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7,996,367 | 1 | 3 | 1. A method using a document system comprising a computer with a processor for executing software instructions for document exchange directed to execution of a document by a plurality of parties, wherein the document is inputted with an input subsystem of the document system from an input source and stored for document exchange, the method comprising: receiving routing information and identifying metadata through the input subsystem; automatically storing the document with the input subsystem from the input source as specified in the routing information along with data automatically generated and structured based on the routing information and metadata; routing the document for execution to the plurality of parties based on the routing information; archiving the executed document in a document archive after automatically verifying that it has been executed by the plurality of parties; and providing search capability with respect to documents that are executed in the document archive and documents that are pending execution, for identifying data regarding the document and/or for text within the document, to the plurality of parties identified in the routing information. | 1. A method using a document system comprising a computer with a processor for executing software instructions for document exchange directed to execution of a document by a plurality of parties, wherein the document is inputted with an input subsystem of the document system from an input source and stored for document exchange, the method comprising: receiving routing information and identifying metadata through the input subsystem; automatically storing the document with the input subsystem from the input source as specified in the routing information along with data automatically generated and structured based on the routing information and metadata; routing the document for execution to the plurality of parties based on the routing information; archiving the executed document in a document archive after automatically verifying that it has been executed by the plurality of parties; and providing search capability with respect to documents that are executed in the document archive and documents that are pending execution, for identifying data regarding the document and/or for text within the document, to the plurality of parties identified in the routing information. 3. The method of claim 1 wherein the text searching is performed with a word processing version of a document that corresponds with a digital image of the document. | 0.689394 |
9,531,581 | 13 | 22 | 13. A system, implemented in one or more configured computer systems, for automatically registering domain names, the system comprising: a data store configured to store specific computer-executable instructions; and one or more computing devices in communication with the data store, the one or more computing devices configured to execute the specific computer-executable instructions to at least: identify a domain name source from information automatically retrieved from one or more network resources; analyze data from the domain name source for a statistically improbable phrase or an atomic term; identify a domain name candidate from the statistically improbable phrase or the atomic term; calculate a value representing a significance of the domain name candidate; determine that the value satisfies a threshold indicating that the domain name candidate is desirable; and automatically register the domain name candidate as a domain name. | 13. A system, implemented in one or more configured computer systems, for automatically registering domain names, the system comprising: a data store configured to store specific computer-executable instructions; and one or more computing devices in communication with the data store, the one or more computing devices configured to execute the specific computer-executable instructions to at least: identify a domain name source from information automatically retrieved from one or more network resources; analyze data from the domain name source for a statistically improbable phrase or an atomic term; identify a domain name candidate from the statistically improbable phrase or the atomic term; calculate a value representing a significance of the domain name candidate; determine that the value satisfies a threshold indicating that the domain name candidate is desirable; and automatically register the domain name candidate as a domain name. 22. The system of claim 13 , wherein the domain name source comprises at least one of a document, an image, a Web page, or a blog. | 0.830729 |
8,566,076 | 11 | 14 | 11. A system for speech translation, comprising: an automatic speech recognition (ASR) engine configured to receive utterances in a first language and decode the utterances to generate an original hypothesis; a bridge module connected to the ASR engine, the bridge module comprising a processor and being configured to receive the original hypothesis output from ASR engine; a transformation model included in the bridge module, the transformation model including one or more transformation features which use the processor and are applied to the original hypothesis to transform the original hypothesis into a new hypothesis that is based on an expected comfortability analysis and that is phonetically similar to the original hypothesis; and a machine translation (MT) engine connected to the bridge module and configured to translate the new hypothesis into a second language, the new hypothesis being generated to be more easily translated by the MT engine. | 11. A system for speech translation, comprising: an automatic speech recognition (ASR) engine configured to receive utterances in a first language and decode the utterances to generate an original hypothesis; a bridge module connected to the ASR engine, the bridge module comprising a processor and being configured to receive the original hypothesis output from ASR engine; a transformation model included in the bridge module, the transformation model including one or more transformation features which use the processor and are applied to the original hypothesis to transform the original hypothesis into a new hypothesis that is based on an expected comfortability analysis and that is phonetically similar to the original hypothesis; and a machine translation (MT) engine connected to the bridge module and configured to translate the new hypothesis into a second language, the new hypothesis being generated to be more easily translated by the MT engine. 14. The system as recited in claim 11 , wherein the transformation model includes a translation comfortability table to measure how comfortable the MT component is translating the new hypotheses. | 0.629278 |
8,155,826 | 13 | 16 | 13. The vehicle behavior learning method according to claim 11 , further comprising: predicting a future occurrence of the detected behavior that is kept in correspondence with the recognized target feature based on the learned behavior information. | 13. The vehicle behavior learning method according to claim 11 , further comprising: predicting a future occurrence of the detected behavior that is kept in correspondence with the recognized target feature based on the learned behavior information. 16. The vehicle behavior learning method according to claim 13 , further comprising: optimizing operations of the vehicle based on the prediction. | 0.565476 |
9,633,312 | 8 | 9 | 8. A system comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving queries from a user device, each received query being assigned to one or more topic-based categories and at least one of the received queries being assigned to multiple different topic-based categories; identifying a set of topic-based categories for the user device, the set of topic-based categories comprising each topic-based category to which at least one of the received queries is assigned; generating, using a plurality of prediction models, a category prediction of a next query to be received from the user device and that has not yet been received from the user device, the category prediction specifying at least one topic-based category to which the next query is predicted to belong, wherein: the plurality of prediction models comprising at least two prediction models that each generate a respective category prediction based on the one or more topic-based categories to which each received query is assigned; each of the plurality of prediction models using different criteria for generating the respective category predictions; and at least one of the prediction models generates a respective category prediction based on a time at which at least one received query was received for each topic-based category in the set of topic-based categories and at least one of the prediction models generates a respective category prediction independent of the time at which at the least one received query was received for each topic-based category in the set of topic-based categories; and providing, to the user device, data that cause a content item related to the at least one topic-based category to be presented at the user device. | 8. A system comprising: a data processing apparatus; and a memory storage apparatus in data communication with the data processing apparatus, the memory storage apparatus storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: receiving queries from a user device, each received query being assigned to one or more topic-based categories and at least one of the received queries being assigned to multiple different topic-based categories; identifying a set of topic-based categories for the user device, the set of topic-based categories comprising each topic-based category to which at least one of the received queries is assigned; generating, using a plurality of prediction models, a category prediction of a next query to be received from the user device and that has not yet been received from the user device, the category prediction specifying at least one topic-based category to which the next query is predicted to belong, wherein: the plurality of prediction models comprising at least two prediction models that each generate a respective category prediction based on the one or more topic-based categories to which each received query is assigned; each of the plurality of prediction models using different criteria for generating the respective category predictions; and at least one of the prediction models generates a respective category prediction based on a time at which at least one received query was received for each topic-based category in the set of topic-based categories and at least one of the prediction models generates a respective category prediction independent of the time at which at the least one received query was received for each topic-based category in the set of topic-based categories; and providing, to the user device, data that cause a content item related to the at least one topic-based category to be presented at the user device. 9. The system of claim 8 , wherein the prediction models comprise a time-based prediction model that generates a respective category prediction of the next query based on the one or more topic-based categories to which each received query is assigned and a difference in submission times of the received queries. | 0.66879 |
8,713,078 | 25 | 26 | 25. A computer system for managing video contents, comprising: a personal electronic device including a processor configured to process information; a storage subsystem configured to store information and computer program code; the computer system configured for: generating a custom taxonomy of topics personalized for a user, based on a viewing history of the user, the custom taxonomy of topics including at least one hierarchical level of subtopics from dynamic data sources, wherein generating the custom taxonomy of topics comprises: collecting a plurality of keywords related to a video topic, wherein the keywords are collected from a plurality of dynamic data sources; and utilizing a taxonomy builder for: identifying one or more video sub-topics of the video topic based on a ranking of the keywords collected for the video topic; and building a topic node in the custom taxonomy of topics, wherein the topic node includes a set comprising: a topic identifier for the video topic; a child topic identifier comprising a list of the video sub-topics identified; and a keyword section comprising the keywords collected for the video topic; and categorizing and ranking a plurality of videos by identifying keywords in video metadata associated with the plurality of videos, and using the hierarchical relationship in the customized taxonomy of topics to determine how closely the plurality of videos are related to the first video topic and the video sub-topics by comparing the keywords identified in the video metadata associated with the plurality of videos to the keyword section. | 25. A computer system for managing video contents, comprising: a personal electronic device including a processor configured to process information; a storage subsystem configured to store information and computer program code; the computer system configured for: generating a custom taxonomy of topics personalized for a user, based on a viewing history of the user, the custom taxonomy of topics including at least one hierarchical level of subtopics from dynamic data sources, wherein generating the custom taxonomy of topics comprises: collecting a plurality of keywords related to a video topic, wherein the keywords are collected from a plurality of dynamic data sources; and utilizing a taxonomy builder for: identifying one or more video sub-topics of the video topic based on a ranking of the keywords collected for the video topic; and building a topic node in the custom taxonomy of topics, wherein the topic node includes a set comprising: a topic identifier for the video topic; a child topic identifier comprising a list of the video sub-topics identified; and a keyword section comprising the keywords collected for the video topic; and categorizing and ranking a plurality of videos by identifying keywords in video metadata associated with the plurality of videos, and using the hierarchical relationship in the customized taxonomy of topics to determine how closely the plurality of videos are related to the first video topic and the video sub-topics by comparing the keywords identified in the video metadata associated with the plurality of videos to the keyword section. 26. The computer system of claim 25 , wherein: the at least one dynamic data source comprises a plurality of web sources; personalized recommendations are provided to a user based on the user's viewing history and dynamic web reference sources; the custom taxonomy of topics is personalized for a user of the personal electronic device; the custom taxonomy of topics is specific to a history of use of the personal electronic device; the personal electronic device includes said taxonomy builder; and the custom taxonomy of topics is stored on the personal electronic device. | 0.693497 |
8,994,732 | 15 | 19 | 15. A computer-implemented method, comprising acts of: receiving a freeform stroke into a stroke input interface; recognizing the stroke as related to a graph or chart, wherein recognizing the stroke comprises processing the stroke through multiple recognizers and resolving any conflicting stroke interpretations of the recognizers; managing annotations associated with the graph or chart; applying the graph or chart to user data to create a graphical view of the user data; presenting the graphical view and interactive menus as part of the graphical view; processing a new user interaction with the graphical view that changes a style of the graph or chart; automatically recalculating and transforming the user data to transform the graph or chart to the changed style according to the new user interaction to fit the graphical view; and utilizing a processor that executes instructions stored in memory to perform at least one of the acts of receiving, recognizing, managing, applying, presenting, processing, or transforming. | 15. A computer-implemented method, comprising acts of: receiving a freeform stroke into a stroke input interface; recognizing the stroke as related to a graph or chart, wherein recognizing the stroke comprises processing the stroke through multiple recognizers and resolving any conflicting stroke interpretations of the recognizers; managing annotations associated with the graph or chart; applying the graph or chart to user data to create a graphical view of the user data; presenting the graphical view and interactive menus as part of the graphical view; processing a new user interaction with the graphical view that changes a style of the graph or chart; automatically recalculating and transforming the user data to transform the graph or chart to the changed style according to the new user interaction to fit the graphical view; and utilizing a processor that executes instructions stored in memory to perform at least one of the acts of receiving, recognizing, managing, applying, presenting, processing, or transforming. 19. The method of claim 15 , further comprising scaling the user data based on a scaling stroke and filtering the user data based on a filtering stroke. | 0.733333 |
7,606,425 | 1 | 3 | 1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library. | 1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library. 3. The method of claim 1 , wherein the one or more clusters are within a feature space of the image sequence. | 0.778455 |
9,594,730 | 11 | 20 | 11. One or more non-transitory computer-readable media storing instructions which, when processed by one or more processors, cause: processing a web page to determine a plurality of segments, wherein each segment from the plurality of segments includes one or more HTML elements; each machine-based classifier of a plurality of machine-based classifiers generating, based at least upon metadata associated with two or more segments from the plurality of segments that indicates one or more presentation features in the HTML elements of the two or more segments from the plurality of segments, a probability output for each segment of the two or more segments from the plurality of segments, wherein each functional category from the plurality of functional categories corresponds to a functional role of HTML elements in the web page; wherein each machine-based classifier from the plurality of machine-based classifiers corresponds to a functional category from the plurality of functional categories; assigning, based on the plurality of probability output, one or more functional categories to each segment of the two or more segments; a first application selecting a first set of functional categories from the plurality of functional categories; a second application that is different than the first application selecting a second set of functional categories from the plurality of functional categories, wherein the second set of functional categories does not include functional categories from the first set of functional categories; the first application selecting for processing, based upon the first set of functional categories and the functional categories assigned to the two or more segments, a first set of one or more segments from the two or more segments; the second application selecting for processing, based upon the second set of functional categories and the functional categories assigned to the two or more segments, a second set of one or more segments from the two or more segments, wherein the second set of one or more segments includes at least one segment that is not in the first set of one or more segments and the first set of one or more segments includes at least one segment that is not in the second set of one or more segments; the first application processing content contained in the first set of one or more segments and not processing content contained in the second set of one or more segments; and the second application processing content contained in the second set of one or more segments and not processing content contained in the first set of one or more segments. | 11. One or more non-transitory computer-readable media storing instructions which, when processed by one or more processors, cause: processing a web page to determine a plurality of segments, wherein each segment from the plurality of segments includes one or more HTML elements; each machine-based classifier of a plurality of machine-based classifiers generating, based at least upon metadata associated with two or more segments from the plurality of segments that indicates one or more presentation features in the HTML elements of the two or more segments from the plurality of segments, a probability output for each segment of the two or more segments from the plurality of segments, wherein each functional category from the plurality of functional categories corresponds to a functional role of HTML elements in the web page; wherein each machine-based classifier from the plurality of machine-based classifiers corresponds to a functional category from the plurality of functional categories; assigning, based on the plurality of probability output, one or more functional categories to each segment of the two or more segments; a first application selecting a first set of functional categories from the plurality of functional categories; a second application that is different than the first application selecting a second set of functional categories from the plurality of functional categories, wherein the second set of functional categories does not include functional categories from the first set of functional categories; the first application selecting for processing, based upon the first set of functional categories and the functional categories assigned to the two or more segments, a first set of one or more segments from the two or more segments; the second application selecting for processing, based upon the second set of functional categories and the functional categories assigned to the two or more segments, a second set of one or more segments from the two or more segments, wherein the second set of one or more segments includes at least one segment that is not in the first set of one or more segments and the first set of one or more segments includes at least one segment that is not in the second set of one or more segments; the first application processing content contained in the first set of one or more segments and not processing content contained in the second set of one or more segments; and the second application processing content contained in the second set of one or more segments and not processing content contained in the first set of one or more segments. 20. The one or more non-transitory computer-readable media of claim 11 , wherein the first application is a web crawler and the first set of one or more segments comprises a set of segments that are assigned a main content functional category. | 0.795798 |
9,679,380 | 9 | 10 | 9. An apparatus comprising: a display; a memory configured to store instructions; and a processor communicatively coupled with the display and the memory and configured to execute the instructions, wherein the instructions cause the processor to access two or more sample images stored in the memory; transforming an input image using each of the sample images to generate output images; generate a metric for each output image corresponding to emotion conveyed by said output image, the emotions arranged along a plurality of emotion dimensions; receive a command to modify an emotion in the input image according to a specified emotion change identified by the user; obtain an emotion-transformed input image by selecting the output image whose generated metric is closest to the specified change; display the emotion-transformed image with the change in the particular emotion. | 9. An apparatus comprising: a display; a memory configured to store instructions; and a processor communicatively coupled with the display and the memory and configured to execute the instructions, wherein the instructions cause the processor to access two or more sample images stored in the memory; transforming an input image using each of the sample images to generate output images; generate a metric for each output image corresponding to emotion conveyed by said output image, the emotions arranged along a plurality of emotion dimensions; receive a command to modify an emotion in the input image according to a specified emotion change identified by the user; obtain an emotion-transformed input image by selecting the output image whose generated metric is closest to the specified change; display the emotion-transformed image with the change in the particular emotion. 10. The apparatus according to claim 9 , wherein the metric comprises values corresponding to magnitudes of the emotions conveyed. | 0.763636 |
8,886,522 | 1 | 3 | 1. One or more non-transitory, tangible computer-readable media having computer-executable instructions for performing a method by running a software program on a computer, the computer operating under an operating system, the method including issuing instructions from the software program to extract semantic bio-entity relationships or patterns from non-annotated data by natural language processing and graph theoretic algorithm, the instructions comprising: receiving a plurality of known bio-entity strings and a plurality of interaction word strings; receiving annotated text as training data that contains true and false patterns; automatically building a decision support tool based on said true and false patterns to which said non-annotated data can be parsed, said decision support tool including at least a first level and a second level, said first level having a first decision node, said second level having a second decision node, said first and second decision nodes each associated with at least a portion of said true and false patterns; receiving said non-annotated data; extracting a textual clause of said non-annotated data that contains non-triplet word strings and at least one triplet, said at least one triplet including a first bio-entity, a second bio-entity, and an interaction word, wherein said interaction word indicates a possible relationship between said first bio-entity and said second bio-entity; automatically parsing said extracted textual clause through said decision support tool to obtain a plurality of components based on dependencies among said plurality of components; extracting said at least one triplet from said plurality of components by attempting to match said plurality of components of said parsed, extracted textual clause to said first level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said first level of said decision support tool; identifying extraction of said at least one triplet as false if said plurality of components fails to match said first level of said decision support tool; as a result of said plurality of components failing to match said first level of said decision support tool, extracting said at least one triplet from said plurality of components by attempting to match said plurality of components to said second level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said second level of said decision support tool, said second level of said decision support tool being a simplified pattern of said first level of said decision support tool to capture textual clauses that are not identical to said extracted textual clause; and identifying extraction of said at least one triplet as false if said plurality of components fails to match said second level of said decision support tool. | 1. One or more non-transitory, tangible computer-readable media having computer-executable instructions for performing a method by running a software program on a computer, the computer operating under an operating system, the method including issuing instructions from the software program to extract semantic bio-entity relationships or patterns from non-annotated data by natural language processing and graph theoretic algorithm, the instructions comprising: receiving a plurality of known bio-entity strings and a plurality of interaction word strings; receiving annotated text as training data that contains true and false patterns; automatically building a decision support tool based on said true and false patterns to which said non-annotated data can be parsed, said decision support tool including at least a first level and a second level, said first level having a first decision node, said second level having a second decision node, said first and second decision nodes each associated with at least a portion of said true and false patterns; receiving said non-annotated data; extracting a textual clause of said non-annotated data that contains non-triplet word strings and at least one triplet, said at least one triplet including a first bio-entity, a second bio-entity, and an interaction word, wherein said interaction word indicates a possible relationship between said first bio-entity and said second bio-entity; automatically parsing said extracted textual clause through said decision support tool to obtain a plurality of components based on dependencies among said plurality of components; extracting said at least one triplet from said plurality of components by attempting to match said plurality of components of said parsed, extracted textual clause to said first level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said first level of said decision support tool; identifying extraction of said at least one triplet as false if said plurality of components fails to match said first level of said decision support tool; as a result of said plurality of components failing to match said first level of said decision support tool, extracting said at least one triplet from said plurality of components by attempting to match said plurality of components to said second level of said decision support tool; identifying extraction of said at least one triplet as true if said plurality of components matches said second level of said decision support tool, said second level of said decision support tool being a simplified pattern of said first level of said decision support tool to capture textual clauses that are not identical to said extracted textual clause; and identifying extraction of said at least one triplet as false if said plurality of components fails to match said second level of said decision support tool. 3. One or more non-transitory,tangible computer-readable media as in claim 1 , further comprising instructions for: receiving a structured form format corresponding to said plurality of known bio-entity strings; and storing said at least one extracted triplet in said structured form format as a result of a classification of said at least one extracted triplet being true, said storing facilitating retrieval of said at least one extracted, true triplet. | 0.85454 |
7,487,515 | 1 | 5 | 1. A computer-implemented method, comprising: providing access to an extensible markup language (XML) schema validation model of an application program to modify the XML schema validation model as the XML schema validation model will be applied to one or more XML documents to be submitted to the application program, the access being provided by one or more of: an application programming interface; and a set of message calls; passing to the XML schema validation model at least one object property configured to implement a modification in the XML schema validation model to be associated with one or more XML documents, wherein the at least one object property includes an object property for returning one of: a list of all XML schema files associated with a document; a description text of a specified XML schema violation for a specified XML element applied to a document; a location of a specified XML schema file; a Namespace uniform resource identifier associated with a specified XML schema file; a list of all XML elements suggested by the application program based on an XML schema file associated with a document and based on an editing context within the document; and a list of all XML elements in a document associated with an XML schema violation based on an associated XML schema file, wherein the modification includes one or more of: a change to an existing XML schema employed by the XML schema validation model; and one or more additional XML schemas; receiving the modification in the XML schema validation model; and applying the XML schema validation model including the modification to the one or more XML documents. | 1. A computer-implemented method, comprising: providing access to an extensible markup language (XML) schema validation model of an application program to modify the XML schema validation model as the XML schema validation model will be applied to one or more XML documents to be submitted to the application program, the access being provided by one or more of: an application programming interface; and a set of message calls; passing to the XML schema validation model at least one object property configured to implement a modification in the XML schema validation model to be associated with one or more XML documents, wherein the at least one object property includes an object property for returning one of: a list of all XML schema files associated with a document; a description text of a specified XML schema violation for a specified XML element applied to a document; a location of a specified XML schema file; a Namespace uniform resource identifier associated with a specified XML schema file; a list of all XML elements suggested by the application program based on an XML schema file associated with a document and based on an editing context within the document; and a list of all XML elements in a document associated with an XML schema violation based on an associated XML schema file, wherein the modification includes one or more of: a change to an existing XML schema employed by the XML schema validation model; and one or more additional XML schemas; receiving the modification in the XML schema validation model; and applying the XML schema validation model including the modification to the one or more XML documents. 5. The computer-implemented method of claim 1 , whereby the at least one object property includes an object method for customizing schema validation error notifications from the XML schema validation model. | 0.723118 |
9,727,606 | 13 | 15 | 13. The one or more non-transitory computer-readable media of claim 10 wherein the predicate is a first predicate of a set of predicates associated with the query, the one or more non-transitory computer-readable media further storing instructions that cause the one or more computing devices to perform operations comprising: for each predicate of the set of predicates: programming a particular circuit into the reconfigurable hardware of the filtering unit based on said each predicate, of the set of predicates, that specifies particular criteria for filtering results of the query; generating a predicate result by loading values from at least one portion of a column into the filtering unit and causing the filtering unit to apply said each predicate to the values; wherein instructions for selecting rows to return as results comprise instructions for: combining each predicate result to generate a final result that identifies rows that satisfy all criteria specified by the set of predicates; selecting the rows that are identified by the final result as satisfying the criteria specified by the set of predicates. | 13. The one or more non-transitory computer-readable media of claim 10 wherein the predicate is a first predicate of a set of predicates associated with the query, the one or more non-transitory computer-readable media further storing instructions that cause the one or more computing devices to perform operations comprising: for each predicate of the set of predicates: programming a particular circuit into the reconfigurable hardware of the filtering unit based on said each predicate, of the set of predicates, that specifies particular criteria for filtering results of the query; generating a predicate result by loading values from at least one portion of a column into the filtering unit and causing the filtering unit to apply said each predicate to the values; wherein instructions for selecting rows to return as results comprise instructions for: combining each predicate result to generate a final result that identifies rows that satisfy all criteria specified by the set of predicates; selecting the rows that are identified by the final result as satisfying the criteria specified by the set of predicates. 15. The one or more non-transitory computer-readable media of claim 13 , wherein instructions for selecting rows as results comprises instructions for: translating the final result into a set of memory addresses; wherein each memory address in the set of memory addresses identifies a memory location of a row that satisfies the criteria specified by the set of predicates. | 0.678448 |
8,886,623 | 2 | 7 | 2. The method of claim 1 further comprising determining, by the training computer, link data associated with the extracted information. | 2. The method of claim 1 further comprising determining, by the training computer, link data associated with the extracted information. 7. The method of claim 2 wherein the determining link data further comprises determining redirects. | 0.72191 |
7,672,865 | 3 | 4 | 3. The method of claim 2 , said transaction data comprising a mixture of interspersed customer purchases, said purchases comprising both of intentional purchases, which comprise a logical or signal part of said transaction data because there is a predictable pattern in intentional purchases of a customer, and emotion driven impulsive purchases, which add noise to the intentional purchase patterns of customers. | 3. The method of claim 2 , said transaction data comprising a mixture of interspersed customer purchases, said purchases comprising both of intentional purchases, which comprise a logical or signal part of said transaction data because there is a predictable pattern in intentional purchases of a customer, and emotion driven impulsive purchases, which add noise to the intentional purchase patterns of customers. 4. The method of claim 3 , further comprising: identifying, by at least one data processor, purchase patterns embedded in said transaction data that are associated with intentional behavior. | 0.5 |
8,832,048 | 12 | 13 | 12. A method of managing information comprising: providing an organization having an information management system comprising one or more rules comprising a context expression stored on a server to manage information of the organization; within the organization, providing a user logged onto a client and a confidential document managed by the information management system; storing a subset of the one or more rules of the policy on the client, wherein the subset of one or more rules of the policy are supported by the client and a first rule of the subset of one or more rules comprises translating the first rule from a first syntax format not supported by the client to a second syntax format supported by the client; when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client only to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location; after the evaluating, updating the one or more rules at the client with the rules stored at the server with one or more updated rules; and after the updating, when the user attempts to perform the operation on the confidential document, evaluating the one or more updated rules at the client only. | 12. A method of managing information comprising: providing an organization having an information management system comprising one or more rules comprising a context expression stored on a server to manage information of the organization; within the organization, providing a user logged onto a client and a confidential document managed by the information management system; storing a subset of the one or more rules of the policy on the client, wherein the subset of one or more rules of the policy are supported by the client and a first rule of the subset of one or more rules comprises translating the first rule from a first syntax format not supported by the client to a second syntax format supported by the client; when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client only to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location; after the evaluating, updating the one or more rules at the client with the rules stored at the server with one or more updated rules; and after the updating, when the user attempts to perform the operation on the confidential document, evaluating the one or more updated rules at the client only. 13. The method of claim 12 wherein the when the user attempts to perform an operation on the confidential document, evaluating the one or more rules to determine whether to store information regarding the attempted operation in a storage location is replaced by when the user performs an operation on the confidential document, storing information regarding the operation in a storage location based on the one or more rules to manage information of the organization. | 0.543945 |
8,646,029 | 1 | 13 | 1. One or more computer-readable storage memories comprising computer readable instructions which, when executed, implement: a security module configured to enable secure information transfer between a web browser's scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, the module configured to enable the at least one object to be returned across the one or more domains being configured to return a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. | 1. One or more computer-readable storage memories comprising computer readable instructions which, when executed, implement: a security module configured to enable secure information transfer between a web browser's scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, the module configured to enable the at least one object to be returned across the one or more domains being configured to return a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 13. The one or more computer-readable storage memories of claim 1 , the type system associated with the calling system being a different type system than a type system of the at least one object's origin. | 0.761682 |
8,671,110 | 6 | 8 | 6. A method comprising: receiving a request, from a model creation environment of a user device, to share a portion of a model with one or more users, the model including information relating to a computation, the model creation environment being used, by the user device, to create models, the models including the model, the model creation environment including an element and the model, the request being generated by the user device based on the user device detecting selection of the element in the model creation environment, and the receiving the request being performed by a computing device associated with a modeling infrastructure, the computing device being different than the user device; receiving the portion of the model, from the user device via the model creation environment, based on the request generated by the user device, the receiving the portion of the model being performed by the computing device; determining whether the received portion of the model is functional, the determining being performed by the computing device; and causing the received portion of the model to be made available to the one or more users based on determining whether the received portion of the model is functional, the causing being performed by the computing device. | 6. A method comprising: receiving a request, from a model creation environment of a user device, to share a portion of a model with one or more users, the model including information relating to a computation, the model creation environment being used, by the user device, to create models, the models including the model, the model creation environment including an element and the model, the request being generated by the user device based on the user device detecting selection of the element in the model creation environment, and the receiving the request being performed by a computing device associated with a modeling infrastructure, the computing device being different than the user device; receiving the portion of the model, from the user device via the model creation environment, based on the request generated by the user device, the receiving the portion of the model being performed by the computing device; determining whether the received portion of the model is functional, the determining being performed by the computing device; and causing the received portion of the model to be made available to the one or more users based on determining whether the received portion of the model is functional, the causing being performed by the computing device. 8. The method of claim 6 , where the model includes a dynamic model. | 0.907104 |
9,395,880 | 4 | 5 | 4. The one or more computer storage media of claim 1 , wherein the method further comprises: receiving user input that selects a first predefined type in one of the one or more fields; and in response to the selection of the first predefined type, displaying one or more additional user interface controls that the user can manipulate to define configurable parameters specific to the first predefined type. | 4. The one or more computer storage media of claim 1 , wherein the method further comprises: receiving user input that selects a first predefined type in one of the one or more fields; and in response to the selection of the first predefined type, displaying one or more additional user interface controls that the user can manipulate to define configurable parameters specific to the first predefined type. 5. The one or more computer storage media of claim 4 , wherein the one or more additional user interface controls include a node path field for receiving a node path, the node path field including a button for launching a node path lookup dialogue, the method further comprising: receiving user input that selects the button; displaying the node path lookup dialogue that includes a sample message; receiving user input that selects a node in the sample message; and automatically creating a node path to the selected node in the node path field. | 0.547264 |
8,112,493 | 3 | 4 | 3. The system of claim 1 , wherein said program logic comprises servlets and wherein said views comprise Java server pages (JSPs). | 3. The system of claim 1 , wherein said program logic comprises servlets and wherein said views comprise Java server pages (JSPs). 4. The system of claim 3 , further comprising a custom tag disposed in said first view for invoking said access checking logic and for omitting said linkage responsive to said access checking logic. | 0.5 |
8,375,299 | 12 | 13 | 12. The computer-readable storage medium of claim 8 , wherein generating the twisties from the text comprises, prior to prompting for confirmation of the twistie headings: generating the twistie heading for each of the twisties. | 12. The computer-readable storage medium of claim 8 , wherein generating the twisties from the text comprises, prior to prompting for confirmation of the twistie headings: generating the twistie heading for each of the twisties. 13. The computer-readable storage medium of claim 12 , wherein the twistie heading for each of the twisties is generated from a corresponding twistie body. | 0.5 |
8,990,889 | 2 | 3 | 2. A system, comprising: at least one processor, and at least one memory storing instructions that, when executed by the at least one processor, cause the system to: receive, by a credentialing and access control system, identity and authentication information associated with at least one internal identity from at least one electronic identity provider that is external to the credentialing and access control system, based on permission granted by at least one user; generate at least a first physical resource token for permitting physical access to a first physical resource; associate the first physical resource token with the at least one internal identity; receive, by the credentialing and access control system and from the at least one user, identity and authentication information derived from the external identity provider that is associated with the at least one internal identity; receive, by the credentialing and access control system, an indication of interaction of the first physical resource token with the first physical resource; and grant access to the first physical resource. | 2. A system, comprising: at least one processor, and at least one memory storing instructions that, when executed by the at least one processor, cause the system to: receive, by a credentialing and access control system, identity and authentication information associated with at least one internal identity from at least one electronic identity provider that is external to the credentialing and access control system, based on permission granted by at least one user; generate at least a first physical resource token for permitting physical access to a first physical resource; associate the first physical resource token with the at least one internal identity; receive, by the credentialing and access control system and from the at least one user, identity and authentication information derived from the external identity provider that is associated with the at least one internal identity; receive, by the credentialing and access control system, an indication of interaction of the first physical resource token with the first physical resource; and grant access to the first physical resource. 3. The system of claim 2 wherein the instructions further cause the system to send configuration instructions to the first physical resource so as to permit access upon the receipt by the first physical resource of the first resource token. | 0.827586 |
9,110,890 | 15 | 17 | 15. The apparatus of claim 14 , wherein the static communication language encoding selector is further operable to: determine a third language indicated for a third avatar of the plurality of avatars; determine that the plurality of encodings does not include an encoding of the static communication in the third language; request a translation of the static communication into the third language which yields a third encoding of the static communication in the third language; associate the third encoding with the static communication object; and transmit the third encoding to a third device, which corresponds to the third avatar, for the third device to render the static communication object with the third encoding of the static communication in the third language. | 15. The apparatus of claim 14 , wherein the static communication language encoding selector is further operable to: determine a third language indicated for a third avatar of the plurality of avatars; determine that the plurality of encodings does not include an encoding of the static communication in the third language; request a translation of the static communication into the third language which yields a third encoding of the static communication in the third language; associate the third encoding with the static communication object; and transmit the third encoding to a third device, which corresponds to the third avatar, for the third device to render the static communication object with the third encoding of the static communication in the third language. 17. The apparatus of claim 15 , wherein the static communication language encoding selector being operable to associate the third encoding of the static communication with the static communication object comprises the static communication language encoding selector being operable to at least one of modify the static communication object to include the third encoding and modify the static communication object to reference the third encoding of the static communication. | 0.5 |
9,135,653 | 232 | 233 | 232. The method of claim 205 comprising at a first time, serving personalized content to the recipient based on the first value associated with the first edge. | 232. The method of claim 205 comprising at a first time, serving personalized content to the recipient based on the first value associated with the first edge. 233. The method of claim 232 comprising at a second time, serving personalized content to the recipient based on the second value associated with the first edge. | 0.5 |
8,578,263 | 1 | 3 | 1. A method for differential dynamic content delivery, the method comprising: providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document, the session document further including a first classified structural element and a second classified structural element received from a presenter; providing a session copy of a first user profile including a first user classification associated with a first classified structural element; providing a session copy of a second user profile including a second user classification associated with the first classified structural element; receiving, from the presenter, a user classification instruction to change the second user classification in the session copy of the second user profile; changing the second user classification to an altered user classification in the session copy of the second user profile to associate the second user classification with a second classified structural element in dependence upon the presenter's instruction, wherein the first user classification remains associated with the first classified structural element; presenting the second classified structural element to the second user in response to the second user classification becoming associated with the second classified structural element; and presenting the first classified structural element to the first user in response to the first user classification remaining associated with the first classified structural element. | 1. A method for differential dynamic content delivery, the method comprising: providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document, the session document further including a first classified structural element and a second classified structural element received from a presenter; providing a session copy of a first user profile including a first user classification associated with a first classified structural element; providing a session copy of a second user profile including a second user classification associated with the first classified structural element; receiving, from the presenter, a user classification instruction to change the second user classification in the session copy of the second user profile; changing the second user classification to an altered user classification in the session copy of the second user profile to associate the second user classification with a second classified structural element in dependence upon the presenter's instruction, wherein the first user classification remains associated with the first classified structural element; presenting the second classified structural element to the second user in response to the second user classification becoming associated with the second classified structural element; and presenting the first classified structural element to the first user in response to the first user classification remaining associated with the first classified structural element. 3. The method of claim 1 wherein providing the session copy of the second user profile including the second user classification further comprises copying at least a portion of the second user profile. | 0.842767 |
9,607,105 | 9 | 10 | 9. The one or more non-transitory computer-readable media of claim 5 , wherein the receiving the search query from the user device comprises receiving the search query from an electronic book reader device. | 9. The one or more non-transitory computer-readable media of claim 5 , wherein the receiving the search query from the user device comprises receiving the search query from an electronic book reader device. 10. The one or more non-transitory computer-readable media of claim 9 , wherein the receiving the search query comprises receiving a selection of text from the electronic book being displayed on the electronic book reader device. | 0.5 |
8,423,886 | 1 | 5 | 1. A system for document analysis, comprising a processor and software configured to a) receive textual documents over an electronic communication network and convert textual documents into image files, identify text in said image files, wherein said text is mapped to the document image using a database comprising text of the document; b) permit a user to add contextual markups to said image files wherein said contextual markups are images or HTML tags that are added to an invisible image that maps exactly onto each image of said image file, and wherein said image file is not modified, c) generate an originality report, wherein said generating said originality report comprises the step of highlighting said sections of said image file identified in the originality report as allegedly containing plagiarized text, wherein said highlighting is glyph aware highlighting that associates glyphs with images using the pixel coordinates of the image, which maps to a text database of said document; and d) display said image file on a display screen, wherein said image file simultaneously displays said contextual markups and said highlights. | 1. A system for document analysis, comprising a processor and software configured to a) receive textual documents over an electronic communication network and convert textual documents into image files, identify text in said image files, wherein said text is mapped to the document image using a database comprising text of the document; b) permit a user to add contextual markups to said image files wherein said contextual markups are images or HTML tags that are added to an invisible image that maps exactly onto each image of said image file, and wherein said image file is not modified, c) generate an originality report, wherein said generating said originality report comprises the step of highlighting said sections of said image file identified in the originality report as allegedly containing plagiarized text, wherein said highlighting is glyph aware highlighting that associates glyphs with images using the pixel coordinates of the image, which maps to a text database of said document; and d) display said image file on a display screen, wherein said image file simultaneously displays said contextual markups and said highlights. 5. The system of claim 1 , wherein said contextual markups are selected from the from the group consisting of editorial comments, peer reviewer comments, corrections, annotations, rubrics, symbols and comments added by said user. | 0.5 |
8,056,128 | 27 | 43 | 27. A method performed by one or more server devices, the method comprising: determining, by one or more processors of the one or more server devices, that a document in a set of ranked documents requests personal or private information from a user, where documents in the set of ranked documents that are well known are ranked higher than documents that are not well known; identifying, by one or more processors of the one or more server devices, the document as being suspect based on whether the document requests personal or private information from the user; analyzing, by one or more processors of the one or more server devices, data or attributes associated with the suspect document, where analyzing data or attributes associated with the suspect document includes analyzing a ranking of the suspect document relative to rankings of other documents in the set of ranked documents; assigning, by one or more processors of the one or more server devices, a fraud score, based on analyzing the data or attributes, to the suspect document; comparing, by one or more processors of the one or more server devices, the fraud score to a first threshold and to a second different threshold; determining, by one or more processors of the one or more server devices, that the suspect document is trustworthy when the fraud score does not pass the first threshold; determining, by one or more processors of the one or more server devices, that the suspect document is untrustworthy when the fraud score passes the second different threshold; obtaining, by one or more processors of the one or more server devices, a determination of trustworthiness from the user when the fraud score is between the first threshold and the second different threshold; and storing an identifier for a document, the fraud score, and a result representing a trustworthiness of the suspect document in a memory associated with the one or more server devices. | 27. A method performed by one or more server devices, the method comprising: determining, by one or more processors of the one or more server devices, that a document in a set of ranked documents requests personal or private information from a user, where documents in the set of ranked documents that are well known are ranked higher than documents that are not well known; identifying, by one or more processors of the one or more server devices, the document as being suspect based on whether the document requests personal or private information from the user; analyzing, by one or more processors of the one or more server devices, data or attributes associated with the suspect document, where analyzing data or attributes associated with the suspect document includes analyzing a ranking of the suspect document relative to rankings of other documents in the set of ranked documents; assigning, by one or more processors of the one or more server devices, a fraud score, based on analyzing the data or attributes, to the suspect document; comparing, by one or more processors of the one or more server devices, the fraud score to a first threshold and to a second different threshold; determining, by one or more processors of the one or more server devices, that the suspect document is trustworthy when the fraud score does not pass the first threshold; determining, by one or more processors of the one or more server devices, that the suspect document is untrustworthy when the fraud score passes the second different threshold; obtaining, by one or more processors of the one or more server devices, a determination of trustworthiness from the user when the fraud score is between the first threshold and the second different threshold; and storing an identifier for a document, the fraud score, and a result representing a trustworthiness of the suspect document in a memory associated with the one or more server devices. 43. The method of claim 27 , where analyzing data or attributes associated with the suspect document further comprises: analyzing user selections of documents from results from an executed search. | 0.70303 |
8,020,187 | 7 | 9 | 7. A method for associating an electronic document work with an action, the document work comprising text, the method comprising: a) electronically extracting within a portable client device features from the electronic document work; b) transmitting the extracted features from the portable client device to one or more servers; c) receiving at the portable client device from the one or more servers an identification of the electronic document work based on the extracted features, wherein the identification is based on a non-exhaustive search identifying a neighbor; d) electronically determining an action based on the identification of the electronic document work; and e) electronically performing the action on the portable client device. | 7. A method for associating an electronic document work with an action, the document work comprising text, the method comprising: a) electronically extracting within a portable client device features from the electronic document work; b) transmitting the extracted features from the portable client device to one or more servers; c) receiving at the portable client device from the one or more servers an identification of the electronic document work based on the extracted features, wherein the identification is based on a non-exhaustive search identifying a neighbor; d) electronically determining an action based on the identification of the electronic document work; and e) electronically performing the action on the portable client device. 9. The method of claim 7 , wherein the electronic document work comprises an image. | 0.82265 |
10,019,994 | 4 | 5 | 4. The method of claim 2 , wherein the collection includes hashtags that meet a predefined popularity metric. | 4. The method of claim 2 , wherein the collection includes hashtags that meet a predefined popularity metric. 5. The method of claim 4 , wherein the predefined popularity metric is a frequency of appearance in the social network within a predefined time period. | 0.5 |
9,716,686 | 1 | 30 | 1. A method for obtaining device information comprising: sending a device description request message to a plurality of remote devices, wherein the device description request message comprises indications of criteria for a responding device that is at least one of the plurality of remote devices, wherein the indications of criteria for the responding device comprises: a fabric identifier that identifies a fabric to which the responding device is connected; a device mode that indicates a mode for the responding device; a vendor identifier that identifies a vendor for the responding device; and a product identifier that identifies a product type for the responding device; and receiving a response message from only the responding device using a wireless communication protocol capable of utilizing more than a single frequency band in response to the device description request message that satisfy all criteria indicated in the indications of criteria, wherein the response message includes device description data about the responding device, and the device description data in the response message is encoded in a tag-length-value format. | 1. A method for obtaining device information comprising: sending a device description request message to a plurality of remote devices, wherein the device description request message comprises indications of criteria for a responding device that is at least one of the plurality of remote devices, wherein the indications of criteria for the responding device comprises: a fabric identifier that identifies a fabric to which the responding device is connected; a device mode that indicates a mode for the responding device; a vendor identifier that identifies a vendor for the responding device; and a product identifier that identifies a product type for the responding device; and receiving a response message from only the responding device using a wireless communication protocol capable of utilizing more than a single frequency band in response to the device description request message that satisfy all criteria indicated in the indications of criteria, wherein the response message includes device description data about the responding device, and the device description data in the response message is encoded in a tag-length-value format. 30. The method of claim 1 , further comprising causing the responding device to add a network using an add network request, wherein the add network request comprises a network configuration field encoded in the tag-length-value format that contains configuration details for the network to be added or created by the responding device, and wherein the configuration details comprise a network name, security types, and credentials for the network. | 0.5 |
8,172,882 | 1 | 6 | 1. An implant comprising: a first hook adapted to be hooked onto a first lateral border of a first superior articular facet of a vertebra; a second hook adapted to be hooked onto a second lateral border of a second superior articular facet of said same vertebra; a connector coupled to the first and second hooks, the connector configured to be positioned between the first hook and the second hook and superior to a spinous process of said same vertebra; and a first lock associated with the first hook and a second lock associated with the second hook; whereby the first hook is adapted to be hooked around the first lateral border of the first superior articular facet, the second hook is adapted to be hooked around the second lateral border of the second superior articular facet; and whereby the first hook and second hook are configured to be moved along said connector towards said spinous process, such that the first hook and second hook can then be locked in place relative to said connector thereby securing the implant to said vertebra; and whereby the first and second hooks each comprise: an upper portion that accepts the connector; a lower portion adapted to engage a lateral border of a superior articular facet; and a movable joint connecting the upper portion and the lower portion such that the lower portion can move relative to the upper portion. | 1. An implant comprising: a first hook adapted to be hooked onto a first lateral border of a first superior articular facet of a vertebra; a second hook adapted to be hooked onto a second lateral border of a second superior articular facet of said same vertebra; a connector coupled to the first and second hooks, the connector configured to be positioned between the first hook and the second hook and superior to a spinous process of said same vertebra; and a first lock associated with the first hook and a second lock associated with the second hook; whereby the first hook is adapted to be hooked around the first lateral border of the first superior articular facet, the second hook is adapted to be hooked around the second lateral border of the second superior articular facet; and whereby the first hook and second hook are configured to be moved along said connector towards said spinous process, such that the first hook and second hook can then be locked in place relative to said connector thereby securing the implant to said vertebra; and whereby the first and second hooks each comprise: an upper portion that accepts the connector; a lower portion adapted to engage a lateral border of a superior articular facet; and a movable joint connecting the upper portion and the lower portion such that the lower portion can move relative to the upper portion. 6. The implant of claim 1 , wherein the connector is configured to be fixed with compression applied by a first set screw to the first hook and by a second set screw to the second hook. | 0.793065 |
9,791,999 | 13 | 15 | 13. An apparatus comprising: a user interface configured to: present a touch phrase button and a plurality of option buttons; receive an input associated with the touch phrase button or the plurality of option buttons; and a processor configured to: receive a first input associated with a touch phrase button, wherein the touch phrase button is in a first state; in response to the first input associated with the touch phrase button, display a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receive a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, display the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text. | 13. An apparatus comprising: a user interface configured to: present a touch phrase button and a plurality of option buttons; receive an input associated with the touch phrase button or the plurality of option buttons; and a processor configured to: receive a first input associated with a touch phrase button, wherein the touch phrase button is in a first state; in response to the first input associated with the touch phrase button, display a plurality of option buttons associated with the touch phrase button, wherein a first text is displayed within each of the option buttons; receive a second input associated with at least one of the plurality of option buttons; and in response to the second input associated with at least one of the plurality of option buttons, display the touch phrase button in a second state, wherein displaying the touch phrase button in the second state comprises automatically associating a second text with the touch phrase button without user input of the second text, wherein the second text is displayed within the touch phrase button, and wherein the second text is related to the second input, and wherein the first text is different than the second text. 15. The apparatus of claim 13 , wherein the plurality of option buttons comprises: a first subset of option buttons comprising answers to a first question, wherein the first subset of option buttons are associated with a first answer type, and a second subset of option buttons comprising answers to a second question, wherein the second subset of option buttons are associated with a second answer type, wherein the first answer type and the second answer type are different. | 0.5 |
9,454,514 | 1 | 5 | 1. A method, comprising: executing, by a processing device, a numeric conversion module as a front-end and back-end translation interface to an application executed by the processing device and compiled by a compiler, wherein the numeric conversion module is dedicated for use by the application and is not used by other applications executed by the processing device; receiving, by the processing device during runtime of the application, a string array of numeric data in a local language other than English wherein the numeric data is used in calculations performed by the application during runtime of the application to generate calculated numerals that are not known in code of the application during compilation of the application by the compiler; converting, by the processing device during the runtime of the application, characters of the string array of numeric data from local language characters not in English alphabet characters and not representable within the 128 characters of an American Standard Code for Information Interchange (ASCII) format into English alphabet digits representable by the 128 characters of ASCII format by utilizing a number conversion matrix; providing, by the processing device during the runtime of the application, the English alphabet digits in the ASCII format to a processing function of the application for use with the calculations of the application during the runtime of the application; performing, by the processing device during runtime of an application, the processing function for the application to calculate numerals as English alphabet digits in the ASCII format; converting, by the processing device during the runtime of the application, the calculated numerals to translated numeric data in the local language other than English by utilizing the number conversion matrix; and providing the translated numeric data to an end user of the application during the runtime of the application without modifying the compiler to process the numeric data in the local language other than English. | 1. A method, comprising: executing, by a processing device, a numeric conversion module as a front-end and back-end translation interface to an application executed by the processing device and compiled by a compiler, wherein the numeric conversion module is dedicated for use by the application and is not used by other applications executed by the processing device; receiving, by the processing device during runtime of the application, a string array of numeric data in a local language other than English wherein the numeric data is used in calculations performed by the application during runtime of the application to generate calculated numerals that are not known in code of the application during compilation of the application by the compiler; converting, by the processing device during the runtime of the application, characters of the string array of numeric data from local language characters not in English alphabet characters and not representable within the 128 characters of an American Standard Code for Information Interchange (ASCII) format into English alphabet digits representable by the 128 characters of ASCII format by utilizing a number conversion matrix; providing, by the processing device during the runtime of the application, the English alphabet digits in the ASCII format to a processing function of the application for use with the calculations of the application during the runtime of the application; performing, by the processing device during runtime of an application, the processing function for the application to calculate numerals as English alphabet digits in the ASCII format; converting, by the processing device during the runtime of the application, the calculated numerals to translated numeric data in the local language other than English by utilizing the number conversion matrix; and providing the translated numeric data to an end user of the application during the runtime of the application without modifying the compiler to process the numeric data in the local language other than English. 5. The method of claim 1 , wherein the string array of numeric data in a local language is not known prior to execution of the application. | 0.781447 |
8,290,779 | 11 | 20 | 11. An apparatus comprising: a communication interface configured to receive a voice call placed from a source station to a destination station; and a processor coupled to the communication interface, wherein the processor is configured to, determine that the voice call includes a translation indicator specifying invocation of a translation service managed by a service provider, based at least in part on the determination, directing the voice call to a gateway configured to route the voice call over a data network to a translation platform, wherein the translation platform is configured to translate, in real-time, speech associated with the voice call from a first language to a second language; and wherein the communication interface is further configured to transmit the translated speech to the destination station. | 11. An apparatus comprising: a communication interface configured to receive a voice call placed from a source station to a destination station; and a processor coupled to the communication interface, wherein the processor is configured to, determine that the voice call includes a translation indicator specifying invocation of a translation service managed by a service provider, based at least in part on the determination, directing the voice call to a gateway configured to route the voice call over a data network to a translation platform, wherein the translation platform is configured to translate, in real-time, speech associated with the voice call from a first language to a second language; and wherein the communication interface is further configured to transmit the translated speech to the destination station. 20. An apparatus according to claim 11 , wherein the voice call is placed over one of either a circuit switched telephony network or a packetized voice network. | 0.792746 |
7,562,286 | 10 | 12 | 10. The document management system according to claim 9 , wherein the document call request accepting device of the document management apparatus is configured to accept, together with the document ID, a request of a method that designates information to be returned by the returning device of the document management apparatus to the client apparatus making the document call request, and wherein the returning device of the document management apparatus is configured to return, when the connection to the desired node specified by the document ID has been made, the information designated by the method to be returned by the returning device to the client apparatus, the information designated by the method to the client apparatus making the document call request. | 10. The document management system according to claim 9 , wherein the document call request accepting device of the document management apparatus is configured to accept, together with the document ID, a request of a method that designates information to be returned by the returning device of the document management apparatus to the client apparatus making the document call request, and wherein the returning device of the document management apparatus is configured to return, when the connection to the desired node specified by the document ID has been made, the information designated by the method to be returned by the returning device to the client apparatus, the information designated by the method to the client apparatus making the document call request. 12. The document management system according to claim 10 , wherein the document call request accepting device is configured to accept, as the request of the method, a request for a content element of the desired node specified by the document ID, and wherein the returning device is configured to return, when the request for the content element of the desired node specified by the document ID has been accepted by the document call request accepting device, the content element of the desired node specified by the document ID, the content element of the desired node specified by the document ID to the client apparatus making the document call request. | 0.5 |
8,954,837 | 9 | 12 | 9. A system for inserting delimiters into a formula, comprising: a processor configured to: successively receive a plurality of selections of cells while in a formula editing mode in a host cell into which a formula is being entered; automatically determine a current context of the formula with respect to which the selections are received; and automatically insert a first delimiter type between references to the cells inserted into the formula in response to receiving the plurality of selections when the current context comprises a first context and automatically insert a second delimiter type between references inserted into the formula in response to receiving the plurality of selections when the current context comprises a second context, wherein each first and second delimiter type spatially separates the references to the cells from each other within the formula by being inserted between the references to the cells; and a memory coupled to the processor and configured to provide instructions to the processor. | 9. A system for inserting delimiters into a formula, comprising: a processor configured to: successively receive a plurality of selections of cells while in a formula editing mode in a host cell into which a formula is being entered; automatically determine a current context of the formula with respect to which the selections are received; and automatically insert a first delimiter type between references to the cells inserted into the formula in response to receiving the plurality of selections when the current context comprises a first context and automatically insert a second delimiter type between references inserted into the formula in response to receiving the plurality of selections when the current context comprises a second context, wherein each first and second delimiter type spatially separates the references to the cells from each other within the formula by being inserted between the references to the cells; and a memory coupled to the processor and configured to provide instructions to the processor. 12. A system as recited in claim 9 , wherein the first context comprises not being in an argument list of a function and wherein the first delimiter type comprises a plus sign. | 0.60181 |
9,972,306 | 12 | 20 | 12. A computer-implemented method for training acoustic models in an automatic speech recognition system comprising the steps of: a. training a first acoustic model in the automatic speech recognition system using a speech corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files by calculating a maximum likelihood criterion of the speech corpus and estimating parameters of a probability distribution of said first acoustic model that maximize the maximum likelihood criterion; b. performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system and determining an average frame likelihood score β for each of the plurality of speech audio files; c. calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the entire corpus; d. performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the plurality of transcriptions in the automatic speech recognition system; e. calculating a phoneme recognition accuracy γ for each of the plurality of speech audio files and a global phoneme recognition accuracy v for the plurality of speech audio files; f. creating a subset speech corpus comprising audio files retained from the plurality of speech audio files which meet at least one predetermined criterion indicating that an audio file has good audio quality, the at least one predetermined criterion comprising at least one criterion selected from the group comprising: a first criterion based on the average frame likelihood score β of the retained speech audio file and the global frame likelihood score δ; and a second criterion based on the phoneme recognition accuracy γ of the retained speech audio file and the global phoneme recognition accuracy v; and g. training a second acoustic model in the automatic speech recognition system with said subset speech corpus. | 12. A computer-implemented method for training acoustic models in an automatic speech recognition system comprising the steps of: a. training a first acoustic model in the automatic speech recognition system using a speech corpus comprising a plurality of speech audio files and a respective plurality of transcriptions for the plurality of speech audio files by calculating a maximum likelihood criterion of the speech corpus and estimating parameters of a probability distribution of said first acoustic model that maximize the maximum likelihood criterion; b. performing a forced Viterbi alignment of the plurality of speech audio files using the trained first acoustic model in the automatic speech recognition system and determining an average frame likelihood score β for each of the plurality of speech audio files; c. calculating a global frame likelihood score δ for the plurality of speech audio files, wherein the global frame likelihood score δ comprises an average of frame likelihoods over the entire corpus; d. performing a phoneme recognition of the plurality of speech audio files using the trained first acoustic model and the plurality of transcriptions in the automatic speech recognition system; e. calculating a phoneme recognition accuracy γ for each of the plurality of speech audio files and a global phoneme recognition accuracy v for the plurality of speech audio files; f. creating a subset speech corpus comprising audio files retained from the plurality of speech audio files which meet at least one predetermined criterion indicating that an audio file has good audio quality, the at least one predetermined criterion comprising at least one criterion selected from the group comprising: a first criterion based on the average frame likelihood score β of the retained speech audio file and the global frame likelihood score δ; and a second criterion based on the phoneme recognition accuracy γ of the retained speech audio file and the global phoneme recognition accuracy v; and g. training a second acoustic model in the automatic speech recognition system with said subset speech corpus. 20. The method of claim 12 , further comprising the step of using the mathematical equation: v = ∑ r = 1 R γ r R to obtain the global phoneme recognition accuracy, wherein γ r represents the phoneme recognition accuracy of a total likelihood score α r of an audio file α r of the plurality of speech audio files. | 0.632558 |
9,710,843 | 1 | 13 | 1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score at least partially based on at least one customization attribute associated with that unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score at least partially based on at least one condition attribute associated with that unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score for that unique item, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties. | 1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score at least partially based on at least one customization attribute associated with that unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score at least partially based on at least one condition attribute associated with that unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score for that unique item, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties. 13. The computer-based recommendation system of claim 1 , wherein the plurality of unique items comprises at least 100 unique items, and generating the recommendation of unique items occurs in real time. | 0.848054 |
7,523,394 | 1 | 4 | 1. A computer-readable storage medium having computer-executable components, comprising: a first component for reading a word-processor document stored as a single XML file; a second component that utilizes an XSD for interpreting the word-processor document; wherein the XSD represents a word-processor's rich formatting and wherein the XSD is published and is available to applications other than the word-processor; a third component for performing actions on the word-processor document; wherein the actions comprise: fully recreating the word-processor document according to a word processor's set of features; storing an image within the word-processor document as a binary encoding; placing all of the text within the word-processor document such that only the text of the word-processor document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; and storing template information as a binary encoding within the word-processor document; and a fourth component configured to validate the word-process document. | 1. A computer-readable storage medium having computer-executable components, comprising: a first component for reading a word-processor document stored as a single XML file; a second component that utilizes an XSD for interpreting the word-processor document; wherein the XSD represents a word-processor's rich formatting and wherein the XSD is published and is available to applications other than the word-processor; a third component for performing actions on the word-processor document; wherein the actions comprise: fully recreating the word-processor document according to a word processor's set of features; storing an image within the word-processor document as a binary encoding; placing all of the text within the word-processor document such that only the text of the word-processor document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; and storing template information as a binary encoding within the word-processor document; and a fourth component configured to validate the word-process document. 4. The computer-readable storage medium of claim 1 , wherein the actions may be selected from parsing, modifying, reading, and creating the word-processor document. | 0.677165 |
8,672,686 | 14 | 23 | 14. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, causes the processor to perform a method for teaching a student in a computer-based learning environment, the method comprising: identifying a first concept that was learned by a first student and that is related to a second concept to be learned by the first student; identifying a first type of content used to teach the first concept to the first student; identifying at least one other student that learned the first concept from the first type of content; identifying a second type of content through which the at least one other student learned the second concept; selecting content corresponding to the second concept and the second type of content; and presenting the content corresponding to the second concept and the second type of content to the first student. | 14. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, causes the processor to perform a method for teaching a student in a computer-based learning environment, the method comprising: identifying a first concept that was learned by a first student and that is related to a second concept to be learned by the first student; identifying a first type of content used to teach the first concept to the first student; identifying at least one other student that learned the first concept from the first type of content; identifying a second type of content through which the at least one other student learned the second concept; selecting content corresponding to the second concept and the second type of content; and presenting the content corresponding to the second concept and the second type of content to the first student. 23. The non-transitory computer-readable medium of claim 14 , wherein selecting the content is based on the length of time the first student spends learning with a type of content corresponding to the first content. | 0.794455 |
9,804,777 | 11 | 15 | 11. A device comprising: a memory; and one or more programmable processors configured to: output, for display, a plurality of characters; receive an input indicative of a slide gesture across one or more regions of a presence-sensitive input device that are associated with a group of characters included in the plurality of characters; determine, based at least in part on one or more of an origination point and a speed of movement associated with the slide gesture, whether the slide gesture represents a character string-level selection or a character-level selection from the group of characters, wherein the character string-level selection comprises a multi-character selection of a character string from the group of characters; responsive to determining that the slide gesture represents the character string-level selection from the group of characters and determining that the input indicative of the slide gesture covers only a portion of at least one character string included in the group of characters, output for display, a graphical selection of the at least one character string, such that the at least one character string is visually differentiated from any of the plurality of characters not included in the group of characters, wherein the character string comprises two or more consecutive characters included in the group of characters, and wherein the at least one character string does not comprise any space characters; and responsive to determining that the slide gesture represents the character-level selection from the group of characters, output for display and in single character increments, a graphical selection of at least one character included in the group of characters, such that the at least one character is visually differentiated from any of the plurality of characters not included in the group of characters; and output, for display and in a preview area of a user interface (UT), one or more occluded characters of the plurality of characters, wherein the plurality of characters is displayed at a display area of the UI, wherein the computing device detects a user contact at a region of the presence-sensitive input device that is associated with the one or more occluded characters, and wherein the preview area of the UI is different from the display area of the UI. | 11. A device comprising: a memory; and one or more programmable processors configured to: output, for display, a plurality of characters; receive an input indicative of a slide gesture across one or more regions of a presence-sensitive input device that are associated with a group of characters included in the plurality of characters; determine, based at least in part on one or more of an origination point and a speed of movement associated with the slide gesture, whether the slide gesture represents a character string-level selection or a character-level selection from the group of characters, wherein the character string-level selection comprises a multi-character selection of a character string from the group of characters; responsive to determining that the slide gesture represents the character string-level selection from the group of characters and determining that the input indicative of the slide gesture covers only a portion of at least one character string included in the group of characters, output for display, a graphical selection of the at least one character string, such that the at least one character string is visually differentiated from any of the plurality of characters not included in the group of characters, wherein the character string comprises two or more consecutive characters included in the group of characters, and wherein the at least one character string does not comprise any space characters; and responsive to determining that the slide gesture represents the character-level selection from the group of characters, output for display and in single character increments, a graphical selection of at least one character included in the group of characters, such that the at least one character is visually differentiated from any of the plurality of characters not included in the group of characters; and output, for display and in a preview area of a user interface (UT), one or more occluded characters of the plurality of characters, wherein the plurality of characters is displayed at a display area of the UI, wherein the computing device detects a user contact at a region of the presence-sensitive input device that is associated with the one or more occluded characters, and wherein the preview area of the UI is different from the display area of the UI. 15. The device of claim 11 , wherein the one or more programmable processors are further configured to: output, for display in a user interface (UI), at least two selection handles, such that at least a first selection handle is positioned before the at least one character string or before the at least one character within the UI, and a second selection handle is positioned after the at least one character string or after the at least one selected character within the UI. | 0.704715 |
7,644,057 | 21 | 22 | 21. The system for classifying text of claim 19 , wherein the statistical engine is further configured to receive real-time feedback to adapt the statistical information provided to one or more learning nodes of the set of learning nodes. | 21. The system for classifying text of claim 19 , wherein the statistical engine is further configured to receive real-time feedback to adapt the statistical information provided to one or more learning nodes of the set of learning nodes. 22. The system for classifying text of claim 21 , wherein the real-time feedback comprises a response of a human agent to the relevance of the text to associated categories based upon the set of match scores. | 0.520737 |
9,942,611 | 17 | 18 | 17. The system of claim 12 , wherein the control circuitry performs a user-selected action at an end of the countdown of the amount of time remaining in the user selected period of time. | 17. The system of claim 12 , wherein the control circuitry performs a user-selected action at an end of the countdown of the amount of time remaining in the user selected period of time. 18. The system of claim 17 , wherein the action comprises generating for display an alert box with a reminder. | 0.612676 |
8,548,153 | 1 | 6 | 1. A method for implementing customized rules for controlling incoming customer communications, comprising: providing an initial menu for customizing rules for controlling incoming customer communications, the initial menu including a selectable option to modify an existing customized rule for controlling incoming customer communications and a selectable option to create a new customized rule for controlling incoming customer communications; processing a request to create a new customized rule for controlling incoming customer communications, wherein the new customized rule is configured to challenge a source of inbound communications for information configured to authorize the inbound communications; providing an initial selection criteria menu to create the new customized rule for controlling incoming customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling incoming customer communications, processing a received selection of a preexisting template from the list of preexisting templates, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input, wherein the stored new customized rule is specified to apply to inbound communications; and when the new customized rule will be built starting from initial blank rule criteria, providing initial blank rule criteria for creating a new customized rule for controlling incoming customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; and wherein the stored new customized rule is implemented at an internal network node of a communications service provider to process communications in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. | 1. A method for implementing customized rules for controlling incoming customer communications, comprising: providing an initial menu for customizing rules for controlling incoming customer communications, the initial menu including a selectable option to modify an existing customized rule for controlling incoming customer communications and a selectable option to create a new customized rule for controlling incoming customer communications; processing a request to create a new customized rule for controlling incoming customer communications, wherein the new customized rule is configured to challenge a source of inbound communications for information configured to authorize the inbound communications; providing an initial selection criteria menu to create the new customized rule for controlling incoming customer communications, the initial selection criteria menu indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; processing a response indicating whether the new customized rule will be built using a preexisting template or starting from initial blank rule criteria; when the new customized rule will be built using a preexisting template, providing a list of preexisting templates for creating new customized rules for controlling incoming customer communications, processing a received selection of a preexisting template from the list of preexisting templates, accepting input to populate the selected preexisting template, and storing a new customized rule based on the selected preexisting template and including accepted input, wherein the stored new customized rule is specified to apply to inbound communications; and when the new customized rule will be built starting from initial blank rule criteria, providing initial blank rule criteria for creating a new customized rule for controlling incoming customer communications, processing a received selection of initial criteria from the initial blank rule criteria, providing a list of rule conditions for the selected initial criteria for the new customized rule, processing a received selection of rule conditions for the selected initial criteria for the new customized rule, and creating and storing a new customized rule based on the selected initial criteria and the selected rule conditions; and wherein the stored new customized rule is implemented at an internal network node of a communications service provider to process communications in accordance with requests and selections received from customers using customer equipment, and wherein the stored new customized rule further includes a selected disposition for when the selected initial criteria and selected rule conditions are met. 6. The method according to claim 1 , wherein the stored new customized rule is specified to apply before notifying a subscriber device at a subscriber destination address. | 0.663386 |
10,083,154 | 1 | 12 | 1. A mobile hand-held device, comprising: a processor; a wireless communications device, to facilitate wireless communication with a network that supports access to the Internet; a touch-sensitive display; and flash memory, operatively coupled to the processor, in which a plurality of instructions are stored comprising a plurality of software components including an HTML rendering engine, wherein the instructions are configured to be executed by the processor to enable the mobile hand-held device to, receive an HTML document including HTML code and cascading style sheet (CSS) code and content associated with the HTML document, the HTML code comprising a plurality of HTML elements including at least one HTML paragraph element, at least one HTML image element, and at least one HTML hyperlink element; process the HTML document with the HTML rendering engine to render a first representation of the HTML document having an interpreted page layout, functionality, and design of the content associated with the HTML document that is in accordance with the HTML code and CSS code, wherein rendering the first representation of the HTML document includes, parsing the HTML document to identify the plurality of HTML elements; logically grouping content associated with HTML elements into HTML objects; generating page layout information including a bounding box for each HTML object; and storing information that links each HTML object with its corresponding page layout information, wherein the page layout information further includes information from which a page layout location of each of the bounding boxes can be determined; translate the first representation of the HTML document to generate a scalable vector representation of the HTML document wherein generating the scalable vector representation includes, defining a primary datum corresponding to the interpreted page layout; for each HTML object, defining an object datum corresponding to a layout location datum for the HTML object's bounding box; generating a vector from the primary datum to the object datum for the HTML object's bounding box; and creating a reference that links the HTML object to the vector that is generated; and render the scalable vector representation of the HTML document on the touch-sensitive display using a first scale factor to display the HTML document at a first zoom level under which the HTML document is displayed to fit across a width of the touch-sensitive display, wherein the scalable vector representation of the HTML document is configured to enable a user to view the HTML document at one or more user-defined zoom levels by rendering the scalable vector representation on the touch-sensitive display using one or more respective scale factors in response to associated user inputs made via the touch-sensitive display, and wherein the interpreted page layout, functionality, and design of the content associated with the HTML document is preserved at each of the first zoom level and the one or more user-defined zoom levels. | 1. A mobile hand-held device, comprising: a processor; a wireless communications device, to facilitate wireless communication with a network that supports access to the Internet; a touch-sensitive display; and flash memory, operatively coupled to the processor, in which a plurality of instructions are stored comprising a plurality of software components including an HTML rendering engine, wherein the instructions are configured to be executed by the processor to enable the mobile hand-held device to, receive an HTML document including HTML code and cascading style sheet (CSS) code and content associated with the HTML document, the HTML code comprising a plurality of HTML elements including at least one HTML paragraph element, at least one HTML image element, and at least one HTML hyperlink element; process the HTML document with the HTML rendering engine to render a first representation of the HTML document having an interpreted page layout, functionality, and design of the content associated with the HTML document that is in accordance with the HTML code and CSS code, wherein rendering the first representation of the HTML document includes, parsing the HTML document to identify the plurality of HTML elements; logically grouping content associated with HTML elements into HTML objects; generating page layout information including a bounding box for each HTML object; and storing information that links each HTML object with its corresponding page layout information, wherein the page layout information further includes information from which a page layout location of each of the bounding boxes can be determined; translate the first representation of the HTML document to generate a scalable vector representation of the HTML document wherein generating the scalable vector representation includes, defining a primary datum corresponding to the interpreted page layout; for each HTML object, defining an object datum corresponding to a layout location datum for the HTML object's bounding box; generating a vector from the primary datum to the object datum for the HTML object's bounding box; and creating a reference that links the HTML object to the vector that is generated; and render the scalable vector representation of the HTML document on the touch-sensitive display using a first scale factor to display the HTML document at a first zoom level under which the HTML document is displayed to fit across a width of the touch-sensitive display, wherein the scalable vector representation of the HTML document is configured to enable a user to view the HTML document at one or more user-defined zoom levels by rendering the scalable vector representation on the touch-sensitive display using one or more respective scale factors in response to associated user inputs made via the touch-sensitive display, and wherein the interpreted page layout, functionality, and design of the content associated with the HTML document is preserved at each of the first zoom level and the one or more user-defined zoom levels. 12. The mobile hand-held device of claim 1 , wherein the primary datum is an origin in a two-dimensional XY coordinate system and the vectors from the primary datum to the object datums for the HTML object bounding boxes comprise XY coordinates in the coordinate system. | 0.747191 |
8,566,938 | 16 | 17 | 16. A system for analyzing electronic messages for phishing detection, comprising: one or more recipient's/recipient organization's email servers; one or more sender's email clients; one or more recipient's email clients; Intranet or Internet; a database; and one or more anti-phishing servers coupled to the database, and further the one or more anti-phishing servers coupled to the one or more recipient's/recipient's organization's email servers, the one or more sender's email clients, and/or the one or more recipient's email clients via Internet or Intranet, wherein the email client plugin module attaches to one or more recipient's email clients and wherein the anti-phishing server comprises: a processor; and a memory coupled to the processor, wherein the memory comprising a anti-phishing module, wherein the anti-phishing module comprises an import module, an analysis and data warehouse module, a mail handler module, an organizational analysis module, an outbound mail relay module, a configuration and management module that are configured to: receiving an email message from one or more sender/sender organizations by one or more recipients/recipient's organization via the mail handler module; obtaining email characteristics by parsing the received email message based on a set of predetermined email characteristics by the analysis and data warehouse module; comparing the email characteristics of the received email message with email characteristics associated with the recipient/recipient organization and/or that sender/sender organization by the analysis and data warehouse module; and declaring the received email message by the recipient/recipient organization as a phishing electronic message based on the outcome of the comparison by the analysis and data warehouse module; wherein the email characteristics are selected from the group consisting of network path used to reach a recipient/recipient organization, geography associated with IP address, email client software used by the sender/sender organization, email client software version used by the sender/sender organization, date, day of week, time, time period of the email, time zone of the sender/sender organization, presence and details of digital signatures in the email, meta data present in header portion of the email, character set used in content of the email, format of the email, email length and subject length, character case of the email, character case of the subject, style of introduction at the top of the email, style and content of the sender/sender organization's signature in the body of the email, other recipient/recipient organizations included in the email, to, and copy circulated (cc'd) email addresses, sender/sender organizations name, sender/sender organizations from and reply to email address, senders organization name, senders domain name, sender's organization's Domain Name Service (DNS) settings including SPF records, sender organization's mail server information, including server ip address, sender/sender organization server network path, sender/sender organization email server software and software version, DKIM signature, spam scoring from spam software, message ID, volume of email sent by the sender/sender organization, volume of email sent by sender's organization, volume of email received by the recipient, volume of email received by recipient organization, details associated with URLs or attachments in the email, whether the recipient/recipient organization has responded to this specific email, and number of interactions between sender and recipient associated with the email and the like; and wherein the configuration and management module allows an administrator to select desired email characteristics to be included in the set of characteristics used for comparing the characteristics of the received email message and to assign a weight of how much each characteristic should influence the likelihood that a new message is a phishing message. | 16. A system for analyzing electronic messages for phishing detection, comprising: one or more recipient's/recipient organization's email servers; one or more sender's email clients; one or more recipient's email clients; Intranet or Internet; a database; and one or more anti-phishing servers coupled to the database, and further the one or more anti-phishing servers coupled to the one or more recipient's/recipient's organization's email servers, the one or more sender's email clients, and/or the one or more recipient's email clients via Internet or Intranet, wherein the email client plugin module attaches to one or more recipient's email clients and wherein the anti-phishing server comprises: a processor; and a memory coupled to the processor, wherein the memory comprising a anti-phishing module, wherein the anti-phishing module comprises an import module, an analysis and data warehouse module, a mail handler module, an organizational analysis module, an outbound mail relay module, a configuration and management module that are configured to: receiving an email message from one or more sender/sender organizations by one or more recipients/recipient's organization via the mail handler module; obtaining email characteristics by parsing the received email message based on a set of predetermined email characteristics by the analysis and data warehouse module; comparing the email characteristics of the received email message with email characteristics associated with the recipient/recipient organization and/or that sender/sender organization by the analysis and data warehouse module; and declaring the received email message by the recipient/recipient organization as a phishing electronic message based on the outcome of the comparison by the analysis and data warehouse module; wherein the email characteristics are selected from the group consisting of network path used to reach a recipient/recipient organization, geography associated with IP address, email client software used by the sender/sender organization, email client software version used by the sender/sender organization, date, day of week, time, time period of the email, time zone of the sender/sender organization, presence and details of digital signatures in the email, meta data present in header portion of the email, character set used in content of the email, format of the email, email length and subject length, character case of the email, character case of the subject, style of introduction at the top of the email, style and content of the sender/sender organization's signature in the body of the email, other recipient/recipient organizations included in the email, to, and copy circulated (cc'd) email addresses, sender/sender organizations name, sender/sender organizations from and reply to email address, senders organization name, senders domain name, sender's organization's Domain Name Service (DNS) settings including SPF records, sender organization's mail server information, including server ip address, sender/sender organization server network path, sender/sender organization email server software and software version, DKIM signature, spam scoring from spam software, message ID, volume of email sent by the sender/sender organization, volume of email sent by sender's organization, volume of email received by the recipient, volume of email received by recipient organization, details associated with URLs or attachments in the email, whether the recipient/recipient organization has responded to this specific email, and number of interactions between sender and recipient associated with the email and the like; and wherein the configuration and management module allows an administrator to select desired email characteristics to be included in the set of characteristics used for comparing the characteristics of the received email message and to assign a weight of how much each characteristic should influence the likelihood that a new message is a phishing message. 17. The system of claim 16 , wherein either the import module or the email client plugin module directly imports emails received by the recipient/recipient organization over a predetermined time interval, wherein the analysis and data warehouse module parses the recipient/recipient organization's received emails based on the set of predetermined email characteristics to obtain email characteristics of the imported emails, and wherein the analysis and data warehouse module stores the obtained email characteristics associated with the recipient/recipient organization's and/or sender/sender organization's received email in the database. | 0.659405 |
7,487,144 | 1 | 3 | 1. A method for automatically presenting inline answers or suggestions from user-created web-search verticals in response to a general web-search query, the method comprising: receiving a general web-search query from a user in a web-search user interface that has been customized by the user selecting to install one or more user-created web-search vertical tabs in the web-search user interface, wherein the user-created web-search verticals have been created by one or more search-engine consumers rather than a search-engine provider; obtaining general web-search results from the World Wide Web based on the query; accessing the user-created web-search verticals that have been installed in the customized user-interface by the user; determining whether answers or suggestions relevant to the query are available from the installed user-created web-search verticals by first accessing a user-created definition for each of the installed user-created web-search verticals to determine whether return of answers or suggestions are supported by each of the installed user-created web-search verticals, and, second, determining whether any keywords from the query are present in a programmed keyword list in each of the installed user-created web-search verticals; and if return of answers or suggestions are supported and if any keywords from the query are present, then, presenting, on a common display with the general web-search results, at least one answer or suggestion from an installed user-created web-search vertical that supports answers or suggestions and that has at least one keyword from the query in its programmed keyword list. | 1. A method for automatically presenting inline answers or suggestions from user-created web-search verticals in response to a general web-search query, the method comprising: receiving a general web-search query from a user in a web-search user interface that has been customized by the user selecting to install one or more user-created web-search vertical tabs in the web-search user interface, wherein the user-created web-search verticals have been created by one or more search-engine consumers rather than a search-engine provider; obtaining general web-search results from the World Wide Web based on the query; accessing the user-created web-search verticals that have been installed in the customized user-interface by the user; determining whether answers or suggestions relevant to the query are available from the installed user-created web-search verticals by first accessing a user-created definition for each of the installed user-created web-search verticals to determine whether return of answers or suggestions are supported by each of the installed user-created web-search verticals, and, second, determining whether any keywords from the query are present in a programmed keyword list in each of the installed user-created web-search verticals; and if return of answers or suggestions are supported and if any keywords from the query are present, then, presenting, on a common display with the general web-search results, at least one answer or suggestion from an installed user-created web-search vertical that supports answers or suggestions and that has at least one keyword from the query in its programmed keyword list. 3. The method of claim 1 , further comprising storing revenue-sharing data for one of the installed user-created web-search verticals if at least one answer or suggestion is presented from the installed user-created search vertical. | 0.754237 |
9,900,278 | 8 | 9 | 8. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of communicating social media content over a computer network via one or more social media services, the method comprising: receiving content from a first node of an online social network; generating automatically a set of topics in the content; inspecting a target audience of the content by monitoring online activities of the target audience, the monitoring online activities comprising monitoring processor threads running on the one or more processors; determining, based on the monitoring of the online activities, topic popularity corresponding to a topic in the set of topics over a plurality of time ranges, the topic popularity indicating a degree to which the topic is popular with the target audience at a given time range; generating a trending metric associated with the topic, the trending metric indicating a degree to which the topic is currently popular among all users of the online social network; generating a weighted topic popularity for a respective one of the plurality of time ranges, as a function of the topic popularity, the trending metric, and an elapsed time between time associated with the respective time range and a preferred time for posting the content; selecting a time range from the plurality of time ranges based on the weighted topic popularity; and posting the content at the selected time range on the online social network. | 8. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of communicating social media content over a computer network via one or more social media services, the method comprising: receiving content from a first node of an online social network; generating automatically a set of topics in the content; inspecting a target audience of the content by monitoring online activities of the target audience, the monitoring online activities comprising monitoring processor threads running on the one or more processors; determining, based on the monitoring of the online activities, topic popularity corresponding to a topic in the set of topics over a plurality of time ranges, the topic popularity indicating a degree to which the topic is popular with the target audience at a given time range; generating a trending metric associated with the topic, the trending metric indicating a degree to which the topic is currently popular among all users of the online social network; generating a weighted topic popularity for a respective one of the plurality of time ranges, as a function of the topic popularity, the trending metric, and an elapsed time between time associated with the respective time range and a preferred time for posting the content; selecting a time range from the plurality of time ranges based on the weighted topic popularity; and posting the content at the selected time range on the online social network. 9. The non-transitory computer readable storage medium of claim 8 , wherein the determining topic popularity is performed for each topic in the set of topics, wherein all of the topic popularity for the given time range are aggregated and the weighted topic popularity is generated based on the aggregated topic popularity. | 0.5 |
8,433,718 | 18 | 24 | 18. The method according to claim 5 , wherein the step of arranging includes inserting a link contained in the content in the first language in the current content in the second language. | 18. The method according to claim 5 , wherein the step of arranging includes inserting a link contained in the content in the first language in the current content in the second language. 24. The method according to claim 18 , wherein the link includes a Universal Resource Locator (URL). | 0.5 |
6,144,938 | 80 | 87 | 80. A data signal in a carrier wave for a voice user interface with personality, the data signal in a carrier wave comprising: first voice signals, the first voice signals being output by a voice user interface with a verbal personality; and speech signals, the voice user interface with a verbal personality recognizing the speech signals using a recognition grammar, the recognition grammar being stored in a memory and comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, the recognition grammar being selected based on the personality of the virtual assistant. | 80. A data signal in a carrier wave for a voice user interface with personality, the data signal in a carrier wave comprising: first voice signals, the first voice signals being output by a voice user interface with a verbal personality; and speech signals, the voice user interface with a verbal personality recognizing the speech signals using a recognition grammar, the recognition grammar being stored in a memory and comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, the recognition grammar being selected based on the personality of the virtual assistant. 87. The data signal in a carrier wave as recited in claim 80 further comprising: second voice signals, the second voice signals being output by the voice user interface with personality. | 0.707547 |
8,782,516 | 19 | 20 | 19. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, performs acts comprising: obtaining an image of content including paragraphs belonging to a column layout group and a style group; clustering the paragraphs of each style group in the column layout group to identify outlier paragraphs having style attributes outside of a threshold range of the style attributes, wherein the style attributes include at least one of an indentation, a tracking value or line spacing between consecutive lines of text in the paragraph; removing the outlier paragraphs from each style group to create stylized paragraphs; determining a paragraph alignment type of the stylized paragraphs of each style group; determining at least one of a horizontally extending margin or a vertically extending margin of the stylized paragraphs of each style group; associating the at least one horizontally extending margin, vertically extending margin, or paragraph alignment type of the stylized paragraphs of each style group with a paragraph attribute type; selecting a paragraph attribute type according to a dimension of a user system; and displaying the image of content on the user system using the selected paragraph attribute type. | 19. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, performs acts comprising: obtaining an image of content including paragraphs belonging to a column layout group and a style group; clustering the paragraphs of each style group in the column layout group to identify outlier paragraphs having style attributes outside of a threshold range of the style attributes, wherein the style attributes include at least one of an indentation, a tracking value or line spacing between consecutive lines of text in the paragraph; removing the outlier paragraphs from each style group to create stylized paragraphs; determining a paragraph alignment type of the stylized paragraphs of each style group; determining at least one of a horizontally extending margin or a vertically extending margin of the stylized paragraphs of each style group; associating the at least one horizontally extending margin, vertically extending margin, or paragraph alignment type of the stylized paragraphs of each style group with a paragraph attribute type; selecting a paragraph attribute type according to a dimension of a user system; and displaying the image of content on the user system using the selected paragraph attribute type. 20. The one or more non-transitory computer-readable media as recited in claim 19 , wherein determining the horizontally extending margin further comprises: determining a side margin value of the stylized paragraphs of each column layout group; determining a minimum side margin value of the stylized paragraphs associated with the column layout group; reducing the side margin value of the stylized paragraphs in the column layout group by the minimum side margin value to create a reduced side margin value; and determining a representative side margin value based at least in part on the reduced side margin value of the stylized paragraphs of each style group. | 0.5 |
9,137,581 | 4 | 8 | 4. The video recording/playing device as set forth in claim 1 , wherein the processor: extracts words from the electronic program guide and acquires, as an attention word, a word for which an appearance frequency in a second period, following a first period, has increased beyond the appearance frequency in the first period, displays on a screen, as a search word candidate, a word obtained by causing the acquired attention word to operate on the acquired trending word, and receives a selection input for a search word by the user, and retrieves from the program information database program information that includes the search word selected by the user. | 4. The video recording/playing device as set forth in claim 1 , wherein the processor: extracts words from the electronic program guide and acquires, as an attention word, a word for which an appearance frequency in a second period, following a first period, has increased beyond the appearance frequency in the first period, displays on a screen, as a search word candidate, a word obtained by causing the acquired attention word to operate on the acquired trending word, and receives a selection input for a search word by the user, and retrieves from the program information database program information that includes the search word selected by the user. 8. The video recording/playing device as set forth in claim 4 , wherein the processor displays on the screen, as search word candidates, words wherein the acquired attention word has been excluded from the acquired trending word. | 0.753233 |
7,970,944 | 19 | 22 | 19. The method recited in claim 9 , wherein the interface definition mark-up language (IDML) comprises a collection tag for parameterizing collections to be displayed in the user interface. | 19. The method recited in claim 9 , wherein the interface definition mark-up language (IDML) comprises a collection tag for parameterizing collections to be displayed in the user interface. 22. The method recited in claim 19 , wherein the collection tag comprises nested tags including a copy text tag, a resource tag, another collection tag, and a primitive tag. | 0.599537 |
8,886,536 | 8 | 9 | 8. The method of claim 7 , wherein the first natural language utterance, the second natural language utterance, and the third natural language utterance are received during an interactive session between the user and the computer system. | 8. The method of claim 7 , wherein the first natural language utterance, the second natural language utterance, and the third natural language utterance are received during an interactive session between the user and the computer system. 9. The method of claim 8 , wherein the third natural language utterance is received after the second natural language utterance. | 0.5 |
9,577,975 | 16 | 18 | 16. A system comprising: one or more memory devices; and a processor communicatively coupled to the one or more memory devices, the processor operable to: determine a plurality of entities that are displayed in media content being viewed by a user, the plurality of entities comprising at least a first entity and a second entity; access information indicative of the plurality of entities; query a social graph of the social-networking system for first social content associated with the first entity, the social graph comprising: user nodes that are each associated with a particular user of the social-networking system; query the social graph of the social-networking system for second social content associated with the second entity; and provide at least a portion of the queried social content from the social graph for display along with the information on a display device of the user. | 16. A system comprising: one or more memory devices; and a processor communicatively coupled to the one or more memory devices, the processor operable to: determine a plurality of entities that are displayed in media content being viewed by a user, the plurality of entities comprising at least a first entity and a second entity; access information indicative of the plurality of entities; query a social graph of the social-networking system for first social content associated with the first entity, the social graph comprising: user nodes that are each associated with a particular user of the social-networking system; query the social graph of the social-networking system for second social content associated with the second entity; and provide at least a portion of the queried social content from the social graph for display along with the information on a display device of the user. 18. The system of claim 16 , wherein the information comprises a plurality of images, each of the plurality of images associated with one of the plurality of entities. | 0.74697 |
7,783,656 | 1 | 5 | 1. A method of managing an object database for objects comprising: receiving a database path query expression in a computer system with at least one processor, the expression comprising a main expression and a treat-as expression; translating the database path query expression into an object query; and querying the object database using the object query; wherein the translating comprises: breaking the path query expression into nodes; examining each node to identify objects for selection and objects from which selection is made; consolidating objects for selection from each node in the sub-expression into a sub-SELECT clause; consolidating objects for selection in each node of the main expression into a SELECT clause; consolidating objects from which selection is made from nodes in the sub-query into a sub-FROM clause; consolidating objects from which selection is made from nodes in the main query into a FORM clause; and forming the object query from the SELECT clause; from the FROM clause; and from a WHERE clause wherein the WHERE clause consists of the sub-SELECT clause and the sub-FROM clause and a sub-WHERE clause that links the scope of the sub-SELECT clause to the scope of the SELECT clause. | 1. A method of managing an object database for objects comprising: receiving a database path query expression in a computer system with at least one processor, the expression comprising a main expression and a treat-as expression; translating the database path query expression into an object query; and querying the object database using the object query; wherein the translating comprises: breaking the path query expression into nodes; examining each node to identify objects for selection and objects from which selection is made; consolidating objects for selection from each node in the sub-expression into a sub-SELECT clause; consolidating objects for selection in each node of the main expression into a SELECT clause; consolidating objects from which selection is made from nodes in the sub-query into a sub-FROM clause; consolidating objects from which selection is made from nodes in the main query into a FORM clause; and forming the object query from the SELECT clause; from the FROM clause; and from a WHERE clause wherein the WHERE clause consists of the sub-SELECT clause and the sub-FROM clause and a sub-WHERE clause that links the scope of the sub-SELECT clause to the scope of the SELECT clause. 5. The method according to claim 1 wherein access control to objects within the object database is controlled by the object database. | 0.67561 |
9,355,485 | 1 | 3 | 1. A computer-implemented method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: at an electronic device including a computer readable medium, one or more processors, and a display: storing, in the computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, the one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, an image data structure for displaying on the display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion. | 1. A computer-implemented method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: at an electronic device including a computer readable medium, one or more processors, and a display: storing, in the computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, the one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, an image data structure for displaying on the display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion. 3. The method of claim 1 , wherein each of the plurality of values is a proportion, and computing the word size for each of the plurality of words includes multiplying the maximum word size by the proportion associated with the corresponding word. | 0.83961 |
8,327,255 | 30 | 34 | 30. A system for making a computer program product comprising electronic transcript and exhibit files, wherein the system comprises a processor configured to: import one or more electronic transcript files and one or more electronic exhibit files into a publisher module; establish an operable electronic link between the one or more electronic exhibit files and one or more entries in the one or more electronic transcript files that are associated with the one or more electronic exhibit files; store a bundle on a computer readable medium via the publisher module, wherein the bundle comprises the one or more electronic transcript files, the one or more electronic exhibit files, the operable electronic link, and an executable viewer file to view the one or more electronic transcript files and the one or more electronic exhibit files, the computer readable medium comprising a portable device; and provide the one or more electronic transcript files in the bundle via the executable viewer file in the bundle and the one or more electronic exhibit files in the bundle in response to an input activating the operable electronic link via the one or more entries in the one or more provided electronic transcript files. | 30. A system for making a computer program product comprising electronic transcript and exhibit files, wherein the system comprises a processor configured to: import one or more electronic transcript files and one or more electronic exhibit files into a publisher module; establish an operable electronic link between the one or more electronic exhibit files and one or more entries in the one or more electronic transcript files that are associated with the one or more electronic exhibit files; store a bundle on a computer readable medium via the publisher module, wherein the bundle comprises the one or more electronic transcript files, the one or more electronic exhibit files, the operable electronic link, and an executable viewer file to view the one or more electronic transcript files and the one or more electronic exhibit files, the computer readable medium comprising a portable device; and provide the one or more electronic transcript files in the bundle via the executable viewer file in the bundle and the one or more electronic exhibit files in the bundle in response to an input activating the operable electronic link via the one or more entries in the one or more provided electronic transcript files. 34. The system of claim 30 , wherein the operable electronic link between the one or more electronic exhibit files and the one or more entries in the one or more electronic transcript files comprises a hyperlink from the one or more entries in the one or more electronic transcript files to the one or more electronic exhibit files. | 0.786358 |
9,372,844 | 17 | 18 | 17. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method for displaying on a display surface an automatically generated graphical display using a symbolic annotation language; the method comprising: analyzing a business process flow genus to form an alphabet of a compact symbolic language representing a plurality of semantics from a number of symbols, wherein the analyzing comprises determining a representative set of process flow description attributes; capturing a business process flow using one or more symbols of the number of symbols; the business process flow being a species of the business process flow genus, wherein capturing the business process flow using the one or more symbols of the number of symbols comprises mapping the representative set of process flow description attributes into the compact symbolic language while observing a constraint and analyzing characteristics of the business process flow, the business process flow being a species of the business process flow genus; testing the captured business process flow using a schematic of the business process flow; mapping the one or more symbols of the number of symbols to a plurality of constructs of a markup language, one or more constructs of the plurality of constructs to be rendered in a graphical display, wherein mapping the one or more symbols of the number of symbols to the plurality of constructs of the markup language comprises mapping the one or more symbols of the compact symbolic language to a plurality of instance of schematic symbols, mapping the plurality of instances of schematic symbols to the plurality of constructs of the markup language, and mapping the plurality of constructs of the markup language to a plurality of computer-automated processes; and automatically generating and displaying, on a display surface, the business process flow in a graphical user interface using the symbolic annotation language wherein displaying the business process flow is based on the plurality of computer-automated processes. | 17. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a method for displaying on a display surface an automatically generated graphical display using a symbolic annotation language; the method comprising: analyzing a business process flow genus to form an alphabet of a compact symbolic language representing a plurality of semantics from a number of symbols, wherein the analyzing comprises determining a representative set of process flow description attributes; capturing a business process flow using one or more symbols of the number of symbols; the business process flow being a species of the business process flow genus, wherein capturing the business process flow using the one or more symbols of the number of symbols comprises mapping the representative set of process flow description attributes into the compact symbolic language while observing a constraint and analyzing characteristics of the business process flow, the business process flow being a species of the business process flow genus; testing the captured business process flow using a schematic of the business process flow; mapping the one or more symbols of the number of symbols to a plurality of constructs of a markup language, one or more constructs of the plurality of constructs to be rendered in a graphical display, wherein mapping the one or more symbols of the number of symbols to the plurality of constructs of the markup language comprises mapping the one or more symbols of the compact symbolic language to a plurality of instance of schematic symbols, mapping the plurality of instances of schematic symbols to the plurality of constructs of the markup language, and mapping the plurality of constructs of the markup language to a plurality of computer-automated processes; and automatically generating and displaying, on a display surface, the business process flow in a graphical user interface using the symbolic annotation language wherein displaying the business process flow is based on the plurality of computer-automated processes. 18. The computer program product of claim 17 , the method further comprising receiving at least one subroutine call codified in the markup language. | 0.586592 |
7,908,280 | 6 | 8 | 6. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the following steps: receiving search criteria from a user, said search criteria including a free text entry query and a domain identifier identifying a domain; determining to request a search of a first corpus of documents to identify a first set of documents; receiving a first result set for the first corpus of documents, the first result set identifying the first set of documents in order of relevance; determining to request a search of a second corpus of documents to identify a second set of documents; receiving a second result set for the second corpus of documents, the second result set identifying the second set of documents in order of relevance; determining to merge sort the first and second result sets to produce a new result set that is ordered in relevance; and wherein determining to merge sort is based on a relevancy of the search criteria; and wherein the determined scores for each of the identified documents include a document-to-location relevance score, a document-to-text relevance score, and an abstract quality score; and combining the document-to-location relevance scores, the document-to-text, and the abstract quality score to generate a combined relevance score for the identified document. | 6. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the following steps: receiving search criteria from a user, said search criteria including a free text entry query and a domain identifier identifying a domain; determining to request a search of a first corpus of documents to identify a first set of documents; receiving a first result set for the first corpus of documents, the first result set identifying the first set of documents in order of relevance; determining to request a search of a second corpus of documents to identify a second set of documents; receiving a second result set for the second corpus of documents, the second result set identifying the second set of documents in order of relevance; determining to merge sort the first and second result sets to produce a new result set that is ordered in relevance; and wherein determining to merge sort is based on a relevancy of the search criteria; and wherein the determined scores for each of the identified documents include a document-to-location relevance score, a document-to-text relevance score, and an abstract quality score; and combining the document-to-location relevance scores, the document-to-text, and the abstract quality score to generate a combined relevance score for the identified document. 8. A computer-readable storage medium of claim 6 , wherein each of the document identifiers of the first set of documents and the second set of documents identifies a corresponding different document that contains text matching the free text entry query. | 0.710706 |
8,370,143 | 1 | 9 | 1. A computer-implemented method, comprising: receiving, by a computing system, text of a message entered by a user into a communication application program, wherein the text represents typed or audibly spoken content input by the user; determining, by a computing system, a level of randomness of characters in a portion of the text; identifying a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the portion of the text was input; determining, by a computing system, whether the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness; and responsive to determining that the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness, precluding, by a computing system, a text processing system from performing a spell checking procedure on the portion of the text or from performing a word auto complete procedure on the portion of the text. | 1. A computer-implemented method, comprising: receiving, by a computing system, text of a message entered by a user into a communication application program, wherein the text represents typed or audibly spoken content input by the user; determining, by a computing system, a level of randomness of characters in a portion of the text; identifying a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the portion of the text was input; determining, by a computing system, whether the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness; and responsive to determining that the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness, precluding, by a computing system, a text processing system from performing a spell checking procedure on the portion of the text or from performing a word auto complete procedure on the portion of the text. 9. The computer-implemented method of claim 1 , wherein the particular label of a text entry field is for a text entry field that is identified as being used for providing a password. | 0.801087 |
8,855,915 | 1 | 3 | 1. A navigation system, comprising: a navigation apparatus configured to carry out guidance by outputting a voice message; a location and speed detector, configured to detect a location and a speed of the navigation apparatus; a voice message weight storage, configured to store voice message weight association information, which associates a weight with each of multiple voice messages; a rule storage, configured to store priority rule information denoting a rule for deciding a priority for each of the multiple voice messages; a priority decision module, configured to decide a priority for each of the multiple voice messages based on the priority rule information; a voice output, configured to output the multiple voice messages from the navigation apparatus in a sequence conforming to the decided priority, a server configured to communicate with the navigation apparatus, the server including a reference driving performance information transmitter configured to send reference driving performance information to the navigation apparatus, wherein the reference driving performance information is driving performance characteristics information constituting a reference; the navigation apparatus includes: a characteristics acquisition receiver configured to acquire driving performance characteristics of a driver, who drives a vehicle including the navigation apparatus; and an evaluation score calculator configured to calculate an evaluation score of the driver based on the reference driving performance information and the driving performance characteristics of the driver; wherein a rule denoted by the priority rule information is a rule for deciding a priority for each voice message based on: the detected location and speed of the navigation apparatus, the weight of each of the voice messages denoted by the voice message weight association information, and the evaluation score of the driver. | 1. A navigation system, comprising: a navigation apparatus configured to carry out guidance by outputting a voice message; a location and speed detector, configured to detect a location and a speed of the navigation apparatus; a voice message weight storage, configured to store voice message weight association information, which associates a weight with each of multiple voice messages; a rule storage, configured to store priority rule information denoting a rule for deciding a priority for each of the multiple voice messages; a priority decision module, configured to decide a priority for each of the multiple voice messages based on the priority rule information; a voice output, configured to output the multiple voice messages from the navigation apparatus in a sequence conforming to the decided priority, a server configured to communicate with the navigation apparatus, the server including a reference driving performance information transmitter configured to send reference driving performance information to the navigation apparatus, wherein the reference driving performance information is driving performance characteristics information constituting a reference; the navigation apparatus includes: a characteristics acquisition receiver configured to acquire driving performance characteristics of a driver, who drives a vehicle including the navigation apparatus; and an evaluation score calculator configured to calculate an evaluation score of the driver based on the reference driving performance information and the driving performance characteristics of the driver; wherein a rule denoted by the priority rule information is a rule for deciding a priority for each voice message based on: the detected location and speed of the navigation apparatus, the weight of each of the voice messages denoted by the voice message weight association information, and the evaluation score of the driver. 3. The navigation system according to claim 1 , wherein the navigation apparatus further includes the priority decision module and the voice output. | 0.883648 |
9,332,401 | 1 | 7 | 1. A method for dynamically translating the public address announcement comprising: maintaining of a listing of mobile devices currently active within a specified geographic area serviced by a public address system by a multi-lingual module, wherein a native language of a mobile device that is different than a language used by the public address system is automatically noted from the mobile device; converting content for an announcement broadcast by the public address system into a format capable of being transmitted via a wireless communications message; translating the converted content to native languages noted in the listing; and pushing the wireless communications message containing the translated content to corresponding mobile devices in the listing and the wireless communications message containing the converted content to a remainder of the mobile devices in the listing via a wireless network local to the specified geographic area, wherein a wireless standard utilized by said wireless network comprises at least one of IEEE 802.11 and IEEE 802.15. | 1. A method for dynamically translating the public address announcement comprising: maintaining of a listing of mobile devices currently active within a specified geographic area serviced by a public address system by a multi-lingual module, wherein a native language of a mobile device that is different than a language used by the public address system is automatically noted from the mobile device; converting content for an announcement broadcast by the public address system into a format capable of being transmitted via a wireless communications message; translating the converted content to native languages noted in the listing; and pushing the wireless communications message containing the translated content to corresponding mobile devices in the listing and the wireless communications message containing the converted content to a remainder of the mobile devices in the listing via a wireless network local to the specified geographic area, wherein a wireless standard utilized by said wireless network comprises at least one of IEEE 802.11 and IEEE 802.15. 7. The method of claim 1 , wherein the translating of the content is performed by the mobile device. | 0.916667 |
10,027,796 | 1 | 5 | 1. A computer-implemented method of creating a smart reminder, comprising: receiving a user input on a device; processing the user input, comprising: identifying one or more entities associated with the user input, wherein at least one entity is associated with a person; and identifying an action by semantically evaluating the user input to determine a user intention; based at least in part on the processed user input, automatically generating the smart reminder to perform the action; detecting at least one triggering event associated with the smart reminder, wherein detecting the triggering event comprises detecting the person; and based on detecting the at least one triggering event, providing the smart reminder on a display of the device. | 1. A computer-implemented method of creating a smart reminder, comprising: receiving a user input on a device; processing the user input, comprising: identifying one or more entities associated with the user input, wherein at least one entity is associated with a person; and identifying an action by semantically evaluating the user input to determine a user intention; based at least in part on the processed user input, automatically generating the smart reminder to perform the action; detecting at least one triggering event associated with the smart reminder, wherein detecting the triggering event comprises detecting the person; and based on detecting the at least one triggering event, providing the smart reminder on a display of the device. 5. The method of claim 1 , wherein the at least one triggering event is one of an incoming phone call from the person and an outgoing call to the person, and wherein the smart reminder is displayed in response to detecting one of the incoming phone call and the outgoing phone call. | 0.621984 |
7,802,305 | 5 | 6 | 5. The method of claim 4 wherein rendering a potential list comprises: matching proximity expressions against content in the document to identify proximate content; and wherein processing the proximity data against the document to identify content that may be selected for redaction comprises: rendering the proximate content in the potential list. | 5. The method of claim 4 wherein rendering a potential list comprises: matching proximity expressions against content in the document to identify proximate content; and wherein processing the proximity data against the document to identify content that may be selected for redaction comprises: rendering the proximate content in the potential list. 6. The method of claim 5 wherein matching proximity expressions against content in the document to identify proximate content comprises: applying a pattern recognition function to the content in the document using the proximate expressions; and wherein rendering the proximate content in the potential list comprises: rendering instances of content in the document that match content identified by the application of the pattern recognition function to the content in the document. | 0.5 |
7,548,967 | 8 | 9 | 8. The method of claim 7 , wherein said priorities are allocated by numerically naming the individual branches. | 8. The method of claim 7 , wherein said priorities are allocated by numerically naming the individual branches. 9. The method of claim 8 , wherein said step of translating said policies from said executable feature language into said policy conflict detection language further comprises visiting successive ones of said branches downwardly and producing corresponding rules, using the following mapping: name policy to name rule; priority policy to number rules; operation policy to result rule; precondition policy to triggering event rule; target policy to result rule; exceptions policy to constraint rule; and time constraints policy to precondition rule. | 0.5 |
9,286,325 | 14 | 16 | 14. A method for extracting one or more images from a storage medium, the method comprising: selecting a semantic model based on a semantic class determined from a query; checking an availability of a semantically related aesthetic model for the determined semantic class, wherein the semantically related aesthetic model corresponds to an aesthetic model that is configured to compute an aesthetic score for a first image that is associated with a predetermined semantic class, and wherein the semantically related aesthetic model is unable to compute aesthetic score for a second image that is associated with a semantic class other than the predetermined semantic class; selecting one of the semantically related aesthetic model or a generic aesthetic model based on the availability of the semantically related aesthetic model for the determined semantic class, wherein the semantically related aesthetic model is selected if available, and wherein the generic aesthetic model is selected when the semantically related aesthetic model is unavailable for the semantic class; computing a semantic score and an aesthetic score for each of the one or more images based on the semantic model and the selected aesthetic model, respectively; and ranking the one or more images based on the semantic score and the aesthetic score. | 14. A method for extracting one or more images from a storage medium, the method comprising: selecting a semantic model based on a semantic class determined from a query; checking an availability of a semantically related aesthetic model for the determined semantic class, wherein the semantically related aesthetic model corresponds to an aesthetic model that is configured to compute an aesthetic score for a first image that is associated with a predetermined semantic class, and wherein the semantically related aesthetic model is unable to compute aesthetic score for a second image that is associated with a semantic class other than the predetermined semantic class; selecting one of the semantically related aesthetic model or a generic aesthetic model based on the availability of the semantically related aesthetic model for the determined semantic class, wherein the semantically related aesthetic model is selected if available, and wherein the generic aesthetic model is selected when the semantically related aesthetic model is unavailable for the semantic class; computing a semantic score and an aesthetic score for each of the one or more images based on the semantic model and the selected aesthetic model, respectively; and ranking the one or more images based on the semantic score and the aesthetic score. 16. The method of claim 14 , wherein the aesthetic score is computed by the generic aesthetic model based on one or more image features associated with the one or more images independent of the determined semantic class. | 0.504505 |
9,812,127 | 8 | 9 | 8. The method of claim 1 , further comprising generating a user interface for display to the selected annotator for receiving the annotator's annotation. | 8. The method of claim 1 , further comprising generating a user interface for display to the selected annotator for receiving the annotator's annotation. 9. The method of claim 8 , wherein the user interface provides a goal of the scenario and a current state of the dialog. | 0.5 |
9,377,984 | 19 | 20 | 19. An information processing apparatus comprising: a display unit configured to display a preview screen; and a central processing unit which executes a program stored in a memory, wherein the central processing unit functions as: a selection unit configured to select a storing function in accordance with an instruction input in the preview screen; and a display control unit configured to control the display unit to display the preview screen, wherein information of document data and a preview image based on the document data are displayed in the preview screen, wherein if the storing function is selected, the information of the document data is displayed in the preview screen after printing for the document data, and if the storing function is not selected, the information of the document data is not displayed in the preview screen after printing for the document data, wherein a first preview image based on first document data is displayed in the preview screen if first information of the first document data is selected in the preview screen, and a second preview image based on second document data different from the first document data is displayed in the preview screen if second information of the second document data is selected in the preview screen, wherein if the first information is selected in the preview screen and print setting information is changed, print setting information of the first document data is changed and print setting information of the second document data is not changed, and wherein if the second information is selected in the preview screen and print setting information is changed, print setting information of the second document data is changed and print setting information of the first document data is not changed. | 19. An information processing apparatus comprising: a display unit configured to display a preview screen; and a central processing unit which executes a program stored in a memory, wherein the central processing unit functions as: a selection unit configured to select a storing function in accordance with an instruction input in the preview screen; and a display control unit configured to control the display unit to display the preview screen, wherein information of document data and a preview image based on the document data are displayed in the preview screen, wherein if the storing function is selected, the information of the document data is displayed in the preview screen after printing for the document data, and if the storing function is not selected, the information of the document data is not displayed in the preview screen after printing for the document data, wherein a first preview image based on first document data is displayed in the preview screen if first information of the first document data is selected in the preview screen, and a second preview image based on second document data different from the first document data is displayed in the preview screen if second information of the second document data is selected in the preview screen, wherein if the first information is selected in the preview screen and print setting information is changed, print setting information of the first document data is changed and print setting information of the second document data is not changed, and wherein if the second information is selected in the preview screen and print setting information is changed, print setting information of the second document data is changed and print setting information of the first document data is not changed. 20. The information processing apparatus according to claim 19 , wherein each of the first information and the second information indicates a document name. | 0.5 |
9,934,219 | 1 | 5 | 1. A method for internationalization of navigation, the method comprising: receiving, by one or more processors, from a requestor, a request comprising a target destination and a native language; retrieving, by one or more processors, from a database, a plurality of keywords, wherein the plurality of keywords are associated with the native language and a destination language; scoring, by one or more processors, each of the plurality of keywords; determining, by one or more processors, whether a score associated with each of the plurality of keywords exceeds a threshold value; responsive to determining that a score associated with each of the plurality of keywords exceeds the threshold value, translating, by one or more processors, the plurality of keywords from the destination language to the native language; sending, by one or more processors, the translated plurality of keywords to the requestor, wherein the translated plurality of keywords are used to navigate to the target destination; ranking, by one or more processors, the translated plurality of keywords, based on an order of familiarity to a user; implementing, by one or more processors, a set of high ranked keywords as navigation keywords to navigate to the target destination; and navigating, by one or more processors, to the target destination using GPS signals and the set of high ranked keywords. | 1. A method for internationalization of navigation, the method comprising: receiving, by one or more processors, from a requestor, a request comprising a target destination and a native language; retrieving, by one or more processors, from a database, a plurality of keywords, wherein the plurality of keywords are associated with the native language and a destination language; scoring, by one or more processors, each of the plurality of keywords; determining, by one or more processors, whether a score associated with each of the plurality of keywords exceeds a threshold value; responsive to determining that a score associated with each of the plurality of keywords exceeds the threshold value, translating, by one or more processors, the plurality of keywords from the destination language to the native language; sending, by one or more processors, the translated plurality of keywords to the requestor, wherein the translated plurality of keywords are used to navigate to the target destination; ranking, by one or more processors, the translated plurality of keywords, based on an order of familiarity to a user; implementing, by one or more processors, a set of high ranked keywords as navigation keywords to navigate to the target destination; and navigating, by one or more processors, to the target destination using GPS signals and the set of high ranked keywords. 5. The method of claim 1 , wherein scoring each of the plurality of keywords comprises: retrieving, by one or more processors, a level of recognition of the plurality of keywords and a level of relevance of the plurality of keywords, wherein the level of recognition of the plurality of keywords is based in part on the native language of a user. | 0.706282 |
8,943,481 | 24 | 29 | 24. An apparatus for simplifying user interface binding specifications provided to a computer program comprising: means for obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; means for performing a first transformation of the schema to generate the first set of rules for interpretation of the binding specifications in the first grammar level; means for performing a second transformation of the framework to generate a first presentation style for the first grammar level; means for obtaining binding specifications in the first grammar level, the binding specification conforming to the first set of rules; means for applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. | 24. An apparatus for simplifying user interface binding specifications provided to a computer program comprising: means for obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; means for performing a first transformation of the schema to generate the first set of rules for interpretation of the binding specifications in the first grammar level; means for performing a second transformation of the framework to generate a first presentation style for the first grammar level; means for obtaining binding specifications in the first grammar level, the binding specification conforming to the first set of rules; means for applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. 29. The apparatus of claim 24 , wherein the second grammar level compatible with the user interface application is fixed. | 0.826648 |
8,577,814 | 17 | 19 | 17. The system of claim 16 , wherein to assign each candidate rule a fitness score the genetic rule generator is configured to determine the fitness score with a fitness function that is based on the measures of precision and recall for that candidate rule. | 17. The system of claim 16 , wherein to assign each candidate rule a fitness score the genetic rule generator is configured to determine the fitness score with a fitness function that is based on the measures of precision and recall for that candidate rule. 19. The system of claim 17 , wherein the fitness function is structured such that each candidate rule will be assigned a minimum positive score such that the each candidate rule has at least some probability of being selected as a parent. | 0.5 |
8,384,686 | 16 | 17 | 16. A smartphone comprising: a touchscreen display configured to: display a virtual keypad, wherein the virtual keypad includes an insufficient quantity of letter-input keys to map each letter of an alphabet to a single letter-input key, and receive a user selection of a particular letter-input key on the virtual keypad; and a character assignment module configured to determine an individual letter or grouping of letters that has been assigned to the particular letter-input key on the virtual keypad based on an frequency with which the individual letter or grouping of letters occurs in a subset of documents in a corpus; wherein the character assignment module is configured to update an assignment of the letters of the alphabet to the letter-input keys of the virtual keypad based on determining that the documents in the corpus have been updated. | 16. A smartphone comprising: a touchscreen display configured to: display a virtual keypad, wherein the virtual keypad includes an insufficient quantity of letter-input keys to map each letter of an alphabet to a single letter-input key, and receive a user selection of a particular letter-input key on the virtual keypad; and a character assignment module configured to determine an individual letter or grouping of letters that has been assigned to the particular letter-input key on the virtual keypad based on an frequency with which the individual letter or grouping of letters occurs in a subset of documents in a corpus; wherein the character assignment module is configured to update an assignment of the letters of the alphabet to the letter-input keys of the virtual keypad based on determining that the documents in the corpus have been updated. 17. The smartphone of claim 16 , comprising: a text message database configured to store text messages, and a corpus selector configured to select a subset of the text messages that are associated with the user of the mobile device as the subset of documents in the corpus. | 0.5 |
7,899,804 | 10 | 13 | 10. Computer readable media comprising program code that when executed by a programmable processor causes the processor to execute a method for extracting semantic information from text data having associated metadata, the computer readable media comprising: program code for receiving selecting an ordered set of scale values for a plurality of scales corresponding to content setting information; for each scale value program code for determining at least one subset of metadata related to a subset of the scale value; for each of the scales and associated subsets, program code for determining a statistic on occurrences of a given content tagged with the metadata in each subset of the scale value, the given content tagged with at least one of the subset of metadata a number of instances by one or more users; program code for aggregating the statistics for each scale and associated subsets to determine a semantic level for the content that indicates a level of semantic correspondence between the content and the scales and associated subsets based on the statistic on occurrences of the given content tagged with the metadata in each subset of the scale value; program code for determining the scales and associated subsets associated with the given content having a semantic level above a threshold value of occurrences of the given content tagged with the metadata in each subset of the scale value; program code for identifying the determined scales and associated subsets having a semantic level above the threshold value as corresponding to the semantics of the content; and program code for clustering the given content according to the determined scales and associated subsets. | 10. Computer readable media comprising program code that when executed by a programmable processor causes the processor to execute a method for extracting semantic information from text data having associated metadata, the computer readable media comprising: program code for receiving selecting an ordered set of scale values for a plurality of scales corresponding to content setting information; for each scale value program code for determining at least one subset of metadata related to a subset of the scale value; for each of the scales and associated subsets, program code for determining a statistic on occurrences of a given content tagged with the metadata in each subset of the scale value, the given content tagged with at least one of the subset of metadata a number of instances by one or more users; program code for aggregating the statistics for each scale and associated subsets to determine a semantic level for the content that indicates a level of semantic correspondence between the content and the scales and associated subsets based on the statistic on occurrences of the given content tagged with the metadata in each subset of the scale value; program code for determining the scales and associated subsets associated with the given content having a semantic level above a threshold value of occurrences of the given content tagged with the metadata in each subset of the scale value; program code for identifying the determined scales and associated subsets having a semantic level above the threshold value as corresponding to the semantics of the content; and program code for clustering the given content according to the determined scales and associated subsets. 13. The computer readable media of claim 10 , wherein the semantic information includes at least one of location data and event data. | 0.584375 |
9,830,392 | 12 | 13 | 12. A method of query-dependent and content-class based ranking, comprising: receiving a query for a search for content on a web site; performing a query-dependent and content-class based ranking of content available on the web site using a processor, comprising: determining a query-dependent score for content available on the web site based at least in part on the query, comprising: weighing a first value associated with a first attribute of the content by a first weight to obtain a first weighted score; weighing a second value associated with a second attribute of the content by a second weight to obtain a second weighted score, the first weight being different from the second weight; and calculating the query-dependent score based on the first weighted score and the second weighted score; determining a content-class score for content available on the web site in response to the query, comprising: determining a first content-class performance score based on a first query-dependent score, the first query-dependent score being associated with a first content item; determining a second content-class performance score based on a second query-dependent score, the second query-dependent score being associated with a second content item; and determining the content-class score based on the first content-class performance score and the second content-class performance score; and determining an overall score for content available on the web site based at least in part on the query-dependent score and based at least in part on the content-class score; and returning a ranked list of content based at least in part on the query-dependent and content-class based ranking of content available on the web site in response to the query. | 12. A method of query-dependent and content-class based ranking, comprising: receiving a query for a search for content on a web site; performing a query-dependent and content-class based ranking of content available on the web site using a processor, comprising: determining a query-dependent score for content available on the web site based at least in part on the query, comprising: weighing a first value associated with a first attribute of the content by a first weight to obtain a first weighted score; weighing a second value associated with a second attribute of the content by a second weight to obtain a second weighted score, the first weight being different from the second weight; and calculating the query-dependent score based on the first weighted score and the second weighted score; determining a content-class score for content available on the web site in response to the query, comprising: determining a first content-class performance score based on a first query-dependent score, the first query-dependent score being associated with a first content item; determining a second content-class performance score based on a second query-dependent score, the second query-dependent score being associated with a second content item; and determining the content-class score based on the first content-class performance score and the second content-class performance score; and determining an overall score for content available on the web site based at least in part on the query-dependent score and based at least in part on the content-class score; and returning a ranked list of content based at least in part on the query-dependent and content-class based ranking of content available on the web site in response to the query. 13. The method of claim 12 , further comprising: storing web services data associated with the web site, wherein the web services data comprises content on the web site. | 0.5 |
7,917,488 | 16 | 17 | 16. The method of claim 15 , wherein the unified ranking function is expressed as: ψ ( q c , d ) = { ∑ i λ i f i ( q c , d c ) if d is d c ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) + ∑ i , k π ik f i ( q c , d c ) h k ( d c , d e ) if d is d e , where ranking function ψ(q c ,d) is a function of the search query q c and the document d of the first set and the second set of documents; document d e is of the second set of documents in the second language; λ i is corresponding weight parameter; q e is a translation of the search query q c in the second language; ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e ; g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e ; μ ij is corresponding weight parameter; d c is a translation of the document d e in the first language; ƒ i (q c ,d c ) is a monolingual relevancy feature function used for estimating relevancy between the search query q c and the translation document d c ; h k (d c ,d e ) is a feature function associated with document translation between the translation document d c and the document d e ; and h ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ) and ƒ i (q c ,d c ), j is a second index that represents at least one g j (q c ,q e ), k is a third index that represents at least one h k (d c ,d e ). | 16. The method of claim 15 , wherein the unified ranking function is expressed as: ψ ( q c , d ) = { ∑ i λ i f i ( q c , d c ) if d is d c ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) + ∑ i , k π ik f i ( q c , d c ) h k ( d c , d e ) if d is d e , where ranking function ψ(q c ,d) is a function of the search query q c and the document d of the first set and the second set of documents; document d e is of the second set of documents in the second language; λ i is corresponding weight parameter; q e is a translation of the search query q c in the second language; ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e ; g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e ; μ ij is corresponding weight parameter; d c is a translation of the document d e in the first language; ƒ i (q c ,d c ) is a monolingual relevancy feature function used for estimating relevancy between the search query q c and the translation document d c ; h k (d c ,d e ) is a feature function associated with document translation between the translation document d c and the document d e ; and h ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ) and ƒ i (q c ,d c ), j is a second index that represents at least one g j (q c ,q e ), k is a third index that represents at least one h k (d c ,d e ). 17. The method of claim 16 , wherein weight parameters λ i , μ ij , and h ij are determined by optimizing search ranks using a ranking SVM algorithm over a training corpus. | 0.5 |
8,230,003 | 7 | 10 | 7. An XDMC (XML (eXtensible Markup Language) Document Management Client) method for implementing an XML (eXtensible Markup Language) document management function in an XDM (XML Document Management) system having an XDMC and an XDMS (XDM Server), the method comprising the steps of: (a) generating an XCAP (XDM Configuration Access Protocol) PUT request message for retrieving an XML document by the XDMS, the XCAP PUT request message including a first XCAP (Uniform Resource Indicator) URI that identifies a first storage from which the XDMS is to retrieve the XML document and a second XCAP URI that identifies a second storage position to which the retrieved XML document is to be stored by the XDMS; and (b) transmitting the XCAP PUT request message to a corresponding XDMS and not transmitting the XML document itself, wherein the second XCAP URI is obtained by concatenating an XCAP root URI to an XCAP document selector. | 7. An XDMC (XML (eXtensible Markup Language) Document Management Client) method for implementing an XML (eXtensible Markup Language) document management function in an XDM (XML Document Management) system having an XDMC and an XDMS (XDM Server), the method comprising the steps of: (a) generating an XCAP (XDM Configuration Access Protocol) PUT request message for retrieving an XML document by the XDMS, the XCAP PUT request message including a first XCAP (Uniform Resource Indicator) URI that identifies a first storage from which the XDMS is to retrieve the XML document and a second XCAP URI that identifies a second storage position to which the retrieved XML document is to be stored by the XDMS; and (b) transmitting the XCAP PUT request message to a corresponding XDMS and not transmitting the XML document itself, wherein the second XCAP URI is obtained by concatenating an XCAP root URI to an XCAP document selector. 10. The method as claimed in claim 7 , wherein the second XCAP URI of the corresponding XML document in the XCAP PUT request message is in a domain different from that of an XDMS in which a corresponding XML document is to be newly created. | 0.587629 |
9,213,705 | 13 | 14 | 13. The non-transitory computer-readable medium of claim 12 , wherein the first visual content item comprises an image, wherein presenting the first visual content item comprises presenting the image for display. | 13. The non-transitory computer-readable medium of claim 12 , wherein the first visual content item comprises an image, wherein presenting the first visual content item comprises presenting the image for display. 14. The non-transitory computer-readable medium of claim 13 , wherein a different image is presented for display during playback of each of two or more portions of the narration audio content. | 0.5 |
8,831,754 | 1 | 2 | 1. A computer-implemented method comprising: monitoring, by one or more processors, a stream of user click events occurring at an apparatus, each event being associated with a plurality of features describing the event, at least some of the plurality of features being related in a hierarchical manner; creating a graphical data structure comprising variable nodes connected by edges, the plurality of features describing the event being represented by variable nodes and the variable nodes being connected such that sequences of connected variable nodes represent the hierarchical relations between features, each variable node being associated with statistics describing a probability distribution representing a latent event score; arranging a training engine to update the statistics for at least one of the variable nodes on the basis of the monitoring; and predicting an event related to a simultaneous scope search using the graphical data structure. | 1. A computer-implemented method comprising: monitoring, by one or more processors, a stream of user click events occurring at an apparatus, each event being associated with a plurality of features describing the event, at least some of the plurality of features being related in a hierarchical manner; creating a graphical data structure comprising variable nodes connected by edges, the plurality of features describing the event being represented by variable nodes and the variable nodes being connected such that sequences of connected variable nodes represent the hierarchical relations between features, each variable node being associated with statistics describing a probability distribution representing a latent event score; arranging a training engine to update the statistics for at least one of the variable nodes on the basis of the monitoring; and predicting an event related to a simultaneous scope search using the graphical data structure. 2. The computer-implemented method of claim 1 , wherein the statistics for the at least one of the variable nodes are updated by using a Bayesian machine learning process. | 0.669884 |
8,417,855 | 16 | 17 | 16. The device of claim 10 , wherein the data file is a candidate data file. | 16. The device of claim 10 , wherein the data file is a candidate data file. 17. The device of claim 16 , the operations further comprising: receiving another input of the first language object; receiving another second input that comprises another key selection, the another key selection being the same as the one or more key selections; outputting the at least a portion of the another language object and the at least a portion of the particular language object as proposed interpretations of the another second input; receiving another selection of the at least a portion of the another language object; locating an entry in the candidate data file comprising another contextual value object that corresponds with the first language object and that is associated with a key object that corresponds with the another language object; and responsive to locating the entry, moving the another contextual value object and its associated key object from the candidate data file to the contextual data, wherein the another contextual value object is identified based on its associated key object occurring at a second statistically significant incidence with the another language object. | 0.5 |
7,594,172 | 20 | 21 | 20. A computer having a processor and a memory, and running software that executes a method according to claim 1 . | 20. A computer having a processor and a memory, and running software that executes a method according to claim 1 . 21. The computer of claim 20 , further comprising a component that links the processor to a network. | 0.5 |
10,002,189 | 29 | 48 | 29. A non-transitory computer readable storage medium containing an executable program for constructing database queries for searching a database, wherein the program is configured to cause at least one processor to perform the steps of: receiving a user entered search string, the search string comprising one or more words; identifying a first node in an ontology based on the one or more words of the search string, the first node being related to at least one of the one or more words in the search string, wherein the ontology includes at least one node representing a concept and at least one node representing an attribute of the concept; constructing a first database query based on the identified first node in the ontology, the first database query comprising one or more attributes associated with the first node, and a respective value, from the search string, for each of the one or more attributes; after constructing the first database query, searching at least one database using the first database query; identifying, based on a frequency of occurrence of a pair of user events, a second node in the ontology, the second node associated with the first node, the second additional node representing a concept not represented by the received search string, wherein a first user event of the pair of user events corresponds to the first node and a second user event of the pair of user events corresponds to the second node, and wherein for each occurrence of the pair of user events, the first user event and the second user event occur within a predetermined time period; constructing a second database query based on the identified second; after constructing the second database query, searching at least one database using the second database query; and outputting results of the searching. | 29. A non-transitory computer readable storage medium containing an executable program for constructing database queries for searching a database, wherein the program is configured to cause at least one processor to perform the steps of: receiving a user entered search string, the search string comprising one or more words; identifying a first node in an ontology based on the one or more words of the search string, the first node being related to at least one of the one or more words in the search string, wherein the ontology includes at least one node representing a concept and at least one node representing an attribute of the concept; constructing a first database query based on the identified first node in the ontology, the first database query comprising one or more attributes associated with the first node, and a respective value, from the search string, for each of the one or more attributes; after constructing the first database query, searching at least one database using the first database query; identifying, based on a frequency of occurrence of a pair of user events, a second node in the ontology, the second node associated with the first node, the second additional node representing a concept not represented by the received search string, wherein a first user event of the pair of user events corresponds to the first node and a second user event of the pair of user events corresponds to the second node, and wherein for each occurrence of the pair of user events, the first user event and the second user event occur within a predetermined time period; constructing a second database query based on the identified second; after constructing the second database query, searching at least one database using the second database query; and outputting results of the searching. 48. The computer readable storage medium of claim 29 , wherein the second node is associated with the first node based on a link between the first node and the second node. | 0.874269 |
8,832,047 | 13 | 14 | 13. The computer program product of claim 11 , wherein making the comparison comprises comparing cryptographic checksums of the first and second electronic documents. | 13. The computer program product of claim 11 , wherein making the comparison comprises comparing cryptographic checksums of the first and second electronic documents. 14. The computer program product of claim 13 , wherein comparing cryptographic checksums comprises comparing digital signatures embedded in the first and second electronic documents. | 0.5 |
9,563,487 | 8 | 12 | 8. A device, comprising: at least one processor and a memory; the memory having: one or more metadata files associated with one or more Application Programming Interface (API) modules, the one or more metadata files configured to include at least one description of one or more APIs included in the one or more API modules using an abstract type system to describe programmatic access to the one or more APIs, the at least one description being independent from specific programming languages, the one or more metadata files including calling parameter type descriptions associated with the APIs; one or more Application Binary Interface (ABI) modules configured to include one or more machine-level binary contracts for calling the one or more APIs; and one or more generated language projection modules configured to translate at least one type of the abstract type system to at least one type of one or more specific programming languages. | 8. A device, comprising: at least one processor and a memory; the memory having: one or more metadata files associated with one or more Application Programming Interface (API) modules, the one or more metadata files configured to include at least one description of one or more APIs included in the one or more API modules using an abstract type system to describe programmatic access to the one or more APIs, the at least one description being independent from specific programming languages, the one or more metadata files including calling parameter type descriptions associated with the APIs; one or more Application Binary Interface (ABI) modules configured to include one or more machine-level binary contracts for calling the one or more APIs; and one or more generated language projection modules configured to translate at least one type of the abstract type system to at least one type of one or more specific programming languages. 12. The device of claim 8 , wherein the one or more metadata files are configured to describe an object-oriented class, included in the one or more API modules, in an object-oriented manner. | 0.74734 |
7,831,869 | 1 | 6 | 1. A method of writing a block of user data to a tape storage medium, said method comprising: arranging said block of user data into an array of bytes, said array comprising a plurality of rows and a plurality of columns of said bytes; applying an error correction code to individual ones of said rows of bytes, such that said error correction coded rows each comprise four code words, wherein each of the four code words in each corresponding error correction coded row includes data bytes and error correcting bytes; in each of said error correction coded rows, interleaving said four code words of the row; and writing said error correction coded rows each comprising four code words into a diagonal track that extends diagonally across a width of the tape storage medium. | 1. A method of writing a block of user data to a tape storage medium, said method comprising: arranging said block of user data into an array of bytes, said array comprising a plurality of rows and a plurality of columns of said bytes; applying an error correction code to individual ones of said rows of bytes, such that said error correction coded rows each comprise four code words, wherein each of the four code words in each corresponding error correction coded row includes data bytes and error correcting bytes; in each of said error correction coded rows, interleaving said four code words of the row; and writing said error correction coded rows each comprising four code words into a diagonal track that extends diagonally across a width of the tape storage medium. 6. The method as claimed in claim 1 , wherein each of said columns is divided into a pair of interleaved code words. | 0.873362 |
6,016,499 | 28 | 54 | 28. The system of claim 24, further comprising a NetWare Core Protocol API, also known as the NCP API, wherein the driver is also capable of translating a relational database language statement into an executable NCP API sequence that includes a call to a callable element of the NCP API and produces an NCP API result, and the driver is also capable of translating the NCP API result into a relational database result. | 28. The system of claim 24, further comprising a NetWare Core Protocol API, also known as the NCP API, wherein the driver is also capable of translating a relational database language statement into an executable NCP API sequence that includes a call to a callable element of the NCP API and produces an NCP API result, and the driver is also capable of translating the NCP API result into a relational database result. 54. The system of claim 28, wherein the directory services repository component includes a non-mnemonic object name, the relational database language statement identifies a column of a table, and the driver and the API together map the non-mnemonic object name to the column. | 0.64653 |
8,977,555 | 25 | 28 | 25. A non-transitory computer readable medium comprising executable code that, when executed by a processor, causes a computing device to perform a process comprising: receiving, from a speech processing system: an audio presentation comprising a first portion corresponding to a first item and a second portion corresponding to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; presenting the audio presentation; and transmitting, to the speech processing system: audio data received via an audio input component of the computing device; and marker data comprising at least one of the first marker or the second marker. | 25. A non-transitory computer readable medium comprising executable code that, when executed by a processor, causes a computing device to perform a process comprising: receiving, from a speech processing system: an audio presentation comprising a first portion corresponding to a first item and a second portion corresponding to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; presenting the audio presentation; and transmitting, to the speech processing system: audio data received via an audio input component of the computing device; and marker data comprising at least one of the first marker or the second marker. 28. The non-transitory computer readable medium of claim 25 , wherein the marker data and the audio data are transmitted in separate data transmissions. | 0.814634 |
8,019,610 | 1 | 11 | 1. A method for interacting with a user using an automated dialog system, comprising: generating and storing via a processor communicative goals based on a single communication received from the user, the communicative goals being related to all information needed from the user; generating a plurality of sentence plans based on the communicative goals and on a dialog history database comprising previously gathered dialogs and a present dialog to yield a plurality of generated sentence plans, wherein each sentence plan of the plurality of generated sentence plans comprises an unordered set of elementary speech acts encoding the communicative goals, each speech act assigned a canonical lexico-structural representation, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the single communication received from the user; ranking, independent of the user, the plurality of generated sentence plans to yield ranked sentence plans; and outputting at least one of the ranked sentence plans to yield an output sentence plan, wherein each needed communicative goal of the communicative goals are addressed by the output sentence plan. | 1. A method for interacting with a user using an automated dialog system, comprising: generating and storing via a processor communicative goals based on a single communication received from the user, the communicative goals being related to all information needed from the user; generating a plurality of sentence plans based on the communicative goals and on a dialog history database comprising previously gathered dialogs and a present dialog to yield a plurality of generated sentence plans, wherein each sentence plan of the plurality of generated sentence plans comprises an unordered set of elementary speech acts encoding the communicative goals, each speech act assigned a canonical lexico-structural representation, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the single communication received from the user; ranking, independent of the user, the plurality of generated sentence plans to yield ranked sentence plans; and outputting at least one of the ranked sentence plans to yield an output sentence plan, wherein each needed communicative goal of the communicative goals are addressed by the output sentence plan. 11. The method of claim 1 , wherein the method is used in one of a customer care system, a reservation system, parts ordering system, navigation system, information gathering system, and information retrieval system. | 0.641196 |
7,788,591 | 12 | 14 | 12. A computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a method comprising: creating a customizable user interface (UI), using the processor, wherein the creating comprises selecting a UI theme from a plurality of theme templates, using the processor, wherein the UI theme defines an appearance of a customizable product class, the customizable product class comprises one or more customizable products, and the one or more customizable products are available to be purchased, adding one or more UI groups to the UI theme, using the processor, wherein each UI group of the one or more UI groups defines a subclass of the customizable product class, the subclass defines a component product of one or more component products, the component product is related to a customizable product of the one or more customizable products, and the component product is configured to be used in customizing the customizable product, assigning one or more UI controls to the subclass, using the processor, and providing a subclass-specific user interface, using the processor, wherein the subclass-specific user interface is configured to allow customization of the customizable product in a user-specified manner prior to purchase of the customizable product by virtue of being configured to allow selection of the component product using a corresponding UI control of the UI controls, and the corresponding UI control corresponds to the component product. | 12. A computer-readable storage medium containing instructions which, when executed by a processor, cause the processor to perform a method comprising: creating a customizable user interface (UI), using the processor, wherein the creating comprises selecting a UI theme from a plurality of theme templates, using the processor, wherein the UI theme defines an appearance of a customizable product class, the customizable product class comprises one or more customizable products, and the one or more customizable products are available to be purchased, adding one or more UI groups to the UI theme, using the processor, wherein each UI group of the one or more UI groups defines a subclass of the customizable product class, the subclass defines a component product of one or more component products, the component product is related to a customizable product of the one or more customizable products, and the component product is configured to be used in customizing the customizable product, assigning one or more UI controls to the subclass, using the processor, and providing a subclass-specific user interface, using the processor, wherein the subclass-specific user interface is configured to allow customization of the customizable product in a user-specified manner prior to purchase of the customizable product by virtue of being configured to allow selection of the component product using a corresponding UI control of the UI controls, and the corresponding UI control corresponds to the component product. 14. The computer-readable storage medium of claim 12 wherein the UI theme is associated with a set of properties that comprises one or more of a background color, font and multi-lingual text. | 0.5 |
8,813,046 | 1 | 5 | 1. A computer system for analyzing and transforming computer source code, the system comprising: a memory, storing computer executable instructions; and a processor operatively coupled to said memory and configured to execute the instructions to perform the following steps: analyze at least one source code file that processes character text data in an original format to determine compliance with a target locale neutral encoding format, the target locale neutral encoding format being selected from a plurality of locale neutral encoding formats based on a first estimation of the source code file's compliance with at least one of the plurality of locale neutral encoding formats and a second estimation of encoding conversions required to achieve compliance with the at least one of the plurality of locale neutral encoding formats; and transform the source code into a transformed source code that is capable of processing character text data in the target locale encoding format. | 1. A computer system for analyzing and transforming computer source code, the system comprising: a memory, storing computer executable instructions; and a processor operatively coupled to said memory and configured to execute the instructions to perform the following steps: analyze at least one source code file that processes character text data in an original format to determine compliance with a target locale neutral encoding format, the target locale neutral encoding format being selected from a plurality of locale neutral encoding formats based on a first estimation of the source code file's compliance with at least one of the plurality of locale neutral encoding formats and a second estimation of encoding conversions required to achieve compliance with the at least one of the plurality of locale neutral encoding formats; and transform the source code into a transformed source code that is capable of processing character text data in the target locale encoding format. 5. The system of claim 1 , wherein the system generates one or more reports indicating the results of the first and second estimation. | 0.627778 |
8,560,326 | 9 | 10 | 9. A method of providing an interface for use in an automated speech-to-speech translation system, the automated speech-to-speech translation system being operated by a system user and interacted with by a foreign language speaker, the method comprising the steps of: translating speech input between the foreign language speaker and the system user having a multilingual conversation using the automated speech-to-speech translation system; and utilizing an interface of the automated speech-to-speech translation to provide an indication to the foreign language speaker of when it is a turn of the foreign language speaker to commence speaking in a dialog interaction with the system user and provide speech input to the automated speech-to-speech translation system by the foreign language speaker, wherein utilizing an interface comprises: the system user enabling a microphone of the automated speech-to speech translation system via the interface; synthesizing at least one previously-generated text-based scripts into a voice prompt for playback to the foreign language speaker, the voice prompt comprising an audible message in a language understandable to the foreign language speaker to notify the foreign language speaker when it is a turn of the foreign language speaker to input speech to the automated speech-to-speech translation system; playing the audible message to the foreign language speaker to notify the foreign language speaker that is the foreign language speaker's turn for inputting speech to the automated speech-to-speech translation system; and receiving speech uttered into the microphone by the foreign language speaker for translation by the automated speech-to speech translation system. | 9. A method of providing an interface for use in an automated speech-to-speech translation system, the automated speech-to-speech translation system being operated by a system user and interacted with by a foreign language speaker, the method comprising the steps of: translating speech input between the foreign language speaker and the system user having a multilingual conversation using the automated speech-to-speech translation system; and utilizing an interface of the automated speech-to-speech translation to provide an indication to the foreign language speaker of when it is a turn of the foreign language speaker to commence speaking in a dialog interaction with the system user and provide speech input to the automated speech-to-speech translation system by the foreign language speaker, wherein utilizing an interface comprises: the system user enabling a microphone of the automated speech-to speech translation system via the interface; synthesizing at least one previously-generated text-based scripts into a voice prompt for playback to the foreign language speaker, the voice prompt comprising an audible message in a language understandable to the foreign language speaker to notify the foreign language speaker when it is a turn of the foreign language speaker to input speech to the automated speech-to-speech translation system; playing the audible message to the foreign language speaker to notify the foreign language speaker that is the foreign language speaker's turn for inputting speech to the automated speech-to-speech translation system; and receiving speech uttered into the microphone by the foreign language speaker for translation by the automated speech-to speech translation system. 10. The method of claim 9 , further comprising the step of displaying text in a first field of the interface representing translated speech uttered by the system user. | 0.5 |
7,827,125 | 67 | 68 | 67. A computer program product having a computer-readable medium having computer program instructions recorded thereon for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the computer program instruction comprising instructions for: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, where each of the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles by: defining simple profiled score criteria that are based on a single attribute or attribute path, the simple profiled score criteria instantiated as simple profiled score criteria values; wherein a partial score of the simple profiled score criteria value is computed using a similarity measure between a first vector including active profile weights and a second vector corresponding to values referenced by a target concept, where dimensions of the first and second vectors are defined by the values associated with the attribute path specified by the simple profiled score criteria, and wherein length of dimensions of the first vector are defined by the profile weights; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. | 67. A computer program product having a computer-readable medium having computer program instructions recorded thereon for learning user preferences in a search of knowledge base to construct one or more profiles for producing personalized search results, the computer program instruction comprising instructions for: receiving feedback from the user regarding quality of search results presented to the user in a search of a knowledge base that is a semantic network of relationships among concepts and that provides an index of a plurality of documents, the feedback representing how well the search results match an input query provided by the user, the search results including one or more of the documents indexed by the knowledge base; constructing the one or more profiles for the user, based on the feedback received, where each of the search results that receive feedback values are used to construct a model that includes profile weights computed from the feedback values; modifying internal weights used for scoring search criteria applied in producing the search results presented to the user, the modifications made based on the profile weights in the constructed model; generating implicit search criteria for the user based on the one or more profiles by: defining simple profiled score criteria that are based on a single attribute or attribute path, the simple profiled score criteria instantiated as simple profiled score criteria values; wherein a partial score of the simple profiled score criteria value is computed using a similarity measure between a first vector including active profile weights and a second vector corresponding to values referenced by a target concept, where dimensions of the first and second vectors are defined by the values associated with the attribute path specified by the simple profiled score criteria, and wherein length of dimensions of the first vector are defined by the profile weights; and applying the implicit search criteria and modified weights during a subsequent search of the knowledge base conducted by the user producing a subsequent set of search results that are personalized to the user. 68. The computer program product of claim 67 , wherein the input query is selected from a group consisting of: a query for job descriptions and a query for resumes for job candidates. | 0.796214 |
7,991,715 | 19 | 27 | 19. A system for image classification into a plurality of categories, comprising: means for, performing machine learning on a learning set of images; means for, generating a model based on the machine learning of the learning set of images; means for, determining an accuracy metric of the model using a verification set of images as one or more parameters in the model; and means for, generating a set of probability values; wherein each of the probability value of the set of probability values is generated for a pair of categories based on the accuracy metric. | 19. A system for image classification into a plurality of categories, comprising: means for, performing machine learning on a learning set of images; means for, generating a model based on the machine learning of the learning set of images; means for, determining an accuracy metric of the model using a verification set of images as one or more parameters in the model; and means for, generating a set of probability values; wherein each of the probability value of the set of probability values is generated for a pair of categories based on the accuracy metric. 27. The system of claim 19 , further comprising, means for, selecting at least one category of the plurality of categories associable with the image based on the tree structure. | 0.5 |
9,928,526 | 15 | 18 | 15. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including: accessing a set of action messages, each action message of the set of action messages including a set of key/value pairs and an identification of an action assigned to the action message by an abstraction layer, the action representing an actual or inferred user interaction with at least part of a website; extracting, from an action message in the set of action messages, a website identifier, the action message being associated with a user device; determining a session identifier for the action message; identifying, based on the website identifier, a current predictive model configured to generate action predictions, the current predictive model being configured to process a representation one or more past action observations to estimate one or more hidden variables and to generate output data corresponding to a subsequent-action prediction based on the one or more hidden variables; processing input data representing the action identified in the action message using the current predictive model to estimate the one or more hidden variables and to generate the output data corresponding to the subsequent-action prediction; generating an enhanced action message for the action message, at least part of the enhanced action message including prediction information corresponding to the output data, the prediction information representing a likelihood of subsequently detecting, in association with the user device, one or more user interactions with the website that correspond to a particular type of event or action; and outputting the enhanced action message to an enhanced-action-message sink, the enhanced-action-message sink including one or both of a downstream system and a remote system. | 15. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including: accessing a set of action messages, each action message of the set of action messages including a set of key/value pairs and an identification of an action assigned to the action message by an abstraction layer, the action representing an actual or inferred user interaction with at least part of a website; extracting, from an action message in the set of action messages, a website identifier, the action message being associated with a user device; determining a session identifier for the action message; identifying, based on the website identifier, a current predictive model configured to generate action predictions, the current predictive model being configured to process a representation one or more past action observations to estimate one or more hidden variables and to generate output data corresponding to a subsequent-action prediction based on the one or more hidden variables; processing input data representing the action identified in the action message using the current predictive model to estimate the one or more hidden variables and to generate the output data corresponding to the subsequent-action prediction; generating an enhanced action message for the action message, at least part of the enhanced action message including prediction information corresponding to the output data, the prediction information representing a likelihood of subsequently detecting, in association with the user device, one or more user interactions with the website that correspond to a particular type of event or action; and outputting the enhanced action message to an enhanced-action-message sink, the enhanced-action-message sink including one or both of a downstream system and a remote system. 18. The computer-program product as recited in claim 15 , wherein the actions further include: accessing, after the generating the enhanced action message, a subsequent action message, the subsequent action message including an identification of a subsequent action assigned to the action message by the abstraction layer; extracting, from the subsequent action message, a website identifier; determining that the subsequent action message corresponds to the session identifier; and updating the current predictive model based on a comparison involving the subsequent action and the output data. | 0.5 |
9,628,604 | 11 | 16 | 11. A method of controlling a watch type mobile terminal comprising: receiving voice data at a microphone; converting the voice data into a text in a first language; when a first gesture is not detected, translating the text in the first language into text in a second language, and when the first gesture is detected, translating the text in the second language to text in the first language. | 11. A method of controlling a watch type mobile terminal comprising: receiving voice data at a microphone; converting the voice data into a text in a first language; when a first gesture is not detected, translating the text in the first language into text in a second language, and when the first gesture is detected, translating the text in the second language to text in the first language. 16. The method of claim 11 , wherein converting the voice data into the text includes starting the converting when a second gesture and a third gesture are consecutively detected, the second gesture is a moving of the mobile terminal in a first direction, and the third gesture is a moving of the mobile terminal in a second direction which is different from the first direction. | 0.5 |
8,098,976 | 4 | 6 | 4. The method of providing top concepts for a video file, as in claim 1 , the method further comprising: receiving one or more manually generated tags associated with the video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; and based on the ranking of the plurality of words, generating one or more automated tags associated with the video file. | 4. The method of providing top concepts for a video file, as in claim 1 , the method further comprising: receiving one or more manually generated tags associated with the video file; based at least in part on the one or more manually entered tags, determining a preliminary category for the video file based on the preliminary category, generating a targeted transcript of the video file, wherein the targeted transcript includes a plurality of words; generating an ontology of the plurality of words based on the targeted transcript; ranking the plurality of words in the ontology based on a plurality of scoring factors; and based on the ranking of the plurality of words, generating one or more automated tags associated with the video file. 6. The method of providing top concepts for a video file, as in claim 4 , further comprising: determining if the rankings for each of the plurality of words exceed a threshold ranking value; and excluding any of the plurality of words that have a ranking value lower than the threshold value. | 0.754209 |
9,818,450 | 1 | 3 | 1. A method of subtitling, comprising the steps of: obtaining an audio file of dialogue in a first language; obtaining a file of script text corresponding to the dialogue in the audio file in the same first language; determining, by one or more processors of a computing device, a timing correspondence between dialogue in the audio file and words in the script text; detecting at least a first pause during performance of the dialogue in the audio file; defining, by the one or more processors, a respective breakable point in the script text corresponding to the or each detected pause; dividing, by the one or more processors, the script text out into a sequence of subtitle lines of text responsive to the location of one or more of the defined breakable points; obtaining a file of script text corresponding to the dialogue in the audio file in a different second language; obtaining the sequence of subtitle lines of text divided out of the script text of the first language, the sequence comprising a characteristic number of lines; detecting, by the one or more processors corresponding features of the text between both languages; dividing, by the one or more processors, the script text in the second language into a sequence of subtitle lines of text having the same characteristic number of lines, the points of division being responsive to the correspondence of features of the text between both languages; and outputting the sequence of subtitle lines of text for presentation on a display device. | 1. A method of subtitling, comprising the steps of: obtaining an audio file of dialogue in a first language; obtaining a file of script text corresponding to the dialogue in the audio file in the same first language; determining, by one or more processors of a computing device, a timing correspondence between dialogue in the audio file and words in the script text; detecting at least a first pause during performance of the dialogue in the audio file; defining, by the one or more processors, a respective breakable point in the script text corresponding to the or each detected pause; dividing, by the one or more processors, the script text out into a sequence of subtitle lines of text responsive to the location of one or more of the defined breakable points; obtaining a file of script text corresponding to the dialogue in the audio file in a different second language; obtaining the sequence of subtitle lines of text divided out of the script text of the first language, the sequence comprising a characteristic number of lines; detecting, by the one or more processors corresponding features of the text between both languages; dividing, by the one or more processors, the script text in the second language into a sequence of subtitle lines of text having the same characteristic number of lines, the points of division being responsive to the correspondence of features of the text between both languages; and outputting the sequence of subtitle lines of text for presentation on a display device. 3. A method of subtitling according to claim 1 , in which the step of detecting at least a first pause comprises the step of: classifying the pause as a short pause or a long pause according to whether the pause exceeds a predetermined threshold duration. | 0.704176 |
8,127,173 | 9 | 10 | 9. Method according to claim 7 , wherein, in case where each network element is defined by an ontology representation comprising at least one element property, characterizing said network element, and at least one class specificity, characterizing at least partly a class to which belongs said network element, one determines a parameter value while taking into account weights associated to the properties and/or the class specificities of the ontology representation of said failing network element and said other network element(s). | 9. Method according to claim 7 , wherein, in case where each network element is defined by an ontology representation comprising at least one element property, characterizing said network element, and at least one class specificity, characterizing at least partly a class to which belongs said network element, one determines a parameter value while taking into account weights associated to the properties and/or the class specificities of the ontology representation of said failing network element and said other network element(s). 10. Method according to claim 9 , wherein one determines a parameter value from a ratio between a first sum of the weights associated to the class specificities that are common to said failing network element and an other network element and the weights associated to the element properties that are common to said failing network element and said other network element, and a second sum of the weights associated to the class specificities of said failing network element and the weights associated to the element properties of said failing network element. | 0.5 |
9,053,179 | 5 | 6 | 5. The method as claimed in claim 1 , wherein the computer program product further comprises executable instructions that, when read and executed by the computer, causes the computer to: perform a depth-first search in the citation network represented by the established semantic links between documents; and retrieve forward-chained and backward-chained reasons-for-citing and headnotes based on a starting reason-for-citing representing a specified citation. | 5. The method as claimed in claim 1 , wherein the computer program product further comprises executable instructions that, when read and executed by the computer, causes the computer to: perform a depth-first search in the citation network represented by the established semantic links between documents; and retrieve forward-chained and backward-chained reasons-for-citing and headnotes based on a starting reason-for-citing representing a specified citation. 6. The method as claimed in claim 5 , wherein the computer program product further comprises executable instructions that, when read and executed by the computer, causes the computer to display a digest window for allowing a user to view other issues discussed in each document and to transition the display to one of the other issues in the form of a new user-interactive sub-network. | 0.5 |
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