpretation output. | 1. A system for adaptive interpretation of ECG waveforms, the system comprising: a processor; a cluster database of existing ECG datasets organized into clusters, wherein each existing ECG dataset includes an existing ECG waveform with at least one corresponding existing feature and existing interpretation, and wherein the clusters are existing ECG datasets having a common existing feature; a user interface; and a cluster training module executable by the processor to: receive a new ECG waveform and a feature extracted from the new ECG waveform; select a cluster interpretation module based on the feature, wherein the cluster interpretation module is trained on one of the clusters from the cluster database; process the new ECG waveform and/or the feature to provide a cluster interpretation output; display the cluster interpretation output on the user interface; receive clinician input via the user interface accepting or rejecting the cluster interpretation output; and create a new cluster based on the extracted feature when the clinician input rejects the cluster interpretation output. 3. The system of claim 1 , further comprising a general interpretation module trained on a general database of existing ECG datasets, wherein the general interpretation module is executable by the processor to process the new ECG waveform and/or the extracted feature to provide a general interpretation output. | 0.5 |
7,853,622 | 7 | 10 | 7. The method of claim 1 , wherein the selected label type comprises ads selected by or displayed to the users. | 7. The method of claim 1 , wherein the selected label type comprises ads selected by or displayed to the users. 10. The method of claim 7 , wherein outputting a value of a label of the selected label type for a particular media node comprises determining a value for a particular ad label associated with a particular video represented by the particular media node. | 0.5 |
8,458,596 | 17 | 23 | 17. A non-transitory computer-readable medium comprising instructions for execution by a computer, the instructions including a computer-implemented method for providing a mashup dashboard, the instructions for implementing: creating a mashup dashboard, including providing, via a display interface, a listing of pre-defined mashups and a canvas, the pre-defined mashups being stored in a repository, interacting with the user, via the display interface and a user input device interface, to define a visual configuration of the canvas and to drag and drop one of the pre-defined mashups from the listing onto the canvas, and storing, in the repository, the visual configuration of the canvas with the pre-defined mashup as a mashup dashboard, for later retrieval to recreate the visual configuration with the pre-defined mashup executing therein; and using the mashup dashboard, including retrieving the mashup dashboard from the repository; providing, via the display interface, a display of the retrieved mashup dashboard that recreates a visual configuration pre-defined in the stored mashup dashboard, the visual configuration including a pre-defined mashup executing therein to provide live data from the mashup, wherein the visual configuration includes first and second pre-defined mashups executing therein to provide the live data, the instructions for using the mashup dashboard include: providing the live data from the first pre-defined mashup to the second pre-defined mashup which maps the live data of the first pre-defined mashup into different live data and visuals of the second pre-defined mashup as both are executing in the visual configuration, the instructions for creating the mashup dashboard include: interacting with the user via the display interface and the user input device interface to specify how the second pre-defined mashup maps the live data from the first pre-defined mashup into the different live data and visuals of the second pre-defined mashup. | 17. A non-transitory computer-readable medium comprising instructions for execution by a computer, the instructions including a computer-implemented method for providing a mashup dashboard, the instructions for implementing: creating a mashup dashboard, including providing, via a display interface, a listing of pre-defined mashups and a canvas, the pre-defined mashups being stored in a repository, interacting with the user, via the display interface and a user input device interface, to define a visual configuration of the canvas and to drag and drop one of the pre-defined mashups from the listing onto the canvas, and storing, in the repository, the visual configuration of the canvas with the pre-defined mashup as a mashup dashboard, for later retrieval to recreate the visual configuration with the pre-defined mashup executing therein; and using the mashup dashboard, including retrieving the mashup dashboard from the repository; providing, via the display interface, a display of the retrieved mashup dashboard that recreates a visual configuration pre-defined in the stored mashup dashboard, the visual configuration including a pre-defined mashup executing therein to provide live data from the mashup, wherein the visual configuration includes first and second pre-defined mashups executing therein to provide the live data, the instructions for using the mashup dashboard include: providing the live data from the first pre-defined mashup to the second pre-defined mashup which maps the live data of the first pre-defined mashup into different live data and visuals of the second pre-defined mashup as both are executing in the visual configuration, the instructions for creating the mashup dashboard include: interacting with the user via the display interface and the user input device interface to specify how the second pre-defined mashup maps the live data from the first pre-defined mashup into the different live data and visuals of the second pre-defined mashup. 23. The computer-readable medium of claim 17 , further comprising instructions for surfacing a parameter in the mashup in the mashup dashboard to be exposed to the user, wherein the parameter while in the mashup interacts with the user. | 0.609272 |
7,966,554 | 16 | 19 | 16. The apparatus of claim 15 wherein said first marker audio data is delivered on said user interface as a selectable connection which when selected will enable said processor to deliver to said user interface corresponding said third marker visual data. | 16. The apparatus of claim 15 wherein said first marker audio data is delivered on said user interface as a selectable connection which when selected will enable said processor to deliver to said user interface corresponding said third marker visual data. 19. The apparatus of claim 16 wherein the insertion of said third markers in the visual data are based on time. | 0.784047 |
7,630,898 | 9 | 15 | 9. The computer-implemented method of claim 1 , further comprising adding default pronunciations to the pronunciation dictionary based on TTS letter-to-sound rules. | 9. The computer-implemented method of claim 1 , further comprising adding default pronunciations to the pronunciation dictionary based on TTS letter-to-sound rules. 15. The computing device of claim 9 , wherein the linguistic contexts are associated with foreign languages. | 0.5 |
8,676,802 | 23 | 28 | 23. An information retrieval system comprising: a processor coupled to a computer readable medium having instructions stored thereon, wherein the processor executing the instructions implements modules comprising: an interface module that receives at least one search term and searches a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; a database access module that retrieve a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; a matching module that retrieves the associated salient terms for each of the retrieved documents and the associated properties; a clustering module that groups based on a distance metric the retrieved salient terms into one or more clusters of salient terms and provides the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; the interface module that receives a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; the matching module selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; further comprising retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. | 23. An information retrieval system comprising: a processor coupled to a computer readable medium having instructions stored thereon, wherein the processor executing the instructions implements modules comprising: an interface module that receives at least one search term and searches a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; a database access module that retrieve a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; a matching module that retrieves the associated salient terms for each of the retrieved documents and the associated properties; a clustering module that groups based on a distance metric the retrieved salient terms into one or more clusters of salient terms and provides the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; the interface module that receives a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; the matching module selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; further comprising retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. 28. The system of claim 23 , wherein the providing the clusters to the user comprises displaying on a user interface for each cluster provided to the user one or more salient terms for the cluster. | 0.758578 |
8,954,474 | 1 | 2 | 1. A method of maintaining data described in a plurality of data models, the method comprising: using an ontology to describe the data models; and managing the data models using the ontology to support semantic usage of the data in content, the managing including using a validation schema to derive and validate one or more objects governed by the ontology, the one or more objects derived from one or more data-centric components of the content, the content having a structure semantically independent of the ontology; wherein the managing is neutral relative to implementation of the content. | 1. A method of maintaining data described in a plurality of data models, the method comprising: using an ontology to describe the data models; and managing the data models using the ontology to support semantic usage of the data in content, the managing including using a validation schema to derive and validate one or more objects governed by the ontology, the one or more objects derived from one or more data-centric components of the content, the content having a structure semantically independent of the ontology; wherein the managing is neutral relative to implementation of the content. 2. The method of claim 1 , further comprising using a semantic-independent schema to provide the semantically independent structure to the content. | 0.582386 |
8,135,578 | 1 | 5 | 1. A method comprising: accessing a corpus of terms by a parser using a processor in each of a plurality of speech applications; parsing, using said parser and said processor, said corpus of terms in each speech application to produce a plurality of first output sets, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application, wherein said grammar tags are selected from among command grammar tags and collection grammar tags; accessing said plurality of first output sets by a class-relabeler and said processor; replacing by the class-relabeler and said processor, for each of the plurality of speech applications, each of the grammar tags in the plurality of first output sets with a class identifier of an application-generic class, to produce plurality of a second output sets; accessing said plurality of second output sets by a token selector and said processor; processing collectively, by said token selector and said processor, the plurality of second output sets or data derived from the output sets with a statistical language model (SLM) trainer; and generating, using said processor, an application-generic class-based SLM using a set of results from said SLM trainer. | 1. A method comprising: accessing a corpus of terms by a parser using a processor in each of a plurality of speech applications; parsing, using said parser and said processor, said corpus of terms in each speech application to produce a plurality of first output sets, in which expressions identified in the corpus are replaced with corresponding grammar tags from a grammar that is specific to the application, wherein said grammar tags are selected from among command grammar tags and collection grammar tags; accessing said plurality of first output sets by a class-relabeler and said processor; replacing by the class-relabeler and said processor, for each of the plurality of speech applications, each of the grammar tags in the plurality of first output sets with a class identifier of an application-generic class, to produce plurality of a second output sets; accessing said plurality of second output sets by a token selector and said processor; processing collectively, by said token selector and said processor, the plurality of second output sets or data derived from the output sets with a statistical language model (SLM) trainer; and generating, using said processor, an application-generic class-based SLM using a set of results from said SLM trainer. 5. A method as recited in claim 1 , wherein said parsing comprises: for each identified expression, identifying, using said processor, a type of grammar to which the expression corresponds; and selecting a grammar tag to replace the expression based on the identified type of grammar. | 0.766063 |
8,438,032 | 4 | 5 | 4. The method in accordance with claim 3 , further comprising: adding a paralinguistic as SSML codes to said user supplied text. | 4. The method in accordance with claim 3 , further comprising: adding a paralinguistic as SSML codes to said user supplied text. 5. The method in accordance with claim 4 , wherein said paralinguistic is at least one of the following: i) a breath; ii) a cough; iii) a laugh; iv) a sigh; v) a throat clear; or vi) a sniffle. | 0.5 |
9,251,185 | 1 | 2 | 1. One or more computer-readable storage media excluding signals per se having embodied thereon computer-executable instructions that, when executed, perform a method comprising: providing a set of search results returned in response to a search query composed and issued by a user; determining a ranking of the set of returned search results against each other as a function of relevance to the issued search query; selecting for evaluation one or more search results from the returned set of search results based on the ranking; determining a level of quality, that is independent of the terms of the search query, for each of the one or more selected search results from the returned set of search results by employing a classification process, wherein the classification process comprises: targeting features demonstrated by the one or more selected search results to be evaluated; evaluating the targeted features to generate a level-of-quality score for each of the one or more selected search results, wherein the level-of-quality score is evaluated using a cross-result entropy that quantifies a level of similarity between a plurality of the search results, and wherein the search engine is configured to decrease the level-of-quality score based on determining that the cross-result entropy is sufficiently high; comparing the level-of-quality score against a predefined threshold value; and based on the comparison, assigning each of the one or more selected search results an absolute measurement, wherein the absolute measurement indicates good quality when the level-of-quality score is greater than the threshold value, and wherein the absolute measurement indicates poor quality when the level-of-quality score is less than the threshold value; calculating a level of confidence that a rewritten search query will provide new search results that improve the set of search results; automatically rewriting the search query by the search engine to generate the rewritten search query, wherein each key word of the rewritten search query is automatically selected for inclusion in the rewritten search query; and based on the calculated level of confidence indicating that the rewritten search query will provide the new search results that improve the set of search results, and based on identifying that the absolute measurement assigned to at least one of the one or more selected search results indicates the poor quality, automatically conducting a search with the rewritten search query. | 1. One or more computer-readable storage media excluding signals per se having embodied thereon computer-executable instructions that, when executed, perform a method comprising: providing a set of search results returned in response to a search query composed and issued by a user; determining a ranking of the set of returned search results against each other as a function of relevance to the issued search query; selecting for evaluation one or more search results from the returned set of search results based on the ranking; determining a level of quality, that is independent of the terms of the search query, for each of the one or more selected search results from the returned set of search results by employing a classification process, wherein the classification process comprises: targeting features demonstrated by the one or more selected search results to be evaluated; evaluating the targeted features to generate a level-of-quality score for each of the one or more selected search results, wherein the level-of-quality score is evaluated using a cross-result entropy that quantifies a level of similarity between a plurality of the search results, and wherein the search engine is configured to decrease the level-of-quality score based on determining that the cross-result entropy is sufficiently high; comparing the level-of-quality score against a predefined threshold value; and based on the comparison, assigning each of the one or more selected search results an absolute measurement, wherein the absolute measurement indicates good quality when the level-of-quality score is greater than the threshold value, and wherein the absolute measurement indicates poor quality when the level-of-quality score is less than the threshold value; calculating a level of confidence that a rewritten search query will provide new search results that improve the set of search results; automatically rewriting the search query by the search engine to generate the rewritten search query, wherein each key word of the rewritten search query is automatically selected for inclusion in the rewritten search query; and based on the calculated level of confidence indicating that the rewritten search query will provide the new search results that improve the set of search results, and based on identifying that the absolute measurement assigned to at least one of the one or more selected search results indicates the poor quality, automatically conducting a search with the rewritten search query. 2. The media of claim 1 , wherein the set of search results are generated based upon at least one term within the search query. | 0.840852 |
9,117,146 | 9 | 13 | 9. A non-transitory computer-readable medium storing software having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a search query that includes a query image of an object; identifying a training image of the object; identifying a particular sub-region of the training image that a visual object recognition engine indicates as matching the query image; determining, by one or more computers, that the particular sub-region of the training image of the object is located within an annotated sub-region of the training image, wherein the annotated sub-region is associated with an annotation; and in response to determining that the particular sub-region of the training image of the object is located within the annotated sub-region of the training image, providing the annotation for output in response to the search query. | 9. A non-transitory computer-readable medium storing software having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a search query that includes a query image of an object; identifying a training image of the object; identifying a particular sub-region of the training image that a visual object recognition engine indicates as matching the query image; determining, by one or more computers, that the particular sub-region of the training image of the object is located within an annotated sub-region of the training image, wherein the annotated sub-region is associated with an annotation; and in response to determining that the particular sub-region of the training image of the object is located within the annotated sub-region of the training image, providing the annotation for output in response to the search query. 13. The computer-readable medium of claim 9 , wherein determining that the particular sub-region of the training image of the object is located within an annotated sub-region of the training image comprises determining that the particular sub-region of the training image of the object is located within the annotated sub-region in response to determining that a percentage of the particular sub-region of the training image of the object located within the annotated sub-region of the training image meets a threshold. | 0.5 |
9,117,448 | 1 | 6 | 1. An apparatus, comprising: an audio input configured to receive an audio signal representative of a voice input of an associated calling party; the audio input further configured to generate audio data corresponding to the received audio signal; a data interface configured to communicate with one or more associated social graphs, in accordance with an Application Programming Interface (API) corresponding thereto, via an associated internetworking system; and logic coupled with the audio input and the data interface; wherein the logic is configured to identify the calling party and a plurality of social graphs associated with the calling party; wherein the logic is configured to acquire data representative of a called party from the audio data, the data representative of the called party indicating a relationship between the calling party and the called party; wherein the logic converts the data indicating the relationship between the calling party and called party to a form that is compatible with one or more of the plurality of social graphs; wherein the logic initiates a session with the plurality of social graphs in accordance with an identity of the calling party; wherein the logic is configured to initiate, in accordance with a predetermined priority, a prioritized search of the plurality of social graphs associated with the calling party for the data representative of the called party to identify the called party responsive to acquiring the data representative of the called party, wherein the predetermined priority comprises one or more of a time of day, a social characteristic of social graphs of the plurality of social graphs, a business characteristic of social graphs of the plurality of social graphs, a favorite preference of the associated calling party, or a frequency of use by the associated calling party of social graphs of the plurality of social graphs. | 1. An apparatus, comprising: an audio input configured to receive an audio signal representative of a voice input of an associated calling party; the audio input further configured to generate audio data corresponding to the received audio signal; a data interface configured to communicate with one or more associated social graphs, in accordance with an Application Programming Interface (API) corresponding thereto, via an associated internetworking system; and logic coupled with the audio input and the data interface; wherein the logic is configured to identify the calling party and a plurality of social graphs associated with the calling party; wherein the logic is configured to acquire data representative of a called party from the audio data, the data representative of the called party indicating a relationship between the calling party and the called party; wherein the logic converts the data indicating the relationship between the calling party and called party to a form that is compatible with one or more of the plurality of social graphs; wherein the logic initiates a session with the plurality of social graphs in accordance with an identity of the calling party; wherein the logic is configured to initiate, in accordance with a predetermined priority, a prioritized search of the plurality of social graphs associated with the calling party for the data representative of the called party to identify the called party responsive to acquiring the data representative of the called party, wherein the predetermined priority comprises one or more of a time of day, a social characteristic of social graphs of the plurality of social graphs, a business characteristic of social graphs of the plurality of social graphs, a favorite preference of the associated calling party, or a frequency of use by the associated calling party of social graphs of the plurality of social graphs. 6. The apparatus set forth in claim 1 , wherein the logic is further configured to access a database to select a social graph from the plurality of social graphs to search for the data representative of the called party to identify the called party. | 0.63913 |
8,843,364 | 16 | 18 | 16. A method, comprising: for each source of a plurality of sources, generating a plurality of word level models, each word level model corresponding to a respective one word of a plurality of words, each word level model including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components, and probabilities of transition between the dictionaries; for each source, combining the word level models into a single source specific model; and constraining the single source specific models according to high level information that defines valid transitions, the constrained single source specific models being usable to perform source separation on a sound mixture that includes multiple sources. | 16. A method, comprising: for each source of a plurality of sources, generating a plurality of word level models, each word level model corresponding to a respective one word of a plurality of words, each word level model including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components, and probabilities of transition between the dictionaries; for each source, combining the word level models into a single source specific model; and constraining the single source specific models according to high level information that defines valid transitions, the constrained single source specific models being usable to perform source separation on a sound mixture that includes multiple sources. 18. The method of claim 16 , wherein said generating the plurality of word level models includes performing a non-negative hidden Markov technique. | 0.674779 |
8,812,303 | 17 | 18 | 17. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: segment information; determine a language type for the segmented information; search a language dictionary for synonyms of the contents of each information segment in at least one language type; and store the synonyms and contents of each information segment. | 17. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: segment information; determine a language type for the segmented information; search a language dictionary for synonyms of the contents of each information segment in at least one language type; and store the synonyms and contents of each information segment. 18. The non-transitory computer-readable storage medium of claim 17 , wherein the instructions, when executed by the at least one processor, further cause the computing device to: further segment the information into at least one additional segment when contents of the information segment correspond to separate entries in the language dictionary. | 0.5 |
6,163,852 | 10 | 14 | 10. An apparatus for receiving data from a synchronous random access memory, comprising: a data input for receiving a stream of data from the synchronous random access memory, which adheres to the SyncLink interface standard; a data clock input for receiving a data clock signal from the synchronous random access memory for clocking the stream of data; a first memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the first memory register including a plurality of separately-clocked data words; a second memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the second memory register including a plurality of separately-clocked data words; a first system register for receiving data from the first memory register, the first system register being clocked by a system clock signal, which is slower than the data clock signal; a second system register, that is clocked by the system clock signal, for receiving data from the second memory register; and a controller for coordinating actions of the first and second memory registers as well as the first and second system registers so that data is loaded into the second memory register by the data clock signal while data is being loaded into the first system register by the system clock signal and, during alternate cycles, so that data is loaded into the first memory register by the data clock signal while data is being loaded into the second system register by the system clock signal, and wherein the controller is configured to sequentially clock the stream of data into successive words in the plurality of separately-clocked data words in the first memory register and the second memory register. | 10. An apparatus for receiving data from a synchronous random access memory, comprising: a data input for receiving a stream of data from the synchronous random access memory, which adheres to the SyncLink interface standard; a data clock input for receiving a data clock signal from the synchronous random access memory for clocking the stream of data; a first memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the first memory register including a plurality of separately-clocked data words; a second memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the second memory register including a plurality of separately-clocked data words; a first system register for receiving data from the first memory register, the first system register being clocked by a system clock signal, which is slower than the data clock signal; a second system register, that is clocked by the system clock signal, for receiving data from the second memory register; and a controller for coordinating actions of the first and second memory registers as well as the first and second system registers so that data is loaded into the second memory register by the data clock signal while data is being loaded into the first system register by the system clock signal and, during alternate cycles, so that data is loaded into the first memory register by the data clock signal while data is being loaded into the second system register by the system clock signal, and wherein the controller is configured to sequentially clock the stream of data into successive words in the plurality of separately-clocked data words in the first memory register and the second memory register. 14. The apparatus of claim 10, further comprising: a third memory register, that is clocked by the data clock signal, for receiving data from the stream of data; a fourth memory register, that is clocked by the data clock signal, for receiving data from the stream of data; a third system register, that is clocked by the system clock signal, for receiving data from the third memory register; and a fourth system register, that is clocked by the system clock signal, for receiving data from the fourth memory register; wherein the controller is configured to coordinate loading of the first, second, third, and fourth memory registers from the synchronous random access memory using the data clock signal, while the first, second, third and fourth system registers are loaded from the memory registers using the system clock signal, and so that loading of the system registers does not interfere with loading of the memory registers. | 0.5 |
10,073,853 | 13 | 15 | 13. A computer program product for adaptive similarity search resolution in a data deduplication system using a processor device in a computing environment, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: an executable portion that partitions input data into input data chunks, the input data chunks each being at least 4 Megabytes (MB) in size; an executable portion that calculates input similarity elements for an input chunk; an executable portion that uses the input similarity elements to find similar data in a repository of data using a similarity search structure; an executable portion that calculates a resolution level for storing the input similarity elements, the resolution level comprising a number of the input similarity elements in relation to a size of the input chunk; an executable portion that stores the input similarity elements in the calculated resolution level in the similarity search structure; an executable portion that deduplicates the input chunk with the found similar data in the repository of data using the input similarity units in the calculated resolution level; an executable portion that calculates the resolution level for storing the input similarity elements based on calculated sets of similarity element matches and on a calculated deduplication ratio, the deduplication ratio defined as a total size of the input data covered by matches with repository data out of the total size of the input data; and an executable portion that decreases the resolution level of the stored input similarity elements if an aggregated deduplication ratio is not lower than a predefined threshold and an average size of the calculated sets of similarity element matches is not lower than two and a current resolution level is higher than a lowest resolution level. | 13. A computer program product for adaptive similarity search resolution in a data deduplication system using a processor device in a computing environment, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising: an executable portion that partitions input data into input data chunks, the input data chunks each being at least 4 Megabytes (MB) in size; an executable portion that calculates input similarity elements for an input chunk; an executable portion that uses the input similarity elements to find similar data in a repository of data using a similarity search structure; an executable portion that calculates a resolution level for storing the input similarity elements, the resolution level comprising a number of the input similarity elements in relation to a size of the input chunk; an executable portion that stores the input similarity elements in the calculated resolution level in the similarity search structure; an executable portion that deduplicates the input chunk with the found similar data in the repository of data using the input similarity units in the calculated resolution level; an executable portion that calculates the resolution level for storing the input similarity elements based on calculated sets of similarity element matches and on a calculated deduplication ratio, the deduplication ratio defined as a total size of the input data covered by matches with repository data out of the total size of the input data; and an executable portion that decreases the resolution level of the stored input similarity elements if an aggregated deduplication ratio is not lower than a predefined threshold and an average size of the calculated sets of similarity element matches is not lower than two and a current resolution level is higher than a lowest resolution level. 15. The computer program product of claim 13 , further including an executable portion that performs one of: calculating an average size of the calculated sets of similarity element matches, and using the average size to determine the resolution level for storing the input similarity elements. | 0.630653 |
7,912,904 | 21 | 34 | 21. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a server computer system, the one or more programs comprising: instructions for receiving a plurality of messages directed to a user, each message having a unique message identifier; instructions for generating a plurality of conversations, each conversation including a respective conversation identifier and unique subset of the plurality of electronic messages; and instructions for responding to a search request from a client associated with the user, the search request including one or more user-specified query terms, including: instructions for selecting a list of conversations from the plurality of conversations in accordance with the search request, each conversation in the list including at least one electronic message that matches the search request, at least one conversation in the list comprising two or more electronic messages; and instructions for transmitting over a network to the client for display the list of conversations in an order determined in accordance with first predefined criteria, each conversation in the list being represented as a single item in the list of conversations, at least one of the conversations comprising two or more electronic messages, wherein each item representing a conversation having a plurality of messages has an associated icon indicating the number of electronic messages in the conversation. | 21. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a server computer system, the one or more programs comprising: instructions for receiving a plurality of messages directed to a user, each message having a unique message identifier; instructions for generating a plurality of conversations, each conversation including a respective conversation identifier and unique subset of the plurality of electronic messages; and instructions for responding to a search request from a client associated with the user, the search request including one or more user-specified query terms, including: instructions for selecting a list of conversations from the plurality of conversations in accordance with the search request, each conversation in the list including at least one electronic message that matches the search request, at least one conversation in the list comprising two or more electronic messages; and instructions for transmitting over a network to the client for display the list of conversations in an order determined in accordance with first predefined criteria, each conversation in the list being represented as a single item in the list of conversations, at least one of the conversations comprising two or more electronic messages, wherein each item representing a conversation having a plurality of messages has an associated icon indicating the number of electronic messages in the conversation. 34. The computer program product of claim 21 , wherein the single item for a respective conversation in the list includes a subject of the respective conversation and, in addition, a text string from the conversation, the text string having a highlighted instance of at least one of the one or more user-specified query terms. | 0.5 |
9,817,829 | 4 | 5 | 4. The computer-implemented method set forth in claim 1 , wherein a priority of each of the plurality of components is determined for a plurality of time intervals. | 4. The computer-implemented method set forth in claim 1 , wherein a priority of each of the plurality of components is determined for a plurality of time intervals. 5. The computer-implemented method set forth in claim 4 , further comprising storing data indicating a change in priority for at least one component from one time interval to another time interval. | 0.618217 |
7,707,160 | 37 | 41 | 37. The computer system of claim 33 wherein the network is the internet. | 37. The computer system of claim 33 wherein the network is the internet. 41. The computer system of claim 37 wherein online documents correspond to unique names and wherein the factual knowledge associates URLs for downloading the online documents with the unique names in the knowledge base. | 0.5 |
9,483,159 | 1 | 7 | 1. A method comprising: storing reliability data that indicates, for each source of a plurality of sources, a reliability rating of said each source; wherein a first source of the plurality of sources has a first reliability rating that indicates a reliability of the first source, and a second source of the plurality of sources has a second reliability rating that indicates a reliability of the second source and that is different than the first reliability rating; wherein at least one of the first reliability rating or the second reliability rating is based on previous fact checking results; receiving information to be fact checked; selecting at least one of the first source or the second source from among the plurality of sources based on the first reliability rating or the second reliability rating, wherein a difference between the first reliability rating and the second reliability rating indicates that one source is more reliable than the other source; in response to receiving the information to be fact checked, performing a comparison of the information to be fact checked with source information from one or more sources to determine factual accuracy of the information and to generate a fact checking result representative of a factual accuracy of the information, the one or more sources comprising the at least one of the first source or the second source; causing an icon indicative of the fact checking result to be displayed; wherein the method is performed by one or more computing devices. | 1. A method comprising: storing reliability data that indicates, for each source of a plurality of sources, a reliability rating of said each source; wherein a first source of the plurality of sources has a first reliability rating that indicates a reliability of the first source, and a second source of the plurality of sources has a second reliability rating that indicates a reliability of the second source and that is different than the first reliability rating; wherein at least one of the first reliability rating or the second reliability rating is based on previous fact checking results; receiving information to be fact checked; selecting at least one of the first source or the second source from among the plurality of sources based on the first reliability rating or the second reliability rating, wherein a difference between the first reliability rating and the second reliability rating indicates that one source is more reliable than the other source; in response to receiving the information to be fact checked, performing a comparison of the information to be fact checked with source information from one or more sources to determine factual accuracy of the information and to generate a fact checking result representative of a factual accuracy of the information, the one or more sources comprising the at least one of the first source or the second source; causing an icon indicative of the fact checking result to be displayed; wherein the method is performed by one or more computing devices. 7. The method of claim 1 wherein clicking the icon displays the fact checking result as text or audio. | 0.795181 |
9,836,646 | 1 | 7 | 1. A method for selecting character candidates in a method for identifying characters in a digital image, the method comprising the steps of: a) applying a first character identification process to determine first character candidates and a list of segmentation points of the first character candidates, b) generating a list of character widths corresponding to a segmentation point from the list of segmentation points, c) determining a portion of the digital image corresponding to the segmentation point and a character width from the list of character widths, d) applying a character classification method on the portion of the digital image to obtain an ID hypothesis of a character possibly present in the portion of the digital image and a likelihood parameter that relates to a likelihood that the ID hypothesis is correct, and e) selecting the ID hypothesis as a second character candidate in the digital image if the likelihood parameter fulfils a first predetermined criterion. | 1. A method for selecting character candidates in a method for identifying characters in a digital image, the method comprising the steps of: a) applying a first character identification process to determine first character candidates and a list of segmentation points of the first character candidates, b) generating a list of character widths corresponding to a segmentation point from the list of segmentation points, c) determining a portion of the digital image corresponding to the segmentation point and a character width from the list of character widths, d) applying a character classification method on the portion of the digital image to obtain an ID hypothesis of a character possibly present in the portion of the digital image and a likelihood parameter that relates to a likelihood that the ID hypothesis is correct, and e) selecting the ID hypothesis as a second character candidate in the digital image if the likelihood parameter fulfils a first predetermined criterion. 7. A method according to claim 1 , wherein steps c, d and e are repeated for another character width of the list of character widths if the likelihood parameter fulfils the first predetermined criterion and does not fulfil a second predetermined criterion. | 0.753846 |
8,412,515 | 1 | 13 | 1. A computer readable storage medium storing instructions, which, when executed by a computer, perform a method for representing a discourse input, the method comprising: receiving a discourse input; and parsing the discourse input to generate a discourse representation data structure (DRS) that represents entities in the discourse input and linguistic relationships of the entities, the DRS comprising an array of boxes, each box including a set of box elements with associated arguments having markers, wherein the box elements are normalized by deleting unused boxes from the DRS and are initially sorted in a preliminary order based on a box and box element normal form regardless of the markers, and wherein the markers are in a normalized form in the DRS, and the boxes and box elements are sorted based on the preliminary order and based on the marker normal form to obtain the DRS in a normal form, the box elements and associated arguments in the DRS in the normal form including a semantic representation of semantic content of the discourse input. | 1. A computer readable storage medium storing instructions, which, when executed by a computer, perform a method for representing a discourse input, the method comprising: receiving a discourse input; and parsing the discourse input to generate a discourse representation data structure (DRS) that represents entities in the discourse input and linguistic relationships of the entities, the DRS comprising an array of boxes, each box including a set of box elements with associated arguments having markers, wherein the box elements are normalized by deleting unused boxes from the DRS and are initially sorted in a preliminary order based on a box and box element normal form regardless of the markers, and wherein the markers are in a normalized form in the DRS, and the boxes and box elements are sorted based on the preliminary order and based on the marker normal form to obtain the DRS in a normal form, the box elements and associated arguments in the DRS in the normal form including a semantic representation of semantic content of the discourse input. 13. The computer readable storage medium of claim 1 wherein each box element argument comprises: an argument kind field indicative of a kind of the box element argument. | 0.646444 |
8,407,054 | 13 | 14 | 13. A speech synthesis method for a speech synthesis device, the method comprising: performing language processing of input text; selecting a central segment from among a plurality of speech segments based on the language processing result; generating prosody information based on the selected central segment; selecting a non-central segment based on the central segment and the generated prosody information; and generating a synthesized speech waveform based on the central segment, and the non-central segment, wherein generating prosody information of the non-central segment is based on the prosody information of the central segment and the language processing result. | 13. A speech synthesis method for a speech synthesis device, the method comprising: performing language processing of input text; selecting a central segment from among a plurality of speech segments based on the language processing result; generating prosody information based on the selected central segment; selecting a non-central segment based on the central segment and the generated prosody information; and generating a synthesized speech waveform based on the central segment, and the non-central segment, wherein generating prosody information of the non-central segment is based on the prosody information of the central segment and the language processing result. 14. The speech synthesis method according to claim 13 , wherein said selecting the central segment preferentially selects a speech segment having a long segment length as a central segment. | 0.644737 |
10,134,297 | 1 | 8 | 1. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; creating, with the processing system, a word association profile, wherein the word association profile comprises a distribution of association measures for the multiple groups of content words in the document; determining, with the processing system, a complexity for the document based on the word association profile, wherein the document is an essay and the complexity is used to assess a quality of the essay. | 1. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; creating, with the processing system, a word association profile, wherein the word association profile comprises a distribution of association measures for the multiple groups of content words in the document; determining, with the processing system, a complexity for the document based on the word association profile, wherein the document is an essay and the complexity is used to assess a quality of the essay. 8. The method of claim 1 , wherein each group of content words includes only words occurring within a predetermined window of words in the document. | 0.551515 |
9,310,971 | 16 | 17 | 16. A method of displaying document data divided for each page in a document viewing device, said document viewing device including an input device for accepting a user operation, said method comprising the steps of: generating a viewing history of a document by a user based on said user operation performed for a page displayed on a display device; evaluating relevance to an object displayed on said display device and searching for a page relevant to the object displayed on said display device from pages of said document data; determining based on said viewing history whether the relevant page searched is checked or unchecked; generating a shortcut linked to the relevant page searched and determined to be unchecked; and displaying the shortcut together with the displayed object on the display device. | 16. A method of displaying document data divided for each page in a document viewing device, said document viewing device including an input device for accepting a user operation, said method comprising the steps of: generating a viewing history of a document by a user based on said user operation performed for a page displayed on a display device; evaluating relevance to an object displayed on said display device and searching for a page relevant to the object displayed on said display device from pages of said document data; determining based on said viewing history whether the relevant page searched is checked or unchecked; generating a shortcut linked to the relevant page searched and determined to be unchecked; and displaying the shortcut together with the displayed object on the display device. 17. The method according to claim 16 , wherein said step of generating the viewing history includes the step of recording display time as said viewing history for each page displayed on said display device, and the step of determining whether the relevant page searched is checked or unchecked includes the step of comparing said display time with reference time stored in advance for each page of said document, to determine for each said page whether the object is checked or unchecked by said user. | 0.774324 |
8,744,837 | 3 | 4 | 3. The apparatus of claim 1 , wherein the question domain distributor distributes a domain with respect to the user's question based on a law dictionary previously established for each domain or a learning model established by using learning data. | 3. The apparatus of claim 1 , wherein the question domain distributor distributes a domain with respect to the user's question based on a law dictionary previously established for each domain or a learning model established by using learning data. 4. The apparatus of claim 3 , wherein the question domain distributor includes: a language analyzer for analyzing the language of the user's question; a law-based domain distribution block for identifying and distributing a domain for the user's question based on the law dictionary though the language analysis result; a learning model database for storing the learning model established by analyzing the language with respect to the learning data and through mechanical learning of learning quality; and a learning model-based domain distribution block for distributing a domain with respect to the user's question based on the learning model when a domain is not distributed based on the law dictionary. | 0.5 |
8,694,896 | 15 | 17 | 15. A non-transitory computer-readable storage medium having computer-executable instructions that, when executed, cause a server computer to perform operations comprising: determining whether a fictional story concept includes content that meets a predetermined criteria set by a party different than a plurality of collaborators being users supplying the content associated with the fictional story concept over a network; deleting the fictional story concept if the content of the fictional story concept fails to meet the predetermined criteria; if the content of the fictional story concept meets the predetermined criteria, making the fictional story concept available for access to enable the plurality of collaborators to electronically submit competing story content related to an element in the fictional story concept; accepting the received competing story content associated with the fictional story concept from the plurality of collaborators if the received competing story content meets the predetermined criteria; receiving votes over the network from one or more editors in charge of editing a fictional story based on the fictional story concept; and including a story content being part of the competing story content if the received votes indicate that the story content is approved. | 15. A non-transitory computer-readable storage medium having computer-executable instructions that, when executed, cause a server computer to perform operations comprising: determining whether a fictional story concept includes content that meets a predetermined criteria set by a party different than a plurality of collaborators being users supplying the content associated with the fictional story concept over a network; deleting the fictional story concept if the content of the fictional story concept fails to meet the predetermined criteria; if the content of the fictional story concept meets the predetermined criteria, making the fictional story concept available for access to enable the plurality of collaborators to electronically submit competing story content related to an element in the fictional story concept; accepting the received competing story content associated with the fictional story concept from the plurality of collaborators if the received competing story content meets the predetermined criteria; receiving votes over the network from one or more editors in charge of editing a fictional story based on the fictional story concept; and including a story content being part of the competing story content if the received votes indicate that the story content is approved. 17. The non-transitory computer-readable storage medium of claim 15 having computer-executable instructions that, when executed, cause the server computer to determine a reward for one or more of the plurality of collaborators. | 0.691576 |
8,627,442 | 9 | 12 | 9. The article of manufacture of claim 8 , wherein said computer readable program code configured to build said plurality of HTTP message models further comprising computer readable program code configured to develop said plurality of security rules. | 9. The article of manufacture of claim 8 , wherein said computer readable program code configured to build said plurality of HTTP message models further comprising computer readable program code configured to develop said plurality of security rules. 12. The article of manufacture of claim 9 , wherein said computer readable program code configured to build said plurality of HTTP message models comprises computer readable program code configured to build said plurality of HTTP message models in UML. | 0.685786 |
10,157,086 | 29 | 30 | 29. The method of claim 21 , wherein the requesting device is to: operate an input device and a display device to provide a user interface (UI) to enable receipt of commands to edit the visualization; receive the command from the input device to change a visual indication of a dependency in the visualization between two visual representations of task routines in the visualization; and in response to receipt of the command, perform the change specified in the command in the visual indication of a dependency in the visualization as part of the generation of the second DAG from the first DAG to generate the second job flow of the analysis routine from the first job flow of the first analysis routine. | 29. The method of claim 21 , wherein the requesting device is to: operate an input device and a display device to provide a user interface (UI) to enable receipt of commands to edit the visualization; receive the command from the input device to change a visual indication of a dependency in the visualization between two visual representations of task routines in the visualization; and in response to receipt of the command, perform the change specified in the command in the visual indication of a dependency in the visualization as part of the generation of the second DAG from the first DAG to generate the second job flow of the analysis routine from the first job flow of the first analysis routine. 30. The method of claim 29 , comprising: in response to receipt of the second request, retrieving task routine identifiers for all task routines identified in the second DAG and data object identifiers for all data objects identified in the second DAG; using the task routine identifiers retrieved from the second DAG to to make the determination of whether each task routine identified in the second DAG is stored within the at least one federated area or is included in the second request; and using the data object identifiers retrieved from the second DAG to to make the determination of whether each task data object identified in the second DAG is stored within the at least one federated area or is included in the second request. | 0.5 |
9,686,596 | 31 | 32 | 31. The system of claim 17 : wherein the sandboxed application is at least one of a web page, a script, a binary executable, an intermediate bytecode, an abstract syntax tree, and an executable application in the security sandbox, wherein the sandboxed application comprises at least one of a markup language application such as a HyperText Markup Language 5 (HTML5) application, a Javascript® application, an Adobe® Flash® application, a Microsoft® Silverlight® application, a JQuery® application, and an Asynchronous Javascript® and a XML (AJAX) application, and wherein an access control algorithm governs a policy through which a secondary authentication is required when establishing a communication between the sandboxed application and the networked device. | 31. The system of claim 17 : wherein the sandboxed application is at least one of a web page, a script, a binary executable, an intermediate bytecode, an abstract syntax tree, and an executable application in the security sandbox, wherein the sandboxed application comprises at least one of a markup language application such as a HyperText Markup Language 5 (HTML5) application, a Javascript® application, an Adobe® Flash® application, a Microsoft® Silverlight® application, a JQuery® application, and an Asynchronous Javascript® and a XML (AJAX) application, and wherein an access control algorithm governs a policy through which a secondary authentication is required when establishing a communication between the sandboxed application and the networked device. 32. The system of claim 31 , wherein the client device: to utilize an exception to a same origin policy through a use of at least one of a hyperlink, a form, the script, a frame, a header, and an image when establishing the connection between the sandboxed application and the sandbox reachable service. | 0.5 |
8,027,438 | 28 | 31 | 28. A non-transitory computer-readable storage medium storing a computer program for translating electronic messages sent from a first party to a second different party, the computer program, when executed by a computer processor, performing: receiving an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein the electronic message from the first party received at the destination location is translated; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. | 28. A non-transitory computer-readable storage medium storing a computer program for translating electronic messages sent from a first party to a second different party, the computer program, when executed by a computer processor, performing: receiving an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein the electronic message from the first party received at the destination location is translated; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. 31. The non-transitory computer-readable medium of claim 28 , wherein the translating is performed upon the occurrence of at least one of the reception of the electronic message from a particular sender, the reception of the electronic message in a particular language, and the reception of the electronic message in a foreign language. | 0.5 |
10,057,305 | 1 | 7 | 1. One or more computer-readable memories comprising processor-executable instructions which, when executed by one or more processors disposed in a local device, cause the processors to: expose a user interface (UI) on the local device for initiating real-time sharing of content during an active phone call between the local device and a remote device; receive input at a digital assistant instantiated on the local device; parse, at the digital assistant and during the active phone call, the input to identify a selection of content that was referenced in the input from among a collection of shareable content, the collection of shareable content being locally available to the local device or available to the local device from a remote source; receive the selection of content for sharing based on the parsed input; populate a portion of the UI on the local device with pre-staged content selected for sharing but is yet to be shared with the remote device; enable within the portion of the UI, preparation of a presentation of the pre-staged content while preventing the remote device from displaying the pre-staged content; receive an instruction to move the pre-staged content to an active sharing window; move the pre-staged content to the active sharing window that displays the presently shared content while enabling the local device to control pacing of the presentation of content items within the pre-staged content with the remote device; provide highlighting tools on the local device for highlighting portions of the presently shared content in the active sharing window; and provide tools on the local device for creating credits for portions of the presently shared content in the active sharing window, the credits including one or more of animation, identification of shared content that is tagged, links to related content, or links to related user experiences. | 1. One or more computer-readable memories comprising processor-executable instructions which, when executed by one or more processors disposed in a local device, cause the processors to: expose a user interface (UI) on the local device for initiating real-time sharing of content during an active phone call between the local device and a remote device; receive input at a digital assistant instantiated on the local device; parse, at the digital assistant and during the active phone call, the input to identify a selection of content that was referenced in the input from among a collection of shareable content, the collection of shareable content being locally available to the local device or available to the local device from a remote source; receive the selection of content for sharing based on the parsed input; populate a portion of the UI on the local device with pre-staged content selected for sharing but is yet to be shared with the remote device; enable within the portion of the UI, preparation of a presentation of the pre-staged content while preventing the remote device from displaying the pre-staged content; receive an instruction to move the pre-staged content to an active sharing window; move the pre-staged content to the active sharing window that displays the presently shared content while enabling the local device to control pacing of the presentation of content items within the pre-staged content with the remote device; provide highlighting tools on the local device for highlighting portions of the presently shared content in the active sharing window; and provide tools on the local device for creating credits for portions of the presently shared content in the active sharing window, the credits including one or more of animation, identification of shared content that is tagged, links to related content, or links to related user experiences. 7. The one or more computer-readable memories of claim 1 further including instructions that cause the processors to: provide one of telestrating tools or video transport controls when an instance of the presently shared content is video content. | 0.799674 |
8,209,311 | 17 | 20 | 17. A tangible computer-readable medium storing computer instructions, wherein the computer instructions, when executed by a computer system, cause the computer system to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL. | 17. A tangible computer-readable medium storing computer instructions, wherein the computer instructions, when executed by a computer system, cause the computer system to perform a method comprising: receiving a plurality of masks, each mask comprising a string of one or more characters; accessing a list of URLs; for each URL in the list of URLs: identifying any portions of the URL that match the one or more characters in the plurality of masks, and removing from the URL the identified portions to create a resultant URL; and collapsing all identical resultant URLs into one URL. 20. The computer-readable medium of claim 17 , wherein one or more of the URLs are associated with media and include content indicating at least one of an artist of the media, a title of the media, a host of the media, a bit rate of the media, a sampling rate of the media, a linking URL associated with the media, a copyright of the media, and a duration of the media. | 0.545567 |
8,209,333 | 1 | 8 | 1. A computer-implemented method of assessing the suitability of particular key phrases for use in providing contextually-relevant content to users, the method comprising: identifying a key phrase that appears on a page of a site; and generating a score for the key phrase based at least partly on view counts of social media content items associated with the key phrase, said social media content items being accessible to users on one or more social media sites that are separate from said site, said score representing a suitability of the key phrase for selecting contextually relevant content to present on the page, wherein generating the score comprises assessing, based at least partly on the view counts of social media content items, a rate of change in a popularity level of the key phrase; said method performed by a computer system that comprises one or more computers. | 1. A computer-implemented method of assessing the suitability of particular key phrases for use in providing contextually-relevant content to users, the method comprising: identifying a key phrase that appears on a page of a site; and generating a score for the key phrase based at least partly on view counts of social media content items associated with the key phrase, said social media content items being accessible to users on one or more social media sites that are separate from said site, said score representing a suitability of the key phrase for selecting contextually relevant content to present on the page, wherein generating the score comprises assessing, based at least partly on the view counts of social media content items, a rate of change in a popularity level of the key phrase; said method performed by a computer system that comprises one or more computers. 8. The method of claim 1 , further comprising automatically using the score to determine whether to cause an occurrence of the key phrase on the page to be converted into a link for displaying contextually relevant content. | 0.612847 |
8,684,746 | 2 | 4 | 2. The method of claim 1 , further comprising: calculating, in the processor, numerical scores for questions answered correctly by the student at each difficulty; and determining, and storing in the data storage, a placement for the student based, in part, on the numerical scores. | 2. The method of claim 1 , further comprising: calculating, in the processor, numerical scores for questions answered correctly by the student at each difficulty; and determining, and storing in the data storage, a placement for the student based, in part, on the numerical scores. 4. The method of claim 2 , further comprising determining, in the processor, at least one question type threshold is exceeded before determining the student placement. | 0.5 |
9,430,587 | 12 | 13 | 12. The method of claim 11 , wherein the method includes: determining a filtering parameter for filtering thumbnails to be positioned on said map, said filtering parameter included in said user profile; determining whether said thumbnails satisfy the filtering parameter using metadata associated with media objects corresponding to said thumbnails; and filtering said thumbnails based on a determination that said thumbnails correspond to media objects satisfy the filtering parameter, wherein particular ones of said thumbnails satisfying the filtering parameter are positioned on said map, and other particular ones of said thumbnails that do not satisfy the filtering parameter are not positioned on said map. | 12. The method of claim 11 , wherein the method includes: determining a filtering parameter for filtering thumbnails to be positioned on said map, said filtering parameter included in said user profile; determining whether said thumbnails satisfy the filtering parameter using metadata associated with media objects corresponding to said thumbnails; and filtering said thumbnails based on a determination that said thumbnails correspond to media objects satisfy the filtering parameter, wherein particular ones of said thumbnails satisfying the filtering parameter are positioned on said map, and other particular ones of said thumbnails that do not satisfy the filtering parameter are not positioned on said map. 13. The method of claim 12 , wherein said filtering parameter is a time period criterion, wherein particular ones of said thumbnails corresponding to media objects having metadata indicating that the media objects satisfying the time period criterion are positioned on said map, and wherein said other particular ones of said thumbnails corresponding to media objects having metadata indicating that the media objects do not satisfy the time period criterion are not positioned on said map. | 0.504049 |
9,514,116 | 11 | 12 | 11. A method for integrating a gadget with a spreadsheet, comprising: providing an Application Programming Interface (API) for the gadget to communicate with the spreadsheet; receiving a selection of a range of cells of the spreadsheet to bind to the gadget, wherein the selected range of cells comprises one or more cells of the spreadsheet; determining a binding between the selected range of cells of the spreadsheet and the gadget; determining an interaction with the selected range of cells; automatically providing a first notification to the gadget in response to the interaction; receiving a call from the gadget using the API; performing an operation involving the spreadsheet that relates to the received call; after performing the operation, receiving input to change the selected range of cells to adjust the binding to include the changed selected range of cells; and automatically providing a second notification to the gadget in response to the input. | 11. A method for integrating a gadget with a spreadsheet, comprising: providing an Application Programming Interface (API) for the gadget to communicate with the spreadsheet; receiving a selection of a range of cells of the spreadsheet to bind to the gadget, wherein the selected range of cells comprises one or more cells of the spreadsheet; determining a binding between the selected range of cells of the spreadsheet and the gadget; determining an interaction with the selected range of cells; automatically providing a first notification to the gadget in response to the interaction; receiving a call from the gadget using the API; performing an operation involving the spreadsheet that relates to the received call; after performing the operation, receiving input to change the selected range of cells to adjust the binding to include the changed selected range of cells; and automatically providing a second notification to the gadget in response to the input. 12. The method of claim 11 , further comprising in response to providing the first notification to the gadget, performing an action. | 0.668342 |
8,122,033 | 15 | 18 | 15. The computer program product of claim 4 , further comprising program code for: when one or more of the group-by columns of the definition query of the MQT are expanded using functional dependency relationships, creating the first set of columns that includes the group-by columns of the MQT definition query expanded; when one or more of the group-by columns of the incoming query are identified, defining the second set of columns by utilizing the one or more of the group-by columns of the incoming query; when one or more matching columns between the first set and the second set are identified, creating a matched group using the one or more matching columns; when one or more of the group-by columns of the first set that do not belong to the matched group are identified, creating a first unmatched group that comprises the one or more of the group-by columns of the first set that do not belong to the matched group; and when one or more of the group-by columns of the second set that do not belong to the matched group are identified, creating a second unmatched group that comprises the one or more of the group-by columns of the second set that do not belong to the matched group. | 15. The computer program product of claim 4 , further comprising program code for: when one or more of the group-by columns of the definition query of the MQT are expanded using functional dependency relationships, creating the first set of columns that includes the group-by columns of the MQT definition query expanded; when one or more of the group-by columns of the incoming query are identified, defining the second set of columns by utilizing the one or more of the group-by columns of the incoming query; when one or more matching columns between the first set and the second set are identified, creating a matched group using the one or more matching columns; when one or more of the group-by columns of the first set that do not belong to the matched group are identified, creating a first unmatched group that comprises the one or more of the group-by columns of the first set that do not belong to the matched group; and when one or more of the group-by columns of the second set that do not belong to the matched group are identified, creating a second unmatched group that comprises the one or more of the group-by columns of the second set that do not belong to the matched group. 18. The computer program product of claim 15 , further comprising program code for: when the matched group exists and the non-empty first unmatched group and the second unmatched group are identified: (1) determining whether the matched group functionally determines the non-empty first unmatched group and the second unmatched group; and (2) identifying the MQT as a candidate match when (a) the matched group exists and is identified, (b) the matched group functionally determines the non-empty first and second unmatched group(s), and (c) one or more of the qualifying conditions are satisfied; when the matched group does not exist or the matched group exists but does not functionally determine the non-empty first and second unmatched group(s): (1) determining whether the incoming query is based on measures which are exclusively additive; and (2) identifying the MQT as a candidate match when (a) the incoming query is based on measures which are exclusively additive, (b) the number of columns in the first set functionally determines the number of columns in the second set, and (c) one or more of the qualifying conditions are satisfied. | 0.5 |
9,497,153 | 9 | 13 | 9. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify one or more message addressees of an electronic message, the one or more message addressees identifying at least one recipient of the electronic message; identify a segment of the electronic message; determine one or more segment addressees from the at least one recipient, the one or more segment addressees identifying an addressee of the identified segment, wherein the instructions to determine the one or more segment addressees include instructions to: identify at least one noun phrase associated with the segment, determine a coreference resolution for a given noun phrase of the at least one noun phrase, and determine the one or more segment addressees based on the coreference resolution of the given noun phrase; identify a task associated with the segment; associate one or more aspects of the task associated with the segment with the one or more segment addressees; and provide, to the one or more segment addressees, an indication pertaining to the one or more aspects of the task associated with the segment. | 9. A system including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: identify one or more message addressees of an electronic message, the one or more message addressees identifying at least one recipient of the electronic message; identify a segment of the electronic message; determine one or more segment addressees from the at least one recipient, the one or more segment addressees identifying an addressee of the identified segment, wherein the instructions to determine the one or more segment addressees include instructions to: identify at least one noun phrase associated with the segment, determine a coreference resolution for a given noun phrase of the at least one noun phrase, and determine the one or more segment addressees based on the coreference resolution of the given noun phrase; identify a task associated with the segment; associate one or more aspects of the task associated with the segment with the one or more segment addressees; and provide, to the one or more segment addressees, an indication pertaining to the one or more aspects of the task associated with the segment. 13. The system of claim 9 , wherein the instructions to determine the coreference resolution for the given noun phrase include instructions to learn a coreference embedding for the given noun phrase. | 0.728142 |
9,626,348 | 1 | 2 | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. | 1. A method, comprising: receiving, from a plurality of different computing devices and over a respective plurality of network connections, a plurality of data packets, wherein the plurality of different computing devices are operated by a plurality of different users, wherein each data packet in the plurality of data packets comprises: an annotation that has been assigned to a document by a respective user, wherein the annotation is a tuple that comprises a first word or phrase extracted from the document, a second word or phrase extracted from the document, and a third word or phrase extracted from the document, wherein the third word or phrase relates the first word or phrase to the second word or phrase; and relationship data that indicates that the annotation has been assigned to the document, wherein each data packet comprises a different annotation, and each data packet in the plurality of data packets has a same format; aggregating the plurality of data packets in a data repository to form a network of knowledge, wherein the data repository is accessible to a processor; and utilizing the processor to perform at least one processing function over at least one data packet in the data repository. 2. The method of claim 1 , wherein the first word or phrase in the tuple is a subject of a parent phrase in the document, the second word or phrase in the tuple is an object of the parent phrase, and the third word or phrase in the tuple is a predicate that relates the subject with the object. | 0.5 |
8,301,437 | 1 | 8 | 1. A method for tokenizing a character string, comprising: (a) determining if there are any words or phrases in a dictionary that match a series of characters within the character string that begins at the first character of the character string, wherein the character string comprises a non-delimited character string; (b) for each matching word or phrase identified in step (a), assigning the matching word or phrase to a tokenization path, wherein the tokenization path comprises one or more contiguous words or phrases embedded within the character string, and removing a corresponding series of characters from the beginning of the character string, thereby generating a shortened character string associated with the tokenization path or terminating the tokenization path; (c) if no matching word or phrase is identified in step (a), then terminating any tokenization path with which the character string is associated; (d) recursively performing steps (a), (b) and (c) for any shortened character string generated in step (b) until all tokenization paths are terminated; (e) for any tokenization path formed through the performance of steps (a)-(d), calculating a score based on each word or phrase assigned to the tokenization path; and (f) selecting the word(s) and/or phrase(s) associated with a tokenization path having the highest score as tokens associated the character string. | 1. A method for tokenizing a character string, comprising: (a) determining if there are any words or phrases in a dictionary that match a series of characters within the character string that begins at the first character of the character string, wherein the character string comprises a non-delimited character string; (b) for each matching word or phrase identified in step (a), assigning the matching word or phrase to a tokenization path, wherein the tokenization path comprises one or more contiguous words or phrases embedded within the character string, and removing a corresponding series of characters from the beginning of the character string, thereby generating a shortened character string associated with the tokenization path or terminating the tokenization path; (c) if no matching word or phrase is identified in step (a), then terminating any tokenization path with which the character string is associated; (d) recursively performing steps (a), (b) and (c) for any shortened character string generated in step (b) until all tokenization paths are terminated; (e) for any tokenization path formed through the performance of steps (a)-(d), calculating a score based on each word or phrase assigned to the tokenization path; and (f) selecting the word(s) and/or phrase(s) associated with a tokenization path having the highest score as tokens associated the character string. 8. The method of claim 1 , further comprising isolating the character string by performing a tokenization process on an original character string that includes the character string, the tokenization processing comprising: (i) identifying one or more first tokens within the original character string based on any delimiters identified in the original character string; (ii) identifying one or more second tokens within each of the one or more first tokens based on any capital letters identified in each of the one or more first tokens; and (iii) selectively identifying one or more third tokens within each of the one or more second tokens based on alphabetic and numeric character combinations present in each of the one or more second tokens. | 0.5 |
8,490,018 | 16 | 17 | 16. A non-transitory computer-readable storage medium with an executable program for prioritizing choices for selection by a user stored thereon, wherein the program instructs a processor to perform: identifying a current context of a computer program; determining at least one related context that forms a hierarchical relationship with said current context; determining whether there are related contexts that form an association relationship with said current context, where the association relationship is a predetermined relationship established between contexts that is independent from the hierarchical relationship; determining a user history of weighted menu choice selections with respect to said current context, each weight corresponding to the relative likelihood of the associated menu choice selection being selected by a user; receiving an indication that a user has made a menu choice selection based upon said weighted menu choice selections of said user history associated with said current context; updating said user history of said current context by updating said weight associated with said user's menu choice selection; updating an associated user history of related contexts within said hierarchical relationship in which the selected user's menu choice also exists, by updating a weight associated with said user's menu choice selection in that user history by a predetermined value, wherein the value is based upon a distance from said current context within said hierarchical relationship; updating an associated user history of each related context that forms an association relationship with said current context in which the selected user's menu choice also exists by updating a weight associated with said user's menu choice selection in that user history; identifying, by a computing device, a second context of said computer program where the second context is set to the current context; determining weighted menu choices for said second context of said computer program based on said user history; and creating for presentation, a list of said weighted menu choices for selection by said user in said second context. | 16. A non-transitory computer-readable storage medium with an executable program for prioritizing choices for selection by a user stored thereon, wherein the program instructs a processor to perform: identifying a current context of a computer program; determining at least one related context that forms a hierarchical relationship with said current context; determining whether there are related contexts that form an association relationship with said current context, where the association relationship is a predetermined relationship established between contexts that is independent from the hierarchical relationship; determining a user history of weighted menu choice selections with respect to said current context, each weight corresponding to the relative likelihood of the associated menu choice selection being selected by a user; receiving an indication that a user has made a menu choice selection based upon said weighted menu choice selections of said user history associated with said current context; updating said user history of said current context by updating said weight associated with said user's menu choice selection; updating an associated user history of related contexts within said hierarchical relationship in which the selected user's menu choice also exists, by updating a weight associated with said user's menu choice selection in that user history by a predetermined value, wherein the value is based upon a distance from said current context within said hierarchical relationship; updating an associated user history of each related context that forms an association relationship with said current context in which the selected user's menu choice also exists by updating a weight associated with said user's menu choice selection in that user history; identifying, by a computing device, a second context of said computer program where the second context is set to the current context; determining weighted menu choices for said second context of said computer program based on said user history; and creating for presentation, a list of said weighted menu choices for selection by said user in said second context. 17. The non-transitory computer-readable storage medium according to claim 16 , wherein the program further instructs the processor to perform filtering said weighted menu choices to select a smaller number of weighted menu choices for the list of said weighted menu choices. | 0.757067 |
8,648,878 | 13 | 14 | 13. The computing device of claim 10 , wherein the group is a container and each shape within the container includes a member state from a set of: an interior state designating a shape as having an interior spatial relationship with the container; an on boundary state designating a shape as being placed on an edge of the container, wherein the shape having on boundary state are processed to remain in on boundary state; and an outside state designating a shape as being spatially outside the container. | 13. The computing device of claim 10 , wherein the group is a container and each shape within the container includes a member state from a set of: an interior state designating a shape as having an interior spatial relationship with the container; an on boundary state designating a shape as being placed on an edge of the container, wherein the shape having on boundary state are processed to remain in on boundary state; and an outside state designating a shape as being spatially outside the container. 14. The computing device of claim 13 , wherein the container is resized in response to a shape within the container being moved, and wherein an on boundary shape retains its state in response to the container being resized. | 0.5 |
8,457,949 | 1 | 4 | 1. A method for controlling a cartridge of a welding helmet, the method comprising: sequentially performing a welding step, a cutting step, a grinding step, and an X-mode step automatically according to a preset condition, a shade level of an LCD screen, and an operating time of the cartridge, wherein the cartridge includes the LCD screen, a display unit, a controller, and a memory; calculating, by the controller, a work time during which the LCD screen of the cartridge is darkened and storing the calculated work time in the memory and displaying the stored work time on the display unit when entering a life mode entrance step, and storing data of an operating state in multiple preset languages in the memory and displaying data of the operating state in one language, which the controller has selected from among the multiple preset languages, on the display unit, wherein the cartridge further includes a voice recognition unit for recognizing voice of a user, and wherein the controller determines a language recognized by the voice recognition unit and selects data of an operating state of the recognized language stored in the memory and displays the data of the operating state of the recognized language on the display unit. | 1. A method for controlling a cartridge of a welding helmet, the method comprising: sequentially performing a welding step, a cutting step, a grinding step, and an X-mode step automatically according to a preset condition, a shade level of an LCD screen, and an operating time of the cartridge, wherein the cartridge includes the LCD screen, a display unit, a controller, and a memory; calculating, by the controller, a work time during which the LCD screen of the cartridge is darkened and storing the calculated work time in the memory and displaying the stored work time on the display unit when entering a life mode entrance step, and storing data of an operating state in multiple preset languages in the memory and displaying data of the operating state in one language, which the controller has selected from among the multiple preset languages, on the display unit, wherein the cartridge further includes a voice recognition unit for recognizing voice of a user, and wherein the controller determines a language recognized by the voice recognition unit and selects data of an operating state of the recognized language stored in the memory and displays the data of the operating state of the recognized language on the display unit. 4. The method according to claim 1 , wherein a language of information to be read and displayed from the memory, which stores information in at least one language, is selected and set. | 0.901075 |
7,962,925 | 1 | 18 | 1. A system for data binding, comprising: a microprocessor; a schema object model, wherein the schema object model is an object oriented programming language object model that directly models a schema that includes one or more schema definition language types based on a schema definition language, and wherein the schema object model allows manipulation of schema documents in the schema definition language, wherein the schema object model programmatically creates at least one new schema definition language type in the schema based on the one or more schema definition language types pre-defined in the schema definition language, wherein the at least one new schema definition language type is not pre-defined in the schema definition language, and wherein the schema object model supports a pool of empty object trees that are ready to be filled with one or more object oriented programming language objects based on the schema; a schema compiler adapted to accept the schema associated with an Extensible Markup Language (XML) document and generate a set of interfaces that map the one or more schema definition language types of the schema into object-oriented programming language classes using the schema object model with the pool of empty object trees; and an Application Programming Interface (API) to map between the XML document and the object-oriented programming language classes based on at least one empty object tree from the pool of empty object trees. | 1. A system for data binding, comprising: a microprocessor; a schema object model, wherein the schema object model is an object oriented programming language object model that directly models a schema that includes one or more schema definition language types based on a schema definition language, and wherein the schema object model allows manipulation of schema documents in the schema definition language, wherein the schema object model programmatically creates at least one new schema definition language type in the schema based on the one or more schema definition language types pre-defined in the schema definition language, wherein the at least one new schema definition language type is not pre-defined in the schema definition language, and wherein the schema object model supports a pool of empty object trees that are ready to be filled with one or more object oriented programming language objects based on the schema; a schema compiler adapted to accept the schema associated with an Extensible Markup Language (XML) document and generate a set of interfaces that map the one or more schema definition language types of the schema into object-oriented programming language classes using the schema object model with the pool of empty object trees; and an Application Programming Interface (API) to map between the XML document and the object-oriented programming language classes based on at least one empty object tree from the pool of empty object trees. 18. A system according to claim 1 , further comprising a XML Schema Definition (XSD) instance writer adapted to use a type mapping directory and prefilled data structures to output XML when given an object tree. | 0.674383 |
8,904,283 | 1 | 5 | 1. An Advanced Function Presentation (AFP) system configured to generate an AFP document for output, the system comprising: an AFP application generator configured to add an AFP component to the AFP document, and to identify a meta-data object (MDO) for the AFP component; wherein the AFP application generator is further configured to insert a Map Data Resource (MDR) structured field corresponding to the AFP component into the AFP document, wherein the MDR specifies the name of the MDO associating the MDO with a specified scope of objects in the AFP component and further includes a processing mode field indicating whether the MDO is descriptive and does not affect the presentation of the AFP component on an output device or indicating whether the MDO is operational and does affect the presentation of the AFP component on the output device; and an output device configured to determine that the processing mode field, wherein if the MDO is descriptive, then the MDO is ignored, and if the MDO is operational, then at least one of the following is performed: masking a presentation of the AFP component; eliminating a presentation of the AFP component; and partially presenting the AFP component on the output device based on the determination. | 1. An Advanced Function Presentation (AFP) system configured to generate an AFP document for output, the system comprising: an AFP application generator configured to add an AFP component to the AFP document, and to identify a meta-data object (MDO) for the AFP component; wherein the AFP application generator is further configured to insert a Map Data Resource (MDR) structured field corresponding to the AFP component into the AFP document, wherein the MDR specifies the name of the MDO associating the MDO with a specified scope of objects in the AFP component and further includes a processing mode field indicating whether the MDO is descriptive and does not affect the presentation of the AFP component on an output device or indicating whether the MDO is operational and does affect the presentation of the AFP component on the output device; and an output device configured to determine that the processing mode field, wherein if the MDO is descriptive, then the MDO is ignored, and if the MDO is operational, then at least one of the following is performed: masking a presentation of the AFP component; eliminating a presentation of the AFP component; and partially presenting the AFP component on the output device based on the determination. 5. The AFP system of claim 1 wherein the output device is further configured to mask a presentation of the AFP component on the output device based on the determination. | 0.543243 |
5,379,366 | 1 | 2 | 1. A method for representing information in a computer system, comprising the steps of: establishing in said computer system a knowledge representation database made up of individual records, wherein each record is associated with a unique reference number (URN) which identifies each record and wherein each record stores at least one relationship comprised of a characterization and a value, the characterization of said relationship being a URN of a second record which defines [the]a nature of said relationship, and the value of said relationship being a complex data representation composed of at least one internal value, external value, or mixed value which define an object of said relationship, internal values storing only URNs of other records, external values storing external data such as character strings, integers, and real numbers, and mixed values storing a combination of internal and external values; establishing an index to said knowledge representation database made up of the name of each record together with the associated URN of said record, wherein the name of the record is an external value of a relationship stored therein which designates that external value as a character string description of a concept represented by said record; establishing, for each record in said knowledge representation database, fundamental relationships between said record and other records in said database, said fundamental relationships being comprised of intrastratum relationships which store URNs of other records on the same strata or level of abstraction designated as separate libraries within the knowledge representation system, said intrastratum relationships being designated as parent and children relationships which identify the record in which said parent and children relationships are stored as a member of the same library as the records identified by the URNs stored in said intrastratum relationships, and interstrata relationships which store URNs of other records in different strata or libraries, said interstrata relationships being designated as Type record relationships which identify the record in which said Type record relationships are stored as a particular instance of records in another stratum or library; designating certain records as system concepts by storing the URNs of said certain records in a system concept index to said database reserved for records which represent system concepts of said knowledge representation database, system concept records being records which are used as termination points of networks of said fundamental relationships and which are recognized by the system by determining whether the URN or the name of a particular record is in said system concept index, wherein system concept records designating strata or libraries (such as System library, Attribute library, Component library, and Project library) are the termination of parent fundamental relationships, system concept records designating attribute classes (such as Assignment, Connection, Non-Binding, Rules, and External) are the termination of parent fundamental relationships for records which are descendants thereof and which store the URN of the Attribute library system concept as a parent relationship, and system concept records designating attribute properties (such as Name, Data Type, Field Length, and Prompt) are the termination of relationship characterization networks, said system concepts being required to store only fundamental relationships; storing within each record comprising said Attribute library at least one relationship which is characterized by a URN of an attribute property system concept record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said attribute property System record URN is stored; storing within each record comprising said Component library at least one relationship which is characterized by a URN of an Attribute library record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said Attribute library record URN is stored; storing within each record comprising said Project library at least one relationship which is characterized by a URN of a Component library record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said Component library record URN is stored; establishing in said computer system at least one editor for modifying the records and relationships stored in said database, including means for recognizing patterns in the relationships stored in said records; storing said recognized patterns as relationships in the records associated with the recognized patterns; establishing an additional class of system concept records to identify relationships storing values that define said recognized patterns, wherein each of said additional class system concept records represent particular types of patterns in said relationships; operating on said stored patterns in the operation of said at least one editor by reading relationships storing patterns predetermined to be relevant to said at least one editor and using the values of said relationships in limiting the operation of said editor, said relationships storing patterns relevant to said editor being identified by the characterization of said relationships as system concepts identified by the system as being relevant to said editor; establishing in said computer a descriptive database for describing an active concept record designated by a user, comprised of a plurality of records each of which stores a single relationship having an associated URN for said active concept record, and an associated URN for a source record in which said relationship is stored, the URN for said active concept being the URN of the record in said knowledge representation database for which the description in the descriptive database is assembled, and the URN for said source record being the URN of that record in said knowledge representation database in which said relationship is stored; reading a descriptive network for said active concept by reading all records in said knowledge representation database forming a network of related records through the fundamental relationships of parent and type, combining the relationship lists from said read records, and storing said relationships from said read records in said descriptive database, said relationship lists being combined by applying Taxonomy, Type, Composition and User inheritance rules, said relationships being stored in said descriptive database together with the URN of said active concept and the URN of said source record; selecting a view, class and type of display for said active concept and deriving the selected type of display by assigning icons to the records representing concepts in said descriptive database according to the type of display selected, organizing and locating said icons in a display space of said computer according to the selected class, and creating connection icons for interconnections between concept icons located in said display space according to the selected view; and interacting with said knowledge representation database through interaction with said icons in said display space and evaluation of said icon interaction through the use of decision trees for evaluation of the view, command history, system flags, and icon association for identification of appropriate responses to said icon interaction. | 1. A method for representing information in a computer system, comprising the steps of: establishing in said computer system a knowledge representation database made up of individual records, wherein each record is associated with a unique reference number (URN) which identifies each record and wherein each record stores at least one relationship comprised of a characterization and a value, the characterization of said relationship being a URN of a second record which defines [the]a nature of said relationship, and the value of said relationship being a complex data representation composed of at least one internal value, external value, or mixed value which define an object of said relationship, internal values storing only URNs of other records, external values storing external data such as character strings, integers, and real numbers, and mixed values storing a combination of internal and external values; establishing an index to said knowledge representation database made up of the name of each record together with the associated URN of said record, wherein the name of the record is an external value of a relationship stored therein which designates that external value as a character string description of a concept represented by said record; establishing, for each record in said knowledge representation database, fundamental relationships between said record and other records in said database, said fundamental relationships being comprised of intrastratum relationships which store URNs of other records on the same strata or level of abstraction designated as separate libraries within the knowledge representation system, said intrastratum relationships being designated as parent and children relationships which identify the record in which said parent and children relationships are stored as a member of the same library as the records identified by the URNs stored in said intrastratum relationships, and interstrata relationships which store URNs of other records in different strata or libraries, said interstrata relationships being designated as Type record relationships which identify the record in which said Type record relationships are stored as a particular instance of records in another stratum or library; designating certain records as system concepts by storing the URNs of said certain records in a system concept index to said database reserved for records which represent system concepts of said knowledge representation database, system concept records being records which are used as termination points of networks of said fundamental relationships and which are recognized by the system by determining whether the URN or the name of a particular record is in said system concept index, wherein system concept records designating strata or libraries (such as System library, Attribute library, Component library, and Project library) are the termination of parent fundamental relationships, system concept records designating attribute classes (such as Assignment, Connection, Non-Binding, Rules, and External) are the termination of parent fundamental relationships for records which are descendants thereof and which store the URN of the Attribute library system concept as a parent relationship, and system concept records designating attribute properties (such as Name, Data Type, Field Length, and Prompt) are the termination of relationship characterization networks, said system concepts being required to store only fundamental relationships; storing within each record comprising said Attribute library at least one relationship which is characterized by a URN of an attribute property system concept record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said attribute property System record URN is stored; storing within each record comprising said Component library at least one relationship which is characterized by a URN of an Attribute library record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said Attribute library record URN is stored; storing within each record comprising said Project library at least one relationship which is characterized by a URN of a Component library record, wherein said at least one relationship stores the value of the name of the concept represented by the record in which said Component library record URN is stored; establishing in said computer system at least one editor for modifying the records and relationships stored in said database, including means for recognizing patterns in the relationships stored in said records; storing said recognized patterns as relationships in the records associated with the recognized patterns; establishing an additional class of system concept records to identify relationships storing values that define said recognized patterns, wherein each of said additional class system concept records represent particular types of patterns in said relationships; operating on said stored patterns in the operation of said at least one editor by reading relationships storing patterns predetermined to be relevant to said at least one editor and using the values of said relationships in limiting the operation of said editor, said relationships storing patterns relevant to said editor being identified by the characterization of said relationships as system concepts identified by the system as being relevant to said editor; establishing in said computer a descriptive database for describing an active concept record designated by a user, comprised of a plurality of records each of which stores a single relationship having an associated URN for said active concept record, and an associated URN for a source record in which said relationship is stored, the URN for said active concept being the URN of the record in said knowledge representation database for which the description in the descriptive database is assembled, and the URN for said source record being the URN of that record in said knowledge representation database in which said relationship is stored; reading a descriptive network for said active concept by reading all records in said knowledge representation database forming a network of related records through the fundamental relationships of parent and type, combining the relationship lists from said read records, and storing said relationships from said read records in said descriptive database, said relationship lists being combined by applying Taxonomy, Type, Composition and User inheritance rules, said relationships being stored in said descriptive database together with the URN of said active concept and the URN of said source record; selecting a view, class and type of display for said active concept and deriving the selected type of display by assigning icons to the records representing concepts in said descriptive database according to the type of display selected, organizing and locating said icons in a display space of said computer according to the selected class, and creating connection icons for interconnections between concept icons located in said display space according to the selected view; and interacting with said knowledge representation database through interaction with said icons in said display space and evaluation of said icon interaction through the use of decision trees for evaluation of the view, command history, system flags, and icon association for identification of appropriate responses to said icon interaction. 2. The method for representing information in a computer system according to claim 1, further comprising the step of establishing at least one optional user relationship in the knowledge representation database by specifying a user defined Attribute other than a system concept, and storing said user defined Attribute as a record in said knowledge representation database, wherein the URN of said user defined Attribute is stored in records having said user defined Attribute as the characterization of a relationship stored therein. | 0.632231 |
9,002,943 | 4 | 5 | 4. A computer-implemented method comprising: receiving, by a gateway server from a mobile device, a first request to retrieve content from a content server, the request identifying a subscriber using a mobile device, the mobile device, the gateway server, and the content server all being remote and separate from each other; associating, by the gateway server, the identified subscriber with a corresponding user profile, the user profile providing a plurality of rules that define how content is to be displayed; transmitting, by the gateway server to the content server, a second request to retrieve the content from the content server; receiving, by the gateway server, the content from the content server; parsing the content by: deconstructing the content and mapping the deconstructed content to a first document object model, and transforming the mapped content according to the plurality of rules defined in the user profile to generate a second document object model; and transmitting, by the gateway server to the mobile device, the transformed content for rendering on the mobile device. | 4. A computer-implemented method comprising: receiving, by a gateway server from a mobile device, a first request to retrieve content from a content server, the request identifying a subscriber using a mobile device, the mobile device, the gateway server, and the content server all being remote and separate from each other; associating, by the gateway server, the identified subscriber with a corresponding user profile, the user profile providing a plurality of rules that define how content is to be displayed; transmitting, by the gateway server to the content server, a second request to retrieve the content from the content server; receiving, by the gateway server, the content from the content server; parsing the content by: deconstructing the content and mapping the deconstructed content to a first document object model, and transforming the mapped content according to the plurality of rules defined in the user profile to generate a second document object model; and transmitting, by the gateway server to the mobile device, the transformed content for rendering on the mobile device. 5. A method as in claim 4 , wherein the parsing is performed by the gateway server. | 0.935858 |
8,005,816 | 1 | 6 | 1. A method of automatically generating suggested links in a search system, the method comprising: initiating a first crawl across an enterprise corpus owned by an enterprise; discovering during the first crawl a link pointing to a data source, the data source being mis-characterized during the first crawl as outside a boundary of the enterprise corpus owned by the enterprise; automatically storing the link as a first suggested link with other suggested links in a memory; initiating a second crawl across the enterprise corpus after the automatically storing, the second crawl having a different seed uniform resource locator (URL) or different boundary rules than the first crawl; encountering during the second crawl the data source actually within the same boundary of the enterprise corpus; removing, using a processor operatively coupled to the memory, the first suggested link from the other suggested links based on encountering the data source, previously characterized as outside the boundary of the enterprise corpus, within the same boundary of the enterprise corpus during the second crawl; and determining relevancy scoring for the other suggested links. | 1. A method of automatically generating suggested links in a search system, the method comprising: initiating a first crawl across an enterprise corpus owned by an enterprise; discovering during the first crawl a link pointing to a data source, the data source being mis-characterized during the first crawl as outside a boundary of the enterprise corpus owned by the enterprise; automatically storing the link as a first suggested link with other suggested links in a memory; initiating a second crawl across the enterprise corpus after the automatically storing, the second crawl having a different seed uniform resource locator (URL) or different boundary rules than the first crawl; encountering during the second crawl the data source actually within the same boundary of the enterprise corpus; removing, using a processor operatively coupled to the memory, the first suggested link from the other suggested links based on encountering the data source, previously characterized as outside the boundary of the enterprise corpus, within the same boundary of the enterprise corpus during the second crawl; and determining relevancy scoring for the other suggested links. 6. A method according to claim 1 , further comprising: auto-generating keywords for the suggested links. | 0.751196 |
7,735,621 | 73 | 74 | 73. The device of claim 69 wherein the particular currency bill parameter comprises currency bill orientation. | 73. The device of claim 69 wherein the particular currency bill parameter comprises currency bill orientation. 74. The device of claim 73 wherein the particular currency bill parameter comprises forward/reverse orientation. | 0.5 |
4,837,737 | 2 | 3 | 2. An apparatus according to claim 1, wherein said input means comprises a keyboard including character keys for entering the selection commands and function keys. | 2. An apparatus according to claim 1, wherein said input means comprises a keyboard including character keys for entering the selection commands and function keys. 3. An apparatus according to claim 2, wherein said conversion means comprises a memory for storing a set of modified characters, and a conversion key provided on said keyboard for entering a conversion command in response to which said at least one character in the text information stored in said second memory is replaced by at least one modified character. | 0.5 |
10,120,933 | 4 | 5 | 4. The method of claim 2 , wherein the partitioning further comprising: generating a plurality of data clusters, each data cluster including at least one semantic class of the plurality of semantic classes, and wherein substantially similar data elements are assigned to a data cluster, and the plurality of semantic classes correspond to respective blades of the blades of the graded vector space. | 4. The method of claim 2 , wherein the partitioning further comprising: generating a plurality of data clusters, each data cluster including at least one semantic class of the plurality of semantic classes, and wherein substantially similar data elements are assigned to a data cluster, and the plurality of semantic classes correspond to respective blades of the blades of the graded vector space. 5. The method of claim 4 , wherein each semantic class belonging to a data cluster of the plurality of data clusters corresponds to a blade of the blades, which is a heterogeneous space formed by the plurality of data clusters. | 0.5 |
7,805,710 | 1 | 14 | 1. A method of translating a subject code executable by a subject computing architecture into a target code executable by a second computing architecture, wherein the subject code includes at least a first program and a second program, comprising: providing a first translator instance which translates the subject code of the first program into the target code including translating a first portion of the subject code into a portion of the target code; caching said portion of the target code into a shared code cache facility; providing a second translator instance which is different from the first translator instance and which translates the subject code of the second program into the target code, wherein the second translator instance operates simultaneously with the first translator instance; retrieving the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance. | 1. A method of translating a subject code executable by a subject computing architecture into a target code executable by a second computing architecture, wherein the subject code includes at least a first program and a second program, comprising: providing a first translator instance which translates the subject code of the first program into the target code including translating a first portion of the subject code into a portion of the target code; caching said portion of the target code into a shared code cache facility; providing a second translator instance which is different from the first translator instance and which translates the subject code of the second program into the target code, wherein the second translator instance operates simultaneously with the first translator instance; retrieving the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance. 14. The method of claim 1 wherein the portion of target code cached comprises all code blocks corresponding to the same starting subject address. | 0.793447 |
8,874,495 | 12 | 13 | 12. The computing system of claim 9 where the inference data source logic creates a source table adapted for parallel inference by mapping triple component identifiers for the triples associated with the semantic model to a set of compact identifiers that require less storage space than a triple component identifier in the set of triples that requires the most storage space and storing the compact identifiers in the source table. | 12. The computing system of claim 9 where the inference data source logic creates a source table adapted for parallel inference by mapping triple component identifiers for the triples associated with the semantic model to a set of compact identifiers that require less storage space than a triple component identifier in the set of triples that requires the most storage space and storing the compact identifiers in the source table. 13. The computing system of claim 12 where inference data source logic sequentially maps the triple component identifiers to a compact identifier comprising a unique integer value. | 0.673913 |
9,626,968 | 15 | 20 | 15. A processing system comprising: processing circuitry; and a memory device in communication with the processing circuitry, the memory device having computer-executable instructions stored thereon that, when executed by the processing circuitry, instruct the processing circuitry to: receive a portion of a speech record from an audio source, the speech record having been produced by the audio source and transferred to the processing circuitry; determine, from metadata accompanying the portion of the speech record, a first context and a second context for the portion of the speech record, wherein the first context has a first probability of correct context and the second context has a second probability of correct context; process the portion of the speech record to create a first text translation for the portion of the speech record in the first context, wherein the first text translation has a first probability of correct translation within the first context; process the same portion of the speech record to create a second text translation for the portion of the speech record in the second context, wherein the second text translation has a second probability of correct translation within the second context; process the first probability of correct translation and the first probability of correct context, to produce a first probability; process the second probability of correct translation within the second context and the second probability of correct context, to produce a second probability; select the first translation as the correct translation when the first probability is greater than the second probability; and select the second translation as the correct translation when the second probability is greater than the first probability. | 15. A processing system comprising: processing circuitry; and a memory device in communication with the processing circuitry, the memory device having computer-executable instructions stored thereon that, when executed by the processing circuitry, instruct the processing circuitry to: receive a portion of a speech record from an audio source, the speech record having been produced by the audio source and transferred to the processing circuitry; determine, from metadata accompanying the portion of the speech record, a first context and a second context for the portion of the speech record, wherein the first context has a first probability of correct context and the second context has a second probability of correct context; process the portion of the speech record to create a first text translation for the portion of the speech record in the first context, wherein the first text translation has a first probability of correct translation within the first context; process the same portion of the speech record to create a second text translation for the portion of the speech record in the second context, wherein the second text translation has a second probability of correct translation within the second context; process the first probability of correct translation and the first probability of correct context, to produce a first probability; process the second probability of correct translation within the second context and the second probability of correct context, to produce a second probability; select the first translation as the correct translation when the first probability is greater than the second probability; and select the second translation as the correct translation when the second probability is greater than the first probability. 20. The processing system of claim 15 , wherein the portion of the speech record is a portion of a conversation and the context for the portion of the speech record is a position of the portion of the speech record within the conversation. | 0.5 |
10,102,772 | 11 | 12 | 11. A method of enabling communication by complementary users of a language learning exchange, the method comprising: by at least one processor, executing programming instructions that cause the at least one processor to: identify a first user in a user community of a language learning platform; identify, for the first user, associated profile information comprising a native language and a language of interest; use the profile information to automatically identify a complementary user in the user community who has (i) a native language that matches the language of interest of the first user, and (ii) a language of interest that matches the native language of the first user; cause a first local computing device of the first user and a second local computing device of the complementary user to each output a learning exchange interface through which the first user and the complementary user may communicate in the language learning exchange; receive a source, a category, or a topic from the first user or the complementary user via a topic profile interface of that user's learning exchange interface; retrieve, from a set of language learning content, content that corresponds to the received source, category or topic; and cause the language learning interfaces to present the retrieved content to the first user and the complementary user in either of the languages. | 11. A method of enabling communication by complementary users of a language learning exchange, the method comprising: by at least one processor, executing programming instructions that cause the at least one processor to: identify a first user in a user community of a language learning platform; identify, for the first user, associated profile information comprising a native language and a language of interest; use the profile information to automatically identify a complementary user in the user community who has (i) a native language that matches the language of interest of the first user, and (ii) a language of interest that matches the native language of the first user; cause a first local computing device of the first user and a second local computing device of the complementary user to each output a learning exchange interface through which the first user and the complementary user may communicate in the language learning exchange; receive a source, a category, or a topic from the first user or the complementary user via a topic profile interface of that user's learning exchange interface; retrieve, from a set of language learning content, content that corresponds to the received source, category or topic; and cause the language learning interfaces to present the retrieved content to the first user and the complementary user in either of the languages. 12. The method of claim 11 : further comprising receiving, by the at least one processor from the first user or the complementary user, user generated content; wherein retrieving the content that corresponds to the received source, category or topic comprises retrieving the user generated content. | 0.786533 |
9,338,226 | 5 | 6 | 5. A computer implemented method executed on a computing device to perform Big Data processing in a system with actor oriented platform, the method comprises: establishing an actor network with a plurality of actors and connecting the actor network to a cloud server in a cloud network; establishing a distributed virtual machine (DVM) network with a plurality of DVMs and connecting the DVM network to the actor network, and wherein the plurality of actors is connected respectively to the plurality of DVMs based on a predefined protocol; scheduling a plurality of resources connected to an actor in the actor network by using a scheduler provided in the system server; changing a connection between the plurality of actors and the plurality of DVMs with a stop and start mechanism provided in the server; and balancing a load on the actor with a cloud balancer provided in the server and wherein the cloud balancer is connected to the actor in the actor network, and wherein executing the cloud balancer application to stop an operation of a process agent in a first DVM and to start an operation of a process agent in a second DVM, when the process agent in the first DVM consumes extra resources, and wherein the cloud balancer application is executed to provide a first command to the first DVM to stop the operation of the process agent in the first DVM and a second command to the second DVM to start the operation of the second DVM; and adding three fundamental operations over actor systems using a system server to manage schedules, to provide resources and to enable messaging for an asynchronous set of actors in the actor network, wherein the three fundamental operations includes Perform, Transform and Balance (PTB) operations, and wherein the actors are organized in Actor Sets to realize a protocol, application or data operators that are connected to other actors based on a process composition defined by the PTB operations, and wherein the Perform operation is added to realizes a continuous message routing service, and wherein the Transfer operation is added to define a piped topology and interconnection of two actors in the actor system to provide a continuous service, and wherein the Balance operation is added to define a separation paradigm of service results, and wherein the server uses functional programming and scala to realize perform, transform and balance operations over actor systems. | 5. A computer implemented method executed on a computing device to perform Big Data processing in a system with actor oriented platform, the method comprises: establishing an actor network with a plurality of actors and connecting the actor network to a cloud server in a cloud network; establishing a distributed virtual machine (DVM) network with a plurality of DVMs and connecting the DVM network to the actor network, and wherein the plurality of actors is connected respectively to the plurality of DVMs based on a predefined protocol; scheduling a plurality of resources connected to an actor in the actor network by using a scheduler provided in the system server; changing a connection between the plurality of actors and the plurality of DVMs with a stop and start mechanism provided in the server; and balancing a load on the actor with a cloud balancer provided in the server and wherein the cloud balancer is connected to the actor in the actor network, and wherein executing the cloud balancer application to stop an operation of a process agent in a first DVM and to start an operation of a process agent in a second DVM, when the process agent in the first DVM consumes extra resources, and wherein the cloud balancer application is executed to provide a first command to the first DVM to stop the operation of the process agent in the first DVM and a second command to the second DVM to start the operation of the second DVM; and adding three fundamental operations over actor systems using a system server to manage schedules, to provide resources and to enable messaging for an asynchronous set of actors in the actor network, wherein the three fundamental operations includes Perform, Transform and Balance (PTB) operations, and wherein the actors are organized in Actor Sets to realize a protocol, application or data operators that are connected to other actors based on a process composition defined by the PTB operations, and wherein the Perform operation is added to realizes a continuous message routing service, and wherein the Transfer operation is added to define a piped topology and interconnection of two actors in the actor system to provide a continuous service, and wherein the Balance operation is added to define a separation paradigm of service results, and wherein the server uses functional programming and scala to realize perform, transform and balance operations over actor systems. 6. The method according to claim 5 further comprises sending a message to the actor of the system server to disconnect an actor connected to one DVM and to connect the actor to another DVM based on the load of the process agent present in each DVM to balance the load on the actor. | 0.5 |
9,760,545 | 1 | 10 | 1. A method comprising: entering a source digitized text into a memory of an information technology system; delineating the source digitized text into a plurality of segments by a user; associating a first selection of the segments by the user with a first tag; individually assigning by the user a unique sequence number to each segment of the first selection, whereby each segment of the first selection is associated with a unique sequence number within the first selection; associating a second selection of the segments by the user with a second tag; individually assigning by the user a unique sequence number to each segment of the second selection, whereby each segment of the second selection is associated with a unique sequence number within the second selection; receiving a user command to proceed to thereafter sequentially render segments associated with the first tag; generating a first node record and associating the segments associated with the first tag with the first node record; associating the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially rendering each segment associated with the first tag node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; receiving a user command to sequentially render segments associated with the second tag; generating a second node record and associating segments associated with the second tag with the second node record; sequentially rendering segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. | 1. A method comprising: entering a source digitized text into a memory of an information technology system; delineating the source digitized text into a plurality of segments by a user; associating a first selection of the segments by the user with a first tag; individually assigning by the user a unique sequence number to each segment of the first selection, whereby each segment of the first selection is associated with a unique sequence number within the first selection; associating a second selection of the segments by the user with a second tag; individually assigning by the user a unique sequence number to each segment of the second selection, whereby each segment of the second selection is associated with a unique sequence number within the second selection; receiving a user command to proceed to thereafter sequentially render segments associated with the first tag; generating a first node record and associating the segments associated with the first tag with the first node record; associating the first node record with at least one other selected segment associated with the second tag when at least one of the segments associated with the first node record shares the second tag; sequentially rendering each segment associated with the first tag node record in accordance with the order of each individually assigned sequence number of each segment of the first selection until the associated selected segment is rendered; receiving a user command to sequentially render segments associated with the second tag; generating a second node record and associating segments associated with the second tag with the second node record; sequentially rendering segments associated with the second node record in accordance with the order of each individually assigned sequence number of each segment of the second selection. 10. The method of claim 1 , wherein the first selection of the segments is user defined. | 0.751412 |
9,495,354 | 1 | 9 | 1. A method comprising: receiving, from a client device of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network; parsing the structured query to identify a first query constraint and one or more second query constraints; identifying an inverse constraint associated with the first query constraint, wherein the first query constraint has been previously flagged as identifying greater than a threshold number of objects; and generating a query command based on the structured query, wherein the query command comprises the inverse constraint and the one or more second query constraints. | 1. A method comprising: receiving, from a client device of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network; parsing the structured query to identify a first query constraint and one or more second query constraints; identifying an inverse constraint associated with the first query constraint, wherein the first query constraint has been previously flagged as identifying greater than a threshold number of objects; and generating a query command based on the structured query, wherein the query command comprises the inverse constraint and the one or more second query constraints. 9. The method of claim 1 , further: the first query constraint is for a first object-type, the first query constraint corresponding to an inverted index mapping the first object-type to a second object-type; and the inverse constraint is for the second object-type, the inverse constraint corresponding to a forward index mapping the second object-type to the first object-type. | 0.762264 |
9,626,081 | 1 | 14 | 1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries. | 1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries. 14. The system of claim 1 , wherein the database is periodically updated and indexed by an automated process. | 0.904386 |
6,141,642 | 13 | 15 | 13. The method of claim 10, further comprising a plurality of language processing units, each one of said language processing units receiving one language selected from among said plurality of languages, a first language processing unit receiving said multiple language text when said multiple language text corresponds to the language of said first language processing unit, said first language processing unit being among said plurality of language processing units. | 13. The method of claim 10, further comprising a plurality of language processing units, each one of said language processing units receiving one language selected from among said plurality of languages, a first language processing unit receiving said multiple language text when said multiple language text corresponds to the language of said first language processing unit, said first language processing unit being among said plurality of language processing units. 15. The method of claim 13, further comprising converting said audio wave data into analog audio signals. | 0.946862 |
8,626,054 | 33 | 44 | 33. A non-transitory computer-readable storage medium for causing a computer system to execute processing for automatically annotating essays, the computer readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: identifying a sentence of the essay; determining a plurality of features associated with said sentence; determining a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application, and wherein said discourse element is at least one of: a background, a thesis statement, a main point, and support; and annotating said essay based on said probability. | 33. A non-transitory computer-readable storage medium for causing a computer system to execute processing for automatically annotating essays, the computer readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: identifying a sentence of the essay; determining a plurality of features associated with said sentence; determining a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application, and wherein said discourse element is at least one of: a background, a thesis statement, a main point, and support; and annotating said essay based on said probability. 44. The computer-readable storage medium of claim 33 , wherein the plurality of features includes a rhetorical feature. | 0.878819 |
9,454,606 | 1 | 16 | 1. A method, comprising: receiving, at a computer, an initial search criteria associated with a first database, wherein the first database includes a plurality of entity representations with each entity representation having at least one field with each field having at least one field value; screening the initial search criteria for applicability to representations of natural people in the first database; using a first field match template to determine a first subset of the plurality of entity representations associated with the screened initial search criteria; determining that the initial search criteria specifies two or more different field values for a single field, and responsive to the determining: using a second field match template to determine a second subset of the plurality of entity representations associated with the screened initial search criteria; merging subset field value weights of the first and second subset; summing the subset field value weights for each field of the merged first subset and second subset according to each entity representation of the screened initial search criteria; determining, from the summed field value weights, total weights according to each entity representation; determining a target entity representation based on an entity representation having a highest total weight; determining a confidence level based on the total weights; generating a supplemental search criteria comprising field values from the target entity representation and based at least in part on the determined confidence level exceeding a threshold amount; combining the screened initial search criteria and the supplemental search criteria to produce an enhanced search criteria; and sending, from the computer, to a search engine, the enhanced search criteria, wherein the enhanced search criteria is used to search a second database. | 1. A method, comprising: receiving, at a computer, an initial search criteria associated with a first database, wherein the first database includes a plurality of entity representations with each entity representation having at least one field with each field having at least one field value; screening the initial search criteria for applicability to representations of natural people in the first database; using a first field match template to determine a first subset of the plurality of entity representations associated with the screened initial search criteria; determining that the initial search criteria specifies two or more different field values for a single field, and responsive to the determining: using a second field match template to determine a second subset of the plurality of entity representations associated with the screened initial search criteria; merging subset field value weights of the first and second subset; summing the subset field value weights for each field of the merged first subset and second subset according to each entity representation of the screened initial search criteria; determining, from the summed field value weights, total weights according to each entity representation; determining a target entity representation based on an entity representation having a highest total weight; determining a confidence level based on the total weights; generating a supplemental search criteria comprising field values from the target entity representation and based at least in part on the determined confidence level exceeding a threshold amount; combining the screened initial search criteria and the supplemental search criteria to produce an enhanced search criteria; and sending, from the computer, to a search engine, the enhanced search criteria, wherein the enhanced search criteria is used to search a second database. 16. The method of claim 1 , wherein the at least one field is associated with a name of an employer. | 0.871465 |
8,121,999 | 9 | 10 | 9. the method as in claim 8 , wherein the social network data used to derive the weighting term is an established social network relationship. | 9. the method as in claim 8 , wherein the social network data used to derive the weighting term is an established social network relationship. 10. the method as in claim 9 , wherein historical search data associated with the established network relationship is used in ranking at least a portion of the search result items. | 0.5 |
7,761,844 | 14 | 15 | 14. The system of claim 1 , further comprising a plurality of predefined platform types. | 14. The system of claim 1 , further comprising a plurality of predefined platform types. 15. The system of claim 14 , wherein the template storage includes at least one dedicated template for each platform type. | 0.613924 |
9,875,239 | 1 | 7 | 1. A computer program product for implementing an online document sharing community in a network environment including a plurality of participant computers operated by participants in the online document sharing community and a storage system storing documents, wherein the computer program product is implemented in a non-transitory computer readable storage medium and includes a computer program executed to perform operations, the operations comprising: maintaining, in a database, participant information for a plurality of participants registered with the database, wherein the participant information for at least one of the participants is associated with document information in the database for at least one document owned by the participant, wherein the document information identifies a document in the storage system, an owner of the document, a public/private status flag indicating whether the document is public or private, a public description providing a description of the document that does not include all content of the document, a provide public description field indicating whether the public description is to be provided to requesting participants not in a group of participants allowed access to the document, and wherein the document information for at least one document indicated as private indicates the group of participants allowed to access the document; receiving a request for a page from a requesting participant computer, wherein the requesting participant computer comprises one of the participant computers operated by a requesting participant comprising one of the participants in the online document sharing community; determining a document to include in the page; determining whether the public/private status flag indicates whether the document is public or private; including in the page an access element to provide access to the content of the document in response to the determining that the public/private status flag indicates that the document is public; determining whether the requesting participant is a member of the group of participants allowed access to the document in response to determining that the public/private status flag indicates that the document is private; determining whether the provide public description field indicates that the public description is to be provided in response to the determining that the requesting participant is not a member of the group of participants allowed to access the document; including in the page access to the public description for the document in response to determining that the public/private status flag indicates that the document is private, in response to the determining that the requesting participant is not a member of the group of participants allowed to access the document, and in response to the determining that the provide public description field indicates that the public description is to be provided; including in the page the access element to provide access to the content of the document in response to the determining that the public/private status flag indicates that the document is private and in response to the determining that the requesting participant is a member of the group of participants allowed to access the document; and returning the page to the requesting participant computer. | 1. A computer program product for implementing an online document sharing community in a network environment including a plurality of participant computers operated by participants in the online document sharing community and a storage system storing documents, wherein the computer program product is implemented in a non-transitory computer readable storage medium and includes a computer program executed to perform operations, the operations comprising: maintaining, in a database, participant information for a plurality of participants registered with the database, wherein the participant information for at least one of the participants is associated with document information in the database for at least one document owned by the participant, wherein the document information identifies a document in the storage system, an owner of the document, a public/private status flag indicating whether the document is public or private, a public description providing a description of the document that does not include all content of the document, a provide public description field indicating whether the public description is to be provided to requesting participants not in a group of participants allowed access to the document, and wherein the document information for at least one document indicated as private indicates the group of participants allowed to access the document; receiving a request for a page from a requesting participant computer, wherein the requesting participant computer comprises one of the participant computers operated by a requesting participant comprising one of the participants in the online document sharing community; determining a document to include in the page; determining whether the public/private status flag indicates whether the document is public or private; including in the page an access element to provide access to the content of the document in response to the determining that the public/private status flag indicates that the document is public; determining whether the requesting participant is a member of the group of participants allowed access to the document in response to determining that the public/private status flag indicates that the document is private; determining whether the provide public description field indicates that the public description is to be provided in response to the determining that the requesting participant is not a member of the group of participants allowed to access the document; including in the page access to the public description for the document in response to determining that the public/private status flag indicates that the document is private, in response to the determining that the requesting participant is not a member of the group of participants allowed to access the document, and in response to the determining that the provide public description field indicates that the public description is to be provided; including in the page the access element to provide access to the content of the document in response to the determining that the public/private status flag indicates that the document is private and in response to the determining that the requesting participant is a member of the group of participants allowed to access the document; and returning the page to the requesting participant computer. 7. The computer program product of claim 1 , wherein the group of participants allowed to access the document have accepted terms of a non-disclosure agreement (NDA) with respect to the document. | 0.842995 |
6,152,612 | 5 | 8 | 5. A method as described in claim 4 further comprising the step of d) scheduling said plurality of C++ user processes for execution according to said concurrency, wherein said step d) is performed by a C++ scheduler and comprises the steps of: d1) representing clock signals of said circuit as clock objects in C++ within said plurality of C++ user processes, said clock objects declared as instances of a clock class of said C++ library; d2) synchronizing said plurality of C++ user processes to an edge of a respective clock object by sequentially scheduling said plurality of C++ user processes for execution upon the occurrence of said edge of said respective clock.sub.-- object, said edge obtained from a priority queue maintained in said memory; and d3) at the completion of a clock cycle of said clock object, computing the time of a next edge of said clock object and storing said time into said priority queue. | 5. A method as described in claim 4 further comprising the step of d) scheduling said plurality of C++ user processes for execution according to said concurrency, wherein said step d) is performed by a C++ scheduler and comprises the steps of: d1) representing clock signals of said circuit as clock objects in C++ within said plurality of C++ user processes, said clock objects declared as instances of a clock class of said C++ library; d2) synchronizing said plurality of C++ user processes to an edge of a respective clock object by sequentially scheduling said plurality of C++ user processes for execution upon the occurrence of said edge of said respective clock.sub.-- object, said edge obtained from a priority queue maintained in said memory; and d3) at the completion of a clock cycle of said clock object, computing the time of a next edge of said clock object and storing said time into said priority queue. 8. A method as described in claim 5 further comprising the steps of: representing multi-valued logic in said C++ library wherein signal values of: logical high ("1"); logical low ("0"); high impedance; and unknown are represented by separate internal values; and performing AND, OR, XOR and NOT functions on arguments of said multi-valued logic. | 0.712978 |
9,734,208 | 5 | 13 | 5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving an electronic transcript of a conversation of spoken dialogue involving two or more participants, the electronic transcript comprising a plurality of words; determining an attribute of the electronic transcript from at least some of the plurality of words; searching, using the attribute, a collection of topics stored in an electronic data store to identify a first topic and a second topic relevant to the conversation; generating, from the electronic transcript, an annotated electronic transcript comprising a first embedded indication of the first topic and a second embedded indication the second topic, wherein the first embedded indication is configured for presentation as a textual representation of the first topic to indicate availability of electronically stored data about the first topic, the textual representation different from a visual representation of another portion of the annotated electronic transcript; sending the annotated electronic transcript to a computing device associated with a participant of the conversation; receiving, from the computing device, input data representing a user selection to cause presentation of additional information associated with the first topic; and sending a portion of the electronically stored data about the first topic, to the computing device, wherein the portion of the electronically stored data is different from the annotated electronic transcript and represents a portion of shared knowledge. | 5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving an electronic transcript of a conversation of spoken dialogue involving two or more participants, the electronic transcript comprising a plurality of words; determining an attribute of the electronic transcript from at least some of the plurality of words; searching, using the attribute, a collection of topics stored in an electronic data store to identify a first topic and a second topic relevant to the conversation; generating, from the electronic transcript, an annotated electronic transcript comprising a first embedded indication of the first topic and a second embedded indication the second topic, wherein the first embedded indication is configured for presentation as a textual representation of the first topic to indicate availability of electronically stored data about the first topic, the textual representation different from a visual representation of another portion of the annotated electronic transcript; sending the annotated electronic transcript to a computing device associated with a participant of the conversation; receiving, from the computing device, input data representing a user selection to cause presentation of additional information associated with the first topic; and sending a portion of the electronically stored data about the first topic, to the computing device, wherein the portion of the electronically stored data is different from the annotated electronic transcript and represents a portion of shared knowledge. 13. The computer-implemented method of claim 5 , wherein determining the attribute of the electronic transcript comprises looking up an attribute corresponding to a word of the electronic transcript. | 0.793996 |
7,653,541 | 9 | 10 | 9. The speech processing device according to claim 1 , further comprising: comparison means for comparing an acoustic score obtained by matching a predetermined duration of the input utterance against known words with an acoustic score obtained by recognition of a syllable typewriter, wherein the comparison means estimates that the duration corresponds to an unknown word if the acoustic score by recognition of a syllable typewriter is superior to the other score. | 9. The speech processing device according to claim 1 , further comprising: comparison means for comparing an acoustic score obtained by matching a predetermined duration of the input utterance against known words with an acoustic score obtained by recognition of a syllable typewriter, wherein the comparison means estimates that the duration corresponds to an unknown word if the acoustic score by recognition of a syllable typewriter is superior to the other score. 10. The speech processing device according to claim 9 , wherein the comparison means compares the acoustic score obtained by matching a predetermined duration of the input utterance against known words with the acoustic score obtained by recognition of a syllable typewriter after the comparison means corrects the acoustic score obtained by recognition of a syllable typewriter. | 0.5 |
9,235,812 | 5 | 7 | 5. A computer implemented method for automatic document classification, the method comprising: extracting with an extraction module structural, syntactical and semantic information from a document and normalizing with the extraction module the extracted information; generating with a machine learning module a model representation for automatic document classification based on feature vectors built from the normalized and extracted semantic information for supervised and unsupervised clustering and machine learning; and selecting with a classification module a non-classified document from a document collection, and extracting via the extraction module normalized structural, syntactical and semantic information from the selected document, and generating via the machine learning module a model representation of the selected document based on feature vectors, and matching with the classification module the model representation of the selected document against the machine learning model representation and generating with the classification module a document category, and classification for display to a user, wherein the extracted information includes named entities, properties of entities, noun-phrases facts, events, and concepts. | 5. A computer implemented method for automatic document classification, the method comprising: extracting with an extraction module structural, syntactical and semantic information from a document and normalizing with the extraction module the extracted information; generating with a machine learning module a model representation for automatic document classification based on feature vectors built from the normalized and extracted semantic information for supervised and unsupervised clustering and machine learning; and selecting with a classification module a non-classified document from a document collection, and extracting via the extraction module normalized structural, syntactical and semantic information from the selected document, and generating via the machine learning module a model representation of the selected document based on feature vectors, and matching with the classification module the model representation of the selected document against the machine learning model representation and generating with the classification module a document category, and classification for display to a user, wherein the extracted information includes named entities, properties of entities, noun-phrases facts, events, and concepts. 7. The method of claim 5 , wherein the extracted information is normalized by using normalization rules, groupers, thesauri, taxonomies, and string-matching algorithms. | 0.839695 |
10,162,886 | 1 | 4 | 1. A method comprising, by one or more computer systems: receiving, from a client system of a user of an online social network, a query inputted by the user, wherein the query comprises a plurality of n-grams; parsing the query to identify a subset of n-grams of the plurality of n-grams; generating, for each identified n-gram, an embedding of the n-gram, wherein embeddings correspond to points in a d-dimensional embedding space; determining, for each identified n-gram, one or more word senses corresponding to one or more embeddings of the word senses, respectively; calculating, for each determined word sense for each identified n-gram, a relatedness-score for the word sense based on one or more similarity metrics of the embedding of the word sense and the embeddings of each of the one or more other word senses corresponding to the other identified n-grams, respectively; selecting, for each identified n-gram, one of the one or more word senses determined for the identified n-gram having one or more relatedness-scores, respectively, the selected word sense having a highest relatedness-score of the one or more respective relatedness-scores; identifying one or more objects matching at least a portion of the query; ranking each identified object based on a quality of matching of the object to one or more selected word senses; and sending, to the client system in response to the query, a search-results interface for display, wherein the search-results interface comprises one or more search results corresponding to one or more of the identified objects, respectively, each identified object corresponding to a search result having a rank greater than a threshold rank. | 1. A method comprising, by one or more computer systems: receiving, from a client system of a user of an online social network, a query inputted by the user, wherein the query comprises a plurality of n-grams; parsing the query to identify a subset of n-grams of the plurality of n-grams; generating, for each identified n-gram, an embedding of the n-gram, wherein embeddings correspond to points in a d-dimensional embedding space; determining, for each identified n-gram, one or more word senses corresponding to one or more embeddings of the word senses, respectively; calculating, for each determined word sense for each identified n-gram, a relatedness-score for the word sense based on one or more similarity metrics of the embedding of the word sense and the embeddings of each of the one or more other word senses corresponding to the other identified n-grams, respectively; selecting, for each identified n-gram, one of the one or more word senses determined for the identified n-gram having one or more relatedness-scores, respectively, the selected word sense having a highest relatedness-score of the one or more respective relatedness-scores; identifying one or more objects matching at least a portion of the query; ranking each identified object based on a quality of matching of the object to one or more selected word senses; and sending, to the client system in response to the query, a search-results interface for display, wherein the search-results interface comprises one or more search results corresponding to one or more of the identified objects, respectively, each identified object corresponding to a search result having a rank greater than a threshold rank. 4. The method of claim 1 , wherein for each identified n-gram, the one or more word senses are determined based on one or more similarity metrics of the embedding of the n-gram and the embeddings of the one or more word senses, respectively. | 0.893551 |
7,945,691 | 9 | 12 | 9. A system comprising: a data distribution device comprising: memory operable to store: a repository comprising data conveyance rules and rule templates associated with the data conveyance rules, the data conveyance rules being used by the data distribution device to determine under what conditions to send data to a data output device, and a rule editor for modifying the data conveyance rules and the rule templates; and a processor operable to: determine whether a first message indicating that a set of the data conveyance rules to be modified has been received from the data output device, the data conveyance rules being identified using at least one of a user name for a user associated with the first message and a data output device identifier for the data output device, the data conveyance rules pertaining to messages delivered to the data output device subsequent to the first message, if the first message to modify has been received, identify a rule template associated with the set, the identified rule template comprising at least one parameter, generate and send, from the data distribution device to the data output device over a communication network, a second message specifying a user interface corresponding to the identified template and the at least one parameter associated with the data conveyance rules that are to be modified, the second message causing the data output device to generate a user interface based on the specified user interface and the identified at least one parameter in the second message, determine whether a third message comprising a specification of the parameter has been received from the data output device, and if the third message specifying the parameter has been received, create a rule by binding the rule template with the specified parameter, the created rule thereafter forming part of the data conveyance rules; wherein the data distribution device maintains a state of the data output device so that the data distribution device provides the data output device with only new data; wherein the data is persisted at the data output device across trips between the data distribution device and the data output device. | 9. A system comprising: a data distribution device comprising: memory operable to store: a repository comprising data conveyance rules and rule templates associated with the data conveyance rules, the data conveyance rules being used by the data distribution device to determine under what conditions to send data to a data output device, and a rule editor for modifying the data conveyance rules and the rule templates; and a processor operable to: determine whether a first message indicating that a set of the data conveyance rules to be modified has been received from the data output device, the data conveyance rules being identified using at least one of a user name for a user associated with the first message and a data output device identifier for the data output device, the data conveyance rules pertaining to messages delivered to the data output device subsequent to the first message, if the first message to modify has been received, identify a rule template associated with the set, the identified rule template comprising at least one parameter, generate and send, from the data distribution device to the data output device over a communication network, a second message specifying a user interface corresponding to the identified template and the at least one parameter associated with the data conveyance rules that are to be modified, the second message causing the data output device to generate a user interface based on the specified user interface and the identified at least one parameter in the second message, determine whether a third message comprising a specification of the parameter has been received from the data output device, and if the third message specifying the parameter has been received, create a rule by binding the rule template with the specified parameter, the created rule thereafter forming part of the data conveyance rules; wherein the data distribution device maintains a state of the data output device so that the data distribution device provides the data output device with only new data; wherein the data is persisted at the data output device across trips between the data distribution device and the data output device. 12. The system of claim 9 , wherein: the memory is further operable to store a rule engine; and the processor is further operable to: determine whether a message comprising a subscription request has been received, if a subscription request has been received, identify data conveyance rules associated with the subscription request, and send data in accordance with the identified rules. | 0.5 |
7,761,478 | 12 | 16 | 12. The method of claim 11 , wherein the merging includes mapping a first object in a first intermediate model to a second object in a second intermediate model. | 12. The method of claim 11 , wherein the merging includes mapping a first object in a first intermediate model to a second object in a second intermediate model. 16. The method of claim 12 , wherein the mapping includes heuristically mapping objects using at least one other mapping of objects. | 0.554054 |
7,574,659 | 18 | 27 | 18. A search engine method, comprising: storing records relating to a content of a plurality of information resources at a first database; storing records relating to commercial messages at a second database; persistently storing an identifier; receiving a search query and automatically defining in dependence thereon a query of the first database to retrieve hyperlinked identifiers of records of the first database corresponding to the search query, and a selection of records from the second database to define hyperlinked identifiers of records of the second database relating to commercial messages associated with at least one of the search query and the persistent identifier; automatically organizing the identifiers of records from the first database together with the identifiers of records from the second database in a common output, in further dependence on the stored identifier; wherein the step of automatically organizing comprises: defining a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database and inserting the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and automatically recording accounting information for at least one of a presentation and a selection of an identifier of a record from the second database with respect to an account maintained by an entity relating to a corresponding commercial message. | 18. A search engine method, comprising: storing records relating to a content of a plurality of information resources at a first database; storing records relating to commercial messages at a second database; persistently storing an identifier; receiving a search query and automatically defining in dependence thereon a query of the first database to retrieve hyperlinked identifiers of records of the first database corresponding to the search query, and a selection of records from the second database to define hyperlinked identifiers of records of the second database relating to commercial messages associated with at least one of the search query and the persistent identifier; automatically organizing the identifiers of records from the first database together with the identifiers of records from the second database in a common output, in further dependence on the stored identifier; wherein the step of automatically organizing comprises: defining a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database and inserting the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and automatically recording accounting information for at least one of a presentation and a selection of an identifier of a record from the second database with respect to an account maintained by an entity relating to a corresponding commercial message. 27. The method according to claim 18 , wherein the common output comprises an applet having executable code therein. | 0.89913 |
9,244,979 | 17 | 25 | 17. One or more non-transitory storage media storing instructions which, when executed by one or more processors, cause: storing summary data that (a) specifies a number of each element of a plurality of elements of an XML document that is part of XML data and (b) indicates a hierarchical relationship among the plurality of elements; identifying, in a particular query that targets a portion of the XML data, a plurality of predicates that comprises a first subset and a second subset that is different than the first subset; analyzing the summary data based on the first subset of the plurality of predicates; determining that at least a first predicate in the first subset of the plurality of predicates is correlated with a second predicate in the second subset of the plurality of predicates; in response to determining that the first predicate is correlated with the second predicate, generating a single selectivity value based on the first subset of the plurality of predicates, one or more predicates that do not belong to the first subset of the plurality of predicates, and the summary data; associating the single selectivity value with the first subset of the plurality predicates; and estimating, based on the single selectivity value, a cost of executing the particular query. | 17. One or more non-transitory storage media storing instructions which, when executed by one or more processors, cause: storing summary data that (a) specifies a number of each element of a plurality of elements of an XML document that is part of XML data and (b) indicates a hierarchical relationship among the plurality of elements; identifying, in a particular query that targets a portion of the XML data, a plurality of predicates that comprises a first subset and a second subset that is different than the first subset; analyzing the summary data based on the first subset of the plurality of predicates; determining that at least a first predicate in the first subset of the plurality of predicates is correlated with a second predicate in the second subset of the plurality of predicates; in response to determining that the first predicate is correlated with the second predicate, generating a single selectivity value based on the first subset of the plurality of predicates, one or more predicates that do not belong to the first subset of the plurality of predicates, and the summary data; associating the single selectivity value with the first subset of the plurality predicates; and estimating, based on the single selectivity value, a cost of executing the particular query. 25. The one or more non-transitory storage media of claim 17 , wherein the second predicate indicates a particular path in the XML data and the first subset of the plurality of predicates are constrained to elements under the particular path. | 0.657224 |
8,417,528 | 13 | 18 | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. | 13. The method of claim 12 , further comprising: converting the phoneme graph to a word-phoneme graph, the word-phoneme graph assigning a word and associated phonetic transcription to each edge. 18. The method according to claim 13 , further comprising: converting the word-phoneme graph to the word graph, the word graph assigning a word to each edge. | 0.739203 |
9,792,332 | 9 | 12 | 9. A system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and based at least in part on the score, determine whether to output to the first user information about the second user. | 9. A system comprising: memory for storing event data representing user-generated events that reflect user affinities for particular items, wherein the user-generated events comprise user actions that can be monitored by a computing device; and at least one computing device including a processor in communication with the memory, the at least one computing device operative to: generate a score that reflects a degree to which item affinities of a first user of a plurality of users are similar to item affinities of a second user of said plurality of users, said score taking into consideration a first plurality of user-generated events by the first user reflecting a set of item affinities of the first user, and a second plurality of user-generated events by the second user reflecting a set of item affinities of the second user, wherein generating the score further comprises accessing item similarity data to determine whether an item in the set of item affinities of the first user is similar to an item in the set of item affinities of the second user; and based at least in part on the score, determine whether to output to the first user information about the second user. 12. The system of claim 9 , wherein the score reflects a degree to which an item in the set of item affinities of the first user is related to an item in the set of item affinities of the second user. | 0.760192 |
8,285,196 | 9 | 12 | 9. A method of operating an electronic device comprising communication circuitry and at least one non-volatile memory having stored therein one or both of firmware and software, the method comprising: communicating with a distribution server that supports delivery of a questionnaire to the electronic device and that processes responses from the electronic device; receiving a questionnaire from the distribution server and displaying it to a user; receiving the user's input and gathering a response; and communicating the response to the distribution server along with a demographic profile reference stored in the at least one non-volatile memory of the electronic device. | 9. A method of operating an electronic device comprising communication circuitry and at least one non-volatile memory having stored therein one or both of firmware and software, the method comprising: communicating with a distribution server that supports delivery of a questionnaire to the electronic device and that processes responses from the electronic device; receiving a questionnaire from the distribution server and displaying it to a user; receiving the user's input and gathering a response; and communicating the response to the distribution server along with a demographic profile reference stored in the at least one non-volatile memory of the electronic device. 12. The method of claim 9 , wherein the demographic profile reference comprises a URN or a link to demographic profile data stored in the electronic device and the electronic device communicates the response to the distribution server along with the demographic profile data. | 0.572981 |
8,137,105 | 1 | 2 | 1. A computer implemented method for reviewing vocabulary comprising: using a computer and a graphical user interface on a display connected to the computer, and responsive to a user selecting a chapter from a plurality of chapters in a Chinese-English textbook, a question language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, and an answer language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, displaying a plurality of vocabulary words from the chapter, displaying a question containing a vocabulary word in the question language; responsive to the user inputting an answer in the answer language, determining if the answer is a correct answer; responsive to the vocabulary word or the answer being in Simplified Chinese, translating the vocabulary word or the answer into Traditional Chinese by accessing a Simplified Chinese/Traditional Chinese conversion table; wherein a determination if the answer is a correct answer is performed by determining whether the vocabulary word and the answer both match an entry in a Traditional Chinese/Pin Yin/English dictionary encoded in Unicode. | 1. A computer implemented method for reviewing vocabulary comprising: using a computer and a graphical user interface on a display connected to the computer, and responsive to a user selecting a chapter from a plurality of chapters in a Chinese-English textbook, a question language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, and an answer language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, displaying a plurality of vocabulary words from the chapter, displaying a question containing a vocabulary word in the question language; responsive to the user inputting an answer in the answer language, determining if the answer is a correct answer; responsive to the vocabulary word or the answer being in Simplified Chinese, translating the vocabulary word or the answer into Traditional Chinese by accessing a Simplified Chinese/Traditional Chinese conversion table; wherein a determination if the answer is a correct answer is performed by determining whether the vocabulary word and the answer both match an entry in a Traditional Chinese/Pin Yin/English dictionary encoded in Unicode. 2. The method of claim 1 further comprising: displaying statistics regarding the user's performance in answering a plurality of questions. | 0.711297 |
8,700,414 | 1 | 2 | 1. In a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects, and wherein a workflow system handles task-based operations in a structured environment, the computer system further comprising at least one monitored operations system that generates alerts to notify participants of events within the at least one monitored operations system, a computer implemented method of handling alerts in a structured manner comprising: transmitting by the computer system, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; initiating a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log; storing, by the computer system, the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event; ending the event resolution log when the determined participant signals to the computer system a resolution of the first event; generating by the computer system a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item; and storing by the computer system the workflow process template in the workflow system in association with a category identifier associated with the first event. | 1. In a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects, and wherein a workflow system handles task-based operations in a structured environment, the computer system further comprising at least one monitored operations system that generates alerts to notify participants of events within the at least one monitored operations system, a computer implemented method of handling alerts in a structured manner comprising: transmitting by the computer system, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; initiating a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log; storing, by the computer system, the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event; ending the event resolution log when the determined participant signals to the computer system a resolution of the first event; generating by the computer system a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item; and storing by the computer system the workflow process template in the workflow system in association with a category identifier associated with the first event. 2. The method of claim 1 , wherein the determined participant and the future determined participant are the same person and the event resolution log provides a reminder during handling of the second event as to how the first event was resolved. | 0.809375 |
8,239,383 | 1 | 8 | 1. A computer-implemented method for managing execution of a query against a database having a multiplicity of data records, comprising: receiving, from a requesting entity, a query against the database; and performing an automated execution process, comprising: (i) iteratively executing the query against different samples of the database, each sample including a different subset of the multiplicity of data records; (ii) after each iterative execution of the query, determining whether a query result obtained for the iterative execution satisfies a predefined condition; and (iii) if the predefined condition is not satisfied, performing a predefined action. | 1. A computer-implemented method for managing execution of a query against a database having a multiplicity of data records, comprising: receiving, from a requesting entity, a query against the database; and performing an automated execution process, comprising: (i) iteratively executing the query against different samples of the database, each sample including a different subset of the multiplicity of data records; (ii) after each iterative execution of the query, determining whether a query result obtained for the iterative execution satisfies a predefined condition; and (iii) if the predefined condition is not satisfied, performing a predefined action. 8. The method of claim 1 , further comprising, prior to iteratively executing the query against the samples of the database: receiving alternative definitions from the requesting entity, the alternative definitions indicating at least one of: (i) authorized modifications to the query; and (ii) authorized modifications to the predefined condition. | 0.5 |
7,617,511 | 31 | 36 | 31. One or more computer storage media comprising instructions that, when executed, direct a computing device to perform a method, the method comprising: invoking a preference entry page, wherein the preference entry page comprises: at least one program attribute value associated with a program identified in an electronic programming guide (EPG); a preference rating area associated with each program attribute value through which a preference rating may be indicated, the preference rating indicating a user like or dislike for the program attribute value associated with the preference rating area, wherein the preference entry page associated with the program is invoked by the user from the EPG; and a save control, that when actuated, facilitates storage of each indicated preference rating and corresponding program attribute value, wherein entering and storing the preference rating indicates that the program attribute value associated with the preference rating is a preferred program attribute value; and associating a numerical significance value with each preferred program attribute value, each numerical significance value denoting a relative importance of each preferred program attribute value with regard to each other preferred program attribute value, wherein for each preferred program attribute value that matches an attribute value of an upcoming program, the associated numerical significance value and the associated preference rating facilitate calculation of a program score for the upcoming program. | 31. One or more computer storage media comprising instructions that, when executed, direct a computing device to perform a method, the method comprising: invoking a preference entry page, wherein the preference entry page comprises: at least one program attribute value associated with a program identified in an electronic programming guide (EPG); a preference rating area associated with each program attribute value through which a preference rating may be indicated, the preference rating indicating a user like or dislike for the program attribute value associated with the preference rating area, wherein the preference entry page associated with the program is invoked by the user from the EPG; and a save control, that when actuated, facilitates storage of each indicated preference rating and corresponding program attribute value, wherein entering and storing the preference rating indicates that the program attribute value associated with the preference rating is a preferred program attribute value; and associating a numerical significance value with each preferred program attribute value, each numerical significance value denoting a relative importance of each preferred program attribute value with regard to each other preferred program attribute value, wherein for each preferred program attribute value that matches an attribute value of an upcoming program, the associated numerical significance value and the associated preference rating facilitate calculation of a program score for the upcoming program. 36. The one or more computer storage media as recited in claim 31 , wherein the preference rating comprises a numerical value in a range from a negative integer to a positive integer. | 0.686644 |
8,923,838 | 15 | 16 | 15. The method as recited in claim 1 , wherein instructional information is audibly transmitted to the user over the network for facilitating the programming of the cellular phone by the user. | 15. The method as recited in claim 1 , wherein instructional information is audibly transmitted to the user over the network for facilitating the programming of the cellular phone by the user. 16. The method as recited in claim 15 , wherein the instructional information is tailored based on the cellular phone of the user. | 0.5 |
8,706,680 | 1 | 7 | 1. An automated method that enables a user to prepare a report using a computer system having a processor, an input interface, and an output interface, said method comprising: entering context information into the input interface; displaying a single lexeme query and associated lexeme responses from a lexicon containing a plurality of such queries and associated responses on the computer system's output interface; allowing the user to select a response to the lexeme query from the display wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance, and wherein the user is constrained to respond to the queries in the order they are presented by the system; determining whether the selected lexeme response instructs the system to move forward to the next section of the report, and if so, moving the system forward to the next section of the report; determining whether the selected lexeme is an active lexeme, and if so, executing the task associated with the active lexeme; determining whether the selected lexeme sets new predicants to be true, and if so, adding the predicants to a predicant list stored by the system; determining the next lexeme query in the order established by the coherence of the lexicon which contains one or more predicants matching the current predicant list and displaying this next lexeme query on the computer system's output interface; iterating this process until the report is complete; and concatenating and exporting the content of the selected lexeme responses in one or more styles. | 1. An automated method that enables a user to prepare a report using a computer system having a processor, an input interface, and an output interface, said method comprising: entering context information into the input interface; displaying a single lexeme query and associated lexeme responses from a lexicon containing a plurality of such queries and associated responses on the computer system's output interface; allowing the user to select a response to the lexeme query from the display wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance, and wherein the user is constrained to respond to the queries in the order they are presented by the system; determining whether the selected lexeme response instructs the system to move forward to the next section of the report, and if so, moving the system forward to the next section of the report; determining whether the selected lexeme is an active lexeme, and if so, executing the task associated with the active lexeme; determining whether the selected lexeme sets new predicants to be true, and if so, adding the predicants to a predicant list stored by the system; determining the next lexeme query in the order established by the coherence of the lexicon which contains one or more predicants matching the current predicant list and displaying this next lexeme query on the computer system's output interface; iterating this process until the report is complete; and concatenating and exporting the content of the selected lexeme responses in one or more styles. 7. The method of claim 1 further comprising the step of entering text into the report manually. | 0.613821 |
9,720,961 | 17 | 20 | 17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. | 17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. 20. The computer program product of claim 17 , wherein the operations further comprise: receiving a query that references a variable having the algebraic data type; and computing one or more tuples that satisfy the query, wherein each of the one or more tuples that satisfies the query is an injector tuple defined by a respective injector relation of one of the alternative subtypes for the algebraic data type. | 0.5 |
9,354,763 | 1 | 10 | 1. A method comprising: (a) displaying, to a user via an electronic display associated with an electronic device, a login interface; (b) receiving, at the electronic device from the user, input corresponding to login credentials of a user account of the user; (c) communicating, from the electronic device, data corresponding to the login credentials; (d) displaying, to the user via the electronic display, a video selection interface configured to allow the user to a select a video for viewing; (e) receiving, at the electronic device from the user, input corresponding to selection of a video for viewing; (f) communicating, from the electronic device, data corresponding to the selected video; (g) receiving, at the electronic device, (i) data corresponding to the video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (h) displaying, to the user via the electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment button configured to allow the user to add a comment to the video; and (i) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (j) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, the first length being a length calculated based on a total length of the video; (k) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (l) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (m) receiving, at the electronic device from the user, input corresponding to engagement of the comment button; (n) in response to receiving input corresponding to engagement of the comment button, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (o) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (p) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. | 1. A method comprising: (a) displaying, to a user via an electronic display associated with an electronic device, a login interface; (b) receiving, at the electronic device from the user, input corresponding to login credentials of a user account of the user; (c) communicating, from the electronic device, data corresponding to the login credentials; (d) displaying, to the user via the electronic display, a video selection interface configured to allow the user to a select a video for viewing; (e) receiving, at the electronic device from the user, input corresponding to selection of a video for viewing; (f) communicating, from the electronic device, data corresponding to the selected video; (g) receiving, at the electronic device, (i) data corresponding to the video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (h) displaying, to the user via the electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment button configured to allow the user to add a comment to the video; and (i) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (j) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, the first length being a length calculated based on a total length of the video; (k) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (l) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (m) receiving, at the electronic device from the user, input corresponding to engagement of the comment button; (n) in response to receiving input corresponding to engagement of the comment button, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (o) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (p) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. 10. The method of claim 1 , wherein the electronic device is a tablet, slate computer, or smartphone. | 0.950197 |
8,073,700 | 1 | 4 | 1. A method carried out by at least one computer, the method comprising acts of: receiving a request comprising speech data from a mobile device; querying a network service using query information obtained from the speech data, whereby search results are received from the network service; formatting the search results for presentation on a display of the mobile device; generating a voice grammar based at least in part on the search results; and sending the search results and the voice grammar generated from the search results to the mobile device. | 1. A method carried out by at least one computer, the method comprising acts of: receiving a request comprising speech data from a mobile device; querying a network service using query information obtained from the speech data, whereby search results are received from the network service; formatting the search results for presentation on a display of the mobile device; generating a voice grammar based at least in part on the search results; and sending the search results and the voice grammar generated from the search results to the mobile device. 4. The method of claim 1 , wherein the act of sending further comprises resending, to the mobile device, a different voice grammar from a prior transaction with the mobile device, with the search results and the voice grammar. | 0.785171 |
8,316,028 | 7 | 8 | 7. A method for biometric indexing and searching based on a matching operation, for a probe in a biometric corpus comprising: performing the matching operation between templates in the biometric corpus and prototype templates to obtain template-match scores; averaging the template-match scores for each of a plurality of templates to generate a template-typicality score; and dividing template-typicality scores of all the templates in the biometric corpus into typicality ranges, each typicality range corresponding to a typicality sub-corpus of a typicality-indexed corpus that has about a same number of templates as other typicality sub-corpuses corresponding to other typicality ranges, and each of templates in the typicality sub-corpus having a template-typicality score within a typicality range of the typicality sub-corpus. | 7. A method for biometric indexing and searching based on a matching operation, for a probe in a biometric corpus comprising: performing the matching operation between templates in the biometric corpus and prototype templates to obtain template-match scores; averaging the template-match scores for each of a plurality of templates to generate a template-typicality score; and dividing template-typicality scores of all the templates in the biometric corpus into typicality ranges, each typicality range corresponding to a typicality sub-corpus of a typicality-indexed corpus that has about a same number of templates as other typicality sub-corpuses corresponding to other typicality ranges, and each of templates in the typicality sub-corpus having a template-typicality score within a typicality range of the typicality sub-corpus. 8. The method of claim 7 further comprising: performing the matching operation between the probe and the prototype templates to generate probe-match scores; averaging the probe-match scores to generate a probe-typicality score; and selecting a typicality sub-corpus based on the probe-typicality score as the search corpus. | 0.5 |
8,493,883 | 15 | 22 | 15. A system comprising: a plurality of identification modules, each identification module being configured to identify select matching entities of a first network model and a second network model, based on rules that are specific to the select entities, the second network model having a different arrangement of entities than the first network model, and the identification module establishes a correspondence between corresponding entities in each model, and a control engine that is configured to selectively enable each identification module in a sequence that effects an identification of each of the entities of the first network model and the second network model, and a difference processor that is configured to compare entities having corresponding identifications in each of the first and second network models, to determine configuration differences between corresponding entities of the first and second network models, wherein each of the first and second network models provides a high-fidelity representation of the actual network, and includes representations of physical devices and links between the devices, identifying select matching entities includes a sequence of refinements of objects in each of the first and second network models, the sequence of refinements correspond to mapping to different network entities, each refinement is based on a set of rules associated with the network entity corresponding to the refinement, and the mapping at each refinement includes: providing a label to each network object associated with the network entity, combining each label from each refinement of the sequence of refinements to identify each network object by a composite label, and identifying the matching entities in each of the first and second network models as those having the same composite label. | 15. A system comprising: a plurality of identification modules, each identification module being configured to identify select matching entities of a first network model and a second network model, based on rules that are specific to the select entities, the second network model having a different arrangement of entities than the first network model, and the identification module establishes a correspondence between corresponding entities in each model, and a control engine that is configured to selectively enable each identification module in a sequence that effects an identification of each of the entities of the first network model and the second network model, and a difference processor that is configured to compare entities having corresponding identifications in each of the first and second network models, to determine configuration differences between corresponding entities of the first and second network models, wherein each of the first and second network models provides a high-fidelity representation of the actual network, and includes representations of physical devices and links between the devices, identifying select matching entities includes a sequence of refinements of objects in each of the first and second network models, the sequence of refinements correspond to mapping to different network entities, each refinement is based on a set of rules associated with the network entity corresponding to the refinement, and the mapping at each refinement includes: providing a label to each network object associated with the network entity, combining each label from each refinement of the sequence of refinements to identify each network object by a composite label, and identifying the matching entities in each of the first and second network models as those having the same composite label. 22. The system of claim 15 , wherein the difference processor is configured to distinguish changed entities, added entities, and removed entities. | 0.813299 |
6,151,608 | 41 | 57 | 41. The system as claimed in claim 40 wherein the data map architect loads the data from the at least one source into at least one temporary table having source and destination fields. | 41. The system as claimed in claim 40 wherein the data map architect loads the data from the at least one source into at least one temporary table having source and destination fields. 57. The system as claimed in claim 41 wherein the update processor moves the data from the at least one source to the at least one temporary table. | 0.718391 |
8,990,070 | 17 | 19 | 17. A computer program product for building an expression, the computer program product comprising: a non-transitory computer-readable storage medium; and computer-readable program code embodied in the non-transitory computer-readable storage medium, where the computer-readable program code, when executed by a processor of a computer, is configured to perform: displaying an expression on a computer display via a graphical user interface, where the expression includes a non-terminal display object corresponding to a non-terminal element defined in a grammar; and in response to receiving selection of the non-terminal display object, displaying a candidate terminal display object and a candidate non-terminal display object, where the candidate terminal display object corresponds to a terminal element within the grammar, and where the candidate non-terminal display object corresponds to another non-terminal element within the grammar; in response to receiving selection of the candidate terminal display object, replacing the selected non-terminal display object in the expression with the selected candidate terminal display object; and in response to receiving selection of the candidate non-terminal display object, replacing the selected non-terminal display object in the expression with the candidate non-terminal display object, where the candidate non-terminal display object is further replaced by one of another candidate terminal display object and another candidate non-terminal display object until no non-terminal display object remains in the displayed expression. | 17. A computer program product for building an expression, the computer program product comprising: a non-transitory computer-readable storage medium; and computer-readable program code embodied in the non-transitory computer-readable storage medium, where the computer-readable program code, when executed by a processor of a computer, is configured to perform: displaying an expression on a computer display via a graphical user interface, where the expression includes a non-terminal display object corresponding to a non-terminal element defined in a grammar; and in response to receiving selection of the non-terminal display object, displaying a candidate terminal display object and a candidate non-terminal display object, where the candidate terminal display object corresponds to a terminal element within the grammar, and where the candidate non-terminal display object corresponds to another non-terminal element within the grammar; in response to receiving selection of the candidate terminal display object, replacing the selected non-terminal display object in the expression with the selected candidate terminal display object; and in response to receiving selection of the candidate non-terminal display object, replacing the selected non-terminal display object in the expression with the candidate non-terminal display object, where the candidate non-terminal display object is further replaced by one of another candidate terminal display object and another candidate non-terminal display object until no non-terminal display object remains in the displayed expression. 19. The computer program product of claim 17 where the computer-readable program code is configured to perform adding a new expression section to the expression. | 0.837702 |
9,633,653 | 8 | 9 | 8. The device as recited in claim 1 , further comprising a communication interface, and wherein the processor-executable instructions further program the one or more processors to: receive, via the communication interface, user information corresponding to the digital work from a plurality of user devices; and wherein the first probability of occurrence associated with the n-gram is weighted based at least in part on the user information. | 8. The device as recited in claim 1 , further comprising a communication interface, and wherein the processor-executable instructions further program the one or more processors to: receive, via the communication interface, user information corresponding to the digital work from a plurality of user devices; and wherein the first probability of occurrence associated with the n-gram is weighted based at least in part on the user information. 9. The device as recited in claim 8 , wherein the user information includes at least one of information corresponding to a user highlight of the digital work or information corresponding to a user annotation to the digital work. | 0.5 |
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