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8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe the plurality of spoken utterances occurring during a call, assign each of the plurality of spoken utterances with a corresponding set of classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned classifications and the corresponding plurality of spoken utterances to a training data set. | 8. An apparatus, comprising: a receiver configured to receive a plurality of spoken utterances and record them in a database memory; and a processor configured to transcribe the plurality of spoken utterances occurring during a call, assign each of the plurality of spoken utterances with a corresponding set of classifications, determine a confidence rating associated with each of the plurality of spoken utterances and the assigned set of classifications, and perform at least one of reclassify the plurality of spoken utterances with new classifications based on at least one additional classification operation, and add the assigned classifications and the corresponding plurality of spoken utterances to a training data set. 12. The apparatus of claim 8 , wherein if the determined confidence rating associated with each of the plurality of spoken utterances produces confidence ratings that are below a predefined threshold then the processor is configured to reclassify the plurality of spoken utterances with new classifications based on at least two different classification operations. | 0.718819 |
1. A method, performed by a computing system, for providing a dictating service, comprising: receiving a speech signal in response to vocalization, by a user, of an incremental portion of a complete utterance, the speech signal being from a microphone; interpreting the incremental portion based on the speech signal, to provide recognized speech, prior to the user finishing the complete utterance; and providing rendered text associated with the recognized speech on an output presentation displayed on a display screen prior to the user finishing the complete utterance, wherein providing the rendered text on the output presentation further comprises modifying a rate at which the rendered text is presented on the output presentation, the rate being modified based on a level of uncertainty associated with each part of the rendered text. | 1. A method, performed by a computing system, for providing a dictating service, comprising: receiving a speech signal in response to vocalization, by a user, of an incremental portion of a complete utterance, the speech signal being from a microphone; interpreting the incremental portion based on the speech signal, to provide recognized speech, prior to the user finishing the complete utterance; and providing rendered text associated with the recognized speech on an output presentation displayed on a display screen prior to the user finishing the complete utterance, wherein providing the rendered text on the output presentation further comprises modifying a rate at which the rendered text is presented on the output presentation, the rate being modified based on a level of uncertainty associated with each part of the rendered text. 3. The method of claim 1 , wherein one or more incremental portions of the complete utterance correspond to respective phrases of the complete utterance. | 0.768014 |
16. A computer program product comprising a non-transitory tangible storage medium storing computer program instructions executable to perform a method comprising: storing a script associated with a campaign and a set of user information for a user selected for the campaign, the script specifying a plurality of events; executing a first instruction corresponding to the script, wherein the first instruction is operable to send a first communication to the user from a server; determining a value for a variable associated with an event specified by the script, wherein the determination of the value is based on an interaction with the first communication by the user; determining a second instruction according to the script based on the set of user information; and executing the second instruction to send a second communication to the user from the server. | 16. A computer program product comprising a non-transitory tangible storage medium storing computer program instructions executable to perform a method comprising: storing a script associated with a campaign and a set of user information for a user selected for the campaign, the script specifying a plurality of events; executing a first instruction corresponding to the script, wherein the first instruction is operable to send a first communication to the user from a server; determining a value for a variable associated with an event specified by the script, wherein the determination of the value is based on an interaction with the first communication by the user; determining a second instruction according to the script based on the set of user information; and executing the second instruction to send a second communication to the user from the server. 18. The computer program product of claim 16 , wherein the set of user information is obtained from a user interaction with an email. | 0.631667 |
10. A computer-implemented system for generating a training set for use during document review, comprising: an assignment module to assign classification codes to a set of documents; a classification receipt module to receive further classification codes assigned to the same set of documents; a comparison module to compare the classification code for at least one document with the further classification code for that document; a determination module to determine whether a disagreement exists between the assigned classification code and the further classification code for at least one document; an identification module to identify those documents with disagreeing classification codes as training set candidates; a training set module to apply a stop threshold to the training set candidates and to designate the training set candidates as a training set when the stop threshold is satisfied, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and a processor to execute the modules. | 10. A computer-implemented system for generating a training set for use during document review, comprising: an assignment module to assign classification codes to a set of documents; a classification receipt module to receive further classification codes assigned to the same set of documents; a comparison module to compare the classification code for at least one document with the further classification code for that document; a determination module to determine whether a disagreement exists between the assigned classification code and the further classification code for at least one document; an identification module to identify those documents with disagreeing classification codes as training set candidates; a training set module to apply a stop threshold to the training set candidates and to designate the training set candidates as a training set when the stop threshold is satisfied, wherein the stop threshold comprises one of a percentage of disagreement, a number of documents with disagreeing classifications, and a zero-defect test; and a processor to execute the modules. 13. A system according to claim 10 , wherein the classification codes are assigned by a machine and the further classification codes are assigned by a further machine. | 0.59289 |
10. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, selecting an original object from an item of original content, wherein the original object comprises at least one original attribute; selecting a replacement object from a source other than the item of original content; replacing, in the item of original content, at least one original attribute of the selected original object with at least one attribute of the replacement object to form an item of modified content; determining a coherence value for the item of modified content, wherein the coherence value is based at least in part on a number of times that two or more words included in the item of modified content appear together in a plurality of items of original content; and based at least in part on a determination that the coherence value does not satisfy a threshold value, replacing, in the item of modified content, the at least one attribute of the selected replacement object with at least one of: a different attribute of the selected replacement object or an attribute of a different replacement object. | 10. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, selecting an original object from an item of original content, wherein the original object comprises at least one original attribute; selecting a replacement object from a source other than the item of original content; replacing, in the item of original content, at least one original attribute of the selected original object with at least one attribute of the replacement object to form an item of modified content; determining a coherence value for the item of modified content, wherein the coherence value is based at least in part on a number of times that two or more words included in the item of modified content appear together in a plurality of items of original content; and based at least in part on a determination that the coherence value does not satisfy a threshold value, replacing, in the item of modified content, the at least one attribute of the selected replacement object with at least one of: a different attribute of the selected replacement object or an attribute of a different replacement object. 13. The computer-implemented method of claim 10 , wherein the original object is selected based at least partially on user input. | 0.617889 |
16. A computer program product comprising electronic transcript and exhibit files, wherein the computer program product comprises a computer readable medium that stores: an importing module configured to import one or more electronic transcript files and one or more electronic exhibit files; an association module configured to 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; and a bundle that comprises the one or more electronic transcript files, the one or more electronic exhibit files, the operable electronic link, and an executable viewer module configured to: provide the one or more electronic transcript files in the bundle; and provide 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, the computer readable medium comprising a portable device. | 16. A computer program product comprising electronic transcript and exhibit files, wherein the computer program product comprises a computer readable medium that stores: an importing module configured to import one or more electronic transcript files and one or more electronic exhibit files; an association module configured to 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; and a bundle that comprises the one or more electronic transcript files, the one or more electronic exhibit files, the operable electronic link, and an executable viewer module configured to: provide the one or more electronic transcript files in the bundle; and provide 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, the computer readable medium comprising a portable device. 20. The computer program product of claim 16 , wherein the executable viewer module in the bundle is further configured to provide a remote processor access to the one or more electronic transcript files and the one or more electronic exhibit files in the bundle over a network connection. | 0.692825 |
12. The computer-implemented method of claim 9 , wherein the method further comprises: determining a level of confidence associated with a network domain in which the network location resides, and wherein the determination of whether the retrieved information confirms the validity of the correction submission is dependent on the level of confidence. | 12. The computer-implemented method of claim 9 , wherein the method further comprises: determining a level of confidence associated with a network domain in which the network location resides, and wherein the determination of whether the retrieved information confirms the validity of the correction submission is dependent on the level of confidence. 13. The computer-implemented method of claim 12 , wherein determining the level of confidence associated with the network location comprises determining whether a network domain of the network location is listed on a list of trusted network domains. | 0.879773 |
17. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; and third program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects; and wherein the first, second, and third program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 17. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; and third program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects; and wherein the first, second, and third program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 18. The computer system of claim 17 , further comprising: fourth program instructions to data mine a data structure for the non-contextual data object and the context object, wherein said data mining locates said at least one specific data store that comprises data contained in the non-contextual data object and the context object; and wherein the fourth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 0.5 |
1. A computer implemented method, comprising: receiving a search query for a programming code search engine; searching a programming code database with the search query in a form of a search criterion that conforms to an underlying storage of textual keywords and metadata, the programming code database being populated with programming code from one or more repositories of programming code, the programming code in the programming code database being indexed by use of a full-text analysis of the programming code, the full-text analysis including: a plain-text analysis that evaluates the programming code as plain text to extract a set of plain text keywords found in the programming code; and a plain text-based statistical analysis that derives statistical metadata from the set of plain text keywords; scoring results of the searching according to a scoring criterion, the scoring criterion including a reuse score that tracks a copying for reuse of lines of programming instructions in the programming code database; and presenting the results of the searching in a ranked order according to the scoring, the results being a subset of the programming code corresponding to the search query. | 1. A computer implemented method, comprising: receiving a search query for a programming code search engine; searching a programming code database with the search query in a form of a search criterion that conforms to an underlying storage of textual keywords and metadata, the programming code database being populated with programming code from one or more repositories of programming code, the programming code in the programming code database being indexed by use of a full-text analysis of the programming code, the full-text analysis including: a plain-text analysis that evaluates the programming code as plain text to extract a set of plain text keywords found in the programming code; and a plain text-based statistical analysis that derives statistical metadata from the set of plain text keywords; scoring results of the searching according to a scoring criterion, the scoring criterion including a reuse score that tracks a copying for reuse of lines of programming instructions in the programming code database; and presenting the results of the searching in a ranked order according to the scoring, the results being a subset of the programming code corresponding to the search query. 22. The method of claim 1 , wherein the search query further includes a language specific search query component for parsing of the programming code to extract and store certain meta data and statistics as additional search query criteria and to aid a scoring and ranking of the results of the searching. | 0.665157 |
1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts. | 1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts. 3. The method according to claim 1 , wherein identifying a group of syntactic structures comprises identifying a word. | 0.857558 |
1. A method for shifting and recharging an emotional state of a user with word sequencing presented on a data processing apparatus with a display and an input, the method comprising the steps of: receiving, from the user through the input of the data processing apparatus, a selection of a first word sequence set defined by a mood recharging characteristic value, the first word sequence set including a plurality of words each with at least one corresponding definition; generating on the display with a first predefined typeface a first one of the plurality of words in the selected first word sequence set; generating on the display with a second predefined typeface, while the first one of the plurality of words remains generated on the display, a first one of the at least one corresponding definition of the first one of the plurality of words in the selected first word sequence set for a time duration corresponding to a predefined cadence rate value; and prompting the user with a question related to the mood recharging characteristic value and associated with the first word sequence set. | 1. A method for shifting and recharging an emotional state of a user with word sequencing presented on a data processing apparatus with a display and an input, the method comprising the steps of: receiving, from the user through the input of the data processing apparatus, a selection of a first word sequence set defined by a mood recharging characteristic value, the first word sequence set including a plurality of words each with at least one corresponding definition; generating on the display with a first predefined typeface a first one of the plurality of words in the selected first word sequence set; generating on the display with a second predefined typeface, while the first one of the plurality of words remains generated on the display, a first one of the at least one corresponding definition of the first one of the plurality of words in the selected first word sequence set for a time duration corresponding to a predefined cadence rate value; and prompting the user with a question related to the mood recharging characteristic value and associated with the first word sequence set. 2. The method of claim 1 , further comprising: receiving on the data processing apparatus through the input a user-supplied answer to the question. | 0.654985 |
17. One or more non-transitory computer-readable storage media having instructions stored thereon, that when executed by one or more processors, cause the one or more processors to perform: receiving, by a computing device comprising a natural language understanding automatic speech recognition computing engine device, a first natural language input comprising one or more words; activating, by the natural language understanding automatic speech recognition computing engine device, a first task based on the first natural language input, wherein the first task is associated with one or more first task agents configured for retrieving information associated with the first task; prompting, by the natural language understanding automatic speech recognition computing engine device and via a first of the one or more first task agents, for a subsequent natural language input based on a first transcription of the first natural language input and based on a first intent associated with the first task; receiving, by the natural language understanding automatic speech recognition computing engine device and while the first task is activated, a second natural language input comprising one or more words; responsive to determining, by the natural language understanding automatic speech recognition computing engine device, that a task activation switching parameter associated with the first task is not a false value and that a second intent associated with the second natural language input is different from the first intent associated with the first task, determining, by the natural language understanding automatic speech recognition computing engine device: one or more candidate second tasks that are capable of being activated based on one or more task switching rules that identify one or more tasks that are allowed to interrupt the activated first task, wherein an interrupted task is arranged in a task stack memory component of the computing device; and one or more candidate third tasks that are incapable of being activated based on the one or more task switching rules; activating, by the natural language understanding automatic speech recognition computing engine device, one of the one or more candidate second tasks, wherein the activated candidate second task is associated with one or more second task agents configured for retrieving information associated with the activated candidate second task; responsive to satisfying the one or more second task agents with the first natural language input, the second natural language input, or an additional natural language input, performing, by the computing device, an action associated with the activated second candidate task; determining, by the natural language understanding automatic speech recognition computing engine device, whether the second natural language input satisfies the one or more first task agents associated with the first task; performing, by the computing device, an action associated with the first task responsive to the second natural language input satisfying the one or more first task agents; and prompting, by the natural language understanding automatic speech recognition computing engine device and via one of the one or more first task agents, for a second subsequent natural language input based on the first transcription of the first natural language input responsive to the second natural language input not satisfying the one or more first task agents. | 17. One or more non-transitory computer-readable storage media having instructions stored thereon, that when executed by one or more processors, cause the one or more processors to perform: receiving, by a computing device comprising a natural language understanding automatic speech recognition computing engine device, a first natural language input comprising one or more words; activating, by the natural language understanding automatic speech recognition computing engine device, a first task based on the first natural language input, wherein the first task is associated with one or more first task agents configured for retrieving information associated with the first task; prompting, by the natural language understanding automatic speech recognition computing engine device and via a first of the one or more first task agents, for a subsequent natural language input based on a first transcription of the first natural language input and based on a first intent associated with the first task; receiving, by the natural language understanding automatic speech recognition computing engine device and while the first task is activated, a second natural language input comprising one or more words; responsive to determining, by the natural language understanding automatic speech recognition computing engine device, that a task activation switching parameter associated with the first task is not a false value and that a second intent associated with the second natural language input is different from the first intent associated with the first task, determining, by the natural language understanding automatic speech recognition computing engine device: one or more candidate second tasks that are capable of being activated based on one or more task switching rules that identify one or more tasks that are allowed to interrupt the activated first task, wherein an interrupted task is arranged in a task stack memory component of the computing device; and one or more candidate third tasks that are incapable of being activated based on the one or more task switching rules; activating, by the natural language understanding automatic speech recognition computing engine device, one of the one or more candidate second tasks, wherein the activated candidate second task is associated with one or more second task agents configured for retrieving information associated with the activated candidate second task; responsive to satisfying the one or more second task agents with the first natural language input, the second natural language input, or an additional natural language input, performing, by the computing device, an action associated with the activated second candidate task; determining, by the natural language understanding automatic speech recognition computing engine device, whether the second natural language input satisfies the one or more first task agents associated with the first task; performing, by the computing device, an action associated with the first task responsive to the second natural language input satisfying the one or more first task agents; and prompting, by the natural language understanding automatic speech recognition computing engine device and via one of the one or more first task agents, for a second subsequent natural language input based on the first transcription of the first natural language input responsive to the second natural language input not satisfying the one or more first task agents. 20. The one or more non-transitory computer-readable storage media of claim 17 , wherein the instructions further cause the one or more processors to perform: receiving, while the first task and the activated candidate second task are activated, a third natural language input comprising one or more words; responsive to determining that a third intent associated with the third natural language input is different from the first intent associated with the first task and from the second intent associated with the second natural language input, determining one or more candidate fourth tasks that are capable of being activated based on one or more second task switching rules that identify one or more tasks that are allowed to interrupt the activated first task and the activated candidate second task; activating one of the one or more candidate fourth tasks, wherein the activated candidate fourth task is associated with one or more fourth task agents; and responsive to satisfying the one or more fourth task agents, performing an action associated with the activated fourth candidate task. | 0.5 |
1. A method to generate selected tabular data from an object relational data model using a faceted interaction interface, the method comprising: providing, by a processor, a faceted interaction interface to specify a faceted query to provide the selected tabular data from the object relational data model, wherein the faceted query comprises at least one facet and at least one facet condition; constructing, by the processor, an object relational graph from a plurality of input object tables of the object relational data model, wherein constructing the object relational graph comprises creating a node of the object relational graph corresponding to each input object table; selecting, by the processor, each object in the object relational graph which contains the at least one facet; identifying, by the processor, each object in the object relational graph on which the at least one facet condition applies; generating, by the processor, at least one object group from the object relational graph, each object group comprising a path from a top level object which contains the at least one facet in the object relational graph to an object which contains the at least one facet and which does not have any children in the object relational graph; and generating, by the processor, an object table for each object group, wherein the object table comprises selected tabular data from the object relational data model. | 1. A method to generate selected tabular data from an object relational data model using a faceted interaction interface, the method comprising: providing, by a processor, a faceted interaction interface to specify a faceted query to provide the selected tabular data from the object relational data model, wherein the faceted query comprises at least one facet and at least one facet condition; constructing, by the processor, an object relational graph from a plurality of input object tables of the object relational data model, wherein constructing the object relational graph comprises creating a node of the object relational graph corresponding to each input object table; selecting, by the processor, each object in the object relational graph which contains the at least one facet; identifying, by the processor, each object in the object relational graph on which the at least one facet condition applies; generating, by the processor, at least one object group from the object relational graph, each object group comprising a path from a top level object which contains the at least one facet in the object relational graph to an object which contains the at least one facet and which does not have any children in the object relational graph; and generating, by the processor, an object table for each object group, wherein the object table comprises selected tabular data from the object relational data model. 2. The method of claim 1 , wherein constructing the object relational graph comprises listing each object or column of data from each input object table in the node corresponding to each input object table. | 0.647935 |
8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program comprises a natural language processing pipeline configured to execute on a data processing system to: receive an input document to be ingested into a corpus; divide the input document into a plurality of input passages; identify whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add the filtered plurality of input passages into the corpus. | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program comprises a natural language processing pipeline configured to execute on a data processing system to: receive an input document to be ingested into a corpus; divide the input document into a plurality of input passages; identify whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add the filtered plurality of input passages into the corpus. 11. The computer program product of claim 8 , wherein annotating the input passage comprises annotating the input passage for linguistic part-of-speech features. | 0.859862 |
6. The method of claim 1 , wherein determining, for the user, a best page of a cluster of pages associated with the queried concept based on information about the user further comprises: retrieving preferences information for similar users of the social networking system compared to the user; and determining the best page of the cluster of pages based on the retrieved preferences information for the similar users of the social networking system connected compared to the user. | 6. The method of claim 1 , wherein determining, for the user, a best page of a cluster of pages associated with the queried concept based on information about the user further comprises: retrieving preferences information for similar users of the social networking system compared to the user; and determining the best page of the cluster of pages based on the retrieved preferences information for the similar users of the social networking system connected compared to the user. 7. The method of claim 6 , wherein similar users of the social networking system compared to the user comprises users of the social networking system that are in the same demographic as the user. | 0.841463 |
1. A method for managing Resource Description Framework (“RDF”) graphs in a distributed system, the method on a client information processing system comprising: receiving at least one modification request for modifying an RDF graph in a shared data store, wherein the modification request includes at least one precondition query created based on a change set generated on a local shared data store associated with the shared data store, an expected result set, and the change set, wherein the precondition query comprises a set of preconditions that test a state of the RDF graph before executing the change set, wherein at least one precondition in the set of preconditions is based on a state of the local shared data store prior to the change set being applied at the local data store, wherein the expected result set is a set of results expected by the precondition query in response to applying the set of preconditions to the RDF graph, and wherein the change set is at least one statement that changes a set of data elements in the RDF graph; applying the precondition query to the RDF graph at the shared data store; analyzing a set of results of the precondition query; and sending, in response to the set of results of the precondition query matching the expected result set, a transaction request associated with the modification request to a server information processing system communicatively coupled to the shared data storage, wherein the transaction request comprises the change set. | 1. A method for managing Resource Description Framework (“RDF”) graphs in a distributed system, the method on a client information processing system comprising: receiving at least one modification request for modifying an RDF graph in a shared data store, wherein the modification request includes at least one precondition query created based on a change set generated on a local shared data store associated with the shared data store, an expected result set, and the change set, wherein the precondition query comprises a set of preconditions that test a state of the RDF graph before executing the change set, wherein at least one precondition in the set of preconditions is based on a state of the local shared data store prior to the change set being applied at the local data store, wherein the expected result set is a set of results expected by the precondition query in response to applying the set of preconditions to the RDF graph, and wherein the change set is at least one statement that changes a set of data elements in the RDF graph; applying the precondition query to the RDF graph at the shared data store; analyzing a set of results of the precondition query; and sending, in response to the set of results of the precondition query matching the expected result set, a transaction request associated with the modification request to a server information processing system communicatively coupled to the shared data storage, wherein the transaction request comprises the change set. 4. The method of claim 1 , wherein the precondition query is one of: a SPARQL SELECT statement; and a SPARQL ASK statement. | 0.604712 |
1. A method of checking a source code, comprising: converting the source code to an installation model by a model construction unit; converting the installation model to a generalization model by an installation-generalization model conversion unit, wherein the generalization model includes generalized program information which does not depend on a language of the source code; converting the generalization model to an abstraction model by an abstraction model conversion unit, wherein the abstraction model is in an intermediate format that does not depend on the language of the source code; converting the abstraction model to a nonfunctional constraint additional generalization model by a nonfunctional constraint addition processing unit, wherein the nonfunctional constraint addition processing unit adds a nonfunctional constraint to each function of the abstraction model based on a nonfunctional rule; converting the nonfunctional constraint additional generalization model to an inspection model by a generalization-inspection model conversion unit, wherein the inspection model is in a language of a model checking tool; converting the inspection model to an inspection code by an inspection code writing unit; and checking the inspection code by the model checking tool to determine whether the source code is validated. | 1. A method of checking a source code, comprising: converting the source code to an installation model by a model construction unit; converting the installation model to a generalization model by an installation-generalization model conversion unit, wherein the generalization model includes generalized program information which does not depend on a language of the source code; converting the generalization model to an abstraction model by an abstraction model conversion unit, wherein the abstraction model is in an intermediate format that does not depend on the language of the source code; converting the abstraction model to a nonfunctional constraint additional generalization model by a nonfunctional constraint addition processing unit, wherein the nonfunctional constraint addition processing unit adds a nonfunctional constraint to each function of the abstraction model based on a nonfunctional rule; converting the nonfunctional constraint additional generalization model to an inspection model by a generalization-inspection model conversion unit, wherein the inspection model is in a language of a model checking tool; converting the inspection model to an inspection code by an inspection code writing unit; and checking the inspection code by the model checking tool to determine whether the source code is validated. 4. The method of claim 1 , wherein the nonfunctional constraint includes a temporal constraint or a capacitive constraint. | 0.772222 |
10. The method of claim 9 , wherein the determining further comprises identifying a corpus of information comprising a plurality of terms and a plurality of topical entries, each term of the plurality of terms corresponding to a topical entry of the plurality of topical entries. | 10. The method of claim 9 , wherein the determining further comprises identifying a corpus of information comprising a plurality of terms and a plurality of topical entries, each term of the plurality of terms corresponding to a topical entry of the plurality of topical entries. 11. The method of claim 10 , wherein the determining further comprises counting, within each topical entry of the plurality of topical entries, occurrences of list terms from each list of the plurality of lists. | 0.934112 |
28. A method of using a computer to make a probability table for use in apparatus for determining whether a sense for a word is lexically appropriate to a given position in a text, the method of making the table comprising the steps of: using the computer system to make and store a conditional sample of a text corpus accessible to the computer system, the conditional sample including contexts from the text corpus which are semantically related to the sense specified in a given word/sense pair; using the computer system to determine for each word which occurs in the conditional sample a weight of that word in the conditional sample with regard to the probability that the word of the given word/sense pair has the sense specified in the given word/sense pair, the determination of the weight being done using a Bayesian technique; and storing a table entry in the computer system which includes the weight of the word for each of the occurring words which has more than a given weight. | 28. A method of using a computer to make a probability table for use in apparatus for determining whether a sense for a word is lexically appropriate to a given position in a text, the method of making the table comprising the steps of: using the computer system to make and store a conditional sample of a text corpus accessible to the computer system, the conditional sample including contexts from the text corpus which are semantically related to the sense specified in a given word/sense pair; using the computer system to determine for each word which occurs in the conditional sample a weight of that word in the conditional sample with regard to the probability that the word of the given word/sense pair has the sense specified in the given word/sense pair, the determination of the weight being done using a Bayesian technique; and storing a table entry in the computer system which includes the weight of the word for each of the occurring words which has more than a given weight. 29. The method set forth in claim 28 wherein: the step of making a conditional sample is done using contexts which are predominantly substantially longer than the average length of the sentences in the text corpus. | 0.593366 |
3. The method of claim 1 , wherein at least one context entry in the context store comprises a context entry metadata element defining restrictions on the use of the at least one context entry. | 3. The method of claim 1 , wherein at least one context entry in the context store comprises a context entry metadata element defining restrictions on the use of the at least one context entry. 4. The method of claim 3 , wherein the restrictions on the use of the at least one context entry include at least one restriction based on a protocol. | 0.936346 |
1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. | 1. A method, performed by a computing system, for generating trending action statistics that match a query, comprising: receiving, by a server, the query identifying one or more of: a search action or a search action target; selecting a set of posts relevant to the query, the set of posts comprising one or more action posts that contain at least one sentence that specifies a post action and a post action target; for one or more selected action posts of the one or more action posts: dividing the selected action post into one or more sentences; creating, for at least one action sentence of the one or more sentences, a dependency structure correlating a performed action identified in the action sentence with an action target identified in the action sentence, wherein the identification of the performed action comprises a first identifier, within the action sentence, corresponding to the performed action, and wherein the identification of the action target comprises a second identifier, within the action sentence, corresponding to one or more objects of the action sentence; determining, based on the dependency structure, that the selected action post matches the query by: determining that the search action specified in the query matches the performed action identified in the dependency structure; or determining that the search action target specified in the query matches the action target identified in the dependency structure; in response to determining that the selected action post matches the query, updating a count of matching actions or a count of matching action targets corresponding to the action or action target identified in the dependency structure; communicating between the server and a database to generate a response to the query by computing statistics based on the count of matching actions or the count of matching action targets; and providing the response to the query. 11. The method of claim 1 wherein the computed statistics used to generate the response to the query are further based on a count of non-matching posts or non-matching sentences that, based on another dependency structure generated for each non-matching sentence, do not match the search action specified in the query or do not match the search action target specified in the query. | 0.545987 |
1. A system, comprising: a mobile computing device associated with a vehicle and comprising a cellular network interface configured to receive or send a text message over a cellular network; and a network computing device, comprising a network interface, and configured to: obtain, from the mobile computing device or another network computing device, information indicating a driving situation related to the vehicle; determine an access level based on the obtained information; and transmit the access level to the mobile computing device; wherein the mobile computing device is configured to: determine that a user associated with the mobile computing device is attempting to send a first outgoing text message during a drive; determine a first message priority level of the first outgoing text message; determine a first recipient priority level of a first recipient of the first outgoing text message; based on the access level, the first message priority level, and the first recipient priority level, block the user from sending the first outgoing text message and set a reminder regarding the first outgoing text message; determine that the drive has ended; and in response to determining that the drive has ended and based on the reminder, prompt the user to send the first outgoing text message. | 1. A system, comprising: a mobile computing device associated with a vehicle and comprising a cellular network interface configured to receive or send a text message over a cellular network; and a network computing device, comprising a network interface, and configured to: obtain, from the mobile computing device or another network computing device, information indicating a driving situation related to the vehicle; determine an access level based on the obtained information; and transmit the access level to the mobile computing device; wherein the mobile computing device is configured to: determine that a user associated with the mobile computing device is attempting to send a first outgoing text message during a drive; determine a first message priority level of the first outgoing text message; determine a first recipient priority level of a first recipient of the first outgoing text message; based on the access level, the first message priority level, and the first recipient priority level, block the user from sending the first outgoing text message and set a reminder regarding the first outgoing text message; determine that the drive has ended; and in response to determining that the drive has ended and based on the reminder, prompt the user to send the first outgoing text message. 7. The system of claim 1 , wherein the mobile computing device is configured to: receive a second access level; determine that the user is attempting to send a second outgoing text message; determine a second message priority level of the second outgoing text message; determine a second recipient priority level of a second recipient of the second outgoing text message; and based on the second access level, the second message priority level, and the second recipient priority level, allow the user to send the second outgoing text message. | 0.782262 |
1. An apparatus for providing a user interface in an on-demand software service environment, the apparatus comprising: a network interface; and a processor system comprising at least one processor, the processor system configured for: receiving, via the network interface, a component request from a first client device; determining a first component definition corresponding to the component request includes a second component definition, the second component definition being at a lower level of a component definition hierarchy than the first component definition, the first component definition being associated with a first component type, and the second component definition being associated with a second component type, the first component definition and the second component definition being associated with one or more components of a user interface; determining access to the second component definition is allowed; locating class-level definition source code for the first component definition upon the determination the access to the second component definition is allowed; identifying the first component definition within the source code; determining a language of the first component definition; determining a language of the second component definition; selecting a parser according to the language of the first component definition; parsing the source code to create the first component definition; storing the first component definition in a first registry associated with the first component type and the second component definition in a second registry associated with the second component type, wherein the first registry is selected for storing the first component definition based on a first reference to the first registry in a master registry indicating the first component type and the language of the first component definition, and the second registry is selected for storing the second component definition based on a second reference to the second registry in the master registry indicating the second component type and the language of the second component definition; and transmitting, to the first client device, an intermediate representation of the requested component, the intermediate representation allowing the first client device to create an instance of the requested component. | 1. An apparatus for providing a user interface in an on-demand software service environment, the apparatus comprising: a network interface; and a processor system comprising at least one processor, the processor system configured for: receiving, via the network interface, a component request from a first client device; determining a first component definition corresponding to the component request includes a second component definition, the second component definition being at a lower level of a component definition hierarchy than the first component definition, the first component definition being associated with a first component type, and the second component definition being associated with a second component type, the first component definition and the second component definition being associated with one or more components of a user interface; determining access to the second component definition is allowed; locating class-level definition source code for the first component definition upon the determination the access to the second component definition is allowed; identifying the first component definition within the source code; determining a language of the first component definition; determining a language of the second component definition; selecting a parser according to the language of the first component definition; parsing the source code to create the first component definition; storing the first component definition in a first registry associated with the first component type and the second component definition in a second registry associated with the second component type, wherein the first registry is selected for storing the first component definition based on a first reference to the first registry in a master registry indicating the first component type and the language of the first component definition, and the second registry is selected for storing the second component definition based on a second reference to the second registry in the master registry indicating the second component type and the language of the second component definition; and transmitting, to the first client device, an intermediate representation of the requested component, the intermediate representation allowing the first client device to create an instance of the requested component. 3. The apparatus of claim 1 , wherein the processor system is further configured to determine whether the class-level definition is cached, and wherein the locating process is performed if the processor system determines that the class-level definition is not cached. | 0.523616 |
4. The computer-implemented method of claim 2 , wherein a relationship between the selected replacement object and a second replacement object is different from the relationship between the selected original object and the second original object. | 4. The computer-implemented method of claim 2 , wherein a relationship between the selected replacement object and a second replacement object is different from the relationship between the selected original object and the second original object. 5. The computer-implemented method of claim 4 further comprising replacing, in the item of original content, the relationship between the selected original object and the second original object with the relationship between the selected replacement object and the second replacement object. | 0.861252 |
1. A method, for use with a processor, the method comprising: accessing information for use in determining payload information conveyed in a watermarked image, the accessed information having been produced prior to watermarking an image to produce the watermarked image, said payload information being associated with a watermark included in said watermarked image, said watermarked image and said image being arithmetically encoded by an arithmetic code, said watermark modifying at least one syntax element of said image and having watermarked said image by replacing arithmetically coded bits directly without prior arithmetic decoding and re-encoding of said image, and the accessed information including: location information that identifies a location of a set of pixels in the watermarked image, wherein the set of pixels conveys the payload information in a pixel-domain representation of the set of pixels of the watermarked image, one or more values for a feature in the pixel-domain representation of the set of pixels, wherein the one or more values for the feature indicate whether first payload information or second payload information is conveyed in the pixel-domain representation by the set of pixels, and wherein the one or more values comprise: a first value for the feature in the pixel-domain representation of the set of pixels, wherein the first value for the feature indicates that the first payload information is conveyed in the pixel-domain representation by the set of pixels; and a second value for the feature in the pixel-domain representation of the set of pixels, wherein the second value for the feature indicates that the second payload information is conveyed in the pixel-domain representation by the set of pixels; accessing the watermarked image said watermarked image having a test value for the feature based on said modified at least one syntax element; determining the a-test value for the feature of the set of pixels in the accessed watermarked image; comparing the test value with at least one of the first value and second values for the feature; and determining the payload information based on a result of the comparing of the test value. | 1. A method, for use with a processor, the method comprising: accessing information for use in determining payload information conveyed in a watermarked image, the accessed information having been produced prior to watermarking an image to produce the watermarked image, said payload information being associated with a watermark included in said watermarked image, said watermarked image and said image being arithmetically encoded by an arithmetic code, said watermark modifying at least one syntax element of said image and having watermarked said image by replacing arithmetically coded bits directly without prior arithmetic decoding and re-encoding of said image, and the accessed information including: location information that identifies a location of a set of pixels in the watermarked image, wherein the set of pixels conveys the payload information in a pixel-domain representation of the set of pixels of the watermarked image, one or more values for a feature in the pixel-domain representation of the set of pixels, wherein the one or more values for the feature indicate whether first payload information or second payload information is conveyed in the pixel-domain representation by the set of pixels, and wherein the one or more values comprise: a first value for the feature in the pixel-domain representation of the set of pixels, wherein the first value for the feature indicates that the first payload information is conveyed in the pixel-domain representation by the set of pixels; and a second value for the feature in the pixel-domain representation of the set of pixels, wherein the second value for the feature indicates that the second payload information is conveyed in the pixel-domain representation by the set of pixels; accessing the watermarked image said watermarked image having a test value for the feature based on said modified at least one syntax element; determining the a-test value for the feature of the set of pixels in the accessed watermarked image; comparing the test value with at least one of the first value and second values for the feature; and determining the payload information based on a result of the comparing of the test value. 12. The method of claim 1 further comprising: repeating the operations of accessing information, determining the test value, comparing the test value, and determining the payload information, the repeating being done one or more times for additional locations in the watermarked image. | 0.611497 |
10. An information handling device, comprising: an input component; a processor; a memory device assessable to the processor and storing code executable by the processor to: receive, at an input component, user input comprising one or more words; identify an emotion associated with the one or more words; create an emotion tag including the emotion associated with the one or more words; store the emotion tag in a memory; analyze one or more emotion tags; and modify the user input based on the analyzing, wherein to modify comprises changing a visual rendering of the user input. | 10. An information handling device, comprising: an input component; a processor; a memory device assessable to the processor and storing code executable by the processor to: receive, at an input component, user input comprising one or more words; identify an emotion associated with the one or more words; create an emotion tag including the emotion associated with the one or more words; store the emotion tag in a memory; analyze one or more emotion tags; and modify the user input based on the analyzing, wherein to modify comprises changing a visual rendering of the user input. 12. The information handling device of claim 10 , wherein storing of the emotion tag in a memory occurs locally to the information handling device. | 0.574561 |
9. An online help system, comprising: a memory storing a hierarchy of folders and files, wherein the folders respectively correspond to different topics of information that can be viewed within the help system, and HTML files at the first level of hierarchy within said folders contain metatags associated with data relating to the display of a table of contents for the respective topics to which said folders correspond; means responsive to the selection of a topic of interest for searching the files in the folder corresponding to said topic to identify files of a predetermined type; means for examining the identified files to locate said metatags; means for retrieving a stored HTML template file; means for merging data associated with the metatags into said HTML template file to thereby generate an HTML file containing data associated with the located metatags; and means for displaying a table of contents for the topic of interest in accordance with said generated file. | 9. An online help system, comprising: a memory storing a hierarchy of folders and files, wherein the folders respectively correspond to different topics of information that can be viewed within the help system, and HTML files at the first level of hierarchy within said folders contain metatags associated with data relating to the display of a table of contents for the respective topics to which said folders correspond; means responsive to the selection of a topic of interest for searching the files in the folder corresponding to said topic to identify files of a predetermined type; means for examining the identified files to locate said metatags; means for retrieving a stored HTML template file; means for merging data associated with the metatags into said HTML template file to thereby generate an HTML file containing data associated with the located metatags; and means for displaying a table of contents for the topic of interest in accordance with said generated file. 13. The system of claim 9 , wherein said predetermined type is a text file. | 0.701299 |
1. A method for Cascading Style Sheet (CSS) selector matching, which method comprises: receiving content including markup language text and text which includes at least one CSS selector; parsing the markup language into a Document Object Model (DOM) tree; parsing the text which includes at least one CSS selector into a data structure representing the at least one CSS selector; compiling the data structure into machine code; and executing the machine code to perform the CSS selector matching, wherein the executing of the machine code comprises: for each DOM node from said DOM tree, invoking the machine code for the at least one CSS selector to determine whether each of the at least one CSS selector matches the DOM node, and for each of the at least one CSS selector determined to match the DOM node, apply a corresponding CSS property to the DOM node. | 1. A method for Cascading Style Sheet (CSS) selector matching, which method comprises: receiving content including markup language text and text which includes at least one CSS selector; parsing the markup language into a Document Object Model (DOM) tree; parsing the text which includes at least one CSS selector into a data structure representing the at least one CSS selector; compiling the data structure into machine code; and executing the machine code to perform the CSS selector matching, wherein the executing of the machine code comprises: for each DOM node from said DOM tree, invoking the machine code for the at least one CSS selector to determine whether each of the at least one CSS selector matches the DOM node, and for each of the at least one CSS selector determined to match the DOM node, apply a corresponding CSS property to the DOM node. 2. A method according to claim 1 , wherein the data structure is a byte-code or an Abstract Syntax Tree (AST). | 0.932564 |
21. A system comprising: one or more processors; one or more computer-readable media; and one or more modules maintained on the one or more computer-readable media that, when executed by the one or more processors, cause the one or more processors to perform operations including: accessing training data, the training data comprising one or more features of a first portion of text from within a first body of text, the first portion of text having been selected through a first user interaction received by a first computing device associated with a first user; training a classifier based at least in part on the accessed training data, wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of a second body of text will be annotated by a second user based on the first portion of text having been selected through the first user interaction; identifying a third portion of text and a fourth portion of text from within the second body of text; using the classifier to assign to the third portion of text a first score that indicates a probability that the third portion of text portion will be annotated by future users; using the classifier to assign to the fourth portion of text a second score that indicates a probability that the fourth portion of text portion will be annotated by future users, wherein the first score and the second score are assigned by the classifier based at least in part on the first user interaction; ranking the third portion of text and the fourth portion of text based at least in part on the first score and the second score; and identify the fourth portion of text, the fourth portion of text being identified based at least partly on the ranking. | 21. A system comprising: one or more processors; one or more computer-readable media; and one or more modules maintained on the one or more computer-readable media that, when executed by the one or more processors, cause the one or more processors to perform operations including: accessing training data, the training data comprising one or more features of a first portion of text from within a first body of text, the first portion of text having been selected through a first user interaction received by a first computing device associated with a first user; training a classifier based at least in part on the accessed training data, wherein, once trained, the classifier is configured to assign scores indicating a probability that a corresponding portion of a second body of text will be annotated by a second user based on the first portion of text having been selected through the first user interaction; identifying a third portion of text and a fourth portion of text from within the second body of text; using the classifier to assign to the third portion of text a first score that indicates a probability that the third portion of text portion will be annotated by future users; using the classifier to assign to the fourth portion of text a second score that indicates a probability that the fourth portion of text portion will be annotated by future users, wherein the first score and the second score are assigned by the classifier based at least in part on the first user interaction; ranking the third portion of text and the fourth portion of text based at least in part on the first score and the second score; and identify the fourth portion of text, the fourth portion of text being identified based at least partly on the ranking. 24. The system as recited in claim 21 , wherein the one or more features include at least one of: words used in the first portion of text, and synonyms of the words used in the first portion of text. | 0.659751 |
17. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. | 17. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: capturing an action along with generated dynamic content and associated metadata in response to said presenter performing said action on said screen of said host environment. 18. The system as recited in claim 17 , wherein the program instructions of the computer program further comprise: translating said dynamic content into said preferred native language of said attendee using said associated meta; and relaying said action along with said translated dynamic content to said attendee from said virtual environment. | 0.875309 |
1. A method comprising: receiving a target document containing target graphics data, the target graphics data including at least one of pixel data or vector object data; based on the target graphics data, automatically determining input device actions in a graphics design application as a test case to emulate a user input device creating test graphics data substantially similar to the target graphics data; and determining one or more graphics data attributes of selected graphics data of the target graphics data, wherein determining input device actions includes generating an input device action for selecting an appropriate graphics data attribute through a user interface control of the graphics design application. | 1. A method comprising: receiving a target document containing target graphics data, the target graphics data including at least one of pixel data or vector object data; based on the target graphics data, automatically determining input device actions in a graphics design application as a test case to emulate a user input device creating test graphics data substantially similar to the target graphics data; and determining one or more graphics data attributes of selected graphics data of the target graphics data, wherein determining input device actions includes generating an input device action for selecting an appropriate graphics data attribute through a user interface control of the graphics design application. 7. The method of claim 1 , wherein determining input device actions includes generating input device actions with indirect actions to emulate a real-world user. | 0.751544 |
9. The computer program product of claim 8 , wherein the final result set includes at least one result from the first result set, wherein the greater weight applied to the first result set is further based on a publication source of at least one result in the first result set, wherein the publication source is not a search engine and corresponds to an entity publishing the at least one result, wherein each subquery includes at least one of: (i) at least one generalized term of the set of generalized terms, and (ii) a subset of terms of the at least one term of the query, wherein the plurality of subqueries are generated responsive to user input specifying to generate the subqueries, wherein the operation further comprises: merging the result sets after executing each of the plurality of subqueries. | 9. The computer program product of claim 8 , wherein the final result set includes at least one result from the first result set, wherein the greater weight applied to the first result set is further based on a publication source of at least one result in the first result set, wherein the publication source is not a search engine and corresponds to an entity publishing the at least one result, wherein each subquery includes at least one of: (i) at least one generalized term of the set of generalized terms, and (ii) a subset of terms of the at least one term of the query, wherein the plurality of subqueries are generated responsive to user input specifying to generate the subqueries, wherein the operation further comprises: merging the result sets after executing each of the plurality of subqueries. 10. The computer program product of claim 9 , wherein at least two subqueries of the plurality of subqueries are executed on different search engines, wherein the first subquery and the second subquery, of the plurality of subqueries, are constructed to offset broadness in the first subquery with specificity in the second subquery by: (i) including, in the first subquery, a hypernym corresponding to a third sensitive term of the plurality of sensitive terms, and (ii) including the third sensitive term in the second subquery. | 0.771801 |
1. A method of coding a first signal at a predetermined bit rate, the first signal reflecting speech information and comprising sets of signal segments, each set comprising a plurality of N signal segments, the method comprising the steps of: a. coding the N signal segments of a set with a first speech coder to provide a first coded representation for each of the N signal segments; b. for each of one or more of the N signal segments, forming a second signal reflecting speech information not coded by the first speech coder; and c. responsive to a coding criterion, coding a number, M, of second signals with a second speech coder to provide a second coded representation for each of said M second signals, where 1<M<N-1 and where the number of second signals coded, M, is determined based on the predetermined bit rate; such that, of said N signal segments, a number, P, of said signal segments are coded with use of the first speech coder, said M signal segments are coded with use of both the first and second speech coders, and wherein N=P+M. | 1. A method of coding a first signal at a predetermined bit rate, the first signal reflecting speech information and comprising sets of signal segments, each set comprising a plurality of N signal segments, the method comprising the steps of: a. coding the N signal segments of a set with a first speech coder to provide a first coded representation for each of the N signal segments; b. for each of one or more of the N signal segments, forming a second signal reflecting speech information not coded by the first speech coder; and c. responsive to a coding criterion, coding a number, M, of second signals with a second speech coder to provide a second coded representation for each of said M second signals, where 1<M<N-1 and where the number of second signals coded, M, is determined based on the predetermined bit rate; such that, of said N signal segments, a number, P, of said signal segments are coded with use of the first speech coder, said M signal segments are coded with use of both the first and second speech coders, and wherein N=P+M. 8. The method of claim 1 wherein the step of coding N signal segments with a first speech coder comprises: a. generating a plurality of modified signal segments based on a signal segment to be coded; b. coding a modified signal segment to produce a modified signal segment coded representation; c. synthesizing an estimate of the modified signal segment based on the modified signal segment coded representation; d. determining an error between the signal segment to be coded and the synthesized estimate of the modified signal segment; and e. selecting as the first coded representation of the signal segment to be coded a particular modified signal segment coded representation based on an error evaluation process. | 0.5 |
1. A method comprising: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions; generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions; wherein the method is performed by one or more computers. | 1. A method comprising: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions; generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions; wherein the method is performed by one or more computers. 3. The method of claim 1 , wherein the query conforms to the SQL/XML query language. | 0.716622 |
1. A computer-implemented method, comprising: receiving, at a data processing apparatus, a first image search query and first image search results that are responsive to the first image search query, the first image search query being one or more terms in a first language; obtaining, by the data processing apparatus, translations of the first image search query, wherein each translation is a translation of the first image search query into a respective second language different from the first language, and wherein obtaining the translations of the first image search query comprises: recieving a plurality of candidate translations of the first image search query, determining a score for each candidate translation, and selecting the translations form the candidate translations according to the scores; receiving, at the data processing apparatus, for each translation of the first image search query, respective image search results that are determined to be responsive to the translation of the first image search query when the translation is used as an image search query; providing first instructions to a client device that, when executed by the client device, cause the client device to present a user interface including: one or more of the first image search results responsive to the first image search query; and a respective cross-language search option for each of the translations of the first image search query, the respective cross-language search option for each translation including the translation and a preview of the respective image search results responsive to the translation, wherein each cross-language search result is selectable in the user interface. | 1. A computer-implemented method, comprising: receiving, at a data processing apparatus, a first image search query and first image search results that are responsive to the first image search query, the first image search query being one or more terms in a first language; obtaining, by the data processing apparatus, translations of the first image search query, wherein each translation is a translation of the first image search query into a respective second language different from the first language, and wherein obtaining the translations of the first image search query comprises: recieving a plurality of candidate translations of the first image search query, determining a score for each candidate translation, and selecting the translations form the candidate translations according to the scores; receiving, at the data processing apparatus, for each translation of the first image search query, respective image search results that are determined to be responsive to the translation of the first image search query when the translation is used as an image search query; providing first instructions to a client device that, when executed by the client device, cause the client device to present a user interface including: one or more of the first image search results responsive to the first image search query; and a respective cross-language search option for each of the translations of the first image search query, the respective cross-language search option for each translation including the translation and a preview of the respective image search results responsive to the translation, wherein each cross-language search result is selectable in the user interface. 3. The method of claim 1 , further comprising, in response to a selection of a first cross-language search result, providing second instructions to the client device that, when executed by the client device, cause the client device to present a user interface including a first translation corresponding to first the cross-language search result and the respective image search results that are responsive to the first translation. | 0.528197 |
1. A computer-readable medium having computer-executable instructions that when executed by a processor perform compiling a source program written in a native programming language, the source program having a plurality of internal semantic objects written in the native programming language, according to acts comprising: determining, based on an implicit type conversion, whether an internal semantic object of the plurality of internal semantic objects within the source program written in the native programming language is used in a way signifying that an external semantic data object is to be created to represent the internal semantic object; and selectively processing the internal semantic object based on the implicit type conversion, by: when the implicit type conversion indicates that the internal semantic object is used in a way signifying that the external semantic data object is to be created, processing, according to a syntax of the native programming language, the internal semantic object of the plurality of internal semantic objects and creating the external semantic data object representing the instructions included in the internal semantic object; and when the implicit type conversion does not indicate that the internal semantic object is used in a way signifying that the external semantic data object is to be created, converting the internal semantic object into object code. | 1. A computer-readable medium having computer-executable instructions that when executed by a processor perform compiling a source program written in a native programming language, the source program having a plurality of internal semantic objects written in the native programming language, according to acts comprising: determining, based on an implicit type conversion, whether an internal semantic object of the plurality of internal semantic objects within the source program written in the native programming language is used in a way signifying that an external semantic data object is to be created to represent the internal semantic object; and selectively processing the internal semantic object based on the implicit type conversion, by: when the implicit type conversion indicates that the internal semantic object is used in a way signifying that the external semantic data object is to be created, processing, according to a syntax of the native programming language, the internal semantic object of the plurality of internal semantic objects and creating the external semantic data object representing the instructions included in the internal semantic object; and when the implicit type conversion does not indicate that the internal semantic object is used in a way signifying that the external semantic data object is to be created, converting the internal semantic object into object code. 6. The computer-readable medium of claim 1 , wherein the external semantic data object contains a reference to a second external semantic data object. | 0.662234 |
17. A non-transitory 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 for rendering arranged content search results: causing, at least in part, a rendering of a plurality of result objects in a single view in a user interface of the user device, the rendering of the plurality of result objects comprising: causing, at least in part, tracking of access events associated with a plurality of the result objects, wherein the plurality of the result objects are from a plurality of search domains, wherein the tracking of access events comprises tracking a number of times that one or more of the plurality of result objects has been accessed to develop a tracking history for the one or more of the plurality of result objects, wherein the tracking of access events further comprises tracking a number of times that the one or more of the plurality of result objects has been accessed from a first domain of local content stored on the user device and/or from a second domain of remote content accessible via a network; causing, at least in part, determining a context of the user device during the tracking of the access events; causing, at least in part, mapping of the determined context of the user device associated with the tracked access events; causing, at least in part, determining a rank value for the respective result objects based, at least in part, on the mapping and the tracking history of the respective result objects; causing, at least in part, a sorting of the ranked result objects according to the determined rank value; and rendering, at least in part, the sorted ranked result objects in the single view in the user interface of the user device. | 17. A non-transitory 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 for rendering arranged content search results: causing, at least in part, a rendering of a plurality of result objects in a single view in a user interface of the user device, the rendering of the plurality of result objects comprising: causing, at least in part, tracking of access events associated with a plurality of the result objects, wherein the plurality of the result objects are from a plurality of search domains, wherein the tracking of access events comprises tracking a number of times that one or more of the plurality of result objects has been accessed to develop a tracking history for the one or more of the plurality of result objects, wherein the tracking of access events further comprises tracking a number of times that the one or more of the plurality of result objects has been accessed from a first domain of local content stored on the user device and/or from a second domain of remote content accessible via a network; causing, at least in part, determining a context of the user device during the tracking of the access events; causing, at least in part, mapping of the determined context of the user device associated with the tracked access events; causing, at least in part, determining a rank value for the respective result objects based, at least in part, on the mapping and the tracking history of the respective result objects; causing, at least in part, a sorting of the ranked result objects according to the determined rank value; and rendering, at least in part, the sorted ranked result objects in the single view in the user interface of the user device. 19. The non-transitory computer-readable storage medium of claim 17 , wherein a contextual engine maps the context of the user device to the tracked access events. | 0.55215 |
5. The method of claim 1 , further comprising: obtaining text associated with an image; determining that an image classification model is trained for an n-gram matching the text; obtaining a feature vector for the image; and classifying the image based on the feature vector and the image classification model. | 5. The method of claim 1 , further comprising: obtaining text associated with an image; determining that an image classification model is trained for an n-gram matching the text; obtaining a feature vector for the image; and classifying the image based on the feature vector and the image classification model. 10. The method of claim 5 , wherein obtaining text associated with the image comprises obtaining text that does not appear on a Web page with the image. | 0.908447 |
1. A computer implemented method, comprising: receiving a search query for a programming code search engine; searching a programming code database with the search query in a form of a search criterion that conforms to an underlying storage of textual keywords and metadata, the programming code database being populated with programming code from one or more repositories of programming code, the programming code in the programming code database being indexed by use of a full-text analysis of the programming code, the full-text analysis including: a plain-text analysis that evaluates the programming code as plain text to extract a set of plain text keywords found in the programming code; and a plain text-based statistical analysis that derives statistical metadata from the set of plain text keywords; scoring results of the searching according to a scoring criterion, the scoring criterion including a reuse score that tracks a copying for reuse of lines of programming instructions in the programming code database; and presenting the results of the searching in a ranked order according to the scoring, the results being a subset of the programming code corresponding to the search query. | 1. A computer implemented method, comprising: receiving a search query for a programming code search engine; searching a programming code database with the search query in a form of a search criterion that conforms to an underlying storage of textual keywords and metadata, the programming code database being populated with programming code from one or more repositories of programming code, the programming code in the programming code database being indexed by use of a full-text analysis of the programming code, the full-text analysis including: a plain-text analysis that evaluates the programming code as plain text to extract a set of plain text keywords found in the programming code; and a plain text-based statistical analysis that derives statistical metadata from the set of plain text keywords; scoring results of the searching according to a scoring criterion, the scoring criterion including a reuse score that tracks a copying for reuse of lines of programming instructions in the programming code database; and presenting the results of the searching in a ranked order according to the scoring, the results being a subset of the programming code corresponding to the search query. 46. The method of claim 1 , wherein the method further comprises: indexing the programming code to generate an index; the index including keywords found based on the text in the programming code with a corresponding count of the frequency of each keyword in the programming code, and the indexing generated by parsing the programming code using a regular expression process including a pattern matching expression process that is specific to the syntax of the particular programming language used in the programming code; and the searching including comparing the search query with the generated index to produce the syntax aware textual search result. | 0.582221 |
2. The method of claim 1 , wherein the peer manager is configured to maintain a plurality of communications channels via a corresponding one of local MDS peer instances for exchanging metadata with a plurality of remote peers, respectively. | 2. The method of claim 1 , wherein the peer manager is configured to maintain a plurality of communications channels via a corresponding one of local MDS peer instances for exchanging metadata with a plurality of remote peers, respectively. 3. The method of claim 2 , further comprising: receiving a first signal from the first remote peer indicating that the first communications channel is no longer needed; and in response to the first signal, destroying by the peer manager the first local MDS peer instance to shut down the first communications channel. | 0.903977 |
1. A computer-implemented method for multicultural electronic communication management, the method comprising: initiating, by a user, an electronic communication configured to be transmitted to both a first intended recipient and a second intended recipient; identifying, based on a set of profile data, a first cultural indicator for the first intended recipient; identifying, based on the set of profile data, a second cultural indicator for the second intended recipient; detecting, using a natural language processing technique, a cultural element of the electronic communication; determining, based on both the first cultural indicator and the cultural element, a first cultural-version of the cultural element for the first intended recipient; determining, based on both the second cultural indicator and the cultural element, a second cultural-version of the cultural element for the second intended recipient; establishing, using both the first cultural-version and the second cultural-version, a cultural translation object in the electronic communication; and transmitting, in response to establishing the cultural translation object in the electronic communication, the electronic communication to both the first intended recipient and the second intended recipient. | 1. A computer-implemented method for multicultural electronic communication management, the method comprising: initiating, by a user, an electronic communication configured to be transmitted to both a first intended recipient and a second intended recipient; identifying, based on a set of profile data, a first cultural indicator for the first intended recipient; identifying, based on the set of profile data, a second cultural indicator for the second intended recipient; detecting, using a natural language processing technique, a cultural element of the electronic communication; determining, based on both the first cultural indicator and the cultural element, a first cultural-version of the cultural element for the first intended recipient; determining, based on both the second cultural indicator and the cultural element, a second cultural-version of the cultural element for the second intended recipient; establishing, using both the first cultural-version and the second cultural-version, a cultural translation object in the electronic communication; and transmitting, in response to establishing the cultural translation object in the electronic communication, the electronic communication to both the first intended recipient and the second intended recipient. 11. The method of claim 1 , wherein the cultural element includes a lack of a greeting, the first cultural-version includes a first greeting, and the second cultural-version includes a second greeting. | 0.605522 |
18. A method for controlling a speech recognition function for a data processing system, the data processing system having a display, a speech recognition input device, and a cursor control device, the cursor control device having a selector, the method comprising the steps of: (a) displaying at least one object and a moveable cursor on the display; (b) controlling the moveable cursor on the display in x and y directions simultaneously in response to user-manipulation of the cursor control device; (c) selecting one of the at least one object displayed on the display; (d) activating the speech recognition function in response to engagement of the selector of the cursor control device; (e) inputting a spoken command for the data processing system by the speech recognition input device; (f) displaying on the display the spoken command inputted for the data processing system; (g) displaying on the display a list of alternative commands for the spoken command; (h) selecting either the spoken command or one of the commands in the list of alternative commands in response to user-manipulation of the cursor control device; and (i) deactivating the speech recognition function in response to disengagement of the selector of the cursor control device. | 18. A method for controlling a speech recognition function for a data processing system, the data processing system having a display, a speech recognition input device, and a cursor control device, the cursor control device having a selector, the method comprising the steps of: (a) displaying at least one object and a moveable cursor on the display; (b) controlling the moveable cursor on the display in x and y directions simultaneously in response to user-manipulation of the cursor control device; (c) selecting one of the at least one object displayed on the display; (d) activating the speech recognition function in response to engagement of the selector of the cursor control device; (e) inputting a spoken command for the data processing system by the speech recognition input device; (f) displaying on the display the spoken command inputted for the data processing system; (g) displaying on the display a list of alternative commands for the spoken command; (h) selecting either the spoken command or one of the commands in the list of alternative commands in response to user-manipulation of the cursor control device; and (i) deactivating the speech recognition function in response to disengagement of the selector of the cursor control device. 19. The method of claim 18, wherein the controlling step (b) includes the step of controlling the moveable cursor on the display in response to user-manipulation of the cursor control device that comprises one of a mouse, a joystick, a track-ball, or a touch tablet. | 0.5 |
5. Device for the blind equalisation of the effects of a transmission channel on a digital speech signal ({s.sub.n (t)}) passing through said transmission channel, comprising at least: means for transforming said digital speech signal into a set of cepstral vectors, said set of cepstral vectors being representative of said digital speech signal over a given horizon; means for generating a reference cepstrum that is representative, for each of the cepstral vectors of said set of cepstral vectors, of the long-term cepstrum of this speech signal; means for adaptive filtering, on the basis of said reference cepstrum, of each of the cepstral vectors enabling generation of a set of equalised cepstral vectors in which the effect of said transmission channel are substantially suppressed, said set of equalised cepstral vectors being representative of an equalised digital speech signal, said means for adaptive filtering comprising at least for each cepstral vector ({C.sub.n (i)}), i.epsilon. and for a reference cepstrum ({R.sub.n (i)}) representative, for each of the cepstral vectors, of the long-term cepstrum of this speech signal, means for calculating an error signal (E(i)) between each component of rank i (C.sub.n (i)) of each equalised cepstral vector ({C.sub.n (i)}) and the corresponding component of identical rank (R.sub.n (i)) of the reference cepstrum ({R.sub.n (i)}), E(i)=R .sub.n (i)-C.sub.n (i)); and means for equalisation of said cepstral vector ({C.sub.n (i)}) transmitting a component (C.sub.n (i)) of the equalised cepstral vector ({C.sub.n (i)}) on the basis of each component (C.sub.n (i)) of each cepstral vector ({C.sub.n (i)}) and said error signal (E(i)). | 5. Device for the blind equalisation of the effects of a transmission channel on a digital speech signal ({s.sub.n (t)}) passing through said transmission channel, comprising at least: means for transforming said digital speech signal into a set of cepstral vectors, said set of cepstral vectors being representative of said digital speech signal over a given horizon; means for generating a reference cepstrum that is representative, for each of the cepstral vectors of said set of cepstral vectors, of the long-term cepstrum of this speech signal; means for adaptive filtering, on the basis of said reference cepstrum, of each of the cepstral vectors enabling generation of a set of equalised cepstral vectors in which the effect of said transmission channel are substantially suppressed, said set of equalised cepstral vectors being representative of an equalised digital speech signal, said means for adaptive filtering comprising at least for each cepstral vector ({C.sub.n (i)}), i.epsilon. and for a reference cepstrum ({R.sub.n (i)}) representative, for each of the cepstral vectors, of the long-term cepstrum of this speech signal, means for calculating an error signal (E(i)) between each component of rank i (C.sub.n (i)) of each equalised cepstral vector ({C.sub.n (i)}) and the corresponding component of identical rank (R.sub.n (i)) of the reference cepstrum ({R.sub.n (i)}), E(i)=R .sub.n (i)-C.sub.n (i)); and means for equalisation of said cepstral vector ({C.sub.n (i)}) transmitting a component (C.sub.n (i)) of the equalised cepstral vector ({C.sub.n (i)}) on the basis of each component (C.sub.n (i)) of each cepstral vector ({C.sub.n (i)}) and said error signal (E(i)). 7. Device according to claim 5, wherein said means for calculating the error signal (E(i)) and said means for equalisation of said cepstral vector ({C.sub.n (i)}) comprise, for each component (C.sub.n (i)) of said cepstral vector, a subtractor circuit receiving said component (R.sub.n (i)) of the reference cepstrum ({R.sub.n (i)}) and said component (C.sub.n (i)) of said equalised cepstral vector ({C.sub.n (i)}) and transmitting said error signal (E(i)); means for adaptation of this error signal (E(i)) comprising: a circuit which multiplies by a multiplying coefficient .mu. transmitting a weighted error signal (E*(i)); an adder circuit with two inputs and one output, a first input receiving said weighted error signal (E*(i)) and a second input receiving the signal transmitted by said first adder circuit via a slow-rise circuit that delays by a predetermined duration, the output of said slow-rise circuit transmitting an adaptation signal (H.sub.n (i)); and an equalising adder circuit receiving said cepstral coefficient (C.sub.n (i)) and said adaptation signal (H.sub.n (i)) and transmitting said equalised cepstral coefficient (C.sub.n (i)). | 0.5 |
1. A method comprising: periodically sampling a user environment via a set of environmental sensors integrated into a communication device; deriving a set of environmental circumstances based at least partially on an output of the set of environmental sensors by an analysis module in communication with the set of environmental sensors; and comparing, by the analysis module, the derived set of environmental circumstances to a set of templates to determine whether there is a matching template, wherein if more than one of the templates matches the derived set of environmental circumstances, a best-match template is determined, and wherein if there is a matching template, an action script is executed. | 1. A method comprising: periodically sampling a user environment via a set of environmental sensors integrated into a communication device; deriving a set of environmental circumstances based at least partially on an output of the set of environmental sensors by an analysis module in communication with the set of environmental sensors; and comparing, by the analysis module, the derived set of environmental circumstances to a set of templates to determine whether there is a matching template, wherein if more than one of the templates matches the derived set of environmental circumstances, a best-match template is determined, and wherein if there is a matching template, an action script is executed. 3. The method of claim 1 , wherein the best-match template is determined by applying a set of logic rules to the set of templates. | 0.618048 |
11. A computer program product comprising a computer-readable memory having computer program logic recorded thereon, which, when executed by a processing unit, performs operations to execute an application, the operations comprising: obtaining an application definition file that includes an application definition; parsing the application definition to identify components and parameters associated with the components, each component comprising a distinct unit of execution within the application and is being in a non-executable form, and the application definition including one or more first values to be input to at least one of the components identified, one or more properties relating to how output is to be presented from the at least one of the components identified, and information indicating whether one or more second values output from a first one of the identified components is to be used as an input to a second one of the identified components; obtaining one or more component code files that include programming logic associated with each type of component identified in the application definition, the programming logic being configured to execute each type of component identified in the application definition; obtaining one or more component description files that include metadata associated with each type of component identified in the application definition; for each component type identified: creating a factory; and using the factory to generate a plurality of executable versions of the identified components for the component type using at least the programming logic and the metadata obtained for the component type, each of the plurality of executable versions being generated by modifying the programming logic for the component type based on a respective one or more parameters of the identified parameters that are associated with a respective identified component of the identified components; and managing execution of each of the executable components, the application being created by selectively combining graphical representations of the identified components by a user via a graphical user interface, the application definition file and the one or more component description files being created in response to the user saving the created application via the graphical user interface. | 11. A computer program product comprising a computer-readable memory having computer program logic recorded thereon, which, when executed by a processing unit, performs operations to execute an application, the operations comprising: obtaining an application definition file that includes an application definition; parsing the application definition to identify components and parameters associated with the components, each component comprising a distinct unit of execution within the application and is being in a non-executable form, and the application definition including one or more first values to be input to at least one of the components identified, one or more properties relating to how output is to be presented from the at least one of the components identified, and information indicating whether one or more second values output from a first one of the identified components is to be used as an input to a second one of the identified components; obtaining one or more component code files that include programming logic associated with each type of component identified in the application definition, the programming logic being configured to execute each type of component identified in the application definition; obtaining one or more component description files that include metadata associated with each type of component identified in the application definition; for each component type identified: creating a factory; and using the factory to generate a plurality of executable versions of the identified components for the component type using at least the programming logic and the metadata obtained for the component type, each of the plurality of executable versions being generated by modifying the programming logic for the component type based on a respective one or more parameters of the identified parameters that are associated with a respective identified component of the identified components; and managing execution of each of the executable components, the application being created by selectively combining graphical representations of the identified components by a user via a graphical user interface, the application definition file and the one or more component description files being created in response to the user saving the created application via the graphical user interface. 12. The computer program product of claim 11 , wherein the application definition is formatted in accordance with a markup language. | 0.574468 |
7. A method, comprising: accepting, using a computer, interaction from a first user to access a website and to interact with at least a first character on said website; subsequent to said accepting interaction from the first user, registering, using the computer, a second character by said first user on said website by receiving entry of a unique code that is associated with the second character and is entered into the computer, where the unique code as entered is uniquely identified with the second character, and wherein the unique code when entered causes information indicative of the second character to be obtained from a database of characteristics and associated with the second character during registration, and grants the first user access to a portion of the website for interacting with said second character, wherein said interacting customizes said second character; and subsequent to said grant of access to the portion of the website for interacting with the second character, transferring the second character from the first user to a second user, where said transfer comprises deactivating the unique code to prevent using the unique code to access the second character by entering the unique code, creating and providing a new unique code to the second user, wherein the new unique code is subsequently received from the second user and used to register and associate the character as customized by the first user with the second user, and granting the first user continued access to said first character on said website. | 7. A method, comprising: accepting, using a computer, interaction from a first user to access a website and to interact with at least a first character on said website; subsequent to said accepting interaction from the first user, registering, using the computer, a second character by said first user on said website by receiving entry of a unique code that is associated with the second character and is entered into the computer, where the unique code as entered is uniquely identified with the second character, and wherein the unique code when entered causes information indicative of the second character to be obtained from a database of characteristics and associated with the second character during registration, and grants the first user access to a portion of the website for interacting with said second character, wherein said interacting customizes said second character; and subsequent to said grant of access to the portion of the website for interacting with the second character, transferring the second character from the first user to a second user, where said transfer comprises deactivating the unique code to prevent using the unique code to access the second character by entering the unique code, creating and providing a new unique code to the second user, wherein the new unique code is subsequently received from the second user and used to register and associate the character as customized by the first user with the second user, and granting the first user continued access to said first character on said website. 11. A method as in claim 7 , wherein said interacting comprises training the character to increase values associated with said second character, said values each associated with an attribute of said second character. | 0.54548 |
16. The digital computer system of claims 8 or 9, wherein said second certain of said operands are floating point numeric operands, and said hexidecimal ALU means further comprises: first hexidecimal arithmetic ALU means connected for performing said operations on mantissa fields of said at least floating point operands, second hexidecimal arithmetic ALU means for performing said operation on exponent fields of said at least floating point operands, and control means connected from said first arithmetic ALU means and from said second arithmetic ALU means for providing control signals for coordinating said operations performed by said first arithmetic ALU means and said second arithmetic ALU means so that said operations performed on said mantissa fields and said exponent fields of said at least floating point operands are performed concurrently. | 16. The digital computer system of claims 8 or 9, wherein said second certain of said operands are floating point numeric operands, and said hexidecimal ALU means further comprises: first hexidecimal arithmetic ALU means connected for performing said operations on mantissa fields of said at least floating point operands, second hexidecimal arithmetic ALU means for performing said operation on exponent fields of said at least floating point operands, and control means connected from said first arithmetic ALU means and from said second arithmetic ALU means for providing control signals for coordinating said operations performed by said first arithmetic ALU means and said second arithmetic ALU means so that said operations performed on said mantissa fields and said exponent fields of said at least floating point operands are performed concurrently. 17. The digital computer system of claim 16, wherein said hexidecimal ALU means further comprises: first register file means connected from outputs and to inputs of said first hexidecimal arithmetic means for storing at least said mantissa fields and said results of said operations on said mantissa fields, and second register file means connected from outputs of and to inputs of said second hexidecimal arithmetic means for storing at least said exponent fields and said results of said operations on said exponent fields, said first and second register file means having control inputs connected in parallel from said control means to operate in parallel. | 0.816304 |
1. A method comprising: receiving a source text in a first language; generating, via a processor, a machine translation of the source text, wherein the machine translation is in a second language distinct from the first language; generating a first list of alternative translation possibilities in the second language corresponding to a first portion of the source text; generating a second list of alternative translation possibilities in the second language corresponding to a second portion of the source text, wherein the first portion of the source text is distinct from the second portion of the source text; ranking the first list of alternative translation possibilities, to yield a ranked first list of translation alternatives in a first order; presenting, to a first user, the machine translation, the ranked first list of translation alternatives in the first order, and the second list of alternative translation possibilities, wherein the user is participating in a collaborative translation of the source text from the first language to the second language with a second user, the collaborative translation allowing the machine translation, the ranked list, and the second list of alternative translation possibilities to simultaneously be presented to both the first user and the second user; receiving an input from the first user, the input identifying a translation possibility from the second list of alternative translation possibilities; re-ranking the ranked first list of alternative translation possibilities in the first order based on the input, to yield a re-ranked first list of translation alternatives in a second order; presenting the re-ranked first list of translation alternatives to the first user; and transmitting the re-ranked first list of translation alternatives to a device associated with the second user for display to the second user, such that the re-ranked first list of translation alternatives is simultaneously presented to both the first user and the second user. | 1. A method comprising: receiving a source text in a first language; generating, via a processor, a machine translation of the source text, wherein the machine translation is in a second language distinct from the first language; generating a first list of alternative translation possibilities in the second language corresponding to a first portion of the source text; generating a second list of alternative translation possibilities in the second language corresponding to a second portion of the source text, wherein the first portion of the source text is distinct from the second portion of the source text; ranking the first list of alternative translation possibilities, to yield a ranked first list of translation alternatives in a first order; presenting, to a first user, the machine translation, the ranked first list of translation alternatives in the first order, and the second list of alternative translation possibilities, wherein the user is participating in a collaborative translation of the source text from the first language to the second language with a second user, the collaborative translation allowing the machine translation, the ranked list, and the second list of alternative translation possibilities to simultaneously be presented to both the first user and the second user; receiving an input from the first user, the input identifying a translation possibility from the second list of alternative translation possibilities; re-ranking the ranked first list of alternative translation possibilities in the first order based on the input, to yield a re-ranked first list of translation alternatives in a second order; presenting the re-ranked first list of translation alternatives to the first user; and transmitting the re-ranked first list of translation alternatives to a device associated with the second user for display to the second user, such that the re-ranked first list of translation alternatives is simultaneously presented to both the first user and the second user. 2. The method of claim 1 , further comprising presenting to the first user the machine translation, the input, and the re-ranked list of translation alternatives in the second order. | 0.560802 |
1. A teaching system for testing and improving behavioral conduct of human subjects who are developmentally disadvantaged, comprising: a plurality of palm-sized, data logging devices, each of said data logging devices being configured to be carried by a respective professional trained to test and teach the human subject and being structured for guiding the professional through a protocol of testing and behavior improving steps and for logging responses emitted from the human subjects, in response to various triggers and stimuli; a computer system operatively coupled with said plurality of palm-sized data logging devices to receive and provide information from and to said plurality of data logging devices, wherein: (a) each of said data logging devices comprise a built-in facility that enables said data logging device to log results related to one or more of an activity, skill, social event, appropriate behavior, or inappropriate behavior of the human subject being tested and treated; (b) each of said data logging devices comprise a facility which enables uploading and/or downloading of data to a central data and control repository of said computer system, which categorizes and maintains results in accordance with various criteria; (c) a processor associated with the computer system which is structured to analyze the data and to develop standardized responses to said results, and to update said standardized responses based on progressive downloading of said data to said central data and control repository; and (d) wherein the logging devices comprise a facility that enables time stamping events within a behavioral stream and recording the number of correct or incorrect behavioral responses and recording response times or reaction times. | 1. A teaching system for testing and improving behavioral conduct of human subjects who are developmentally disadvantaged, comprising: a plurality of palm-sized, data logging devices, each of said data logging devices being configured to be carried by a respective professional trained to test and teach the human subject and being structured for guiding the professional through a protocol of testing and behavior improving steps and for logging responses emitted from the human subjects, in response to various triggers and stimuli; a computer system operatively coupled with said plurality of palm-sized data logging devices to receive and provide information from and to said plurality of data logging devices, wherein: (a) each of said data logging devices comprise a built-in facility that enables said data logging device to log results related to one or more of an activity, skill, social event, appropriate behavior, or inappropriate behavior of the human subject being tested and treated; (b) each of said data logging devices comprise a facility which enables uploading and/or downloading of data to a central data and control repository of said computer system, which categorizes and maintains results in accordance with various criteria; (c) a processor associated with the computer system which is structured to analyze the data and to develop standardized responses to said results, and to update said standardized responses based on progressive downloading of said data to said central data and control repository; and (d) wherein the logging devices comprise a facility that enables time stamping events within a behavioral stream and recording the number of correct or incorrect behavioral responses and recording response times or reaction times. 22. The system of claim 1 , wherein said plurality of palm-sized data logging devices include master devices and standard user devices. | 0.57423 |
39. A tangible computer-readable medium comprising computer-executable instructions that when executed on a processor performs the following steps: managing electronic advertisement service orders selected from a menu providing a plurality of advertisement services, each of said advertisement services including: an advertisement format specific to the advertisement service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, and an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; providing secure access to advertisements and business information; providing automated payment transactions generated in accordance with a predetermined advertisement payment schedule; managing advertising services presented to an advertiser in accordance with a particular business listing; managing advertisement content and business listing selection activity associated with a particular advertiser; posting and verifying charges electronically; and publishing the advertisement in said display area associated with said selected advertising service, said advertisement presented in a particular order relative to other advertisements based on said advertiser priority associated with said selected advertising service. | 39. A tangible computer-readable medium comprising computer-executable instructions that when executed on a processor performs the following steps: managing electronic advertisement service orders selected from a menu providing a plurality of advertisement services, each of said advertisement services including: an advertisement format specific to the advertisement service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, and an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; providing secure access to advertisements and business information; providing automated payment transactions generated in accordance with a predetermined advertisement payment schedule; managing advertising services presented to an advertiser in accordance with a particular business listing; managing advertisement content and business listing selection activity associated with a particular advertiser; posting and verifying charges electronically; and publishing the advertisement in said display area associated with said selected advertising service, said advertisement presented in a particular order relative to other advertisements based on said advertiser priority associated with said selected advertising service. 40. The system of claim 39 , the instructions further including instructions for: providing a database including business information, advertisement information, and transaction information; and performing queries of the database. | 0.630461 |
8. An apparatus comprising at least a processor and a memory, wherein the processor and/or memory are configured to perform the following operations: obtaining a plurality of models for classifying a plurality of messages based on a plurality of message features for each message, each message sent via a computer network between a selected one of the promoting entity accounts and one or more subscribing users that subscribe to receive messages from such selected promoting entity account, wherein each model is trained to identify whether a message belongs to a particular class based on a lexicon that was generated for such particular class and a training set of messages that belong to the particular class and messages that do not belong to the particular class; and classifying a new message based on the models and retaining classification information regarding the new message in a database that is accessible by a user so as to review the classification information on a computer display. | 8. An apparatus comprising at least a processor and a memory, wherein the processor and/or memory are configured to perform the following operations: obtaining a plurality of models for classifying a plurality of messages based on a plurality of message features for each message, each message sent via a computer network between a selected one of the promoting entity accounts and one or more subscribing users that subscribe to receive messages from such selected promoting entity account, wherein each model is trained to identify whether a message belongs to a particular class based on a lexicon that was generated for such particular class and a training set of messages that belong to the particular class and messages that do not belong to the particular class; and classifying a new message based on the models and retaining classification information regarding the new message in a database that is accessible by a user so as to review the classification information on a computer display. 9. The apparatus of claim 8 , wherein the processor and/or memory are further configured to provide content from the new message to other users who are not subscribers to the new message's corresponding promoting entity account based on the classification of such new message. | 0.654939 |
11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value. | 11. A system, comprising: at least one processor; and a memory storing executable instructions that, when executed by the at least one processor, causes the at least one processor to perform the following operations: extracting an audio track from an electronic media content; detecting, based on a speech model, a speaker segment within the extracted audio track; determining, by the processor, a first probability of the detected speaker segment being associated with an individual speaker by using both a speaker speech model and a non-speaker speech model, wherein the speaker speech model represents an individual speaker and the non-speaker speech model represents common characteristics from one or more speakers; determining a first ranking value of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment and probabilities for detected speaker segments within the other electronic media content; receiving a search query from a user; determining a second ranking value of the electronic media content based on relevancy between the query and the individual speaker; and determining a final ranking value of the electronic media content based on the first ranking value and the second ranking value. 14. The system of claim 11 , further comprising: presenting the electronic media content to the user based on the final ranking. | 0.742489 |
1. A method of coupling human neural response with computer pattern analysis for enhanced single-event detection of significant non-stationary brain responses triggered upon occurrence of a task-relevant stimulus, comprising: measuring EEG signals associated with a person's brain activity from a plurality of electrodes placed on the person's scalp; subdividing the EEG signals into a plurality of different time windows; extracting features from the EEG signals for each said different time window; presenting the extracted features to a respective plurality of computer-implemented spatial classifiers trained to detect spatial patterns of said extracted features during different time windows from the occurrence of the task-relevant stimulus and to generate first level outputs indicative of the occurrence or absence of a significant brain response; and presenting the spatial classifiers' first level outputs to a temporal classifier, said temporal classifier configured to implement feature-level fusion or decision-level fusion to detect temporal patterns across the different time windows relating to the evolution of the non-stationary brain response to task-relevant stimulus and to generate a second level output indicative of the occurrence or absence of the significant non-stationary brain response. | 1. A method of coupling human neural response with computer pattern analysis for enhanced single-event detection of significant non-stationary brain responses triggered upon occurrence of a task-relevant stimulus, comprising: measuring EEG signals associated with a person's brain activity from a plurality of electrodes placed on the person's scalp; subdividing the EEG signals into a plurality of different time windows; extracting features from the EEG signals for each said different time window; presenting the extracted features to a respective plurality of computer-implemented spatial classifiers trained to detect spatial patterns of said extracted features during different time windows from the occurrence of the task-relevant stimulus and to generate first level outputs indicative of the occurrence or absence of a significant brain response; and presenting the spatial classifiers' first level outputs to a temporal classifier, said temporal classifier configured to implement feature-level fusion or decision-level fusion to detect temporal patterns across the different time windows relating to the evolution of the non-stationary brain response to task-relevant stimulus and to generate a second level output indicative of the occurrence or absence of the significant non-stationary brain response. 7. The method of claim 1 , wherein the temporal classifier comprises a feature-level fuser implemented using a probabilistic or recurrent learning method. | 0.75478 |
4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. 5. The computing system of claim 4 wherein the relevancy generator is configured to use the arguments and current context to disambiguate otherwise ambiguous search results to obtain the given search result, based on the current context and the arguments. | 0.885952 |
7. An information processing method for use in an electronic apparatus, the method comprising: detecting a voice information; obtaining a first content information and a first voiceprint information from the voice information; controlling the electronic apparatus to run a first application corresponding to the first content information; and controlling the electronic apparatus to run a second application other than the first application if the first voiceprint information is a preset voiceprint information, wherein the obtaining the first content information and the first voiceprint information from the voice information comprises: obtaining a first reliability degree of the first content information and a second reliability degree of the first voiceprint information, wherein the first reliability degree corresponds to reliability of the first content information and the second reliability degree corresponds to reliability of the first voiceprint information; selecting a first reliability degree threshold from at least two preset reliability degree thresholds; determining whether the first reliability degree is larger than the first reliability degree threshold to obtain a first determination result and/or determining whether the second reliability degree is larger than the first reliability degree threshold to obtain a second determination result; and setting the first content information as a final content information if the first determination result is YES and setting the first voiceprint information as a final voiceprint information if the second determination result is YES, wherein the first determination result being YES indicates that the first content information is accurate and the second determination result being YES indicates that the first voiceprint information is accurate. | 7. An information processing method for use in an electronic apparatus, the method comprising: detecting a voice information; obtaining a first content information and a first voiceprint information from the voice information; controlling the electronic apparatus to run a first application corresponding to the first content information; and controlling the electronic apparatus to run a second application other than the first application if the first voiceprint information is a preset voiceprint information, wherein the obtaining the first content information and the first voiceprint information from the voice information comprises: obtaining a first reliability degree of the first content information and a second reliability degree of the first voiceprint information, wherein the first reliability degree corresponds to reliability of the first content information and the second reliability degree corresponds to reliability of the first voiceprint information; selecting a first reliability degree threshold from at least two preset reliability degree thresholds; determining whether the first reliability degree is larger than the first reliability degree threshold to obtain a first determination result and/or determining whether the second reliability degree is larger than the first reliability degree threshold to obtain a second determination result; and setting the first content information as a final content information if the first determination result is YES and setting the first voiceprint information as a final voiceprint information if the second determination result is YES, wherein the first determination result being YES indicates that the first content information is accurate and the second determination result being YES indicates that the first voiceprint information is accurate. 10. The method according to claim 7 , further comprising, after the controlling the electronic apparatus to run the first application corresponding to the first content information and controlling the electronic apparatus to run the second application other than the first application if the first voiceprint information is the preset voiceprint information: obtaining a first authentication information corresponding to the first application by running the second application, the first authentication information being stored in the electronic apparatus and used for authentication of the first application. | 0.661385 |
13. A system for comparing handwriting, the system comprising: one or more processors operable to: modify, one or more color characteristics associated with each of a first electronic document and a second electronic document; extract one or more segments from the modified first electronic document and the modified second electronic document, wherein the one or more segments include a handwritten text; create one or more sets of segments from the one or more segments; receive an information indicating categorization of each segment in a set of segments in one or more categories, wherein the information is provided by one or more crowdworkers based on the handwriting in each segment; and determine a similarity score based on a count of segments in each of the one or more categories, wherein the similarity score is deterministic of a degree of similarity between the modified first electronic document and the modified second electronic document. | 13. A system for comparing handwriting, the system comprising: one or more processors operable to: modify, one or more color characteristics associated with each of a first electronic document and a second electronic document; extract one or more segments from the modified first electronic document and the modified second electronic document, wherein the one or more segments include a handwritten text; create one or more sets of segments from the one or more segments; receive an information indicating categorization of each segment in a set of segments in one or more categories, wherein the information is provided by one or more crowdworkers based on the handwriting in each segment; and determine a similarity score based on a count of segments in each of the one or more categories, wherein the similarity score is deterministic of a degree of similarity between the modified first electronic document and the modified second electronic document. 16. The system of claim 13 , wherein the one or more processors are further operable to permute the one or more segments from each of the modified first electronic document and the modified second electronic document. | 0.625 |
17. An apparatus for compressing genetic sequencing data in a text-based format, the apparatus including a processor and a non-transitory processor-readable medium having processor-executable instructions stored thereon, the processor-executable instructions comprising instructions for: receiving genetic sequencing data obtained using a high throughput genetic sequencing instrument; parsing information included in text of the genetic sequencing data into a plurality of fields, wherein the information includes title information, sequence data and quality data and wherein the plurality of fields includes a title information field, a sequence data field and a quality data field; collecting statistics with respect to one or more symbols represented by strings that are included in each of the plurality of fields; identifying, for each of the plurality of fields, an encoding algorithm that achieves greatest compression gains with respect to the field based on the collected statistics, by determining, for each field of the genetic sequencing data, an optimized encoding algorithm selected from the group consisting of an arithmetic encoding algorithm, a Markov encoding algorithm, and a Huffman encoding algorithm; generating bitstreams, compressed from the genetic sequencing data, by encoding each of the plurality of fields of the genetic sequencing data using the respective identified encoding algorithm; and outputting a unified bitstream by merging the generated bitstreams encoded for each of the plurality of fields. | 17. An apparatus for compressing genetic sequencing data in a text-based format, the apparatus including a processor and a non-transitory processor-readable medium having processor-executable instructions stored thereon, the processor-executable instructions comprising instructions for: receiving genetic sequencing data obtained using a high throughput genetic sequencing instrument; parsing information included in text of the genetic sequencing data into a plurality of fields, wherein the information includes title information, sequence data and quality data and wherein the plurality of fields includes a title information field, a sequence data field and a quality data field; collecting statistics with respect to one or more symbols represented by strings that are included in each of the plurality of fields; identifying, for each of the plurality of fields, an encoding algorithm that achieves greatest compression gains with respect to the field based on the collected statistics, by determining, for each field of the genetic sequencing data, an optimized encoding algorithm selected from the group consisting of an arithmetic encoding algorithm, a Markov encoding algorithm, and a Huffman encoding algorithm; generating bitstreams, compressed from the genetic sequencing data, by encoding each of the plurality of fields of the genetic sequencing data using the respective identified encoding algorithm; and outputting a unified bitstream by merging the generated bitstreams encoded for each of the plurality of fields. 21. The apparatus of claim 17 , wherein the instructions for collecting statistics includes instructions for collecting the statistics by identifying a quality value (Qmax) with a maximum occurrence in the text. | 0.527991 |
1. A method for text editing on an electronic device having a processor and display, the method comprising: receiving user input corresponding to at least one keystroke at the electronic device during text entry in a text editing program; disambiguating ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the electronic device, wherein the first specific subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, displaying a plurality of specific subject matter lexicons to the user of the electronic device while displaying text previously entered within the text editing program; receiving a selection by the user of the electronic device of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguating the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and displaying at least one disambiguation result to the user of the electronic device. | 1. A method for text editing on an electronic device having a processor and display, the method comprising: receiving user input corresponding to at least one keystroke at the electronic device during text entry in a text editing program; disambiguating ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the electronic device, wherein the first specific subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, displaying a plurality of specific subject matter lexicons to the user of the electronic device while displaying text previously entered within the text editing program; receiving a selection by the user of the electronic device of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguating the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and displaying at least one disambiguation result to the user of the electronic device. 6. The method according to claim 1 , further comprising accessing a server for downloading at least one of the first specific subject matter lexicon and the second specific subject matter lexicon. | 0.621203 |
8. A computer-readable medium having computer executable instructions stored thereon for automatically learning a set of weak classifiers, comprising instructions for: receiving a set of weighted positive examples corresponding to instances in a set of training data; receiving a set of weighted negative examples not corresponding to instances in the set of training data; specifying a number of weak classifiers to be learned; selecting a unique rectangular filter for each of the weak classifiers to be learned; for detection windows of each rectangular filter, constructing a histogram of the weights of the positive and negative examples; iteratively transforming each histogram into a histogram having a variable number of variably sized bins; and outputting each transformed histogram to form a set of weak classifiers. | 8. A computer-readable medium having computer executable instructions stored thereon for automatically learning a set of weak classifiers, comprising instructions for: receiving a set of weighted positive examples corresponding to instances in a set of training data; receiving a set of weighted negative examples not corresponding to instances in the set of training data; specifying a number of weak classifiers to be learned; selecting a unique rectangular filter for each of the weak classifiers to be learned; for detection windows of each rectangular filter, constructing a histogram of the weights of the positive and negative examples; iteratively transforming each histogram into a histogram having a variable number of variably sized bins; and outputting each transformed histogram to form a set of weak classifiers. 9. The computer-readable medium of claim 8 further comprising instructions for constructing a combination classifier from the set of weak classifiers. | 0.578431 |
8. A computer processing system for generating an object relevance display, the system comprising: a computer, including a non-transitory computer readable storage memory and an object ordering processor, wherein the object ordering processor, in response to receiving an object relevance display request comprising a set of objects to display, retrieves a set of stored relevance values associated with the set of objects and sorts the set of objects according to their associated relevance values, wherein a relevance value is calculated based on the number of references to an object wherein calculating each relevance value comprises associating a weight factor with each of a set of metadata sources, calculating a weighted number of references for each of the set of metadata sources by multiplying the number of references determined from a metadata source by the weight factor associated with the metadata source, and calculating the relevance value based on a weighted number of references to the object determined from the set of metadata sources; and a display generator that generates the object relevance display in response to receiving the sorted set of objects, the object relevance display comprising a set of icons representing the sorted set of objects and their associated relevance values. | 8. A computer processing system for generating an object relevance display, the system comprising: a computer, including a non-transitory computer readable storage memory and an object ordering processor, wherein the object ordering processor, in response to receiving an object relevance display request comprising a set of objects to display, retrieves a set of stored relevance values associated with the set of objects and sorts the set of objects according to their associated relevance values, wherein a relevance value is calculated based on the number of references to an object wherein calculating each relevance value comprises associating a weight factor with each of a set of metadata sources, calculating a weighted number of references for each of the set of metadata sources by multiplying the number of references determined from a metadata source by the weight factor associated with the metadata source, and calculating the relevance value based on a weighted number of references to the object determined from the set of metadata sources; and a display generator that generates the object relevance display in response to receiving the sorted set of objects, the object relevance display comprising a set of icons representing the sorted set of objects and their associated relevance values. 10. The computer processing system of claim 8 wherein the set of icons are graphic icons that indicate magnitudes of the relevance values corresponding to the sorted set of objects. | 0.566158 |
1. A method comprising: (a) receiving, at an electronic device, (i) data corresponding to a video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (b) displaying, to a user via an electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment control configured to allow the user to add a comment to the video; and (c) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (d) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, wherein the first length is one of a preconfigured length and a length determined based on a total length of the video; (e) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (f) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (g) receiving, at the electronic device from the user, input corresponding to engagement of the comment control; (h) in response to receiving input corresponding to engagement of the comment control, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (i) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (j) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. | 1. A method comprising: (a) receiving, at an electronic device, (i) data corresponding to a video, and (ii) data corresponding to a plurality of point comments associated with the video, each of the plurality of point comments being associated with a single point in time and with a particular user account of a plurality of user accounts, (iii) data corresponding to a plurality of segment comments associated with the video, each of the plurality of segment comments being associated with a video segment representing a span of time of the video and with a particular user account of the plurality of user accounts; (b) displaying, to a user via an electronic display associated with the electronic device, a video annotation interface comprising (i) a video pane configured to display the video, (ii) a first video timeline bar including a video play-head indicating a current point of the video which is being played, (iii) a second segment timeline bar disposed below the first video timeline bar, the second segment timeline bar including initial and final handles configured to define a segment of the video for playing, (iv) a first plurality of point comment markers identifiable as point comment markers by the presence of a first geometric shape displayed in connection with the video timeline bar, each of the first plurality of comment markers corresponding to one of the plurality of point comments associated with the video, (v) a second plurality of segment comment markers identifiable as segment comment markers by the presence of a second geometric shape displayed in connection with the video timeline bar, each of the second plurality of comment markers corresponding to one of the plurality of segment comments associated with the video, (vi) a comment display pane displaying text corresponding to at least some of the plurality of comments associated with the video, and (vii) a comment control configured to allow the user to add a comment to the video; and (c) receiving, at the electronic device from the user, input corresponding to engagement at a first point on the segment timeline bar; (d) automatically, in response to receiving the input corresponding to engagement at the first point on the segment timeline bar, moving the initial and final handles of the segment timeline bar to define a first segment of a first length centered around the first point, wherein the first length is one of a preconfigured length and a length determined based on a total length of the video; (e) receiving, at the electronic device from the user, input corresponding to dragging of the final handle to change the length of the first segment to a second length; (f) receiving, at the electronic device from the user, input corresponding to dragging of the first segment on the segment timeline bar, and simultaneously moving the initial and final handles while keeping the first segment its current length in response thereto; (g) receiving, at the electronic device from the user, input corresponding to engagement of the comment control; (h) in response to receiving input corresponding to engagement of the comment control, displaying, to the user via the electronic display associated with the electronic device, a comment interface; (i) receiving, at the electronic device from the user, input corresponding to one or more desired annotations; and (j) in response to receiving input corresponding to one or more desired annotations, (i) associating the input one or more annotations with the selected first segment of the video, (ii) updating the video annotation interface so that the plurality of comment markers displayed in connection with the video timeline bar includes a new segment comment marker corresponding to the first segment, and (iii) displaying an indication of the input one or more annotations overlaid over the video in the video pane. 2. The method of claim 1 , wherein the received data corresponding to a plurality of point comments associated with the video includes data corresponding to a particular point comment which includes an identification of a point of the video associated with the comment. | 0.513669 |
1. A recognition dictionary evaluation apparatus, comprising: a calculation module configured to calculate, in response to an update of a recognition dictionary file in which feature amount data indicating appearance feature amount of each commodity is stored, a recognition rate by item of each commodity according to the feature amount data of the updated recognition dictionary file; an evaluation module configured to evaluate the recognition dictionary file based on the recognition rate by item of each commodity calculated by the calculation module; a detection module configured to detect, in a case in which the recognition dictionary file is evaluated to be improper by the evaluation module, a low recognition commodity of which a correct recognition rate that a commodity is correctly recognized from all commodities is lower than a given level, and an incorrect recognition commodity of which an incorrect recognition rate is high within the recognition rate by item of the low recognition commodity; and a notification module configured to notify the items of the low recognition commodity and the incorrect recognition commodity detected by the detection module, wherein, the evaluation module takes at least one of the following four evaluation conditions as an evaluation condition to evaluate whether the recognition dictionary file is proper or improper: evaluation condition one: “whether or not the correct recognition rate of the commodity of which the recognition dictionary data is updated is greater than a first threshold value” evaluation condition two: “whether or not the average of the correct recognition rates of all the commodities is greater than a second threshold value” evaluation condition three: “whether or not a lowering width of the average of the correct recognition rates of all the commodities is lower than a third threshold value” and evaluation condition four: “whether or not the lowering width of the correct recognition rate of the commodity of which the recognition dictionary data is not updated is lower than a fourth threshold value”. | 1. A recognition dictionary evaluation apparatus, comprising: a calculation module configured to calculate, in response to an update of a recognition dictionary file in which feature amount data indicating appearance feature amount of each commodity is stored, a recognition rate by item of each commodity according to the feature amount data of the updated recognition dictionary file; an evaluation module configured to evaluate the recognition dictionary file based on the recognition rate by item of each commodity calculated by the calculation module; a detection module configured to detect, in a case in which the recognition dictionary file is evaluated to be improper by the evaluation module, a low recognition commodity of which a correct recognition rate that a commodity is correctly recognized from all commodities is lower than a given level, and an incorrect recognition commodity of which an incorrect recognition rate is high within the recognition rate by item of the low recognition commodity; and a notification module configured to notify the items of the low recognition commodity and the incorrect recognition commodity detected by the detection module, wherein, the evaluation module takes at least one of the following four evaluation conditions as an evaluation condition to evaluate whether the recognition dictionary file is proper or improper: evaluation condition one: “whether or not the correct recognition rate of the commodity of which the recognition dictionary data is updated is greater than a first threshold value” evaluation condition two: “whether or not the average of the correct recognition rates of all the commodities is greater than a second threshold value” evaluation condition three: “whether or not a lowering width of the average of the correct recognition rates of all the commodities is lower than a third threshold value” and evaluation condition four: “whether or not the lowering width of the correct recognition rate of the commodity of which the recognition dictionary data is not updated is lower than a fourth threshold value”. 2. The recognition dictionary evaluation apparatus according to claim 1 , further comprising: a reception module configured to receive the invalidation of either of the low recognition commodity and the incorrect recognition commodity; and an invalidation module configured to invalidate the feature amount data of the commodity of which the invalidation of recognition dictionary file is received. | 0.5 |
1. A method comprising acts of: receiving, from a text segmentation and topic assignment system, a first structured text comprising a plurality of text sections, the first structured text further comprising information indicative of a topic assigned to at least one text section of the plurality of text sections; providing the first structured text to a user for review, comprising providing the at least one text section in association with a section heading corresponding to the topic assigned to the at least one text section; receiving input from the user indicating at least one modification to the first structured text; causing the text segmentation and topic assignment system to process the at least one modification to generate a second structured text; receiving the second structured text from the text segmentation and topic assignment system; and providing the second structured text to the user for review. | 1. A method comprising acts of: receiving, from a text segmentation and topic assignment system, a first structured text comprising a plurality of text sections, the first structured text further comprising information indicative of a topic assigned to at least one text section of the plurality of text sections; providing the first structured text to a user for review, comprising providing the at least one text section in association with a section heading corresponding to the topic assigned to the at least one text section; receiving input from the user indicating at least one modification to the first structured text; causing the text segmentation and topic assignment system to process the at least one modification to generate a second structured text; receiving the second structured text from the text segmentation and topic assignment system; and providing the second structured text to the user for review. 2. The method of claim 1 , further comprising: causing the text segmentation and topic assignment system to process an unstructured text to generate the first structured text. | 0.650114 |
11. The server of claim 10 wherein the processor is further configured to: query an enterprise server using the communication instance to determine the name and receive an image of the communication participant; provide the name and the image to the client application; and receive a selection that selects the communication participant prior to providing one or more contextual information file names. | 11. The server of claim 10 wherein the processor is further configured to: query an enterprise server using the communication instance to determine the name and receive an image of the communication participant; provide the name and the image to the client application; and receive a selection that selects the communication participant prior to providing one or more contextual information file names. 12. The server of claim 11 wherein the processor is further configured to initiate a query to the plurality of contextual information sources, the plurality of contextual information sources being defined in a list for the client application as contextual information file sources. | 0.909963 |
1. A system for generating a representation of a group interaction, comprising: a memory that stores a plurality of voice profiles; and a processor programmed to: generate a transcript of the group interaction from audio source data representing the group interaction, the transcript comprising a sequence of lines of text, each line corresponding to an audible utterance in the audio source data; generate a conversation path from the transcript by labeling each transcript line with an identifier identifying a speaker of the corresponding audible utterance in the audio source data; and generate the representation of the group interaction by associating the conversation path with the plurality of voice profiles, each voice profile corresponding to the identified speaker in the conversation path. | 1. A system for generating a representation of a group interaction, comprising: a memory that stores a plurality of voice profiles; and a processor programmed to: generate a transcript of the group interaction from audio source data representing the group interaction, the transcript comprising a sequence of lines of text, each line corresponding to an audible utterance in the audio source data; generate a conversation path from the transcript by labeling each transcript line with an identifier identifying a speaker of the corresponding audible utterance in the audio source data; and generate the representation of the group interaction by associating the conversation path with the plurality of voice profiles, each voice profile corresponding to the identified speaker in the conversation path. 3. The system of claim 1 , where the processor is further programmed to associate the conversation path with auxiliary data. | 0.662605 |
7. A machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying a first set of hierarchically-organized lists in a first column and a second set of hierarchically-organized lists in a second column subsequent to the first column in the document, each of the first and second sets of hierarchically-organized lists comprising one or more list items identified by a list label; determining that a first list in the first set of hierarchically-organized lists continues as a second list in the second set of hierarchically-organized lists based on an analysis of the list labels of a last list item in the first list and a first list item in the second list; and storing the first list and the second list as a single list structure associated with the document. | 7. A machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying a first set of hierarchically-organized lists in a first column and a second set of hierarchically-organized lists in a second column subsequent to the first column in the document, each of the first and second sets of hierarchically-organized lists comprising one or more list items identified by a list label; determining that a first list in the first set of hierarchically-organized lists continues as a second list in the second set of hierarchically-organized lists based on an analysis of the list labels of a last list item in the first list and a first list item in the second list; and storing the first list and the second list as a single list structure associated with the document. 12. The machine readable medium of claim 7 , wherein at least one column exists between the first column and the second column within a reading order of the document. | 0.680174 |
10. A method comprising: receiving a plurality of terms from a user interface; deriving, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not inn the plurality of received terms; modifying the plurality of terms according to a specified criteria; displaying the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generating a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmitting the query to a web search engine. | 10. A method comprising: receiving a plurality of terms from a user interface; deriving, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not inn the plurality of received terms; modifying the plurality of terms according to a specified criteria; displaying the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generating a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmitting the query to a web search engine. 16. The method of claim 10 , further comprising storing the generated query in a memory for use at a later time. | 0.67759 |
1. A computer-implemented method for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the method comprising acts of: selecting a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; selecting, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receiving voice input provided by the user in response to the first prompt element; using at least one processor to process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, selecting a second voice style for the voice component of a second prompt element of the tapered prompt, and selecting, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. | 1. A computer-implemented method for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the method comprising acts of: selecting a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; selecting, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receiving voice input provided by the user in response to the first prompt element; using at least one processor to process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, selecting a second voice style for the voice component of a second prompt element of the tapered prompt, and selecting, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. 6. The computer-implemented method of claim 1 , further comprising an act of: audibly rendering the voice component of the first prompt element in the first voice style. | 0.557372 |
1. A method, comprising: extracting, by one or more processors of one or more computing devices, a keyword candidate from a document, of a plurality of documents, where each of the plurality of documents is mapped to at least one of a plurality of categories, and where the keyword candidate is included in the document and within one or more prior search queries; calculating, by the one or more processors, a respective frequency that the keyword candidate appears in each of the plurality of categories, where the frequency that the keyword candidate appears in a particular one of the plurality of categories corresponds to a number of occurrences of the keyword candidate in a subset, of the documents, mapped to the particular one of the categories; associating, by the one or more processors and as a keyword, the keyword candidate with the document in response to: determining that each of the respective calculated frequencies, associated with at least one category, of the plurality of categories, to which the document is mapped, exceeds a threshold, and determining that each of the respective calculated frequencies, associated with other categories, of the plurality of categories, to which the document is not mapped, do not exceed the threshold; and prioritizing, by the one or more processors, the document in search results produced in response to a search query related to the keyword and the at least one category associated with the document, where the search query is received after the one or more prior search queries. | 1. A method, comprising: extracting, by one or more processors of one or more computing devices, a keyword candidate from a document, of a plurality of documents, where each of the plurality of documents is mapped to at least one of a plurality of categories, and where the keyword candidate is included in the document and within one or more prior search queries; calculating, by the one or more processors, a respective frequency that the keyword candidate appears in each of the plurality of categories, where the frequency that the keyword candidate appears in a particular one of the plurality of categories corresponds to a number of occurrences of the keyword candidate in a subset, of the documents, mapped to the particular one of the categories; associating, by the one or more processors and as a keyword, the keyword candidate with the document in response to: determining that each of the respective calculated frequencies, associated with at least one category, of the plurality of categories, to which the document is mapped, exceeds a threshold, and determining that each of the respective calculated frequencies, associated with other categories, of the plurality of categories, to which the document is not mapped, do not exceed the threshold; and prioritizing, by the one or more processors, the document in search results produced in response to a search query related to the keyword and the at least one category associated with the document, where the search query is received after the one or more prior search queries. 10. The method of claim 1 , further comprising: storing the keyword for retrieval when the keyword is identified as relevant by a search engine. | 0.657895 |
1. A device comprises: an interface module; and a processing module operably coupled to: receive a digital signal from the interface module; parse the digital signal into a plurality of frames; generate speech characteristic probabilities regarding the plurality of frames; determine a plurality of estimated utterances, wherein an estimated utterance of the plurality of estimated utterances is determined by interpreting one or more representations of the plurality of frames in accordance with one or more of the speech characteristic probabilities; interpreting the one or more speech characteristic probabilities to generate a word bias and language syntax bias and using the word bias to weight word tables and the syntax bias to weight syntax tables, based on the one or more speech characteristic probabilities, and determine one or more words by interpreting the plurality of estimated utterances in accordance with at least one of: the weighted word table and the weighted syntax table for one or more of the speech characteristic probabilities. | 1. A device comprises: an interface module; and a processing module operably coupled to: receive a digital signal from the interface module; parse the digital signal into a plurality of frames; generate speech characteristic probabilities regarding the plurality of frames; determine a plurality of estimated utterances, wherein an estimated utterance of the plurality of estimated utterances is determined by interpreting one or more representations of the plurality of frames in accordance with one or more of the speech characteristic probabilities; interpreting the one or more speech characteristic probabilities to generate a word bias and language syntax bias and using the word bias to weight word tables and the syntax bias to weight syntax tables, based on the one or more speech characteristic probabilities, and determine one or more words by interpreting the plurality of estimated utterances in accordance with at least one of: the weighted word table and the weighted syntax table for one or more of the speech characteristic probabilities. 12. The device of claim 1 , wherein the interface module comprises one or more of: a radio frequency (RF) receiver operably coupled to: receive an RF signal; and convert the RF signal into the digital signal; a network interface module operably coupled to: receive a network signal; and convert the network signal into the digital signal; an audio processing module operably coupled to: receive an analog audio signal; and convert the analog audio signal into the digital signal; and an audio file module operably coupled to: retrieve a formatted audio file; and process the formatted audio file to produce the digital signal. | 0.599226 |
3. The method of claim 1 , wherein generating the query string includes generating a compilation of candidate search terms from multiple documents. | 3. The method of claim 1 , wherein generating the query string includes generating a compilation of candidate search terms from multiple documents. 4. The method of claim 3 , wherein generating the compilation of candidate search terms from multiple documents includes revising the query string as a user progresses through the multiple documents and selects the candidate search terms from at least two different documents in the multiple documents. | 0.932994 |
1. A method for presenting articles to a user on a news reader system, the method comprising: creating a profile for the user; receiving an article from a news provider, wherein the article is stored on a non-transitory computer readable storage medium; analyzing, with a processor, characteristics associated with the article; designating with a processor, a primary article based on the characteristics associated with the article; comparing the characteristics of the article with a second set of characteristics associated with a second article that is currently designated as the primary article; determining whether the article is more optimal for presentation than the second article based on said comparison; designating the article as the primary article if it is determined that the article is more optimal for presentation than the second article; presenting the article to the user for review; receiving an input from the user to highlighting a portion of the article, wherein highlighting the portion of the article comprises selecting the portion of the article with a cursor or touch screen device; in response to highlighting the portion of the article, displaying a menu of selectable options; receiving a second input from the user associated with choosing one of the selectable options; associating the selected portion of the article with the profile created for the user; and in response to a request to view the user's profile, displaying the selected portion of the article along with other content associated with the user's interaction with the news reader system. | 1. A method for presenting articles to a user on a news reader system, the method comprising: creating a profile for the user; receiving an article from a news provider, wherein the article is stored on a non-transitory computer readable storage medium; analyzing, with a processor, characteristics associated with the article; designating with a processor, a primary article based on the characteristics associated with the article; comparing the characteristics of the article with a second set of characteristics associated with a second article that is currently designated as the primary article; determining whether the article is more optimal for presentation than the second article based on said comparison; designating the article as the primary article if it is determined that the article is more optimal for presentation than the second article; presenting the article to the user for review; receiving an input from the user to highlighting a portion of the article, wherein highlighting the portion of the article comprises selecting the portion of the article with a cursor or touch screen device; in response to highlighting the portion of the article, displaying a menu of selectable options; receiving a second input from the user associated with choosing one of the selectable options; associating the selected portion of the article with the profile created for the user; and in response to a request to view the user's profile, displaying the selected portion of the article along with other content associated with the user's interaction with the news reader system. 2. The method as recited in claim 1 , wherein the primary article represents an article that is determined to be the optimal article for presentation to the user on a particular topic. | 0.743056 |
1. A system for cadence management of translated multi-speaker conversations comprising: a pause relationship manager having a hardware function for executing a logical process, the hardware means comprising at least one hardware function selected from a group comprising a microprocessor and an integrated circuit; a demultiplexer portion of the pause relationship manager separating a multi-speaker audio stream into a plurality of single-speaker audio tracks, each track containing one or more first language audio snippets organized according to a timing relationship as related in said multi-speaker audio stream; a pause analyzer portion of the pause relationship manager generating a pause relationship model by determining time relationships between said single-speaker snippets, and assigning pause marker values denoting the each beginning and each ending of each mutual silence pause; a pause relationship manager portion of the pause relationship manager collecting a translated language audio track corresponding to each of said single-speaker tracks, and generating one or more pause relationship controls according to a transformation of said pause relationship model; a multiplexer portion of the pause relationship manager producing a multi-speaker audio output including said translated tracks in which said translated snippets are related in time according to said pause relationship controls. | 1. A system for cadence management of translated multi-speaker conversations comprising: a pause relationship manager having a hardware function for executing a logical process, the hardware means comprising at least one hardware function selected from a group comprising a microprocessor and an integrated circuit; a demultiplexer portion of the pause relationship manager separating a multi-speaker audio stream into a plurality of single-speaker audio tracks, each track containing one or more first language audio snippets organized according to a timing relationship as related in said multi-speaker audio stream; a pause analyzer portion of the pause relationship manager generating a pause relationship model by determining time relationships between said single-speaker snippets, and assigning pause marker values denoting the each beginning and each ending of each mutual silence pause; a pause relationship manager portion of the pause relationship manager collecting a translated language audio track corresponding to each of said single-speaker tracks, and generating one or more pause relationship controls according to a transformation of said pause relationship model; a multiplexer portion of the pause relationship manager producing a multi-speaker audio output including said translated tracks in which said translated snippets are related in time according to said pause relationship controls. 4. The system as set forth in claim 1 wherein said pause relationship manager transforms said pause relationship model to produce beginnings of translated snippets synchronized with beginnings of said first language snippets. | 0.582213 |
7. The method of claim 6 wherein the story generation request comprises data that is indicative of at least one story angle from the angle set data structure. | 7. The method of claim 6 wherein the story generation request comprises data that is indicative of at least one story angle from the angle set data structure. 9. The method of claim 7 further comprising the processor generating and updating a data model relating to the subject based at least in part on the source data and the derived features, and wherein the processing step comprises the processor processing the data model against the angle set data structure to determine whether at least one applicability condition for at least one angle has been satisfied by the data model. | 0.833453 |
1. A method comprising: receiving unstructured text from a first user via a first interface communication, the unstructured text including item information describing an item for publication on a network-based publication system; analyzing the item information to generate structured text signifying at least one meaning of the unstructured text, the structured text including application information describing a plurality of applications including a first application, the first application including the item as a first component, the application information including a first application information describing the first application, the analyzing being performed by the use of at least one processor; storing the application information describing the plurality of applications and the item information in a listing in a database; publishing the listing on the network-based publication system; receiving a query from a second user including keywords that describe the item and a second application including the item; generating second application information describing the second application responsive to identifying the keywords in the query that describe the second application; retrieving the listing from the database based on matching the second application information that was generated from the keywords in the query with the first application information that was stored in the listing; and communicating the listing in a second interface communication to the second user, the second interface communication including visually perceptible user interface elements signifying the item and visually perceptible user interface elements signifying the first application as compatible with the item. | 1. A method comprising: receiving unstructured text from a first user via a first interface communication, the unstructured text including item information describing an item for publication on a network-based publication system; analyzing the item information to generate structured text signifying at least one meaning of the unstructured text, the structured text including application information describing a plurality of applications including a first application, the first application including the item as a first component, the application information including a first application information describing the first application, the analyzing being performed by the use of at least one processor; storing the application information describing the plurality of applications and the item information in a listing in a database; publishing the listing on the network-based publication system; receiving a query from a second user including keywords that describe the item and a second application including the item; generating second application information describing the second application responsive to identifying the keywords in the query that describe the second application; retrieving the listing from the database based on matching the second application information that was generated from the keywords in the query with the first application information that was stored in the listing; and communicating the listing in a second interface communication to the second user, the second interface communication including visually perceptible user interface elements signifying the item and visually perceptible user interface elements signifying the first application as compatible with the item. 9. The method of claim 1 , wherein the analyzing is responsive to the receiving the item information from the first user. | 0.560568 |
12. A system, comprising: a memory storing a plurality of instructions; and a processor configured to access the memory, wherein the processor is further configured to execute the plurality of instructions to at least: receive a continuous query, the continuous query identifying an archived view, the archived view identifying a join operation between a fact relation and a dimension relation; generate a query plan for the continuous query; initialize a state of an operator in the query plan corresponding to the dimension relation; identify if the state of the operator identifies an event that detects a change to the dimension relation; and re-start the continuous query based at least in part on the event that detects the change to the dimension relation; identify a view root operator in the archived view; construct an archiver query for the operator, the operator topologically preceding the view root operator; execute the archiver query to obtain a result set of data records related to an application; and generate a snapshot output of one or more data values related to the application based at least in part on the result set of data records related to the application. | 12. A system, comprising: a memory storing a plurality of instructions; and a processor configured to access the memory, wherein the processor is further configured to execute the plurality of instructions to at least: receive a continuous query, the continuous query identifying an archived view, the archived view identifying a join operation between a fact relation and a dimension relation; generate a query plan for the continuous query; initialize a state of an operator in the query plan corresponding to the dimension relation; identify if the state of the operator identifies an event that detects a change to the dimension relation; and re-start the continuous query based at least in part on the event that detects the change to the dimension relation; identify a view root operator in the archived view; construct an archiver query for the operator, the operator topologically preceding the view root operator; execute the archiver query to obtain a result set of data records related to an application; and generate a snapshot output of one or more data values related to the application based at least in part on the result set of data records related to the application. 14. The system of claim 12 , wherein the processor is further configured to execute the plurality of instructions to at least initialize the state of the operator based at least in part on the result set of data records. | 0.716539 |
11. A non-transitory computer-readable storage medium comprising instructions that, when executed, configure at least one processor to: while receiving initial audio data indicating an initial portion of voice input, output, for display, an initial speech recognition graphical user interface (GUI) including at least one element, wherein the at least one element is output for display in a first visual format to indicate the computing device is receiving the initial audio data; generate, based at least in part on the initial audio data, a transcription of the initial audio data; and while receiving additional audio data indicating a second portion of the voice input: determine, based at least in part on a comparison of at least one a word from the transcription to a preconfigured set of actions, a voice-initiated action associated with the initial portion of the voice input; and responsive to determining the voice-initiated action and prior to executing the voice-initiated action: output, for display, a first updated speech recognition GUI including an animation of a change in a position of the at least one element, from the initial speech recognition GUI, wherein the animation of the change in the position indicates that the voice-initiated action has been determined based on the initial audio data; after outputting the first update speech recognition GUI, outputting, by the computing device and for display, a second updated speech recognition GUI including the at least one element from the initial speech recognition GUI, the at least one element from the initial speech recognition GUI being displayed in a second visual format, different from the first visual format, to further indicate that the voice-initiated action has been determined from the initial audio data; and executing the voice-initiated action based on initial audio data and the additional audio data. | 11. A non-transitory computer-readable storage medium comprising instructions that, when executed, configure at least one processor to: while receiving initial audio data indicating an initial portion of voice input, output, for display, an initial speech recognition graphical user interface (GUI) including at least one element, wherein the at least one element is output for display in a first visual format to indicate the computing device is receiving the initial audio data; generate, based at least in part on the initial audio data, a transcription of the initial audio data; and while receiving additional audio data indicating a second portion of the voice input: determine, based at least in part on a comparison of at least one a word from the transcription to a preconfigured set of actions, a voice-initiated action associated with the initial portion of the voice input; and responsive to determining the voice-initiated action and prior to executing the voice-initiated action: output, for display, a first updated speech recognition GUI including an animation of a change in a position of the at least one element, from the initial speech recognition GUI, wherein the animation of the change in the position indicates that the voice-initiated action has been determined based on the initial audio data; after outputting the first update speech recognition GUI, outputting, by the computing device and for display, a second updated speech recognition GUI including the at least one element from the initial speech recognition GUI, the at least one element from the initial speech recognition GUI being displayed in a second visual format, different from the first visual format, to further indicate that the voice-initiated action has been determined from the initial audio data; and executing the voice-initiated action based on initial audio data and the additional audio data. 12. The non-transitory computer-readable storage medium of claim 11 , wherein: the first visual format of the at least one element from the initial speech recognition GUI comprises an image representative of a speech recognition mode of the computing device, and the second visual format of the at least one element from the initial speech recognition GUI comprises an image representative of the voice-initiated action. | 0.636619 |
8. The system of claim 1 in which the portion of document content comprises a portion of conditional text. | 8. The system of claim 1 in which the portion of document content comprises a portion of conditional text. 9. The system of claim 8 in which the portion of document content comprises a clause in a document. | 0.942615 |
12. A system, comprising: a plurality of processing devices in data communication, wherein the processing devices are operable to perform operations comprising: for each representation of a plurality of representations of predictive models, selecting a model implementation from a plurality of model implementation for the representation, wherein each representation is associated with a respective user and comprises a description of a respective predictive model, the selection based on a status of the representation's respective user; associating each of the model implementations with a respective node in a directed graph wherein for one or more ordered pairs of nodes in the graph the prediction output of a model implementation associated with a first node in the pair serves as input to a model implementation associated with a second node in the pair; determining, from the directed graph, a subset of model implementations that can be executed in parallel based on edge dependencies in the directed graph; and causing the models in the subset of model implementations to be executed in parallel. | 12. A system, comprising: a plurality of processing devices in data communication, wherein the processing devices are operable to perform operations comprising: for each representation of a plurality of representations of predictive models, selecting a model implementation from a plurality of model implementation for the representation, wherein each representation is associated with a respective user and comprises a description of a respective predictive model, the selection based on a status of the representation's respective user; associating each of the model implementations with a respective node in a directed graph wherein for one or more ordered pairs of nodes in the graph the prediction output of a model implementation associated with a first node in the pair serves as input to a model implementation associated with a second node in the pair; determining, from the directed graph, a subset of model implementations that can be executed in parallel based on edge dependencies in the directed graph; and causing the models in the subset of model implementations to be executed in parallel. 14. The system of claim 12 , the operations further comprising: assigning a system resource quota to at least one respective user; determining an amount of system resources that the model implementations for the respective user have consumed over a given period of time; and selecting the model implementation based on an amount of unconsumed system resources according to the system resource quota, wherein an amount of system resources that can be consumed by the selected model implementation does not exceed the amount of unconsumed system resources. | 0.581862 |
1. A method of automatically generating a notification for presentation in a user interface on a computer system of a member of a plurality of members of an online computerized social networking system, the notification including a recommendation of a context pertaining to a topic of interest of the member, the method comprising: storing a plurality of content items in a database of the online computerized social networking system, the plurality of content items generated by the plurality of members of the online computerized social networking system; detecting a plurality of interactions initiated by the member of the plurality of members with respect to the plurality of content items: determining a topic of interest of the member based on the detecting of the plurality of interactions and based on a similarity between a plurality of subjects corresponding to the plurality of content items; and based on a detecting of an action by the member pertaining to the topic of interest, automatically generating the notification, the recommendation of the context identifying a relationship between the topic of interest and a subset of the plurality of content items stored in the database of the online computerized social networking system, the subset of the plurality of content items being maintained by a group of the plurality of members separately from content items that are generally-accessible by the plurality of members. | 1. A method of automatically generating a notification for presentation in a user interface on a computer system of a member of a plurality of members of an online computerized social networking system, the notification including a recommendation of a context pertaining to a topic of interest of the member, the method comprising: storing a plurality of content items in a database of the online computerized social networking system, the plurality of content items generated by the plurality of members of the online computerized social networking system; detecting a plurality of interactions initiated by the member of the plurality of members with respect to the plurality of content items: determining a topic of interest of the member based on the detecting of the plurality of interactions and based on a similarity between a plurality of subjects corresponding to the plurality of content items; and based on a detecting of an action by the member pertaining to the topic of interest, automatically generating the notification, the recommendation of the context identifying a relationship between the topic of interest and a subset of the plurality of content items stored in the database of the online computerized social networking system, the subset of the plurality of content items being maintained by a group of the plurality of members separately from content items that are generally-accessible by the plurality of members. 2. The method of claim 1 , further comprising selecting the context from a plurality of contexts based on a relevance of the context to the member in comparison to a relevance of an additional context of the plurality of contexts to the member. | 0.527851 |
12. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: selecting a plurality of candidate videos from videos identified in a response to a search query derived from a label for an object category; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects in the object category in the initial frames; for each initial frame including an initial image of an object in the object category, tracking the object through surrounding frames to identify additional images of the object; selecting one or more images from the one or more initial images and one or more additional images as database images of objects belonging to the object category; generating statistics that identify frequencies of co-occurrences of objects in the candidate videos; and using the database images as training data for one or more learning models that predict a context of images or videos. | 12. A system comprising one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: selecting a plurality of candidate videos from videos identified in a response to a search query derived from a label for an object category; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects in the object category in the initial frames; for each initial frame including an initial image of an object in the object category, tracking the object through surrounding frames to identify additional images of the object; selecting one or more images from the one or more initial images and one or more additional images as database images of objects belonging to the object category; generating statistics that identify frequencies of co-occurrences of objects in the candidate videos; and using the database images as training data for one or more learning models that predict a context of images or videos. 14. The system of claim 12 , wherein detecting an initial image of an object in a particular initial frame comprises: selecting a plurality of bounding boxes from the initial frame; and selecting an image contained in a particular bounding box of the plurality of bounding boxes as an initial image of the object. | 0.507546 |
36. The computer-readable volatile or non-volatile medium of claim 25 , wherein the instructions that cause the one or more processors to perform the step of said XML processor receiving said one or more requests for said particular information include instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of receiving a request regarding a first annotation that is associated with said particular XML element of said XML-based input stream, wherein said first annotation is defined in information that dictates the structure of corresponding XML data. | 36. The computer-readable volatile or non-volatile medium of claim 25 , wherein the instructions that cause the one or more processors to perform the step of said XML processor receiving said one or more requests for said particular information include instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of receiving a request regarding a first annotation that is associated with said particular XML element of said XML-based input stream, wherein said first annotation is defined in information that dictates the structure of corresponding XML data. 37. The computer-readable volatile or non-volatile medium of claim 36 , wherein said information that dictates the structure of corresponding XML data comprises a second annotation definition that is associated with a second XML element of said XML-based input stream that is different than said particular XML element, wherein the instructions that cause the one or more processors to perform the step of said XML processor receiving said one or more requests for said particular information include instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of receiving a request regarding said second annotation, and wherein the one or more sequences of instructions further comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of: before responding to said request regarding said second annotation, responding to a request regarding whether said particular XML element is defined in said information that dictates the structure of corresponding XML data. | 0.734017 |
8. A speech producing apparatus comprising: input means for selectively receiving either a sequence of input data containing a plurality of phonological linguistic unit indicia and a plurality of word boundary indicia, each word boundary indicia indicative of a word boundary, corresponding to a phrase of human speech or at least one phonological linguistic unit indicia and a single word boundary indicia corresponding to a single word of human speech; mode determining means connected to said input means for entering a phrase mode if said sequence of input data corresponds to a phrase of human speech and for entering a word mode if said sequence of input data corresponds to a single word of human speech; phonemic memory means for storing speech synthesis parameters corresponding to each of said phonological linguistic unit indicia; control means connected to said input means, said mode determining means and said phonemic memory means for converting said sequence of input data into a sequence of speech synthesis parameters by (1) recalling said speech synthesis parameters corresponding to said received phonological linguistic unit indicia when in said phrase mode and (2) recalling said speech synthesis parameters from said phonemic memory means corresponding to said received phonological linguistic unit indicia except (a) recalling speech synthesis parameters corresponding to word final phonological linguistic unit indicia when a corresponding internal phonological linguistic unit indicia occurs at the end of said word, and (b) recalling speech synthesis parameters corresponding to long strong vowels when a corresponding short strong vowel occurs at the end of said word or is the final vowel of said word and is followed by only voiced consonant phonological linguistic unit indicia; and speech synthesis means connected to said control means for generating one or more audible words of human language corresponding to said sequence of speech synthesis parameters. | 8. A speech producing apparatus comprising: input means for selectively receiving either a sequence of input data containing a plurality of phonological linguistic unit indicia and a plurality of word boundary indicia, each word boundary indicia indicative of a word boundary, corresponding to a phrase of human speech or at least one phonological linguistic unit indicia and a single word boundary indicia corresponding to a single word of human speech; mode determining means connected to said input means for entering a phrase mode if said sequence of input data corresponds to a phrase of human speech and for entering a word mode if said sequence of input data corresponds to a single word of human speech; phonemic memory means for storing speech synthesis parameters corresponding to each of said phonological linguistic unit indicia; control means connected to said input means, said mode determining means and said phonemic memory means for converting said sequence of input data into a sequence of speech synthesis parameters by (1) recalling said speech synthesis parameters corresponding to said received phonological linguistic unit indicia when in said phrase mode and (2) recalling said speech synthesis parameters from said phonemic memory means corresponding to said received phonological linguistic unit indicia except (a) recalling speech synthesis parameters corresponding to word final phonological linguistic unit indicia when a corresponding internal phonological linguistic unit indicia occurs at the end of said word, and (b) recalling speech synthesis parameters corresponding to long strong vowels when a corresponding short strong vowel occurs at the end of said word or is the final vowel of said word and is followed by only voiced consonant phonological linguistic unit indicia; and speech synthesis means connected to said control means for generating one or more audible words of human language corresponding to said sequence of speech synthesis parameters. 14. A speech producing apparatus as claimed in claim 8, further comprising: word stress determining means for determining the word stress syllable of said word in word mode from the sequence of input data by (1) setting the word stress syllable to the single vowel syllable if there is a single vowel in the word, (2) setting the word stress syllable to the syllable including the strong vowel if there is a single strong vowel in the word, (3) setting the word stress syllable to the first syllable including a strong vowel in which there are a plurality of strong vowels, except (4) setting the word stress syllable to the last syllable including a strong vowel prior to one of a predetermined group of suffixes. | 0.5 |
15. The method of claim 13 , wherein the interface represents the concept hierarchy as a graph comprising a plurality of nodes connected by a plurality of links, wherein a particular node of the plurality of nodes corresponds to a particular concept and wherein a particular link between a pair of nodes represents a semantic relationship between concepts corresponding to the pair of nodes. | 15. The method of claim 13 , wherein the interface represents the concept hierarchy as a graph comprising a plurality of nodes connected by a plurality of links, wherein a particular node of the plurality of nodes corresponds to a particular concept and wherein a particular link between a pair of nodes represents a semantic relationship between concepts corresponding to the pair of nodes. 18. The method of claim 15 , wherein a size of a node is partially based on a number of hierarchical levels below the concept corresponding to the node, and wherein more hierarchical levels below the concept corresponding to the node are displayed as larger nodes than nodes that have fewer hierarchical levels below the concept corresponding to the node. | 0.869693 |
14. A computer-implemented method of recognition processing of data, comprising: defining a probability space within a set of constraints for recognition processing of data; reserving a section of the probability space for integrating application-dependent information; utilizing at least one of user specific information, a specific scenario, a specific environment, or other information specific to a user interaction as application-dependent information; integrating the application-dependent information into the reserved section of the probability space as a sub-set of the constraints; and utilizing a microprocessor that executes instructions stored in a memory. | 14. A computer-implemented method of recognition processing of data, comprising: defining a probability space within a set of constraints for recognition processing of data; reserving a section of the probability space for integrating application-dependent information; utilizing at least one of user specific information, a specific scenario, a specific environment, or other information specific to a user interaction as application-dependent information; integrating the application-dependent information into the reserved section of the probability space as a sub-set of the constraints; and utilizing a microprocessor that executes instructions stored in a memory. 19. The method of claim 14 , further comprising: biasing specific categories of the application-dependent information with various weights based on a likelihood that the application-dependent information will be used. | 0.5 |
17. An automated reasoning system adapted for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, said automated reasoning system comprising: a module adapted to provide a print product description; a module adapted to extract asset metadata from a plurality of resources associated with said print product description; a processor adapted to process said asset metadata through said automated reasoning system to infer predefined characteristics from said asset metadata to form inferred metadata; and a module adapted to utilize said inferred metadata to add and parameterize a process node including said inferred metadata to a process network. | 17. An automated reasoning system adapted for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, said automated reasoning system comprising: a module adapted to provide a print product description; a module adapted to extract asset metadata from a plurality of resources associated with said print product description; a processor adapted to process said asset metadata through said automated reasoning system to infer predefined characteristics from said asset metadata to form inferred metadata; and a module adapted to utilize said inferred metadata to add and parameterize a process node including said inferred metadata to a process network. 18. The automated reasoning system of claim 17 further comprising a rules-based reasoning module. | 0.542806 |
22. The system according to claim 1 wherein said structured representation of rules further comprises: a binder function enabled to generate a conclusion fact or set of facts from the fact or facts corresponding to a premise node or node group. | 22. The system according to claim 1 wherein said structured representation of rules further comprises: a binder function enabled to generate a conclusion fact or set of facts from the fact or facts corresponding to a premise node or node group. 25. The system according to claim 22 wherein said structured representation of rules further comprises: a conclusion node group further comprising an antecedent node group, a consequent node group. | 0.872571 |
1. A search method, comprising: obtaining from a search log database one or more search term candidates that are relevant to a present search query, wherein each one or more search term candidates includes at least one term associated with a respective property; for each of the one or more obtained search term candidates, retrieving, from the search log database, the respective property associated with the at least one term of the one or more search term candidates; for each of one or more retrieved properties of the one or more search term candidates, determining a matching result for a term in the present search query and the at least one term associated with the respective property; determining whether to rewrite the present search query based at least in part on one or more matching results comprising: assigning property values to the one or more retrieved properties of the one or more search term candidates and the present search query based at least in part on the one or more matching results; obtaining one or more matching result values corresponding to the property values of the one or more search term candidates, wherein the property values are processed based at least in part on a linear weighting approach or converting the property values into the one or more matching result values based at least in part on a Maximum Entropy Model; and determining whether the one or more matching result values are greater than a threshold; and responsive to determining to rewrite the present search query, rewriting, by a data rewriting system, the present search query to provide a rewritten present search query based at least in part on the one or more matching results, and performing, by a search engine, a search based at least in part on the rewritten present search query. | 1. A search method, comprising: obtaining from a search log database one or more search term candidates that are relevant to a present search query, wherein each one or more search term candidates includes at least one term associated with a respective property; for each of the one or more obtained search term candidates, retrieving, from the search log database, the respective property associated with the at least one term of the one or more search term candidates; for each of one or more retrieved properties of the one or more search term candidates, determining a matching result for a term in the present search query and the at least one term associated with the respective property; determining whether to rewrite the present search query based at least in part on one or more matching results comprising: assigning property values to the one or more retrieved properties of the one or more search term candidates and the present search query based at least in part on the one or more matching results; obtaining one or more matching result values corresponding to the property values of the one or more search term candidates, wherein the property values are processed based at least in part on a linear weighting approach or converting the property values into the one or more matching result values based at least in part on a Maximum Entropy Model; and determining whether the one or more matching result values are greater than a threshold; and responsive to determining to rewrite the present search query, rewriting, by a data rewriting system, the present search query to provide a rewritten present search query based at least in part on the one or more matching results, and performing, by a search engine, a search based at least in part on the rewritten present search query. 5. The method as recited in claim 1 , wherein, after performing a search based on the rewritten present search query, the method further comprises: causing a search result to be displayed to a user client. | 0.628163 |
157. The system of claim 156 , wherein the processor is further configured to: when the experience range is zero: set the term of experience to zero; and when the experience range is greater than zero: determine a start time for the experience range; determine an end time for the experience range; compute a time difference between the start time and the end time; and set the term of experience to the time difference. | 157. The system of claim 156 , wherein the processor is further configured to: when the experience range is zero: set the term of experience to zero; and when the experience range is greater than zero: determine a start time for the experience range; determine an end time for the experience range; compute a time difference between the start time and the end time; and set the term of experience to the time difference. 160. The system of claim 157 , wherein the term of experience is not an integer. | 0.923033 |
1. A piano key identification system comprising: a plurality of informational stickers securable to an individual one of a plurality of keys of a musical instrument, the informational stickers each including indicia printed thereon communicating to an individual an identity of the particular key to which a particular informational sticker can be attached; said informational stickers each comprising a base web formed in a substantially rectangular configuration, said base web being formed of a flexible material having an adhesive applied to a bottom surface thereof and operable to effect securement of the base web to an upper surface of a key; and, a removable template backing configured so as to depict a piano keyboard, with the informational stickers each being attached to the respective keys of the piano keyboard depicted on the template backing. | 1. A piano key identification system comprising: a plurality of informational stickers securable to an individual one of a plurality of keys of a musical instrument, the informational stickers each including indicia printed thereon communicating to an individual an identity of the particular key to which a particular informational sticker can be attached; said informational stickers each comprising a base web formed in a substantially rectangular configuration, said base web being formed of a flexible material having an adhesive applied to a bottom surface thereof and operable to effect securement of the base web to an upper surface of a key; and, a removable template backing configured so as to depict a piano keyboard, with the informational stickers each being attached to the respective keys of the piano keyboard depicted on the template backing. 14. The piano key identification system of claim 1, wherein the indicia comprises braille indicia in the form of an aligned matrix of large braille projections and small braille projections extending from the base web. | 0.529211 |
35. The computer program product of claim 3 wherein the subject comprises a company, wherein the received source data comprises stock price information associated with the company, and wherein the angle set data structure comprises (1) data representative of a plurality of story angles corresponding to a plurality of different stock price story angles, and (2) for each stock price story angle, data associated therewith that identifies at least one applicability condition for that stock price story angle. | 35. The computer program product of claim 3 wherein the subject comprises a company, wherein the received source data comprises stock price information associated with the company, and wherein the angle set data structure comprises (1) data representative of a plurality of story angles corresponding to a plurality of different stock price story angles, and (2) for each stock price story angle, data associated therewith that identifies at least one applicability condition for that stock price story angle. 37. The computer program product of claim 35 wherein one of the stock price story angles comprises a “gapping” stock price story angle. | 0.827574 |
87. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; and determining a personal proximity and a professional proximity and overall proximity between actors. | 87. A method to enable improved analysis and use of sociological data, the method comprising: identifying causal relationships between a plurality of documents; identifying a plurality of characteristics of a communication, including a modality used, actors involved, and proximate events of relevance; enabling a user to query based on all of the characteristics available; and determining a personal proximity and a professional proximity and overall proximity between actors. 89. The method of claim 87 further comprising: identifying divergence between the proximity between actors and a tone used in a communication between actors. | 0.75759 |
25. A voice processing apparatus as set forth in claim 24 , wherein: speaker data stored in said voiceprint data memory means is made to corresponds to each of said plurality of unidirectional microphones; and said data processing means processes attribute data corresponding to said first speaker data based on comparing first speaker data obtained by comparing voiceprint data stored in the voiceprint data memory means with second speaker data corresponding to said selected one microphone. | 25. A voice processing apparatus as set forth in claim 24 , wherein: speaker data stored in said voiceprint data memory means is made to corresponds to each of said plurality of unidirectional microphones; and said data processing means processes attribute data corresponding to said first speaker data based on comparing first speaker data obtained by comparing voiceprint data stored in the voiceprint data memory means with second speaker data corresponding to said selected one microphone. 26. A voice processing apparatus as set forth in claim 25 , wherein said data processing means compares said first speaker data with said second speaker data and, only when the first and second speaker data match, processes attribute data corresponding to said second speaker data. | 0.859613 |
1. A system for generating a graph lattice from exemplary images, said system comprising: at least one processor programmed to: receive exemplary data graphs of the exemplary images, wherein nodes of the exemplary data graphs are formed from primitives; generate graph lattice nodes of size one from the primitives; until a termination condition is met, repeatedly: generate candidate graph lattice nodes from accepted graph lattice nodes, including the graph lattice nodes of size one and promoted graph lattice nodes, and the exemplary data graphs; select one or more candidate graph lattice nodes, the selected candidate graph lattice nodes preferentially discriminating exemplary data graphs which are less discriminable than other exemplary data graphs using the accepted graph lattice nodes, wherein the selection of the one or more candidate graph lattice nodes includes a scoring operation where a high score indicates that a particular exemplary data graph is mapped to by many subgraphs of accepted graph lattice nodes that are not mapped to many other exemplary data graphs, indicating there are many discriminating subgraph features for the particular exemplary data graph, and a low score indicates the particular exemplary data graph is not mapped to by unique or highly discriminative features, and is more confusable with other exemplary data graphs, wherein each graph lattice node, including the accepted graph lattice nodes and the candidate graph lattice nodes, includes a subgraph, a vote weight, and at least one mapping of the subgraph to the exemplary data graphs, and wherein the scoring operation includes: scoring each candidate graph lattice node according to a scoring function, the scoring function including a ratio, wherein a numerator of the ratio is based on the vote weight of the candidate graph lattice node, and wherein a denominator of the ratio is a summation of vote weights of accepted graph lattice nodes mapping to exemplary data graphs the candidate graph lattice node maps to; and, the selection of the one or more candidate graph lattice nodes further includes selecting most highly scored candidate graph lattice nodes according to selection criteria; and, promote the selected graph lattice nodes to accepted status; wherein the graph lattice is formed from the accepted graph lattice nodes and relations between the accepted graph lattice nodes. | 1. A system for generating a graph lattice from exemplary images, said system comprising: at least one processor programmed to: receive exemplary data graphs of the exemplary images, wherein nodes of the exemplary data graphs are formed from primitives; generate graph lattice nodes of size one from the primitives; until a termination condition is met, repeatedly: generate candidate graph lattice nodes from accepted graph lattice nodes, including the graph lattice nodes of size one and promoted graph lattice nodes, and the exemplary data graphs; select one or more candidate graph lattice nodes, the selected candidate graph lattice nodes preferentially discriminating exemplary data graphs which are less discriminable than other exemplary data graphs using the accepted graph lattice nodes, wherein the selection of the one or more candidate graph lattice nodes includes a scoring operation where a high score indicates that a particular exemplary data graph is mapped to by many subgraphs of accepted graph lattice nodes that are not mapped to many other exemplary data graphs, indicating there are many discriminating subgraph features for the particular exemplary data graph, and a low score indicates the particular exemplary data graph is not mapped to by unique or highly discriminative features, and is more confusable with other exemplary data graphs, wherein each graph lattice node, including the accepted graph lattice nodes and the candidate graph lattice nodes, includes a subgraph, a vote weight, and at least one mapping of the subgraph to the exemplary data graphs, and wherein the scoring operation includes: scoring each candidate graph lattice node according to a scoring function, the scoring function including a ratio, wherein a numerator of the ratio is based on the vote weight of the candidate graph lattice node, and wherein a denominator of the ratio is a summation of vote weights of accepted graph lattice nodes mapping to exemplary data graphs the candidate graph lattice node maps to; and, the selection of the one or more candidate graph lattice nodes further includes selecting most highly scored candidate graph lattice nodes according to selection criteria; and, promote the selected graph lattice nodes to accepted status; wherein the graph lattice is formed from the accepted graph lattice nodes and relations between the accepted graph lattice nodes. 2. The system according to claim 1 , wherein the primitives include junction types of rectilinear line art. | 0.667495 |
7. A system for opinion processing and visualization for display on a computer screen, comprising: a data acquisition module configured to collection information on entities from structured and unstructured data sources, the data acquisition module configured to combine voluminous structured data from the structure data sources into a normalized representation to be stored in an entity database, each structured data being normalized with encoded one or more attribute for linking to the original structured data source, the data acquisition module configured to normalize the unstructured data from the unstructured data source into a post database; an analytics module configured to retrieve and link each post data from the post database to an entity in the entity database, the analytics module configured to determine the sentiment type associated with each electronic post linked to a particular entity, the analytics module configured to score the quality of each electronic post based on a predetermined criteria, the analytics module configured to compare one or more entities over time based on different attributes including buzz ranking and mood ranking, wherein the buzz ranking and the mood ranking for a particular entity are scored relative to the confined number of entities in the entity database; and a visualization module configured to aggregate the results of the scored structured electronic social media messages and the scored normalized unstructured electronic social media messages for one or more entities organized for display as a transformed visual representation based on the extracted one or more entities from the search query, the transformed visual representation including buzz ranking and mood ranking; wherein the transformed visual representation comprises a timeline entity graphical view with social media inflections over a period of time and a heat map of social media sentiments for the industry associated with the entity, the size and color coding for each company in the industry dependent on the amount of social medial posts and the type of sentiment. | 7. A system for opinion processing and visualization for display on a computer screen, comprising: a data acquisition module configured to collection information on entities from structured and unstructured data sources, the data acquisition module configured to combine voluminous structured data from the structure data sources into a normalized representation to be stored in an entity database, each structured data being normalized with encoded one or more attribute for linking to the original structured data source, the data acquisition module configured to normalize the unstructured data from the unstructured data source into a post database; an analytics module configured to retrieve and link each post data from the post database to an entity in the entity database, the analytics module configured to determine the sentiment type associated with each electronic post linked to a particular entity, the analytics module configured to score the quality of each electronic post based on a predetermined criteria, the analytics module configured to compare one or more entities over time based on different attributes including buzz ranking and mood ranking, wherein the buzz ranking and the mood ranking for a particular entity are scored relative to the confined number of entities in the entity database; and a visualization module configured to aggregate the results of the scored structured electronic social media messages and the scored normalized unstructured electronic social media messages for one or more entities organized for display as a transformed visual representation based on the extracted one or more entities from the search query, the transformed visual representation including buzz ranking and mood ranking; wherein the transformed visual representation comprises a timeline entity graphical view with social media inflections over a period of time and a heat map of social media sentiments for the industry associated with the entity, the size and color coding for each company in the industry dependent on the amount of social medial posts and the type of sentiment. 10. The system of claim 7 , wherein the transformed visual representation comprises a comparison entity graphical view between two dissimilar entities. | 0.560496 |
9. A user-customized content providing method, comprising: searching a content set related to user's search query word; asking an apparatus for user preference information including a user profile and tag information, the user profile including a keyword collected in the apparatus and a point applied with a weight given per keyword; receiving the user preference information from the apparatus; determining a ranking of the content set according to the relation to the user preference information; and providing the ranked content set to the apparatus, wherein the keyword is detected by using tag information extracted from at least one tag of an anchor tag, a form tag and a combination thereof that are included in a web document outputted to the apparatus, and wherein the point per keyword is calculated based on data related to a number of selections of the keyword by the user, selection of the keyword comprising clicking the anchor tag including the keyword. | 9. A user-customized content providing method, comprising: searching a content set related to user's search query word; asking an apparatus for user preference information including a user profile and tag information, the user profile including a keyword collected in the apparatus and a point applied with a weight given per keyword; receiving the user preference information from the apparatus; determining a ranking of the content set according to the relation to the user preference information; and providing the ranked content set to the apparatus, wherein the keyword is detected by using tag information extracted from at least one tag of an anchor tag, a form tag and a combination thereof that are included in a web document outputted to the apparatus, and wherein the point per keyword is calculated based on data related to a number of selections of the keyword by the user, selection of the keyword comprising clicking the anchor tag including the keyword. 10. The method of claim 9 , wherein the keyword is detected by extracting a stop word from words included in a mapping table and query words, all parts or some parts of tag information included in the web document being written in the mapping table. | 0.626154 |
20. A method for speech translation, comprising: receiving an original output from a first component; transforming the original output into a new output that is more easily translated by a second component based on an expected comfortability analysis and that is phonetically similar to the original hypothesis wherein the transforming includes: integrating a plurality of features in a log-linear transformation model; and hypotheses searching using one or more transformation features which are applied to the original hypothesis to transform the original hypothesis into a new hypothesis for processing by the second component. | 20. A method for speech translation, comprising: receiving an original output from a first component; transforming the original output into a new output that is more easily translated by a second component based on an expected comfortability analysis and that is phonetically similar to the original hypothesis wherein the transforming includes: integrating a plurality of features in a log-linear transformation model; and hypotheses searching using one or more transformation features which are applied to the original hypothesis to transform the original hypothesis into a new hypothesis for processing by the second component. 21. The method as recited in claim 20 , wherein the one or more transformation features includes at least one of a phonetic similarity table and a phrase confusion table configured to provide a new hypothesis that is phonetically similar to the original hypothesis. | 0.652456 |
29. The system of claim 25 , where the plurality of applications are associated with the file type by rules in a set of selection rules defining conditions for selecting an application to be used to open files. | 29. The system of claim 25 , where the plurality of applications are associated with the file type by rules in a set of selection rules defining conditions for selecting an application to be used to open files. 30. The system of claim 29 , where the selection rules include one or more of user-defined preferences associating applications with file types or administrator preferences applicable to all users of the computing environment. | 0.913585 |
9. An apparatus that can be used to specify a subset of data, comprising: a communication interface; a storage device; and one or more processors in communication with the storage device and the communication interface, the one or more processors implement a user interface using the communication interface, the one or more processors receive a first input at the user interface for a first field of a natural language expression, the first input indicates a first data value for the first field, the one or more processors access options for a second field of the natural language expression that are determined based on the first data value and data stored in data group, the one or more processors display the second field and the options for the second field, the one or more processors receive a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field, the one or more processors access options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group, the one or more processors display the third field and the options for the third field, the one or more processors receive a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language, the one or more processors access and report a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. | 9. An apparatus that can be used to specify a subset of data, comprising: a communication interface; a storage device; and one or more processors in communication with the storage device and the communication interface, the one or more processors implement a user interface using the communication interface, the one or more processors receive a first input at the user interface for a first field of a natural language expression, the first input indicates a first data value for the first field, the one or more processors access options for a second field of the natural language expression that are determined based on the first data value and data stored in data group, the one or more processors display the second field and the options for the second field, the one or more processors receive a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field, the one or more processors access options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group, the one or more processors display the third field and the options for the third field, the one or more processors receive a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language, the one or more processors access and report a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. 10. The apparatus of claim 9 , wherein: the one or more processors monitor performance of a software system; the one or more processors collect and store performance data of the software system based on the monitoring, the stored performance data is the data group; the one or more processors determine that a condition exists in the software system based on the monitoring; and the one or more processors pre-populate the natural language expression based on the determined condition existing in the software system and display the pre-populated natural language expression in the user interface prior to the receiving the first input. | 0.5 |
1. A computer-implemented method comprising: extracting a text string and context information for the text string using a processor, wherein the extracting extracts the text string and the context information for the text string from an application to be translated, the text string is to be translated, the context information for the text string is configured to identify a location of the text string in the application to be translated, and the context information comprises a plurality of identifiers; searching an application archive for an existing translation of the text string, using the processor, wherein the searching is performed using a subset of the identifiers, the subset of identifiers is a plurality of the plurality of identifiers of the context information for the text string, the searching for the existing translation is limited using at least one identifier in the subset of identifiers, the searching results in a set of translations, each translation in the set of translations matches at least one identifier from the subset of identifiers, and the set of translations comprises the existing translation; and selecting the existing translation from the set of translations using the processor, wherein the existing translation is selected from the set of translations as the translation that matches the most identifiers from the subset of identifiers. | 1. A computer-implemented method comprising: extracting a text string and context information for the text string using a processor, wherein the extracting extracts the text string and the context information for the text string from an application to be translated, the text string is to be translated, the context information for the text string is configured to identify a location of the text string in the application to be translated, and the context information comprises a plurality of identifiers; searching an application archive for an existing translation of the text string, using the processor, wherein the searching is performed using a subset of the identifiers, the subset of identifiers is a plurality of the plurality of identifiers of the context information for the text string, the searching for the existing translation is limited using at least one identifier in the subset of identifiers, the searching results in a set of translations, each translation in the set of translations matches at least one identifier from the subset of identifiers, and the set of translations comprises the existing translation; and selecting the existing translation from the set of translations using the processor, wherein the existing translation is selected from the set of translations as the translation that matches the most identifiers from the subset of identifiers. 9. The computer-implemented method of claim 1 , wherein the translation is provided by a user. | 0.641435 |
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