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1. A computer system including instructions stored on one or more computer-readable medium and executable by one or more processors, the computer system comprising: a statistic calculator configured to receive a plurality of content files and to determine at least one statistical measure of the content of the plurality of content files, said statistic calculator configured to store the at least one statistical measure within a statistics repository; a cluster controller configured to cause the one or more processors to generate a hierarchy of clusters based on the at least one statistical measure stored in the statistics repository, wherein the hierarchy of clusters comprises at least two levels, each cluster within a first level of the hierarchy of clusters comprising at least one content file, each cluster within a second level of the hierarchy of clusters comprising at least one cluster of the first level of the hierarchy of clusters; an aggregator configured to aggregate the content files of each cluster, and transmit the aggregated content file to said cluster controller to form a third level of the hierarchy of clusters; a label manager configured to cause the one or more processors to determine a label for each cluster within the hierarchy of clusters based on the at least one statistical measure, the label identifying a topic of information contained within each cluster, the topic related to at least one of a problem experienced by a user and a request for assistance in solving the problem; and a taxonomy manager configured to cause the one or more processors to output a taxonomy based on the hierarchy of clusters and the determined labels.
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1. A computer system including instructions stored on one or more computer-readable medium and executable by one or more processors, the computer system comprising: a statistic calculator configured to receive a plurality of content files and to determine at least one statistical measure of the content of the plurality of content files, said statistic calculator configured to store the at least one statistical measure within a statistics repository; a cluster controller configured to cause the one or more processors to generate a hierarchy of clusters based on the at least one statistical measure stored in the statistics repository, wherein the hierarchy of clusters comprises at least two levels, each cluster within a first level of the hierarchy of clusters comprising at least one content file, each cluster within a second level of the hierarchy of clusters comprising at least one cluster of the first level of the hierarchy of clusters; an aggregator configured to aggregate the content files of each cluster, and transmit the aggregated content file to said cluster controller to form a third level of the hierarchy of clusters; a label manager configured to cause the one or more processors to determine a label for each cluster within the hierarchy of clusters based on the at least one statistical measure, the label identifying a topic of information contained within each cluster, the topic related to at least one of a problem experienced by a user and a request for assistance in solving the problem; and a taxonomy manager configured to cause the one or more processors to output a taxonomy based on the hierarchy of clusters and the determined labels. 2. The computer system of claim 1 , wherein said cluster controller further comprises at least one cluster algorithm module, said at least one cluster algorithm module configured to assign the at least one content file to each cluster within the first level of the hierarchy of clusters.
| 0.501397 |
17. A method for accepting text input on an electronic device, comprising: displaying a preliminary input area on a display, the preliminary input area comprising first, second, and third regions; displaying a text box on the display; receiving character entries via a keyboard; displaying the character entries in the first region and the text box; generating candidate predictions for a first text unit based on the character entries; ranking the candidate predictions for the first text unit, based on a first plurality of criteria; displaying, in the first region, one of the candidate predictions of the first text unit as an initial prediction of the first text unit, based on the rankings of the candidate predictions for the first text unit; generating first predictions for the second text unit based on the candidate predictions for the first text unit, wherein first predictions for the second text unit are generated by a predictive algorithm that predicts subsequent text units based on preceding text units; ranking the first predictions for the second text unit based on a second plurality of criteria; displaying, in the second region, one of the first predictions of the second text unit, based on the rankings of the first predictions for the second text unit; receiving user input to accept the initial prediction of the first text unit displayed in the first region; displaying the accepted initial prediction in the third region; displaying, in the first region, the prediction displayed in the second region, as the current prediction of the first text unit; generating second predictions for the second text unit based on the current prediction of the first text unit; ranking the second predictions for the second text unit based on a third plurality of criteria; displaying, in the second region, one of the second predictions of the second text unit, based on the rankings of the second predictions for the second text unit; and displaying the accepted initial prediction in the text box.
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17. A method for accepting text input on an electronic device, comprising: displaying a preliminary input area on a display, the preliminary input area comprising first, second, and third regions; displaying a text box on the display; receiving character entries via a keyboard; displaying the character entries in the first region and the text box; generating candidate predictions for a first text unit based on the character entries; ranking the candidate predictions for the first text unit, based on a first plurality of criteria; displaying, in the first region, one of the candidate predictions of the first text unit as an initial prediction of the first text unit, based on the rankings of the candidate predictions for the first text unit; generating first predictions for the second text unit based on the candidate predictions for the first text unit, wherein first predictions for the second text unit are generated by a predictive algorithm that predicts subsequent text units based on preceding text units; ranking the first predictions for the second text unit based on a second plurality of criteria; displaying, in the second region, one of the first predictions of the second text unit, based on the rankings of the first predictions for the second text unit; receiving user input to accept the initial prediction of the first text unit displayed in the first region; displaying the accepted initial prediction in the third region; displaying, in the first region, the prediction displayed in the second region, as the current prediction of the first text unit; generating second predictions for the second text unit based on the current prediction of the first text unit; ranking the second predictions for the second text unit based on a third plurality of criteria; displaying, in the second region, one of the second predictions of the second text unit, based on the rankings of the second predictions for the second text unit; and displaying the accepted initial prediction in the text box. 18. The method of claim 17 , wherein the candidate predictions for the first text unit are based on the character entries and candidate predictions that have been previously accepted.
| 0.518536 |
13. A method for preparing large amounts of data for analytical processing, comprising: receiving a query; utilizing a processor to determine multiple tasks based on the query; providing the multiple tasks to a plurality of cluster nodes through usage of one-way messaging, wherein the plurality of cluster nodes comprises a hierarchical arrangement of multiple cluster nodes that are subservient to one or more parent cluster nodes, and further wherein the multiple tasks that are provided to the plurality of cluster nodes are assigned based on the association of the data content accessible by each of the plurality of cluster nodes with the data content required by the one or more tasks; partitioning the tasks into a plurality of sub-tasks at one or more of the plurality of cluster nodes; selecting one or more sub-tasks at the one or more of the plurality of cluster nodes; providing the selected subtasks to multiple cluster nodes that are subservient to the cluster node that is providing the selected subtasks; monitoring the progress of a first task at a first cluster node of the multiple cluster nodes, wherein the monitoring includes determining whether the first task is completed within a first threshold of time, and reassigning the first task from the first cluster node of the multiple cluster nodes to a second cluster node of the multiple cluster nodes if the first task is not completed within the first threshold of time; aggregating results provided from the plurality of cluster nodes with respect to the multiple tasks; and providing the aggregated results to an object linking and embedding database (OLE DB) client.
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13. A method for preparing large amounts of data for analytical processing, comprising: receiving a query; utilizing a processor to determine multiple tasks based on the query; providing the multiple tasks to a plurality of cluster nodes through usage of one-way messaging, wherein the plurality of cluster nodes comprises a hierarchical arrangement of multiple cluster nodes that are subservient to one or more parent cluster nodes, and further wherein the multiple tasks that are provided to the plurality of cluster nodes are assigned based on the association of the data content accessible by each of the plurality of cluster nodes with the data content required by the one or more tasks; partitioning the tasks into a plurality of sub-tasks at one or more of the plurality of cluster nodes; selecting one or more sub-tasks at the one or more of the plurality of cluster nodes; providing the selected subtasks to multiple cluster nodes that are subservient to the cluster node that is providing the selected subtasks; monitoring the progress of a first task at a first cluster node of the multiple cluster nodes, wherein the monitoring includes determining whether the first task is completed within a first threshold of time, and reassigning the first task from the first cluster node of the multiple cluster nodes to a second cluster node of the multiple cluster nodes if the first task is not completed within the first threshold of time; aggregating results provided from the plurality of cluster nodes with respect to the multiple tasks; and providing the aggregated results to an object linking and embedding database (OLE DB) client. 16. The method of claim 13 , further comprising: receiving an identity of a user; and generating the query based at least in part upon the received identity.
| 0.637993 |
7. The targeting system of claim 6 , wherein the targeting server assigns a feature vector to each of the identified keywords and to estimate the performance of the feature vector in targeting the specific offer to the desired audience.
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7. The targeting system of claim 6 , wherein the targeting server assigns a feature vector to each of the identified keywords and to estimate the performance of the feature vector in targeting the specific offer to the desired audience. 9. The targeting system of claim 7 , wherein the feature vector of a keyword includes at least one value indicative a relationship between the keyword and at least one cluster of member profiles.
| 0.934833 |
1. A speech recognition apparatus comprising: a generating unit configured to generate sequences of speech features from characteristics of entered speech for respective frames having an arbitrary temporal width; a model storage unit having a plurality of phrases expressed on basis of grammar and one or more continuous phrase segments obtained by dividing the respective phrase, the model storage unit configured to store state transition models which express time series changes of the speech features for respective phrase segments as state-to-state transition relating to the speech features; a first grammar storage unit configured to store grammar segments relating to one or more continuous phrase segments which belong to each of the phrases; a second grammar storage unit configured to store at least part of the grammar segments transferred from the first grammar storage unit and to be able to read out information stored therein in a reading time shorter than that required for the first grammar storage unit; a first decoder configured to obtain forward probabilities of respective states of the state transition models for the sequence of speech features generated by the generating unit with respect to each of the frames, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a grammar transfer unit configured to transfer a trailing grammar segment relating to a trailing phrase segment which trails one of said continuous phrase segments, from the first grammar storage unit to the second grammar storage unit when the forward probability of final state among said states of the state transition models is obtained by the first decoder; a second decoder configured to obtain the forward probabilities of the respective states of the state transition models for a sequence of trailing speech features as the sequence of speech features for the trailing segment as generated by the generating unit with respect to each of the frames, continuously after the speech feature sequences, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a third decoder configured to obtain the forward probabilities of the respective states of the state transition models for the trailing speech feature sequences for the respective frames, by referring to the trailing grammar segment transferred to the second grammar storage unit and the state transition models stored in the model storage unit; a recognition control unit configured to (1) carry out recognition for the respective phrases, (2) activate the first decoder until the transfer of the trailing grammar segment is started, (3) activate the second decoder in parallel to the transfer from the start to the completion of the transfer, (4) activate the third decoder upon completion of the transfer, and (5) repeat the operations from (2) to (4) until all the operations for the phrase segments belonging to the respective phrases to obtain final forward probabilities for the respective phrases; and a recognizing unit configured to output the phrase which give the highest forward probability from among the respective final forward probabilities of the plurality of phrases as a result of recognition of the speech feature sequence.
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1. A speech recognition apparatus comprising: a generating unit configured to generate sequences of speech features from characteristics of entered speech for respective frames having an arbitrary temporal width; a model storage unit having a plurality of phrases expressed on basis of grammar and one or more continuous phrase segments obtained by dividing the respective phrase, the model storage unit configured to store state transition models which express time series changes of the speech features for respective phrase segments as state-to-state transition relating to the speech features; a first grammar storage unit configured to store grammar segments relating to one or more continuous phrase segments which belong to each of the phrases; a second grammar storage unit configured to store at least part of the grammar segments transferred from the first grammar storage unit and to be able to read out information stored therein in a reading time shorter than that required for the first grammar storage unit; a first decoder configured to obtain forward probabilities of respective states of the state transition models for the sequence of speech features generated by the generating unit with respect to each of the frames, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a grammar transfer unit configured to transfer a trailing grammar segment relating to a trailing phrase segment which trails one of said continuous phrase segments, from the first grammar storage unit to the second grammar storage unit when the forward probability of final state among said states of the state transition models is obtained by the first decoder; a second decoder configured to obtain the forward probabilities of the respective states of the state transition models for a sequence of trailing speech features as the sequence of speech features for the trailing segment as generated by the generating unit with respect to each of the frames, continuously after the speech feature sequences, by referring to the grammar segments stored in the second grammar storage unit and the state transition models stored in the model storage unit; a third decoder configured to obtain the forward probabilities of the respective states of the state transition models for the trailing speech feature sequences for the respective frames, by referring to the trailing grammar segment transferred to the second grammar storage unit and the state transition models stored in the model storage unit; a recognition control unit configured to (1) carry out recognition for the respective phrases, (2) activate the first decoder until the transfer of the trailing grammar segment is started, (3) activate the second decoder in parallel to the transfer from the start to the completion of the transfer, (4) activate the third decoder upon completion of the transfer, and (5) repeat the operations from (2) to (4) until all the operations for the phrase segments belonging to the respective phrases to obtain final forward probabilities for the respective phrases; and a recognizing unit configured to output the phrase which give the highest forward probability from among the respective final forward probabilities of the plurality of phrases as a result of recognition of the speech feature sequence. 4. The apparatus according to claim 1 , wherein the grammar transfer unit stops the transfer of the trailing grammar segments when the transfer is not completed even when a predetermined time is elapsed.
| 0.617274 |
1. A method of training an information extraction system to extract information from a natural language input, comprising: initializing a structured language model with syntactically annotated training data, the annotated training data including a parse tree for a sentence having syntactic labels comprising a frame label indicating an overall action being referred to by the sentence and slot labels identifying attributes of the action; training the structured language model by generating parses with the initialized structured language model using annotated training data that has semantic constituent labels with semantic constituent boundaries identified, wherein the structured language model is trained as a match constrained parser which generates a set of syntactic parses for a given word string that all match the constituent boundaries specified by the semantic parse, by determining whether unlabeled constituents that define the semantic parse are included in a set of constituents that define the syntactic parse, wherein any parses that do not match the constituent boundaries are discarded; replacing the syntactic labels in the parse tree with joint syntactic and semantic labels based on the generated parses excluding the discarded parses; and retraining the structured language model in which the structured language model generates parses that are constrained to identically match the semantic constituent labels of the joint syntactic and semantic labels and constrained to match all of the semantic constituent boundaries.
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1. A method of training an information extraction system to extract information from a natural language input, comprising: initializing a structured language model with syntactically annotated training data, the annotated training data including a parse tree for a sentence having syntactic labels comprising a frame label indicating an overall action being referred to by the sentence and slot labels identifying attributes of the action; training the structured language model by generating parses with the initialized structured language model using annotated training data that has semantic constituent labels with semantic constituent boundaries identified, wherein the structured language model is trained as a match constrained parser which generates a set of syntactic parses for a given word string that all match the constituent boundaries specified by the semantic parse, by determining whether unlabeled constituents that define the semantic parse are included in a set of constituents that define the syntactic parse, wherein any parses that do not match the constituent boundaries are discarded; replacing the syntactic labels in the parse tree with joint syntactic and semantic labels based on the generated parses excluding the discarded parses; and retraining the structured language model in which the structured language model generates parses that are constrained to identically match the semantic constituent labels of the joint syntactic and semantic labels and constrained to match all of the semantic constituent boundaries. 5. The method of claim 1 wherein generating parses comprises: generating syntactic parses with syntactic labels, wherein the syntactic parses are constrained to match the semantic constituent boundaries; and generating semantic parses with semantic labels, wherein the semantic parses are constrained to match the semantic constituent labels in the annotated training data.
| 0.565783 |
7. A system according to claim 6 wherein said pen enabled computing device and said computer program product cooperate for receiving an indication from a user of the handwritten input to be edited and also for receiving textual input from a keyboard to form the data with which the handwritten input is edited.
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7. A system according to claim 6 wherein said pen enabled computing device and said computer program product cooperate for receiving an indication from a user of the handwritten input to be edited and also for receiving textual input from a keyboard to form the data with which the handwritten input is edited. 8. A system according to claim 7 wherein said computer program product edits the handwritten input by altering the coordinate representation of at least some strokes of the handwritten input in order to alter spacing of at least one stroke encompassed by a bounding box so as to at least one of insert the textual input between strokes encompassed by adjacent bounding boxes and replace a stroke encompassed by a bounding box containing handwritten input with the textual input.
| 0.738051 |
6. The method of claim 1 , wherein the transformation program includes a transformation template that defines symmetric programming constructs responsible for transforming the requested XML data structure into the application programming language data structure.
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6. The method of claim 1 , wherein the transformation program includes a transformation template that defines symmetric programming constructs responsible for transforming the requested XML data structure into the application programming language data structure. 8. The method of claim 6 , wherein the transformation template includes tt namespace elements, literal XML elements, attributes and text.
| 0.929858 |
1. A computer-implemented method of processing incoming documents received by a financial institution, the method comprising: scanning a first set of documents into electronic form; receiving, by a computer system, a plurality of documents in electronic form, wherein the plurality of documents comprises the first set of documents and a second set of documents received by the financial institution in electronic form, and wherein the computer system comprises at least one processor and operatively associated memory; classifying, by the computer system, each of the plurality of documents into at least one of a plurality of document classifications; extracting, by the computer system, metadata from the plurality of documents; executing, by the computer system, a first workflow for processing documents classified in a first document classification selected from the plurality of document classifications, wherein the first document classification describes incoming client correspondence documents received by the financial institution from clients of the financial institution, and where executing the first workflow comprises, for each document classified in the first document classification: determining whether the document comprises an indication of a customer complaint; and conditioned on whether the document comprises an indication of a customer complaint, forwarding the document to personnel for processing the complaint; and executing, by the computer system, a second workflow for processing documents classified in a second document classification selected from the plurality of document classifications, wherein the second document classification includes returned mail documents, and wherein executing the workflow comprises, for each document classified in the second document classification: correlating the document with a client account; conditioned upon a date of the document being before a most recent address change associated with the client account indicating that the document should be resent to the current address associated with the client account; conditioned upon the document having been returned more than once, storing an indication that the client account associated with the document is undeliverable; conditioned upon the document not having been returned more than once, storing an indication that the client account associated with the document is potentially undeliverable.
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1. A computer-implemented method of processing incoming documents received by a financial institution, the method comprising: scanning a first set of documents into electronic form; receiving, by a computer system, a plurality of documents in electronic form, wherein the plurality of documents comprises the first set of documents and a second set of documents received by the financial institution in electronic form, and wherein the computer system comprises at least one processor and operatively associated memory; classifying, by the computer system, each of the plurality of documents into at least one of a plurality of document classifications; extracting, by the computer system, metadata from the plurality of documents; executing, by the computer system, a first workflow for processing documents classified in a first document classification selected from the plurality of document classifications, wherein the first document classification describes incoming client correspondence documents received by the financial institution from clients of the financial institution, and where executing the first workflow comprises, for each document classified in the first document classification: determining whether the document comprises an indication of a customer complaint; and conditioned on whether the document comprises an indication of a customer complaint, forwarding the document to personnel for processing the complaint; and executing, by the computer system, a second workflow for processing documents classified in a second document classification selected from the plurality of document classifications, wherein the second document classification includes returned mail documents, and wherein executing the workflow comprises, for each document classified in the second document classification: correlating the document with a client account; conditioned upon a date of the document being before a most recent address change associated with the client account indicating that the document should be resent to the current address associated with the client account; conditioned upon the document having been returned more than once, storing an indication that the client account associated with the document is undeliverable; conditioned upon the document not having been returned more than once, storing an indication that the client account associated with the document is potentially undeliverable. 9. The method of claim 1 , further comprising: displaying at least one unclassified document to an operator; receiving from the operator an indication of at least one of the plurality of document classifications that corresponds to the document.
| 0.573136 |
10. Implemented within a computer system having a processor and a memory coupled to the processor, a system for compressing an extensible markup language (XML) document, said system comprising program/code modules executing on the processor and providing the functionality of: at least one input for inputting an extensible markup language Schema (XSD) and an XML document; a rules engine for prioritizing components of said XSD; a statistical tree generator for generating a statistical tree based on said prioritized components of said XSD; a parser for parsing said XML document; a structural compressor for encoding the structural content of said XML document based on said parsed document and said statistical tree; and an output for outputting at said compressed XML document, wherein said compressed XML document comprises said encoded structural content and data from said XML document.
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10. Implemented within a computer system having a processor and a memory coupled to the processor, a system for compressing an extensible markup language (XML) document, said system comprising program/code modules executing on the processor and providing the functionality of: at least one input for inputting an extensible markup language Schema (XSD) and an XML document; a rules engine for prioritizing components of said XSD; a statistical tree generator for generating a statistical tree based on said prioritized components of said XSD; a parser for parsing said XML document; a structural compressor for encoding the structural content of said XML document based on said parsed document and said statistical tree; and an output for outputting at said compressed XML document, wherein said compressed XML document comprises said encoded structural content and data from said XML document. 11. The system according to claim 10 , wherein said encoded XML document structure is a binary encoded sequence.
| 0.612355 |
1. In a computing environment, a method implemented by computing system having a processor, the method comprising: receiving a canonical enveloped message from a computer implemented application, wherein the canonical enveloped message comprises payload data and is associated with a context store that stores context information of the canonical enveloped message in a form that is independent of one or more protocols employed by the canonical enveloped message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message including using two or more of the protocol components to process the canonical enveloped message, and by at least adding, removing or modifying context entries in the context store, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; converting the canonical enveloped message to a raw message that does not include the context store; and sending at least a portion of the raw message on a computer implemented communication medium.
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1. In a computing environment, a method implemented by computing system having a processor, the method comprising: receiving a canonical enveloped message from a computer implemented application, wherein the canonical enveloped message comprises payload data and is associated with a context store that stores context information of the canonical enveloped message in a form that is independent of one or more protocols employed by the canonical enveloped message; at a protocol pipeline comprising a plurality of protocol components processing the canonical enveloped message including using two or more of the protocol components to process the canonical enveloped message, and by at least adding, removing or modifying context entries in the context store, wherein each portion of the context information is stored in the context store as a context entry that comprises at least a name element to identify the portion, a value element representing the value of the identified portion, and optionally a metadata element that defines any additional information about the identified portion, such that context information for a plurality of protocol components is aggregated using a common format in the context store; converting the canonical enveloped message to a raw message that does not include the context store; and sending at least a portion of the raw message on a computer implemented communication medium. 10. The method of claim 1 , wherein processing the canonical enveloped message comprises adding or modifying a metadata element of a context entry such that the metadata element of the context entry comprises information about the given protocol component that added or modified the context entry.
| 0.5 |
20. The computer-readable storage medium of claim 1 , the data structure further comprising a fourth table comprised of entries each representing a correspondence between two terms, each entry of the fourth table containing a first term ID identifying a child term, a second term ID identifying a parent term, and an indication of a relationship type that exists between the identified child term and the identified parent term.
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20. The computer-readable storage medium of claim 1 , the data structure further comprising a fourth table comprised of entries each representing a correspondence between two terms, each entry of the fourth table containing a first term ID identifying a child term, a second term ID identifying a parent term, and an indication of a relationship type that exists between the identified child term and the identified parent term. 24. The computer-readable storage medium of claim 20 wherein a distinguished entry of the fourth table contains an indication that the identified child term is enforced by the identified parent term.
| 0.863528 |
16. A system comprising: one or more memory devices; and a processor communicatively coupled to the one or more memory devices, the processor operable to: determine a plurality of entities that are displayed in media content being viewed by a user, the plurality of entities comprising at least a first entity and a second entity; access information indicative of the plurality of entities; query a social graph of the social-networking system for first social content associated with the first entity, the social graph comprising: user nodes that are each associated with a particular user of the social-networking system; query the social graph of the social-networking system for second social content associated with the second entity; and provide at least a portion of the queried social content from the social graph for display along with the information on a display device of the user.
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16. A system comprising: one or more memory devices; and a processor communicatively coupled to the one or more memory devices, the processor operable to: determine a plurality of entities that are displayed in media content being viewed by a user, the plurality of entities comprising at least a first entity and a second entity; access information indicative of the plurality of entities; query a social graph of the social-networking system for first social content associated with the first entity, the social graph comprising: user nodes that are each associated with a particular user of the social-networking system; query the social graph of the social-networking system for second social content associated with the second entity; and provide at least a portion of the queried social content from the social graph for display along with the information on a display device of the user. 20. The system of claim 16 , wherein the information and the portion of the queried first and second social content are provided for display by overlaying the information and the portion of the queried first and second social content on top of the media content being viewed by the user.
| 0.729323 |
6. An automatic speech translation method, comprising: extracting speech features used for speech recognition from an input speech signal in an input language; selecting, by a speech recognizer, an input sentence template that is most closely corresponding to the input speech signal in a set of sentence templates and a word class of the input sentence template from a set of word classes, the input sentence template being composed of the sentence elements having corresponding sentence elements in a second language; forming an input language table including the input sentence template, the word class, and tags showing whether each of the sentence elements of the input sentence template is identified in the extracted speech features; generating a translated language table corresponding to the input language table, wherein the translated language table includes a translated sentence template corresponding to the input sentence template and a translated word corresponding to a word in the word class, and the translated sentence template is composed of the corresponding sentence elements in the second language selecting prosody data corresponding to the translated sentence template; and synthesizing a speech signal based on the prosody data.
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6. An automatic speech translation method, comprising: extracting speech features used for speech recognition from an input speech signal in an input language; selecting, by a speech recognizer, an input sentence template that is most closely corresponding to the input speech signal in a set of sentence templates and a word class of the input sentence template from a set of word classes, the input sentence template being composed of the sentence elements having corresponding sentence elements in a second language; forming an input language table including the input sentence template, the word class, and tags showing whether each of the sentence elements of the input sentence template is identified in the extracted speech features; generating a translated language table corresponding to the input language table, wherein the translated language table includes a translated sentence template corresponding to the input sentence template and a translated word corresponding to a word in the word class, and the translated sentence template is composed of the corresponding sentence elements in the second language selecting prosody data corresponding to the translated sentence template; and synthesizing a speech signal based on the prosody data. 7. The method according to claim 6 , wherein the prosody data includes spacing between words in the translated sentence template or stress applied to each word in the translated sentence template.
| 0.701972 |
1. A method for template based web site development and management comprising: obtaining input of an entity identifier uniquely associated with an entity operating a website, the entity identifier selected by one other than the entity and designating an entity database record within a database maintained by one other than the entity; obtaining entity data including data pertaining to the entity operating the website from the entity database record within the database using the entity identifier; accessing a template for a web page, the template including a content container and a style element; generating the web page for the entity using the template by dynamically inserting the entity data into the content container, the entity data inserted as the web page loads and rendered according to the style element for the web page; enabling revision of the web page by customizing the style element separately from the entity data to thereby create a customized style element; receiving a request to update the web page to include updated entity data from an updated entity database record within the database; obtaining the updated entity data including new data pertaining to the entity from the updated entity database record within the database using the entity identifier; and regenerating the web page using the template and the customized style element by dynamically inserting the updated entity data into the content container as the web page loads and, the web page rendered so as to include the updated entity data rendered according to the customized style element.
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1. A method for template based web site development and management comprising: obtaining input of an entity identifier uniquely associated with an entity operating a website, the entity identifier selected by one other than the entity and designating an entity database record within a database maintained by one other than the entity; obtaining entity data including data pertaining to the entity operating the website from the entity database record within the database using the entity identifier; accessing a template for a web page, the template including a content container and a style element; generating the web page for the entity using the template by dynamically inserting the entity data into the content container, the entity data inserted as the web page loads and rendered according to the style element for the web page; enabling revision of the web page by customizing the style element separately from the entity data to thereby create a customized style element; receiving a request to update the web page to include updated entity data from an updated entity database record within the database; obtaining the updated entity data including new data pertaining to the entity from the updated entity database record within the database using the entity identifier; and regenerating the web page using the template and the customized style element by dynamically inserting the updated entity data into the content container as the web page loads and, the web page rendered so as to include the updated entity data rendered according to the customized style element. 5. The method of claim 1 wherein the template further includes a second content container, the method further comprising: enabling user input of a meta data; incorporating the meta data into the web page by inserting the meta data into the second content container; accepting an updated meta data for inclusion in the web page; and wherein regenerating the web page using the template further includes inserting the updated meta data into the second content container, the second content container presented as directed by the customized style element.
| 0.5 |
69. The computer program product of claim 15 , and further comprising: code for receiving a request; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including a list of potential tags from which a selection is capable of being made; code for, utilizing the interface, receiving the indication of one or more tags utilizing the list; and code for utilizing the one or more tags for correlation purposes.
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69. The computer program product of claim 15 , and further comprising: code for receiving a request; code for, in response to the request, displaying an interface for receiving an indication of one or more tags, the interface including a list of potential tags from which a selection is capable of being made; code for, utilizing the interface, receiving the indication of one or more tags utilizing the list; and code for utilizing the one or more tags for correlation purposes. 70. The computer program product of claim 69 , wherein the list of potential tags includes previously existing tags.
| 0.955456 |
3. The method of claim 1 , wherein scoring sentiments expressed by one or more domain-specific documents is based on a domain-independent sentiment lexicon, the domain-independent sentiment lexicon specifies a magnitude and polarity of sentiment expressed by each of a plurality of n-grams, and wherein scoring sentiment expressed by one or more of the domain-specific documents based on a domain-independent sentiment lexicon comprises: determining whether the n-gram included in the one or more documents is in the domain-independent sentiment lexicon.
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3. The method of claim 1 , wherein scoring sentiments expressed by one or more domain-specific documents is based on a domain-independent sentiment lexicon, the domain-independent sentiment lexicon specifies a magnitude and polarity of sentiment expressed by each of a plurality of n-grams, and wherein scoring sentiment expressed by one or more of the domain-specific documents based on a domain-independent sentiment lexicon comprises: determining whether the n-gram included in the one or more documents is in the domain-independent sentiment lexicon. 4. The method of claim 3 , wherein the score calculated for the n-gram included in the one or more documents is calculated based on one or more factors/techniques from the set consisting of: a score for the n-gram specified in the domain-independent sentiment lexicon; part-of-speech tagging based on a part-of-speech represented by the n-gram within the documents; detecting whether the n-gram is used in a negative manner within the documents; a location of the n-gram in the documents; and stemming to identify a root of an n-gram in the documents.
| 0.693368 |
11. A system for establishing a bridge between two documents, comprising a server, configured to store the two documents; a receiver, coupled to the server, for receiving a first document represented by a hierarchical data structure model having a plurality of first nodes; a first processor, coupled to the server, for generating a second document represented by a flat data structure model having a plurality of flat data structure elements, the second document being an online collaboratively editable document, and for establishing the bridge between the first document and the second document, wherein establishing the bridge includes: linking each of the plurality of first nodes to the plurality of flat data structure elements via a linkage, such that at least a portion of contents of the plurality of first nodes is copied to the plurality of flat data structure elements; and maintaining the bridge, such that an edit to the first document, represented in at least one of the first nodes, is applied to at least one corresponding flat data structure element, thereby applying the edit to the second document.
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11. A system for establishing a bridge between two documents, comprising a server, configured to store the two documents; a receiver, coupled to the server, for receiving a first document represented by a hierarchical data structure model having a plurality of first nodes; a first processor, coupled to the server, for generating a second document represented by a flat data structure model having a plurality of flat data structure elements, the second document being an online collaboratively editable document, and for establishing the bridge between the first document and the second document, wherein establishing the bridge includes: linking each of the plurality of first nodes to the plurality of flat data structure elements via a linkage, such that at least a portion of contents of the plurality of first nodes is copied to the plurality of flat data structure elements; and maintaining the bridge, such that an edit to the first document, represented in at least one of the first nodes, is applied to at least one corresponding flat data structure element, thereby applying the edit to the second document. 16. The system of claim 11 , further comprising a transceiver, configured to transmit a first copy of the first document to a user device including a second processor, wherein the first copy is represented by an additional hierarchical data structure having a plurality of additional nodes, wherein the second processor is configured to generate a second copy represented by an additional flat data structure having a plurality of additional flat data structure elements, and a second bridge between the first copy and the second copy; and wherein the first processor is configured to establish a third bridge between the second copy and the second document, such that a first edit to the second document is applied to the second copy.
| 0.5 |
5. A computer-implemented method for rewriting outbound responses, comprising: receiving an initial web content query response to a web content query, the initial web content query response comprising a web page comprising a plurality of links and a content; allowing an administrator to define one or more rewriting rules for rewriting the received initial web content query response; storing defined rewriting rules in a rule data store to be accessed in response to received web content query responses; identifying defined rewriting rules of the rule data store and determining a union of matching filters defined within the rewriting rules; parsing the received initial web content query response and invoking a rule execution component for one or more patterns within the initial web content query response that match one or more matching filters of the defined rewriting rules to produce a rewritten web content query response, wherein upon encountering a pattern of an HTML tag within the initial web content query response, retrieving a rule list to determine if the HTML tag within the initial web content query response matches one or more rewriting rules, and storing a first modified output web content query response modified by a first rewriting rule to supply as input to a next rewriting rule in an iterated sequence of rewriting rules; executing one or more rewriting rules on a portion of the web content query response; and passing the rewritten web content query response back to a sender from which the initial web content query response was received.
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5. A computer-implemented method for rewriting outbound responses, comprising: receiving an initial web content query response to a web content query, the initial web content query response comprising a web page comprising a plurality of links and a content; allowing an administrator to define one or more rewriting rules for rewriting the received initial web content query response; storing defined rewriting rules in a rule data store to be accessed in response to received web content query responses; identifying defined rewriting rules of the rule data store and determining a union of matching filters defined within the rewriting rules; parsing the received initial web content query response and invoking a rule execution component for one or more patterns within the initial web content query response that match one or more matching filters of the defined rewriting rules to produce a rewritten web content query response, wherein upon encountering a pattern of an HTML tag within the initial web content query response, retrieving a rule list to determine if the HTML tag within the initial web content query response matches one or more rewriting rules, and storing a first modified output web content query response modified by a first rewriting rule to supply as input to a next rewriting rule in an iterated sequence of rewriting rules; executing one or more rewriting rules on a portion of the web content query response; and passing the rewritten web content query response back to a sender from which the initial web content query response was received. 7. The method of claim 5 , further comprising receiving response Hypertext Transfer Protocol (HTTP) headers and server variables associated with the response.
| 0.909762 |
9. A method for automatically internationalizing grammatical output for presentation to a user of a program based on the user's locale, the method comprising: modifying an Abstract Syntax Tree (AST) in response to compilation by a compiler of a predefined AST transformation; compiling a portion of source code, wherein the portion of source code is configured for generating grammatical output to the user of a program following compilation of the predefined AST transformation, wherein the portion of source code comprises a predefined token; referencing a modified node of the AST during compilation of the portion of source code in response to compiling the predefined token; generating a programming method in response to referencing the modified node of the AST during compilation of the portion of source code; incorporating the programming method into a file produced by the compiler, wherein the programming method is configured to call an instance of a message bundle file, and wherein the message bundle file is configured to define an entry key value in a natural language, wherein the natural language is based on a locale of the user.
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9. A method for automatically internationalizing grammatical output for presentation to a user of a program based on the user's locale, the method comprising: modifying an Abstract Syntax Tree (AST) in response to compilation by a compiler of a predefined AST transformation; compiling a portion of source code, wherein the portion of source code is configured for generating grammatical output to the user of a program following compilation of the predefined AST transformation, wherein the portion of source code comprises a predefined token; referencing a modified node of the AST during compilation of the portion of source code in response to compiling the predefined token; generating a programming method in response to referencing the modified node of the AST during compilation of the portion of source code; incorporating the programming method into a file produced by the compiler, wherein the programming method is configured to call an instance of a message bundle file, and wherein the message bundle file is configured to define an entry key value in a natural language, wherein the natural language is based on a locale of the user. 14. The method of claim 9 , wherein the entry key value is presented to the user as part of a user interface of a healthcare application.
| 0.876344 |
14. A non-transitory computer-readable medium storing instructions which, when executed by one or more machines, cause the one or more machines to perform operation comprising: receiving a query comprising one or more words; computing a vector for individual words of the one or more words; determining an initial hidden vector corresponding to a semantic representation of the query; sequentially mapping, using mapping software, the one or more words of the query based on the initial hidden vector; matching the semantic representation of the query, represented in the initial hidden vector, to a semantic representation corresponding to one or more responses; providing, in a user interface, the one or more responses based at least in part on the matching, the user interface indicating a semantic similarity between the query and the one or more responses; receiving click-through data associated with the one or more responses, the click-through data identifying a response from among the one or more responses as a positive match; and training the mapping software based at least in part on the click-through data.
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14. A non-transitory computer-readable medium storing instructions which, when executed by one or more machines, cause the one or more machines to perform operation comprising: receiving a query comprising one or more words; computing a vector for individual words of the one or more words; determining an initial hidden vector corresponding to a semantic representation of the query; sequentially mapping, using mapping software, the one or more words of the query based on the initial hidden vector; matching the semantic representation of the query, represented in the initial hidden vector, to a semantic representation corresponding to one or more responses; providing, in a user interface, the one or more responses based at least in part on the matching, the user interface indicating a semantic similarity between the query and the one or more responses; receiving click-through data associated with the one or more responses, the click-through data identifying a response from among the one or more responses as a positive match; and training the mapping software based at least in part on the click-through data. 17. The non-transitory computer-readable medium of claim 14 , the operations further comprising: prior to the matching, receiving a document of a plurality of responses, the document comprising one or more words; computing a vector for individual words of the one or more words of the document; determining an initial hidden vector for the document; sequentially mapping the one or more words of the document; and determining a semantic representation of the document.
| 0.595652 |
13. At a computer system, the computer system including a processor and system memory, a computer implemented method for data mining on a multidimensional data cube, comprising: accessing multidimensional data; accessing multidimensional expressions defining how to view the multidimensional data as a multidimensional data cube; accessing data mining extensions for performing data mining on data residing in the multidimensional cube; integrating the multidimensional expressions and the data mining extensions into input for data mining model creation; the processor creating a data mining model trained on the multidimensional data from the input; storing the data mining model; performing data predictions against data contained in the multidimensional data cube by data mining the multidimensional data cube in accordance with the data mining model, data mining including performing data mining operations on portions of data contained in the multidimensional data cube in accordance with a multidimensional query element.
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13. At a computer system, the computer system including a processor and system memory, a computer implemented method for data mining on a multidimensional data cube, comprising: accessing multidimensional data; accessing multidimensional expressions defining how to view the multidimensional data as a multidimensional data cube; accessing data mining extensions for performing data mining on data residing in the multidimensional cube; integrating the multidimensional expressions and the data mining extensions into input for data mining model creation; the processor creating a data mining model trained on the multidimensional data from the input; storing the data mining model; performing data predictions against data contained in the multidimensional data cube by data mining the multidimensional data cube in accordance with the data mining model, data mining including performing data mining operations on portions of data contained in the multidimensional data cube in accordance with a multidimensional query element. 16. The method of claim 13 , wherein the data mining extensions correspond to MICROSOFT Data Mining Extension (DMX) specification.
| 0.767224 |
1. A method comprising: inputting a key word; presenting a list of possible synonyms of the key word; soliciting user feedback on whether a possible synonym is a synonym candidate for the key word or not a synonym candidate for the key word; determining a match score of each of the possible synonyms, the match score incorporating the user feedback as input; retaining a number of the possible synonyms up to and including a target number and discarding a number of the possible synonyms in excess of the target number, the discarded synonyms generally having lower match scores than the retained synonyms; said soliciting of feedback comprising inputting one or more additional key words; said method further comprising generating an output synonym list subsequent to said inputting of one or more additional key words, the output synonym list including possible synonyms of one or more additional key words; the output synonym list being derived from comparing, between pairs of words, a context of each instance of each one of the one or more key words among a set of documents.
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1. A method comprising: inputting a key word; presenting a list of possible synonyms of the key word; soliciting user feedback on whether a possible synonym is a synonym candidate for the key word or not a synonym candidate for the key word; determining a match score of each of the possible synonyms, the match score incorporating the user feedback as input; retaining a number of the possible synonyms up to and including a target number and discarding a number of the possible synonyms in excess of the target number, the discarded synonyms generally having lower match scores than the retained synonyms; said soliciting of feedback comprising inputting one or more additional key words; said method further comprising generating an output synonym list subsequent to said inputting of one or more additional key words, the output synonym list including possible synonyms of one or more additional key words; the output synonym list being derived from comparing, between pairs of words, a context of each instance of each one of the one or more key words among a set of documents. 7. The method according to claim 1 , wherein the defined endpoint is established manually.
| 0.698497 |
1. A voice recognition system which recognizes keywords included in input voice, comprising: a first voice recognition processing means for generating a recognition hypothesis graph which indicates a structure of hypothesis that is derived according to a first grammar together with a score associated with respective connections of a recognition unit by executing a voice recognition process based on said first grammar to a voice feature amount of input voice; and a second voice recognition processing means for outputting a recognition result from total score of a hypothesis which is derived according to a second grammar after acquiring said structure and said score of said garbage section from said recognition hypothesis graph, and executing a voice recognition process according to said second grammar that is specified to accept a section other than keywords in input voice as a garbage section to a voice feature amount of input voice, wherein said second voice recognition processing means, to said hypothesis reached to said garbage section in said second grammar, selects no smaller than one voice section having a node which can connected with said hypothesis as a starting point in said recognition hypothesis graph, and connects said structure and said score of a selected voice section with said hypothesis as said structure and said score of said garbage section.
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1. A voice recognition system which recognizes keywords included in input voice, comprising: a first voice recognition processing means for generating a recognition hypothesis graph which indicates a structure of hypothesis that is derived according to a first grammar together with a score associated with respective connections of a recognition unit by executing a voice recognition process based on said first grammar to a voice feature amount of input voice; and a second voice recognition processing means for outputting a recognition result from total score of a hypothesis which is derived according to a second grammar after acquiring said structure and said score of said garbage section from said recognition hypothesis graph, and executing a voice recognition process according to said second grammar that is specified to accept a section other than keywords in input voice as a garbage section to a voice feature amount of input voice, wherein said second voice recognition processing means, to said hypothesis reached to said garbage section in said second grammar, selects no smaller than one voice section having a node which can connected with said hypothesis as a starting point in said recognition hypothesis graph, and connects said structure and said score of a selected voice section with said hypothesis as said structure and said score of said garbage section. 6. The voice recognition system according to claim 1 , wherein said second voice recognition processing means executes said voice recognition process in a reverse direction with time direction of input voice.
| 0.782092 |
9. The method of claim 1 , wherein said one or more declarative rules specify patterns of objects related by said rules.
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9. The method of claim 1 , wherein said one or more declarative rules specify patterns of objects related by said rules. 10. The method of claim 9 , further comprising using variable designations to specify said patterns of objects related by said rules.
| 0.958621 |
19. A computer implemented method for dynamic task selection (executive control) suitable for mapping external inputs and internal goals toward actions that solve problems or elicit external rewards, the method comprising an act of causing a processor to execute instructions encoded on a memory, such that upon execution, the processor perform operations of: receiving sensory inputs; transforming the sensory inputs into clusters of spatial patterns; transforming the clusters of spatial patterns into a spatial schema; encoding transitions between the spatial schema; clustering the spatial schema and encoded spatial schema transitions into a spatio-temporal schema; combining the spatial schema with the spatio-temporal schema to create a bimodal spatio-temporal schema; receiving a reward input and a punishment input, wherein the reward input and the punishment input reflect a current state of an external environment; computing an emotional state and a motivational state from the sensory inputs, the reward input, and the punishment input; combining the bimodal spatio-temporal schema with the reward input, the punishment input, the emotional state, and the motivational state to create an external/internal schema (EXIN schema), wherein the EXIN schema provides a compressed representation assessing emotions, motivations, and rewards; combining the EXIN schema with the bimodal spatio-temporal schema to create a multimodal spatio-temporal schema, wherein the multimodal spatio-temporal schema serves as an episodic memory that can be replayed by the computer implemented method; receiving structures representing a plurality of elements of a motor system; and combining the multimodal spatio-temporal schema with the motor system structures and the EXIN schema to create a motor schema.
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19. A computer implemented method for dynamic task selection (executive control) suitable for mapping external inputs and internal goals toward actions that solve problems or elicit external rewards, the method comprising an act of causing a processor to execute instructions encoded on a memory, such that upon execution, the processor perform operations of: receiving sensory inputs; transforming the sensory inputs into clusters of spatial patterns; transforming the clusters of spatial patterns into a spatial schema; encoding transitions between the spatial schema; clustering the spatial schema and encoded spatial schema transitions into a spatio-temporal schema; combining the spatial schema with the spatio-temporal schema to create a bimodal spatio-temporal schema; receiving a reward input and a punishment input, wherein the reward input and the punishment input reflect a current state of an external environment; computing an emotional state and a motivational state from the sensory inputs, the reward input, and the punishment input; combining the bimodal spatio-temporal schema with the reward input, the punishment input, the emotional state, and the motivational state to create an external/internal schema (EXIN schema), wherein the EXIN schema provides a compressed representation assessing emotions, motivations, and rewards; combining the EXIN schema with the bimodal spatio-temporal schema to create a multimodal spatio-temporal schema, wherein the multimodal spatio-temporal schema serves as an episodic memory that can be replayed by the computer implemented method; receiving structures representing a plurality of elements of a motor system; and combining the multimodal spatio-temporal schema with the motor system structures and the EXIN schema to create a motor schema. 33. A computer implemented method for dynamic task selection as set forth in claim 19 , wherein the reward input is further used as an enticing reset signal when the punishment input has a high value, whereby the enticing reset signal forces the computer implemented method to deselect the EXIN schemas and continue creating new EXIN schemas despite the high value of the punishment input.
| 0.72289 |
16. The method of claim 10 , further comprising, after storing the electronic text file with the inserted keyword hyperlink in the video database, automatically repeating retrieving the storage address, associating the storage address, inserting the keyword hyperlink, and storing the electronic text file with the inserted keyword hyperlink.
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16. The method of claim 10 , further comprising, after storing the electronic text file with the inserted keyword hyperlink in the video database, automatically repeating retrieving the storage address, associating the storage address, inserting the keyword hyperlink, and storing the electronic text file with the inserted keyword hyperlink. 17. The method of claim 16 , wherein automatically repeating retrieving the storage address, associating the storage address, inserting the keyword hyperlink, and storing the electronic text file with the inserted keyword hyperlink occurs on a recurring basis.
| 0.940028 |
1. A computer implemented method comprising: applying speech recognition by one or more computer systems to an audio recording to generate a text version of recognized portions of text; providing an audible output corresponding to the audio recording; displaying, on a user interface rendered on a display device, an expected portion of text that corresponds to the words in the audio recording, the displayed expected portion of text including at least a portion of the expected portion of text that is currently being provided on the audible output; providing visual indicia for the displayed text that corresponds to: the audio that is currently being provided on the audible output, if the recognized portion of text matches the corresponding expected portion of text; and otherwise one or more portions of text which does not match the recognized portion of text, if the recognized portion of text does not match the corresponding expected portion of text.
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1. A computer implemented method comprising: applying speech recognition by one or more computer systems to an audio recording to generate a text version of recognized portions of text; providing an audible output corresponding to the audio recording; displaying, on a user interface rendered on a display device, an expected portion of text that corresponds to the words in the audio recording, the displayed expected portion of text including at least a portion of the expected portion of text that is currently being provided on the audible output; providing visual indicia for the displayed text that corresponds to: the audio that is currently being provided on the audible output, if the recognized portion of text matches the corresponding expected portion of text; and otherwise one or more portions of text which does not match the recognized portion of text, if the recognized portion of text does not match the corresponding expected portion of text. 2. The computer implemented method of claim 1 wherein the visual indicia is highlighting applied on the portion of expected text that is computed to be currently being spoken on the audio output.
| 0.735836 |
1. A platform that facilitates software application development, maintenance, and support, the platform comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving, from a plurality of different computing devices located remotely from one another, structured data and unstructured data for a computer-executable application that is being developed; assigning version information to the structured data and the unstructured data upon receipt of the structured data and the unstructured data; causing the structured data and the unstructured data to be stored in a distributed fashion over a plurality of data repositories, the structured data comprises at least one of a bug report for the computer-executable application, a crash dump created during execution of the computer-executable application, or a binary of the computer-executable application, the unstructured data comprises an email that is assigned to the computer-executable application, wherein causing the structured data and the unstructured data to be stored comprises: formatting the structured data; and formatting the unstructured data, such that the structured data and the unstructured data, upon being formatted, are stored as canonical data having a common format; executing an analytical process over the canonical data to generate a first dataset, wherein executing the analytical process comprises accessing a plurality of defined libraries; and storing the first dataset in at least one data repository of the plurality of data repositories in a format that is accessible by a third party analysis program, the format being different from the common format.
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1. A platform that facilitates software application development, maintenance, and support, the platform comprising: at least one processor; and memory that stores instructions that, when executed by the at least one processor, cause the at least one processor to perform acts comprising: receiving, from a plurality of different computing devices located remotely from one another, structured data and unstructured data for a computer-executable application that is being developed; assigning version information to the structured data and the unstructured data upon receipt of the structured data and the unstructured data; causing the structured data and the unstructured data to be stored in a distributed fashion over a plurality of data repositories, the structured data comprises at least one of a bug report for the computer-executable application, a crash dump created during execution of the computer-executable application, or a binary of the computer-executable application, the unstructured data comprises an email that is assigned to the computer-executable application, wherein causing the structured data and the unstructured data to be stored comprises: formatting the structured data; and formatting the unstructured data, such that the structured data and the unstructured data, upon being formatted, are stored as canonical data having a common format; executing an analytical process over the canonical data to generate a first dataset, wherein executing the analytical process comprises accessing a plurality of defined libraries; and storing the first dataset in at least one data repository of the plurality of data repositories in a format that is accessible by a third party analysis program, the format being different from the common format. 11. The platform of claim 1 , wherein the plurality of data repositories are located in separate countries.
| 0.559914 |
1. A computer-implemented method comprising: a. receiving, by a template module of a computer, from a content database a corpus comprising a set of pre-segmented texts; b. creating, by the template module of the computer, a plurality of modified pre-segmented texts for the set of pre-segmented texts by: i. extracting, by the template module of the computer, a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and ii. applying, by the template module of the computer, at least one domain tag for each pre-segmented text within the set of pre-segmented texts; c. clustering, by the template module of the computer utilizing a k-means clustering technique, the plurality of modified pre-segmented texts into one or more conceptual units, the k-means clustering technique including: i. placing k points into the space represented by a set of modified pre-segmented texts that are being clustered, the k points representing initial group centroids; ii. assigning each of the set of modified pre-segmented texts to the group having the closest centroid; iii. when all of the set of modified pre-segmented texts have been assigned, recalculating the positions of the k centroids; and iv. repeating steps ii. and iii. until the centroids become stable; wherein each of the one or more conceptual units is represented as k clusters and is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively; d. determining a gold template; e. identifying a set of matching templates from the one or more templates within a given conceptual unit, the set of matching templates associated with the gold template; f. ranking the set of matching templates, a ranked set of matching templates being associated with the gold template; g. determining a set of model weights based on one or more ranked sets of matching templates and a set of ranking features; and h. storing the plurality of modified pre-segmented texts, the set of model weights, and the set of semantic terms in the content database.
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1. A computer-implemented method comprising: a. receiving, by a template module of a computer, from a content database a corpus comprising a set of pre-segmented texts; b. creating, by the template module of the computer, a plurality of modified pre-segmented texts for the set of pre-segmented texts by: i. extracting, by the template module of the computer, a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and ii. applying, by the template module of the computer, at least one domain tag for each pre-segmented text within the set of pre-segmented texts; c. clustering, by the template module of the computer utilizing a k-means clustering technique, the plurality of modified pre-segmented texts into one or more conceptual units, the k-means clustering technique including: i. placing k points into the space represented by a set of modified pre-segmented texts that are being clustered, the k points representing initial group centroids; ii. assigning each of the set of modified pre-segmented texts to the group having the closest centroid; iii. when all of the set of modified pre-segmented texts have been assigned, recalculating the positions of the k centroids; and iv. repeating steps ii. and iii. until the centroids become stable; wherein each of the one or more conceptual units is represented as k clusters and is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively; d. determining a gold template; e. identifying a set of matching templates from the one or more templates within a given conceptual unit, the set of matching templates associated with the gold template; f. ranking the set of matching templates, a ranked set of matching templates being associated with the gold template; g. determining a set of model weights based on one or more ranked sets of matching templates and a set of ranking features; and h. storing the plurality of modified pre-segmented texts, the set of model weights, and the set of semantic terms in the content database. 2. The method of claim 1 wherein the set of ranking features includes at least one of: a. a position of each pre-segmented text; b. a type and a number of a set of content; c. an n-gram calculation; d. a template length; and e. an overlap calculation between a current template and the gold template.
| 0.548113 |
23. The method of claim 21 , the popularity information comprising a relative popularity score.
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23. The method of claim 21 , the popularity information comprising a relative popularity score. 25. The method of claim 23 , the relative popularity score reflecting a difference in the number of search queries related to the particular thing received over a first period of time compared to a second period of time.
| 0.960266 |
1. A system comprising: a concept analysis engine including one or more processors, the concept analysis engine comprising: a taxonomy manager configured to obtain a set of one or more taxonomies wherein each of the taxonomies includes one root node and one or more hierarchically ordered paths, wherein each hierarchically ordered path includes the root node and a hierarchically ordered sequence of concept nodes; a concept set engine configured to receive a first set of first set concepts and a second set of second set concepts; a concept pair engine configured to determine a plurality of concept pairs, wherein each concept pair includes one of the first set concepts and one of the second set concepts; a hierarchical path engine configured to determine, for each one of the concept pairs, an associated length of a non-diverging intersection of a first sub-path of one of the hierarchically ordered paths from the root node of one of the taxonomies to a first concept node representing the first set concept and a second sub-path of one of the hierarchically ordered paths from the root node of the one of the taxonomies to a second concept node representing the second set concept, and an associated length of a first portion of the first sub-path from a last concept node included in the non-diverging intersection to the first concept node, and an associated length of a second portion of the second sub-path from the last concept node included in the no-diverging intersection to the second concept node; a concept similarity engine configured to determine pairwise similarity values associated with each of the concept pairs based on ratios based on associated lengths of non-diverging intersections determined by the hierarchical path engine and the associated lengths of the first and second portions, wherein a pairwise similarity value indicating a high similarity is determined for association with concept pairs associated with nonempty non-diverging intersections including the root node and hierarchically immediate successor nodes of the root node that are included in the first sub-path and the second sub-path; and a concept set similarity engine configured to determine a concept set similarity value based on a weighted sum of the pairwise similarity values associated with optimal selected ones of the concept pairs.
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1. A system comprising: a concept analysis engine including one or more processors, the concept analysis engine comprising: a taxonomy manager configured to obtain a set of one or more taxonomies wherein each of the taxonomies includes one root node and one or more hierarchically ordered paths, wherein each hierarchically ordered path includes the root node and a hierarchically ordered sequence of concept nodes; a concept set engine configured to receive a first set of first set concepts and a second set of second set concepts; a concept pair engine configured to determine a plurality of concept pairs, wherein each concept pair includes one of the first set concepts and one of the second set concepts; a hierarchical path engine configured to determine, for each one of the concept pairs, an associated length of a non-diverging intersection of a first sub-path of one of the hierarchically ordered paths from the root node of one of the taxonomies to a first concept node representing the first set concept and a second sub-path of one of the hierarchically ordered paths from the root node of the one of the taxonomies to a second concept node representing the second set concept, and an associated length of a first portion of the first sub-path from a last concept node included in the non-diverging intersection to the first concept node, and an associated length of a second portion of the second sub-path from the last concept node included in the no-diverging intersection to the second concept node; a concept similarity engine configured to determine pairwise similarity values associated with each of the concept pairs based on ratios based on associated lengths of non-diverging intersections determined by the hierarchical path engine and the associated lengths of the first and second portions, wherein a pairwise similarity value indicating a high similarity is determined for association with concept pairs associated with nonempty non-diverging intersections including the root node and hierarchically immediate successor nodes of the root node that are included in the first sub-path and the second sub-path; and a concept set similarity engine configured to determine a concept set similarity value based on a weighted sum of the pairwise similarity values associated with optimal selected ones of the concept pairs. 16. The system of claim 1 further comprising: a concept repository including: a taxonomy storage area configured to taxonomy information associated with the one or more taxonomies; a concept set storage area configured to store concept set information associated with the first set and the second set; and a similarity storage area configured to store the concept set similarity value and similarity information associated with the pairwise similarity values and the associated concept pairs, wherein: the taxonomy manager is configured to obtain the set of one or more taxonomies from the taxonomy storage area, the concept set engine is configured to store the first set and the second set in the concept set storage area, the concept similarity engine is configured to store the similarity information associated with the pairwise similarity values and the associated concept pairs in the similarity storage area, and the concept set similarity engine is configured to store the concept set similarity value in the similarity storage area.
| 0.5 |
1. A method comprising: receiving automatic speech recognition output from a media presentation; receiving a transcription of the media presentation; determining an anchor word time duration requirement; selecting, via a processor, a pair of anchor words in the media presentation based on the automatic speech recognition output and the transcription, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than the anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words.
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1. A method comprising: receiving automatic speech recognition output from a media presentation; receiving a transcription of the media presentation; determining an anchor word time duration requirement; selecting, via a processor, a pair of anchor words in the media presentation based on the automatic speech recognition output and the transcription, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than the anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words. 10. The method of claim 1 , wherein the media presentation is a stored recording of a live event.
| 0.703179 |
19. A method for locating a certificate for an electronic messaging system, wherein acts of the method are performed by a processor of a computing device, the acts comprising: searching for a certificate of a sender of an electronic message based on a canonical name associated with a sender address of the sender, wherein the sender address comprises at least a first user name and at least a first domain name and wherein the canonical name is the sender address with both the first domain name truncated to identify a second domain name and the first user name truncated to identify a second user name.
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19. A method for locating a certificate for an electronic messaging system, wherein acts of the method are performed by a processor of a computing device, the acts comprising: searching for a certificate of a sender of an electronic message based on a canonical name associated with a sender address of the sender, wherein the sender address comprises at least a first user name and at least a first domain name and wherein the canonical name is the sender address with both the first domain name truncated to identify a second domain name and the first user name truncated to identify a second user name. 20. The method according to claim 19 , wherein said canonical name comprises at least one of multiple canonical domain names and multiple canonical user names.
| 0.791503 |
13. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more processors cause: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping.
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13. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more processors cause: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping. 17. The one or more non-transitory computer-readable storage media of claim 13 , wherein the first device context is based on one or more devices other than the first device detectable by the first device.
| 0.607885 |
1. A computer-implemented method for managing a conversational system on a server, the method comprising: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; and reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party.
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1. A computer-implemented method for managing a conversational system on a server, the method comprising: presenting on a user system of a first party, each of at least one chatbot as part of at least one messaging window forming a chat window hosted by a third party, the chatbot adapted to act as a customer service agent for at least one of a good and a service; and a web page document hosted by a second party, the web page document including code to launch the chat window hosted by the third party, and the second party and the third party being independent business entities; displaying a message to the first party through the messaging window; and reviewing a response from the first party using a combination of keyword/response pair scripting and artificial intelligence; and wherein the keyword/response pair scripting, the messaging window and the artificial intelligence are all managed via a web-based management console hosted by the third party, the web-based management console includes components selectable by the second party for managing the messaging window of the chatbot, separate from a window of the web page document hosted by the second party for display on the user system of the first party, the components including at least one event to launch the messaging window of the chatbot in response to code scripting at the web page document hosted by the second party. 4. The method of claim 1 , wherein the web-based management console of the third party includes a management console for managing the messaging window of the chatbot, separate from the window of the web page document of the second party for display on the user system of the first party, the components selectable by the second party includes a keyword/response pair for use by the chatbot and one or more of the following: a greeting; a reading timer; a skin of the messaging window; a typing timer; a skin of the chatbot messaging window; and a title on a window for the messaging window.
| 0.543237 |
16. A non-transitory computer readable storage medium storing programmed computer code, which when executed by a computer system having at least one processor and a memory storing computer programs for execution by the processor, causes the computer system to perform operations comprising: receiving inputs from a user interface framework of an application that implements a user interface framework when at least one text string is to be displayed in a display element of the user interface framework, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface; executing, by the processor, a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework.
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16. A non-transitory computer readable storage medium storing programmed computer code, which when executed by a computer system having at least one processor and a memory storing computer programs for execution by the processor, causes the computer system to perform operations comprising: receiving inputs from a user interface framework of an application that implements a user interface framework when at least one text string is to be displayed in a display element of the user interface framework, the inputs comprising the text string, an amount of available space in the display element, and an identification of the language of the text string; receiving linguistic pre-analysis results from outside the user interface; executing, by the processor, a text reduction algorithm on the text string based upon the linguistic pre-analysis results, wherein executing the text reduction algorithm comprises calculating one or more of entropy, confusion, and style deviation of the short forms of the text string; identifying one or more short forms of the text string that fit within the available space of the display element based on executing the text reduction algorithm; and communicating the identified short forms of the text string to the application or framework for display in the display element of the user interface framework. 17. The computer readable storage medium of claim 16 wherein the operations further comprise: translating a text string to be rendered in the display element of the user interface into a different language; and executing the text reduction algorithm on the translated text string to identify one or more short forms of the translated text string that fit within the available space of the display element.
| 0.53625 |
1. A method for addressing non-functional concerns within an abstract model corresponding to a real-world system, comprising: constructing one or more annotations profiles, each annotations profile describing one or more annotations, each annotation corresponding to and representing one of the non-functional concerns; associating each of a plurality of modeling elements of the abstract model with an annotation corresponding to a non-functional concern of the modeling element; constructing one or more transformation templates, each transformation template transforming the abstract model, including the modeling elements thereof, to a specific implementation platform to which the transformation template corresponds; and, for each transformation template, executing the abstract model as has been transformed to the specific implementation platform to which the transformation template corresponds, such that the non-functional concerns represented by the annotations associated with the modeling elements of the abstract model are consumed.
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1. A method for addressing non-functional concerns within an abstract model corresponding to a real-world system, comprising: constructing one or more annotations profiles, each annotations profile describing one or more annotations, each annotation corresponding to and representing one of the non-functional concerns; associating each of a plurality of modeling elements of the abstract model with an annotation corresponding to a non-functional concern of the modeling element; constructing one or more transformation templates, each transformation template transforming the abstract model, including the modeling elements thereof, to a specific implementation platform to which the transformation template corresponds; and, for each transformation template, executing the abstract model as has been transformed to the specific implementation platform to which the transformation template corresponds, such that the non-functional concerns represented by the annotations associated with the modeling elements of the abstract model are consumed. 3. The method of claim 1 , wherein each non-functional concern is selected from the group of non-functional concerns essentially consisting of: an audit-related task; an integrity and non-communication repudiation-related task; a security policy validation-related task; and, a security authorization-related task.
| 0.624464 |
2. The computer system of claim 1 also configured to perform the steps of: comparing a family of specimen text documents; identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and generating one of the text templates containing at least the one identified paragraph of text.
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2. The computer system of claim 1 also configured to perform the steps of: comparing a family of specimen text documents; identifying one paragraph of text within one of the family of specimen text documents that most closely matches a paragraph of text in all of the other specimen text documents, as compared to all of the other paragraphs in the one specimen text document; and generating one of the text templates containing at least the one identified paragraph of text. 4. The computer system of claim 2 wherein the identifying the paragraph that most closely matches uses a longest common subsequence algorithm.
| 0.934283 |
13. The method of claim 1 , wherein the computer system comprises one or more servers and a virtual router that is independently operable of the one or more servers, wherein receiving the natural language utterance comprises receiving, at the virtual router, the natural language utterance from the first user device, and wherein receiving the non-voice input comprises receiving, at the virtual router, the non-voice user input from the second user device, the method further comprising: transmitting, by the virtual router, the natural language utterance and the non-voice user input to the one or more servers; and receiving, at the virtual router, the user request from the one or more servers, wherein selecting the user processing device comprises selecting, at the virtual router, from among a plurality of user processing devices, the user processing device to process the user request, the selection at the virtual router being based on the determination that content related to the user request resides at the user processing device, and wherein transmitting the user request comprises transmitting, by the virtual router, the user request to the selected user processing device to invoke the selected user processing device to process the user request.
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13. The method of claim 1 , wherein the computer system comprises one or more servers and a virtual router that is independently operable of the one or more servers, wherein receiving the natural language utterance comprises receiving, at the virtual router, the natural language utterance from the first user device, and wherein receiving the non-voice input comprises receiving, at the virtual router, the non-voice user input from the second user device, the method further comprising: transmitting, by the virtual router, the natural language utterance and the non-voice user input to the one or more servers; and receiving, at the virtual router, the user request from the one or more servers, wherein selecting the user processing device comprises selecting, at the virtual router, from among a plurality of user processing devices, the user processing device to process the user request, the selection at the virtual router being based on the determination that content related to the user request resides at the user processing device, and wherein transmitting the user request comprises transmitting, by the virtual router, the user request to the selected user processing device to invoke the selected user processing device to process the user request. 14. The method of claim 13 , further comprising: selecting, at the virtual router, from among the one or more servers and the plurality of user processing devices, the one or more servers to determine the one or more words and the context information, wherein the natural language utterance and the non-voice user input are transmitted to the one or more servers based on the selection of the one or more servers.
| 0.849282 |
6. The method of claim 1 wherein the first data field corresponds to a first document scanned using optical character recognition and the second data field corresponds to a second document scanned using optical character recognition.
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6. The method of claim 1 wherein the first data field corresponds to a first document scanned using optical character recognition and the second data field corresponds to a second document scanned using optical character recognition. 8. The method of claim 6 further comprising a third data field corresponding to a third document scanned using optical character recognition and wherein the relationship defined by the formula relates the first data field to a summation of the second data field with the third data field.
| 0.914173 |
1. A computer-implemented method of determining search results related to a search query, the method comprising: receiving a search query from a computer via a computer network; submitting the search query to a plurality of search engines; receiving, from the plurality of search engines, at least one ranked list of search results based on the search query, the at least one ranked list of search results including a first ranked list of search results received from a first search engine of the plurality of search engines, wherein the first ranked list is without actual relevance values supplied by the first search engine; providing an estimated relevance value for each search result in the first ranked list by: determining an estimated relevance value for a most relevant search result of the first ranked list; determining an estimated relevance value for a less relevant search result of the first ranked list; and determining other estimated relevance values for the search results in the first ranked list based on the estimated relevance value for the most relevant search result and the estimated relevance value for the less relevant search result; determining, for each of the plurality of search engines, a weighting value; determining a weighted relevance value for each search result based on the estimated relevance value when an actual relevance value was not received for the search result from one of the plurality of search engines, the actual relevance value of the search result when the actual relevance value was received for the search result, and the weighting value associated with the search engine that provided the search result; combining the search results into a single list; sorting the search results in the single list based on the weighted relevance values; and sending at least a portion of the single list to the computer via the computer network for display to a user.
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1. A computer-implemented method of determining search results related to a search query, the method comprising: receiving a search query from a computer via a computer network; submitting the search query to a plurality of search engines; receiving, from the plurality of search engines, at least one ranked list of search results based on the search query, the at least one ranked list of search results including a first ranked list of search results received from a first search engine of the plurality of search engines, wherein the first ranked list is without actual relevance values supplied by the first search engine; providing an estimated relevance value for each search result in the first ranked list by: determining an estimated relevance value for a most relevant search result of the first ranked list; determining an estimated relevance value for a less relevant search result of the first ranked list; and determining other estimated relevance values for the search results in the first ranked list based on the estimated relevance value for the most relevant search result and the estimated relevance value for the less relevant search result; determining, for each of the plurality of search engines, a weighting value; determining a weighted relevance value for each search result based on the estimated relevance value when an actual relevance value was not received for the search result from one of the plurality of search engines, the actual relevance value of the search result when the actual relevance value was received for the search result, and the weighting value associated with the search engine that provided the search result; combining the search results into a single list; sorting the search results in the single list based on the weighted relevance values; and sending at least a portion of the single list to the computer via the computer network for display to a user. 11. The method of claim 1 , wherein the weighted relevance value for a first search result with an actual relevance value is the product of the actual relevance value and the weighting value associated with the search engine that provided the search result.
| 0.621317 |
9. A hardware memory device having program instructions stored thereon that, upon execution by a processor of an Information Handling System (IHS), cause the IHS to: provide a portal to a user executing a browser on a client device, wherein the portal includes an interface to a cloud storage provider (CSP) and to a cloud document editing provider (CDEP); allow the user to access a document stored in the CSP and to edit the document using the CDEP via the browser, wherein the document includes a plaintext portion and a formatting portion, and wherein the editing occurs without transmitting the plaintext portion to the CDEP; allow the user to select the document using the browser; retrieve the document from the CSP; provide the document to the client device, wherein the browser is configured to render the document and to allow the user to edit the document via the portal tokenize the document; transmit the tokenized document to the CDEP; receive an edit from a user manipulating the document in the browser; transmit a tokenized version of the edit to the CDEP; and receive a modified, tokenized document from the CDEP.
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9. A hardware memory device having program instructions stored thereon that, upon execution by a processor of an Information Handling System (IHS), cause the IHS to: provide a portal to a user executing a browser on a client device, wherein the portal includes an interface to a cloud storage provider (CSP) and to a cloud document editing provider (CDEP); allow the user to access a document stored in the CSP and to edit the document using the CDEP via the browser, wherein the document includes a plaintext portion and a formatting portion, and wherein the editing occurs without transmitting the plaintext portion to the CDEP; allow the user to select the document using the browser; retrieve the document from the CSP; provide the document to the client device, wherein the browser is configured to render the document and to allow the user to edit the document via the portal tokenize the document; transmit the tokenized document to the CDEP; receive an edit from a user manipulating the document in the browser; transmit a tokenized version of the edit to the CDEP; and receive a modified, tokenized document from the CDEP. 10. The hardware memory device of claim 9 , wherein tokenizing the file includes tokenizing the plaintext portion but not the formatting portion.
| 0.560837 |
20. The system of claim 12 , wherein determining a second set of authoritative users based on the first set of authoritative users comprises applying one or more rules to the first set of authoritative users.
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20. The system of claim 12 , wherein determining a second set of authoritative users based on the first set of authoritative users comprises applying one or more rules to the first set of authoritative users. 21. The system of claim 20 , wherein each authoritative user of the first set of authoritative users is associated with a score to provide a plurality of scores, and a rule of the one or more rules comprises selecting a sub-set of authoritative users from the first set of authoritative users based on the plurality of scores, the second set of authoritative users being at least partially populated with the sub-set of authoritative users.
| 0.841019 |
18. The system of claim 13 , wherein the output device is configured to automatically position the graphical representation of the parent case and the graphical representation of the related cases in the graphical flow-chart format according to a set of rules.
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18. The system of claim 13 , wherein the output device is configured to automatically position the graphical representation of the parent case and the graphical representation of the related cases in the graphical flow-chart format according to a set of rules. 19. The system of claim 18 , wherein the set of rules includes the following rule: when the parent case has one or more related cases that are children to the parent case, and where the parent and child cases were decided in different courts, the graphical representation of the parent case is positioned below the graphical representations of the child cases.
| 0.856427 |
37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information.
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37. An optical disc player for reproducing text subtitle streams recorded on an optical disc, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. 41. The optical disc player of claim 37 , further comprising a font loading buffer configured to load font data before the presentation segment is parsed, wherein the text renderer uses the font data when rendering the text strings stored in the buffer.
| 0.779744 |
14. The device of claim 13 , in which the user interface is further structured to stop delivering the prompts in the vicinity language responsive to an indication to change languages.
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14. The device of claim 13 , in which the user interface is further structured to stop delivering the prompts in the vicinity language responsive to an indication to change languages. 16. The device of claim 14 , in which the indication to change languages is based on a determination that the user is speaking a language that is different from the vicinity language.
| 0.85177 |
27. The system of claim 25 , wherein the system further comprises: a data communication network coupled to the server device; and a data processing device programmed to transmit the search query over the data communication network to the server device.
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27. The system of claim 25 , wherein the system further comprises: a data communication network coupled to the server device; and a data processing device programmed to transmit the search query over the data communication network to the server device. 30. The system of claim 27 , wherein estimating the breadth of the search query comprises estimating the breadth based on a total number of documents in a result set that is responsive to the search query.
| 0.827811 |
1. A method, comprising: receiving, at a computing device, training samples for training a neural network to learn an acoustic speech model, wherein at least one training sample of the training samples represents at least one phone of captured speech; determining a curriculum function for acoustic speech modeling, wherein the curriculum function assigns a difficulty value for a designated training sample of the training samples based on a combination comprising a duration value for the designated training sample and a sound quality value for the designated training sample; for each training sample of the training samples, determining a corresponding difficulty value for the training sample using the curriculum function; ordering the training samples based on the corresponding difficulty values for the training samples; presenting the ordered training samples to the neural network using the computing device to train the neural network on at least a portion of the acoustic speech model; and recognizing a received speech sample using the trained neural network.
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1. A method, comprising: receiving, at a computing device, training samples for training a neural network to learn an acoustic speech model, wherein at least one training sample of the training samples represents at least one phone of captured speech; determining a curriculum function for acoustic speech modeling, wherein the curriculum function assigns a difficulty value for a designated training sample of the training samples based on a combination comprising a duration value for the designated training sample and a sound quality value for the designated training sample; for each training sample of the training samples, determining a corresponding difficulty value for the training sample using the curriculum function; ordering the training samples based on the corresponding difficulty values for the training samples; presenting the ordered training samples to the neural network using the computing device to train the neural network on at least a portion of the acoustic speech model; and recognizing a received speech sample using the trained neural network. 6. The method of claim 1 , wherein the combination further comprises a previously trained neural network probability value for the particular sample.
| 0.850895 |
6. A computer-implemented method comprising: obtaining, by one or more configured computing systems of a group discussion prediction service, information about a distributed group discussion that involves a plurality of users submitting a plurality of content items for the distributed group discussion, the obtained information including information about one or more predictions by the group discussion prediction service regarding future content items that will be submitted for the distributed group discussion; selecting, by the one or more configured computing systems, multiple factors to use in summarizing information about the distributed group discussion; determining, by the one or more configured computing systems, multiple visual aspects to use to display information about the multiple selected factors, wherein the multiple visual aspects include sizes of displayed items and vertical locations of displayed items, and wherein each of the multiple selected factors is associated with at least one of the multiple visual aspects; generating, by the one or more configured computing systems, information for display to one or more users that is based at least in part on the one or more predictions, the generated information including, for each of the multiple selected factors, a summarization that is represented using the at least one visual aspect associated with the selected factor and that is based on at least some of the obtained information corresponding to the selected factor; and providing, by the one or more configured computing systems, the generated information for display to the one or more users.
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6. A computer-implemented method comprising: obtaining, by one or more configured computing systems of a group discussion prediction service, information about a distributed group discussion that involves a plurality of users submitting a plurality of content items for the distributed group discussion, the obtained information including information about one or more predictions by the group discussion prediction service regarding future content items that will be submitted for the distributed group discussion; selecting, by the one or more configured computing systems, multiple factors to use in summarizing information about the distributed group discussion; determining, by the one or more configured computing systems, multiple visual aspects to use to display information about the multiple selected factors, wherein the multiple visual aspects include sizes of displayed items and vertical locations of displayed items, and wherein each of the multiple selected factors is associated with at least one of the multiple visual aspects; generating, by the one or more configured computing systems, information for display to one or more users that is based at least in part on the one or more predictions, the generated information including, for each of the multiple selected factors, a summarization that is represented using the at least one visual aspect associated with the selected factor and that is based on at least some of the obtained information corresponding to the selected factor; and providing, by the one or more configured computing systems, the generated information for display to the one or more users. 20. The method of claim 6 wherein the plurality of content items are separated into multiple categories of information, and wherein the multiple selected factors include at least one of a group of factors that includes a total quantity of supplied content items for each of the multiple categories, an aggregate sentiment of supplied content items for each of the multiple categories, and a rate of change in total quantity of content items supplied between two or more time periods for each of the multiple categories.
| 0.654172 |
5. The non-transitory recording medium of claim 1 , wherein the continuous presentation flag further indicates continuous presentation between a region of text located in the current presentation segment and a region of text located in the previous presentation segment.
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5. The non-transitory recording medium of claim 1 , wherein the continuous presentation flag further indicates continuous presentation between a region of text located in the current presentation segment and a region of text located in the previous presentation segment. 6. The recording medium of claim 5 , wherein the presentation segment includes at least one pair of an inline style and a text string for at least one region of text.
| 0.918127 |
11. A system comprising: data storage to store a main search index; and a main server coupled to the main search index to receive a search request including a keyword, hash the keyword with a plurality of hash functions to obtain a sequence of hash values, perform a search based on the main search index and a sequence of hash values, and return a search result to include identifiers of documents that contain the keyword.
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11. A system comprising: data storage to store a main search index; and a main server coupled to the main search index to receive a search request including a keyword, hash the keyword with a plurality of hash functions to obtain a sequence of hash values, perform a search based on the main search index and a sequence of hash values, and return a search result to include identifiers of documents that contain the keyword. 15. The system of claim 11 , wherein the plurality of indexing servers are owned by autonomous cooperating entities.
| 0.939691 |
14. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; selecting, by a computer system and for a text phrase in a first language, a translation of the text phrase from a set of translations of the text phrase in a second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for a particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the particular member.
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14. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: for each of a plurality of members of a social networking system, maintaining a respective set of connections to other members of the social networking system; selecting, by a computer system and for a text phrase in a first language, a translation of the text phrase from a set of translations of the text phrase in a second language, wherein the selecting is based on one or more actions by one or more other members identified in the set of connections for a particular member maintained by the social networking system, wherein the actions are associated with translations from the set of translations; and presenting the selected translation of the text phrase to the particular member. 25. The computer program product of claim 14 , wherein presenting the selected translation to the particular member further comprises: displaying a confidence level associated with the selected translation, the confidence level based on actions by the one or more other members connected to the member in the social network, the actions associated with translations from the set of translations.
| 0.520329 |
1. A system comprising: a processing apparatus comprising one or more computer processors; a storage apparatus comprising computer memory and storing: a search engine index including searchable content for a plurality of documents, wherein each document is associated with a unique identifier, with a table, and with a join key based upon which the document can be associated with other documents having an identical join key, a join mapping that maps between documents and join keys for a join field, and a bitset index that maps ordinal locations in a join bitset to join keys for a join field; and a search engine operating on the one or more processors, wherein the search engine is configured to execute queries against the search engine index, wherein the processing apparatus is configured to: receive a composite join query comprising a specification of a user query, a specification of a root table, a specification of a join table, and a specification of a join field, wherein the specification of the user query comprises one or more Boolean operations applied to one or more unitary queries; for each of the unitary queries, execute the unitary query against the search engine index using the search engine, filter results of the execution of the unitary query for documents contained in at least one of the root table and the join table, and identify join keys from the join field that correspond to the filtered results by setting bits in a join bitset according to the bitset index; for each of the Boolean operations, apply the Boolean operation according to the user query to one or more join bitsets, wherein the one or more join bitsets are obtained from executed unitary queries, from other applied Boolean operations or from both, to create a join bitset, until all of the one or more Boolean operations have beenapplied; store the join bitset created from an application of a last one of the one or more Boolean operations; retrieve a set of documents from the root table; filter the set of documents from the root table to obtain a set of documents having join keys that match join keys identified by the stored join bitset; and provide the filtered set of documents as a result for the composite join query.
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1. A system comprising: a processing apparatus comprising one or more computer processors; a storage apparatus comprising computer memory and storing: a search engine index including searchable content for a plurality of documents, wherein each document is associated with a unique identifier, with a table, and with a join key based upon which the document can be associated with other documents having an identical join key, a join mapping that maps between documents and join keys for a join field, and a bitset index that maps ordinal locations in a join bitset to join keys for a join field; and a search engine operating on the one or more processors, wherein the search engine is configured to execute queries against the search engine index, wherein the processing apparatus is configured to: receive a composite join query comprising a specification of a user query, a specification of a root table, a specification of a join table, and a specification of a join field, wherein the specification of the user query comprises one or more Boolean operations applied to one or more unitary queries; for each of the unitary queries, execute the unitary query against the search engine index using the search engine, filter results of the execution of the unitary query for documents contained in at least one of the root table and the join table, and identify join keys from the join field that correspond to the filtered results by setting bits in a join bitset according to the bitset index; for each of the Boolean operations, apply the Boolean operation according to the user query to one or more join bitsets, wherein the one or more join bitsets are obtained from executed unitary queries, from other applied Boolean operations or from both, to create a join bitset, until all of the one or more Boolean operations have beenapplied; store the join bitset created from an application of a last one of the one or more Boolean operations; retrieve a set of documents from the root table; filter the set of documents from the root table to obtain a set of documents having join keys that match join keys identified by the stored join bitset; and provide the filtered set of documents as a result for the composite join query. 7. The system of claim 1 , wherein the join table is identified as an outer join table.
| 0.633814 |
7. The method of claim 6 , further comprising: after prompting said recipient to indicate whether to continue with the rendering of said email message as speech, receiving an indication from said recipient to continue with the rendering of said email message as speech; and continuing with the rendering of said email as speech.
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7. The method of claim 6 , further comprising: after prompting said recipient to indicate whether to continue with the rendering of said email message as speech, receiving an indication from said recipient to continue with the rendering of said email message as speech; and continuing with the rendering of said email as speech. 8. The method of claim 7 , as said email message is continued to be rendered as speech, receiving a second signal from said recipient indicating the recipient intends to respond to a second particular part of said email message by inserting a second voice memo at a second particular location in said email message indicated by said recipient; receiving said second voice memo from said recipient, wherein said second voice memo comprises second voice-memo content; storing said second voice memo; inserting a second tag into said email message at said second particular location indicated by said recipient; and providing said second-voice-memo content to said source at said second particular location indicated by said recipient.
| 0.52361 |
1. A method comprising: receiving a search request via a user interface (UI), wherein the search request comprises one or more search terms, the search request specifies a set of repositories, the search request is a request to perform a search on the set of repositories, the set of repositories is a subset of a plurality of repositories, each repository of the set of repositories represents a corresponding type of content of a plurality of types of content, each of the plurality of types of content is in a corresponding of a plurality of formats, the UI is configured to initiate the search using the one or more search terms by communicating the one or more search terms to a search index coupled to the set of repositories via a plurality of repository interfaces, and the search index is coupled to the each repository by a corresponding repository interface of a plurality of repository interfaces; and receiving a plurality of individual search results from the set of repositories at a set of the plurality of repository interfaces, wherein the plurality of individual search results comprise the plurality of types of content; and displaying, on a display device, search results corresponding to the plurality of individual search results, wherein the search is performed on the set of repositories, and the search results are configured to be displayed by virtue of being in a single format.
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1. A method comprising: receiving a search request via a user interface (UI), wherein the search request comprises one or more search terms, the search request specifies a set of repositories, the search request is a request to perform a search on the set of repositories, the set of repositories is a subset of a plurality of repositories, each repository of the set of repositories represents a corresponding type of content of a plurality of types of content, each of the plurality of types of content is in a corresponding of a plurality of formats, the UI is configured to initiate the search using the one or more search terms by communicating the one or more search terms to a search index coupled to the set of repositories via a plurality of repository interfaces, and the search index is coupled to the each repository by a corresponding repository interface of a plurality of repository interfaces; and receiving a plurality of individual search results from the set of repositories at a set of the plurality of repository interfaces, wherein the plurality of individual search results comprise the plurality of types of content; and displaying, on a display device, search results corresponding to the plurality of individual search results, wherein the search is performed on the set of repositories, and the search results are configured to be displayed by virtue of being in a single format. 18. The method of claim 1 , wherein the revised set of repositories further differs from the set of repositories by virtue of exclusion of a de-selected repository from the revised set of repositories, wherein the de-selected repository is included in the set of repositories.
| 0.719979 |
16. The method of claim 12 , wherein combining the separate result sets further comprises marking the final result set.
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16. The method of claim 12 , wherein combining the separate result sets further comprises marking the final result set. 17. The method of claim 16 , wherein marking the final result set further comprises marking a resource in the final result set if the resource is included in two or more of the separate result sets.
| 0.900097 |
35. The computer readable storage device of claim 34 , the one or more query augmentation terms based at least in part on heuristics.
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35. The computer readable storage device of claim 34 , the one or more query augmentation terms based at least in part on heuristics. 36. The computer readable storage device of claim 35 , the method comprising executing the query.
| 0.968246 |
8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: combining a first database of first text-to-speech voice units and a second database of second text-to-speech voice units, the first text-to-speech voice units originating from a different speaker than the second text-to-speech voice units, to yield a combined database; storing the combined database as if the combined database were from a single speaker; determining a selection policy based on a current emotional context; selecting from the combined database, based on the selection policy, voice units of a phonetic category for a synthetic voice, to yield selected voice units, wherein the selected voice units comprise a first voice unit from the first text-to-speech voice units and a second voice unit from the second text-to-speech voice units; and synthesizing speech based on the selected voice units.
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8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: combining a first database of first text-to-speech voice units and a second database of second text-to-speech voice units, the first text-to-speech voice units originating from a different speaker than the second text-to-speech voice units, to yield a combined database; storing the combined database as if the combined database were from a single speaker; determining a selection policy based on a current emotional context; selecting from the combined database, based on the selection policy, voice units of a phonetic category for a synthetic voice, to yield selected voice units, wherein the selected voice units comprise a first voice unit from the first text-to-speech voice units and a second voice unit from the second text-to-speech voice units; and synthesizing speech based on the selected voice units. 11. The system of claim 8 , wherein the first text-to-speech voice units and the second text-to-speech voice units are in distinct styles of speaking.
| 0.557197 |
2. The computer-implemented method of claim 1 , further comprising calculating the reviewer scores for the individual reviewers from the plurality of reviewers that have reviewed a common translation, and wherein calculating the current translation score is further based at least in part on the reviewer scores associated with the at least one reviewer that reviewed the current translation.
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2. The computer-implemented method of claim 1 , further comprising calculating the reviewer scores for the individual reviewers from the plurality of reviewers that have reviewed a common translation, and wherein calculating the current translation score is further based at least in part on the reviewer scores associated with the at least one reviewer that reviewed the current translation. 5. The computer-implemented method of claim 2 , wherein a reviewer of the set of reviewers, having a reviewer score above a threshold, impacts the calculated reviewer scores more heavily than reviewers of the set of reviewers having reviewer scores below the threshold.
| 0.913793 |
1. A computer-implemented method of assisting a user in selecting items from an electronic catalog of video items, the method comprising: (a) obtaining access to metric values derived from a knowledge base of predetermined mediasets associated with the electronic catalog; wherein the metric values reflect a level of association for selected pairs of video items within the knowledge base of mediasets, and wherein the metric values are not affected by any metadata descriptive of the said video items' content, but rather reflect a relative frequency with which the video items in the pair are associated together by various users; (b) receiving an initial selection of at least one video item to define an initial input video set; (c) generating an output video item navigation list responsive to at least one item of the input video set, based on the metric values derived from the knowledge base; and (d) communicating the generated navigation list to a user.
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1. A computer-implemented method of assisting a user in selecting items from an electronic catalog of video items, the method comprising: (a) obtaining access to metric values derived from a knowledge base of predetermined mediasets associated with the electronic catalog; wherein the metric values reflect a level of association for selected pairs of video items within the knowledge base of mediasets, and wherein the metric values are not affected by any metadata descriptive of the said video items' content, but rather reflect a relative frequency with which the video items in the pair are associated together by various users; (b) receiving an initial selection of at least one video item to define an initial input video set; (c) generating an output video item navigation list responsive to at least one item of the input video set, based on the metric values derived from the knowledge base; and (d) communicating the generated navigation list to a user. 12. The method according to claim 1 wherein the catalog of video items comprises html links to the video items.
| 0.609943 |
48. The computer-readable medium of claim 45 , wherein a first plurality of the table data values are spectral intensity values of a digital image, and wherein a second plurality of the table data values are items of metadata relating to the digital image.
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48. The computer-readable medium of claim 45 , wherein a first plurality of the table data values are spectral intensity values of a digital image, and wherein a second plurality of the table data values are items of metadata relating to the digital image. 50. The computer-readable medium of claim 48 , wherein the class network, the process hierarchy and the data network together form a semantic network, and wherein the process step is linked to one of the items of metadata.
| 0.864785 |
21. An apparatus for generating hardware description language (HDL) code, the apparatus comprising: means for receiving an executable, graphical model having a plurality of blocks, wherein the model includes a frame-based interface between at least two of the blocks, the frame-based interface implementable in hardware in a plurality of ways, the plurality of ways in which the frame-enabled block is implementable in hardware include: a fully parallelized way that uses a plurality of first parallel hardware components, a fully serialized way that uses a second serial hardware component, and a combination serialized and parallelized way that uses a plurality of second parallel hardware components and a second serial hardware component; means for receiving a selected preference for a hardware implementation of the frame-based interface between the at least two blocks of the model, the selected preference free from affecting execution of the frame-based interface in the model and to cause the frame-based interface to be implemented in hardware in a particular way of the plurality of ways; means for generating the HDL code for the frame-based interface, the generated HDL code implementing the frame-based interface in hardware in the particular way that satisfies the selected preference, the particular way selected from the group consisting of: the fully parallelized way, in which the plurality of first parallel hardware components are included in the hardware implementation of the frame-enabled block, the fully serialized way, in which the first serial hardware component is included in the hardware implementation of the frame-enabled block, and the combination serialized and parallelized way, in which the second serial hardware component and the plurality of second parallel hardware components are included in the hardware implementation of the frame-enabled block.
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21. An apparatus for generating hardware description language (HDL) code, the apparatus comprising: means for receiving an executable, graphical model having a plurality of blocks, wherein the model includes a frame-based interface between at least two of the blocks, the frame-based interface implementable in hardware in a plurality of ways, the plurality of ways in which the frame-enabled block is implementable in hardware include: a fully parallelized way that uses a plurality of first parallel hardware components, a fully serialized way that uses a second serial hardware component, and a combination serialized and parallelized way that uses a plurality of second parallel hardware components and a second serial hardware component; means for receiving a selected preference for a hardware implementation of the frame-based interface between the at least two blocks of the model, the selected preference free from affecting execution of the frame-based interface in the model and to cause the frame-based interface to be implemented in hardware in a particular way of the plurality of ways; means for generating the HDL code for the frame-based interface, the generated HDL code implementing the frame-based interface in hardware in the particular way that satisfies the selected preference, the particular way selected from the group consisting of: the fully parallelized way, in which the plurality of first parallel hardware components are included in the hardware implementation of the frame-enabled block, the fully serialized way, in which the first serial hardware component is included in the hardware implementation of the frame-enabled block, and the combination serialized and parallelized way, in which the second serial hardware component and the plurality of second parallel hardware components are included in the hardware implementation of the frame-enabled block. 22. The apparatus of claim 21 wherein the model is a block diagram model, a state transition diagram or a Petri net.
| 0.583187 |
14. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: arrange one or more messages in a document plan, wherein messages represent a phrase or a simple sentence and are created in an instance in which an input data stream comprises data that satisfies one or more message requirements, wherein at least a portion of the input data stream comprises non-linguistic data; identify an intended referent in a message of the one or more messages to be referred to in a textual output; determine a lowest common ancestor for the intended referent and a previously referred-to entity within a part-of hierarchy; determine a salient ancestor of the intended referent within the part-of hierarchy; generate a referring noun phrase for the intended referent to be included in a textual output by traversing the part-of hierarchy from the salient ancestor to the lowest common ancestor such that a default descriptor is added to a queue for at least a portion of entities traversed in the part-of-hierarchy, wherein the reference noun phrase comprises a default descriptor of the intended referent and one or more default descriptors of one or more parts of the part-of hierarchy that are traversed; generate the textual output comprising the referring noun phrase such that it is displayable on a user interface, wherein the textual output linguistically describes at least a portion of the input data stream; and display the textual output via a display device.
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14. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: arrange one or more messages in a document plan, wherein messages represent a phrase or a simple sentence and are created in an instance in which an input data stream comprises data that satisfies one or more message requirements, wherein at least a portion of the input data stream comprises non-linguistic data; identify an intended referent in a message of the one or more messages to be referred to in a textual output; determine a lowest common ancestor for the intended referent and a previously referred-to entity within a part-of hierarchy; determine a salient ancestor of the intended referent within the part-of hierarchy; generate a referring noun phrase for the intended referent to be included in a textual output by traversing the part-of hierarchy from the salient ancestor to the lowest common ancestor such that a default descriptor is added to a queue for at least a portion of entities traversed in the part-of-hierarchy, wherein the reference noun phrase comprises a default descriptor of the intended referent and one or more default descriptors of one or more parts of the part-of hierarchy that are traversed; generate the textual output comprising the referring noun phrase such that it is displayable on a user interface, wherein the textual output linguistically describes at least a portion of the input data stream; and display the textual output via a display device. 15. An apparatus according to claim 14 , wherein the at least one memory including the computer program code is further configured to, with the at least one processor, cause the apparatus to: determine that the intended referent is marked as salient; and cause the referring noun phrase to solely comprise the default descriptor of the intended referent.
| 0.502701 |
16. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprises a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query.
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16. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprises a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query. 17. The computer program product of claim 16 , wherein the operations further comprise obtaining the one or more web resources that refer to the book including searching a collection of web resources using data associated with the highest-ranked publication search result to obtain one or more web resources that refer to the book.
| 0.545708 |
2. An apparatus according to claim 1, wherein said feeding means includes a first roller for feeding the documents stacked on said document table and a second roller for separating the documents fed by said first roller, and said first control means includes fourth control means for controlling a rotating direction of the second roller and fifth control means for controlling an operation of said first roller so that said feeding means feeds the documents to said document table.
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2. An apparatus according to claim 1, wherein said feeding means includes a first roller for feeding the documents stacked on said document table and a second roller for separating the documents fed by said first roller, and said first control means includes fourth control means for controlling a rotating direction of the second roller and fifth control means for controlling an operation of said first roller so that said feeding means feeds the documents to said document table. 3. An apparatus according to claim 2, wherein the fourth control means includes means for rotating said second roller in a first direction when the documents stacked on said document table are fed and for rotating said second roller in a second direction opposite the first direction for a predetermined period of time when said detecting means detects that two or more documents are simultaneously fed by said feeding means; and said fifth control means includes means for separating said first roller from the documents when said detecting means detects that two or more documents are simultaneously fed by said feeding means.
| 0.719447 |
14. A computer system for developing, in an existing protocol, load tests of computing systems, comprising: kernel means in memory providing a plurality of kernel actions for use in a subject load test script, the kernel actions being executable at will specializations of core actions stored in memory, the kernel actions being written in an object-oriented programming language underlying the existing protocol such that each individual kernel action is modeled as a respective object in the object-oriented programming language enabling different kernel actions to be treated equally in execution resources including threads and processes, and each kernel action being atomic and extensible; execution means executable by a processor for applying the subject load test script to a number of test clients, the execution means scheduling for execution and executing the kernel actions, the kernel actions being able to be swapped into and out of executable states and individually executed at will and treated equally enabling a number of resources per number of kernel actions instead of per number of test clients, and resulting in use of a relatively small number of resources as compared to the number of test clients, the relatively small number being on the order of less than one thread per user emulated to generate a load, wherein the processor is free from creating a process for each test client and wherein the processor enables a plurality of kernel actions of different test clients in one process; and extension means in memory operatively communicating with the kernel means for extending the protocol including any combination of extending base classes of the protocol and adding features to the protocol, wherein the kernel means enables corresponding references to extensions of the protocol to be automatically added to the subject load test script, resulting in, for a given kernel action, a new kernel action being executed in place of the given kernel action free of modifying rest of the kernel means.
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14. A computer system for developing, in an existing protocol, load tests of computing systems, comprising: kernel means in memory providing a plurality of kernel actions for use in a subject load test script, the kernel actions being executable at will specializations of core actions stored in memory, the kernel actions being written in an object-oriented programming language underlying the existing protocol such that each individual kernel action is modeled as a respective object in the object-oriented programming language enabling different kernel actions to be treated equally in execution resources including threads and processes, and each kernel action being atomic and extensible; execution means executable by a processor for applying the subject load test script to a number of test clients, the execution means scheduling for execution and executing the kernel actions, the kernel actions being able to be swapped into and out of executable states and individually executed at will and treated equally enabling a number of resources per number of kernel actions instead of per number of test clients, and resulting in use of a relatively small number of resources as compared to the number of test clients, the relatively small number being on the order of less than one thread per user emulated to generate a load, wherein the processor is free from creating a process for each test client and wherein the processor enables a plurality of kernel actions of different test clients in one process; and extension means in memory operatively communicating with the kernel means for extending the protocol including any combination of extending base classes of the protocol and adding features to the protocol, wherein the kernel means enables corresponding references to extensions of the protocol to be automatically added to the subject load test script, resulting in, for a given kernel action, a new kernel action being executed in place of the given kernel action free of modifying rest of the kernel means. 16. A computer system as claimed in claim 14 wherein the execution means employs a plurality of queues that allow execution threads to execute any kernel action at any time.
| 0.545516 |
1. A method comprising: receiving, at a first device, a first voice command from a user; at least partly in response to receiving the first voice command from the user, outputting audible content on a speaker of the first device, the audible content including at least a query result responsive to the first voice command and an audio indication of information regarding visual content that is associated with the query result and that is accessible by a second device; receiving, at the first device and at least partly in response to the audible content, a second voice command from the user, the second voice command comprising a request, based at least in part on the audio indication, to present the visual content on the second device; and at least partly in response to receiving the second voice command, instructing an application stored on the second device to output the visual content on a display of the second device.
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1. A method comprising: receiving, at a first device, a first voice command from a user; at least partly in response to receiving the first voice command from the user, outputting audible content on a speaker of the first device, the audible content including at least a query result responsive to the first voice command and an audio indication of information regarding visual content that is associated with the query result and that is accessible by a second device; receiving, at the first device and at least partly in response to the audible content, a second voice command from the user, the second voice command comprising a request, based at least in part on the audio indication, to present the visual content on the second device; and at least partly in response to receiving the second voice command, instructing an application stored on the second device to output the visual content on a display of the second device. 6. The method as recited in claim 1 , further comprising determining the second device proximate to the first device based at least in part detecting, at the first device, a wireless signal associated with the second device, wherein the audio indication includes at least an identity of the second device.
| 0.673017 |
2. A method for placing advertisements on a user interface comprising the steps of: providing a non-transitory computer readable medium including a user interface having a plurality of graphical user interface screens, at least some of said plurality of user interface screens containing user-selectable control objects; and determining which of a plurality of advertisements to display on a user interface screen based on at least the following criteria: topical relevance, said topical relevance being a measure of a relationship between one or more topics associated with each advertisement and one or more topics associated with said user-selectable control objects on said respective user interface screen wherein said topical relevance is calculated as: μ T ( a , p ) = ∑ i = 0 n δ ( a ⋂ t i ) δ ( a ) + δ ( t i ) where δ is the distance of a topic point from the root node.
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2. A method for placing advertisements on a user interface comprising the steps of: providing a non-transitory computer readable medium including a user interface having a plurality of graphical user interface screens, at least some of said plurality of user interface screens containing user-selectable control objects; and determining which of a plurality of advertisements to display on a user interface screen based on at least the following criteria: topical relevance, said topical relevance being a measure of a relationship between one or more topics associated with each advertisement and one or more topics associated with said user-selectable control objects on said respective user interface screen wherein said topical relevance is calculated as: μ T ( a , p ) = ∑ i = 0 n δ ( a ⋂ t i ) δ ( a ) + δ ( t i ) where δ is the distance of a topic point from the root node. 11. The method of claim 2 , wherein said user interface has a plurality of different interface screens, each interface screen being individually displayable at a time; and further wherein each interface screen can be reached through at least one predetermined path through others of said plurality of different interface screens, wherein said step of determining which of a plurality of advertisements to display on a user interface screen based on at least one of the following criteria: topical relevance, contextual relevance, path relevance and cognitive prominence, involves using semantic context associated with a one of said at least one of said predetermined paths used to reach a currently displayed user interface screen.
| 0.5 |
15. A computer program product tangibly embodied on a non-transitory computer readable medium and including instructions which, when executed by at least one processor, are configured to: store an extension file configured to perform an action with respect to a browser application during rendering therewith of a page using a page script associated with a page model, the extension file associated with a content script configured to interact with the page model during rendering of the page sript to provide the page; load the page script, including the page model, into a page script execution environment within a rendering environment of the browser application, the page script execution environment having a page script namespace; implement a content script execution environment within the rendering environment of the browser application, using a copy of the page model within a content script namespace; initiate the action using the content script within the content script execution environment, wherein communication between the content script execution environment and the page script execution environment is restricted to a one-way direction from the content script execution environment to the page script execution environment; send a message to the extension file to implement the action; and perform the action using the extension file and in conjunction with the rendering of the page.
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15. A computer program product tangibly embodied on a non-transitory computer readable medium and including instructions which, when executed by at least one processor, are configured to: store an extension file configured to perform an action with respect to a browser application during rendering therewith of a page using a page script associated with a page model, the extension file associated with a content script configured to interact with the page model during rendering of the page sript to provide the page; load the page script, including the page model, into a page script execution environment within a rendering environment of the browser application, the page script execution environment having a page script namespace; implement a content script execution environment within the rendering environment of the browser application, using a copy of the page model within a content script namespace; initiate the action using the content script within the content script execution environment, wherein communication between the content script execution environment and the page script execution environment is restricted to a one-way direction from the content script execution environment to the page script execution environment; send a message to the extension file to implement the action; and perform the action using the extension file and in conjunction with the rendering of the page. 20. The computer program product of claim 15 , wherein the page script execution environment and the content script execution environment are configured to execute in an execution context of a rendering engine of the browser application, and the extension file is configured to operate in a separate extension process in a separate execution context.
| 0.544708 |
36. The computer-program product of claim 30 , wherein each of the essential substrings includes a first name, and wherein the operations further include: with respect to at least one of the records: retrieving an alternate spelling of the first name included in the respective essential substring.
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36. The computer-program product of claim 30 , wherein each of the essential substrings includes a first name, and wherein the operations further include: with respect to at least one of the records: retrieving an alternate spelling of the first name included in the respective essential substring. 37. The computer-program product of claim 36 , wherein: the alternate spelling is retrieved from a table that includes names that are individually indexed to alternate spellings.
| 0.935587 |
8. The method of claim 1 , wherein the context indicates a window type associated with the at least some of the text.
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8. The method of claim 1 , wherein the context indicates a window type associated with the at least some of the text. 9. The method of claim 8 , wherein a same word or phrase in the closed-captioning content is replaced with different symbols in different window types.
| 0.977797 |
6. A system for processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: provide a natural language utterance as an input to a speech recognition engine; receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine; provide the words or phrases as an input to a conversational language processor; receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases; determine a context for the natural language utterance based at least on the recognized words or phrases; determine that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications; provide the first request to a first application to service the first request; provide the second request to a second application to service the second request; select an advertisement based at least on the determined context and either or both of the first request or the second request; generate a service output responsive to the natural language utterance, the service output comprising: (i) a first output received from the first application responsive to the first request; (ii) a second output received from the second application responsive to the second request; and (iii) the selected advertisement; and provide the service output via an output device.
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6. A system for processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: provide a natural language utterance as an input to a speech recognition engine; receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine; provide the words or phrases as an input to a conversational language processor; receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases; determine a context for the natural language utterance based at least on the recognized words or phrases; determine that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications; provide the first request to a first application to service the first request; provide the second request to a second application to service the second request; select an advertisement based at least on the determined context and either or both of the first request or the second request; generate a service output responsive to the natural language utterance, the service output comprising: (i) a first output received from the first application responsive to the first request; (ii) a second output received from the second application responsive to the second request; and (iii) the selected advertisement; and provide the service output via an output device. 8. The system of claim 6 , wherein the one or more physical processors are further programmed to: use an environmental model to determine environmental information, wherein the context for the natural language utterance is determined based further on the environmental information.
| 0.585202 |
16. A computer-implemented method for permitting a user to interact with a three-dimensional computer model, comprising: storing the model, a mapping defining a geometrical correspondence between portions of the model and respective portions of a real world workspace, and data defining a three-dimensional editing volume of the workspace; and repeatedly performing the following: rendering a 3D image of that portion of the model within the editing volume; receiving first signals from at least one first input device operated by a first hand of the user, and based on the first signals doing any of: modifying the geometrical correspondence between the model and the workspace, modifying the orientation of the editing volume relative to the workspace and translating or rotating said portion of the model relative to the editing volume; and receiving second signals from at least one second input device operated by a second hand of the user, and based upon the second signals doing any of: modifying the 3D position of the editing volume relative to the workspace and modifying or operating upon a portion of the model, wherein the boundaries of the editing volume are at least one of: continuously displayed, displayed when changed, displayed upon any translation or rotation of the editing volume or selection of an active face, displayed upon change of the geometrical correspondence between the model and the workspace, displayed upon input of any signals to the processor via the first input device, and displayed upon user command, and wherein the first signals can only be input via the first input device and the second signals can only be input by the second device such that at any given time each hand of the user controls a specific and distinct set of interactive functionalities.
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16. A computer-implemented method for permitting a user to interact with a three-dimensional computer model, comprising: storing the model, a mapping defining a geometrical correspondence between portions of the model and respective portions of a real world workspace, and data defining a three-dimensional editing volume of the workspace; and repeatedly performing the following: rendering a 3D image of that portion of the model within the editing volume; receiving first signals from at least one first input device operated by a first hand of the user, and based on the first signals doing any of: modifying the geometrical correspondence between the model and the workspace, modifying the orientation of the editing volume relative to the workspace and translating or rotating said portion of the model relative to the editing volume; and receiving second signals from at least one second input device operated by a second hand of the user, and based upon the second signals doing any of: modifying the 3D position of the editing volume relative to the workspace and modifying or operating upon a portion of the model, wherein the boundaries of the editing volume are at least one of: continuously displayed, displayed when changed, displayed upon any translation or rotation of the editing volume or selection of an active face, displayed upon change of the geometrical correspondence between the model and the workspace, displayed upon input of any signals to the processor via the first input device, and displayed upon user command, and wherein the first signals can only be input via the first input device and the second signals can only be input by the second device such that at any given time each hand of the user controls a specific and distinct set of interactive functionalities. 20. The method of claim 16 wherein the first input device generates the first input signals in correspondence to the position and/or orientation of the first input device.
| 0.563319 |
1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users.
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1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. 6. The method of claim 1 , wherein weights are used to filter the network traffic in order to develop the feed for the subset of the additional users.
| 0.827626 |
4. The computing device of claim 1 , wherein the second programming language is at least one of R, JAVA, or Python.
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4. The computing device of claim 1 , wherein the second programming language is at least one of R, JAVA, or Python. 5. The computing device of claim 4 , wherein the operations further comprise: converting an R factor data type associated with the second programming language to a categorical data type associated with the first programming language.
| 0.915706 |
43. A method of processing documents associated with a deposit transaction of a customer, the method comprising: receiving in a document processing system a data file associated with the deposit transaction from a network, the data file including a plurality of records, each record including image data that is reproducible as a visually readable image of at least a portion of a respective document associated with the deposit transaction, a respective value, and respective identifying information; determining if one or more of the plurality of records is a suspect record based on a comparison of the respective identifying information with suspect information stored in the document processing system; determining that one of the records included in the data file associated with the deposit transaction is a suspect record; and in response to the determination of the suspect record, automatically making a suspect notice electronically available, the suspect notice including information indicative of the determination of the suspect record associated with the deposit transaction.
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43. A method of processing documents associated with a deposit transaction of a customer, the method comprising: receiving in a document processing system a data file associated with the deposit transaction from a network, the data file including a plurality of records, each record including image data that is reproducible as a visually readable image of at least a portion of a respective document associated with the deposit transaction, a respective value, and respective identifying information; determining if one or more of the plurality of records is a suspect record based on a comparison of the respective identifying information with suspect information stored in the document processing system; determining that one of the records included in the data file associated with the deposit transaction is a suspect record; and in response to the determination of the suspect record, automatically making a suspect notice electronically available, the suspect notice including information indicative of the determination of the suspect record associated with the deposit transaction. 50. The method of claim 43 , wherein the visually readable images have a resolution of at least about 50 DPI by at least about 50 DPI.
| 0.709067 |
20. The method according to claim 1 , further comprising: classifying each document from anion said N electronic documents as relevant or irrelevant to an issue; generating a computer display of at least one user-selected document within said N electronic documents, wherein at least some words in said user-selected, document are differentially presented depending on their contribution to said classifying of the document as relevant or irrelevant; sequentially removing certain sets of words from each individual document classified and using the text classifier to classify said document's relevance assuming said words are removed, thereby to obtain a relevance output for each set of words; and comparing said relevance output to an output obtained by using the text classifier to classify said individual document without removing any words, thereby to obtain an indication of the contribution of each set of words to the relevance of the document.
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20. The method according to claim 1 , further comprising: classifying each document from anion said N electronic documents as relevant or irrelevant to an issue; generating a computer display of at least one user-selected document within said N electronic documents, wherein at least some words in said user-selected, document are differentially presented depending on their contribution to said classifying of the document as relevant or irrelevant; sequentially removing certain sets of words from each individual document classified and using the text classifier to classify said document's relevance assuming said words are removed, thereby to obtain a relevance output for each set of words; and comparing said relevance output to an output obtained by using the text classifier to classify said individual document without removing any words, thereby to obtain an indication of the contribution of each set of words to the relevance of the document. 36. The method according to claim 20 further comprising: classifying each document from among said N electronic documents as relevant or irrelevant to an issue; and generating a computer display of at least one user-selected document within said N electronic documents, wherein at least some words in said user-selected document are differentially presented depending on their contribution to said classifying of the document as relevant or irrelevant, wherein said words differentially presented are differentially colored and wherein intensity of color is used to represent strength of said contribution for each word.
| 0.77755 |
15. A non-transitory computer readable medium comprising executable instructions for a method for a service-oriented architecture (SOA) system which provides service offerings categorized according to service categories using a taxonomy, the instructions being executed to perform: receiving, in a specification field, a formal definition of a service, the formal definition is for inclusion to define one of service offerings of the SOA system; determining a current grammar which is currently in effect as a specification-requirement of acceptable definitions for a service category in which the service is categorized according to a taxonomy of the SOA system, the current grammar being a common grammar; determining whether the formal definition in the specification field is acceptable, by adhering to the current grammar determined to be currently in effect as the specification-requirement for the category of the service; when the formal definition is determined to be not acceptable according to the current grammar: accepting, automatically without manual intervention, in response to determining that the formal definition is acceptable, for inclusion to define the service in the SOA system, the formal definition in the specification field for the service, when the formal definition in the specification field is determined to be acceptable according to the current grammar; modifying, automatically without manual intervention, in response to determining that the formal definition is acceptable, the current grammar for the taxonomy of the SOA system to provide an updated grammar for the SOA system in which the formal definition of the service that was received in the specification field is now categorized in the service category; and using, in governance of the SOA, the updated grammar as the current grammar which defines service offerings of the SOA system in which the formal definition of the service that was received in the specification field is now categorized in the service category; and when the formal definition is determined to be not acceptable according to the current grammar: rejecting, automatically without manual intervention, in response to determining that the formal definition is acceptable, for the service offerings of the SOA system, the formal definition in the specification field for the service.
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15. A non-transitory computer readable medium comprising executable instructions for a method for a service-oriented architecture (SOA) system which provides service offerings categorized according to service categories using a taxonomy, the instructions being executed to perform: receiving, in a specification field, a formal definition of a service, the formal definition is for inclusion to define one of service offerings of the SOA system; determining a current grammar which is currently in effect as a specification-requirement of acceptable definitions for a service category in which the service is categorized according to a taxonomy of the SOA system, the current grammar being a common grammar; determining whether the formal definition in the specification field is acceptable, by adhering to the current grammar determined to be currently in effect as the specification-requirement for the category of the service; when the formal definition is determined to be not acceptable according to the current grammar: accepting, automatically without manual intervention, in response to determining that the formal definition is acceptable, for inclusion to define the service in the SOA system, the formal definition in the specification field for the service, when the formal definition in the specification field is determined to be acceptable according to the current grammar; modifying, automatically without manual intervention, in response to determining that the formal definition is acceptable, the current grammar for the taxonomy of the SOA system to provide an updated grammar for the SOA system in which the formal definition of the service that was received in the specification field is now categorized in the service category; and using, in governance of the SOA, the updated grammar as the current grammar which defines service offerings of the SOA system in which the formal definition of the service that was received in the specification field is now categorized in the service category; and when the formal definition is determined to be not acceptable according to the current grammar: rejecting, automatically without manual intervention, in response to determining that the formal definition is acceptable, for the service offerings of the SOA system, the formal definition in the specification field for the service. 19. The non-transitory computer readable medium of claim 15 , further comprising instructions executed for modifying the current grammar to provide an updated grammar; storing the updated grammar to use as the current grammar for the service; and evaluating, for the service, the formal definition, which was acceptable under a previous grammar, according to the current grammar which is now updated.
| 0.609277 |
1. A computer-implemented method for an interactive graphical search interface, the method comprising: receiving, from a user via a computer user interface over an electronic network, a plurality of search parameters; generating, by a processor, a search space that includes a user element corresponding to each search parameter, wherein a weight of each search parameter depends on a distance of a position of the corresponding user element to a center of the search space and one or more distances of the corresponding user element to positions of one or more other user elements, wherein a position of each user element in the search space corresponds to the weight of the respective search parameter, and wherein the plurality of search parameters have an initial predetermined weights that are equal, such that the search space is a radially symmetric shape about optimal search output; generating, by the processor by accessing a search engine database, a plurality of search results based on the plurality of search parameters and respective weights of each search parameter; receiving, from the user via the computer user interface, a new position of at least one user element from an interaction by the user with the at least one user element; generating, by the processor upon receiving the new position of at least one user element, new weights for the plurality of search parameters based on each new position received; and generating, by the processor by accessing the search engine database, a plurality of new search results based on the plurality of search parameters and the new weights of each respective search parameter.
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1. A computer-implemented method for an interactive graphical search interface, the method comprising: receiving, from a user via a computer user interface over an electronic network, a plurality of search parameters; generating, by a processor, a search space that includes a user element corresponding to each search parameter, wherein a weight of each search parameter depends on a distance of a position of the corresponding user element to a center of the search space and one or more distances of the corresponding user element to positions of one or more other user elements, wherein a position of each user element in the search space corresponds to the weight of the respective search parameter, and wherein the plurality of search parameters have an initial predetermined weights that are equal, such that the search space is a radially symmetric shape about optimal search output; generating, by the processor by accessing a search engine database, a plurality of search results based on the plurality of search parameters and respective weights of each search parameter; receiving, from the user via the computer user interface, a new position of at least one user element from an interaction by the user with the at least one user element; generating, by the processor upon receiving the new position of at least one user element, new weights for the plurality of search parameters based on each new position received; and generating, by the processor by accessing the search engine database, a plurality of new search results based on the plurality of search parameters and the new weights of each respective search parameter. 2. The method of claim 1 , further comprising: generating, by a processor, a matrix of hyperlinks within the search space, each hyperlink having positions within the search space defining a relevance of each hyperlink to the plurality of search parameters.
| 0.565643 |
8. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause one or more processors to perform operations for correcting words in transcribed text, the operations comprising: providing a plurality of transcribed words from a word lattice for display on a computing device; in response to receiving an indication that a particular transcribed word has been selected, providing for display on the computing device a particular alternate phrase from the word lattice, wherein the particular alternate phrase includes alternate words that correspond to (i) the particular transcribed word and (ii) at least one transcribed word preceding the particular transcribed word; and in response to receiving an indication that the particular alternate phrase has been selected, replacing, with the particular transcribed phrase, (i) the particular transcribed word and (ii) the at least one transcribed word preceding the particular transcribed word.
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8. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause one or more processors to perform operations for correcting words in transcribed text, the operations comprising: providing a plurality of transcribed words from a word lattice for display on a computing device; in response to receiving an indication that a particular transcribed word has been selected, providing for display on the computing device a particular alternate phrase from the word lattice, wherein the particular alternate phrase includes alternate words that correspond to (i) the particular transcribed word and (ii) at least one transcribed word preceding the particular transcribed word; and in response to receiving an indication that the particular alternate phrase has been selected, replacing, with the particular transcribed phrase, (i) the particular transcribed word and (ii) the at least one transcribed word preceding the particular transcribed word. 13. The computer program product of claim 8 , wherein receiving the indication that the particular transcribed word has been selected and receiving the indication that the particular alternate phrase has been selected comprise receiving the indication that the particular transcribed word has been selected and receiving the indication that the particular alternate phrase has been selected through a touchscreen interface of the computing device by a user of the computing device.
| 0.535256 |
15. A system for identifying books located on a bookshelf, the system comprising: a mobile device configured to capture one or more photographic images of the bookshelf; a computer server configured to receive the captured one or more photographic images and to: segment the photographic images into regions, each of the regions corresponding to a respective book spine; analyze at least one of the regions to identify a book corresponding thereto, wherein the computer server is further configured, in furtherance of analyzing the at least one of the regions, to: extract one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; perform a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiate a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing the further book identity; and browse another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf.
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15. A system for identifying books located on a bookshelf, the system comprising: a mobile device configured to capture one or more photographic images of the bookshelf; a computer server configured to receive the captured one or more photographic images and to: segment the photographic images into regions, each of the regions corresponding to a respective book spine; analyze at least one of the regions to identify a book corresponding thereto, wherein the computer server is further configured, in furtherance of analyzing the at least one of the regions, to: extract one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; perform a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiate a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing the further book identity; and browse another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf. 26. The system of claim 15 , wherein the matching operation comprises performing deep neural network similarity learning.
| 0.550997 |
10. The method of claim 1 , wherein receiving user interactions on one or more external systems, further comprises: receiving the user interactions as graph actions performed by users of the social networking system on the first set of graph objects on different external systems; categorizing the user interactions by which of the external systems the graph actions were performed on the first set of graph objects; and storing the categorization of the user interactions by external systems as a parameter in content item objects associated with content items.
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10. The method of claim 1 , wherein receiving user interactions on one or more external systems, further comprises: receiving the user interactions as graph actions performed by users of the social networking system on the first set of graph objects on different external systems; categorizing the user interactions by which of the external systems the graph actions were performed on the first set of graph objects; and storing the categorization of the user interactions by external systems as a parameter in content item objects associated with content items. 11. The method of claim 10 , further comprising: aggregating graph actions performed by users connected to the viewing user based on the graph objects the graph actions were performed on in the different external systems; and generating content items comprising the aggregated graph actions performed by users connected to the viewing user based on the graph objects the graph actions were performed on in the different external systems.
| 0.851292 |
1. A computer implemented method comprising: receiving a search request from a user, the search request including one or more free search terms about a business entity; revising the one or more free search terms to consider related terms to the one or more free search terms; executing a search using an ontology, wherein terminological components of the ontology are generated, at least in part, from metadata of business objects associated with the business entity, the search based on the revised one or more free search terms and semantically facilitated by the terminological components of the ontology associated with the business entity; and identifying at least one search result associated with the revised one or more free search terms; replicating the at least one search result for at least one search received at a later time instance, subsequent to storing the at least one search result; and providing the at least one search result associated with the revised one or more free search terms to the user.
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1. A computer implemented method comprising: receiving a search request from a user, the search request including one or more free search terms about a business entity; revising the one or more free search terms to consider related terms to the one or more free search terms; executing a search using an ontology, wherein terminological components of the ontology are generated, at least in part, from metadata of business objects associated with the business entity, the search based on the revised one or more free search terms and semantically facilitated by the terminological components of the ontology associated with the business entity; and identifying at least one search result associated with the revised one or more free search terms; replicating the at least one search result for at least one search received at a later time instance, subsequent to storing the at least one search result; and providing the at least one search result associated with the revised one or more free search terms to the user. 4. The method of claim 1 , wherein the search searches all classes, roles, and individuals of the ontology.
| 0.855228 |
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.
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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. 23. The method of claim 18, wherein the displaying step (g) includes the step of displaying the list of alternative commands as a menu and the selecting step (h) includes the step of selecting and displaying a synonym menu for one of the alternative commands.
| 0.502538 |
33. A method of enabling a client application executing on a computer to perform operations on data objects defined by a model description stored in a machine-readable medium along with a database schema including one or more database tables configured to store a set of data object instances in a database created from the model description and a model application programming interface from the model description that enables the client application to access data objects in the set of data object instances in the same manner as other data objects, the method comprising: using the model application programming interface to create instance of data objects in the database schema including an instance of an object structure having one-to-one and one-to-many mappings; storing the created data object instances in a machine-readable medium; accessing the created data object instances as a separate data objects with the client application; and performing operations on the accessed data object instances including storing, reading and modifying attributes of the data objects.
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33. A method of enabling a client application executing on a computer to perform operations on data objects defined by a model description stored in a machine-readable medium along with a database schema including one or more database tables configured to store a set of data object instances in a database created from the model description and a model application programming interface from the model description that enables the client application to access data objects in the set of data object instances in the same manner as other data objects, the method comprising: using the model application programming interface to create instance of data objects in the database schema including an instance of an object structure having one-to-one and one-to-many mappings; storing the created data object instances in a machine-readable medium; accessing the created data object instances as a separate data objects with the client application; and performing operations on the accessed data object instances including storing, reading and modifying attributes of the data objects. 41. The method of claim 33 further comprising ordering retrieved data by a value of an attribute of the data.
| 0.837424 |
1. A method comprising: receiving, at a client from a server, data comprising a dashboard, the dashboard being generated at the server by converting each of a spreadsheet file and a dashboard structure file into a text-based, language-independent data interchange format, wherein the dashboard comprises a first component, a second component, and a third component, wherein a rendering of the first component and the second component is dependent on data from a data source, wherein at least one of the first component and the second component comprise a visual component adapted to provide a visual representation of the data from the data source, wherein the third component comprises a prompt, wherein the prompt is adapted to request, from a user, an input of one or more values, wherein one or more cells in the spreadsheet file are changed based on the one or more values input by the user in response to the prompt, and wherein the data source includes the one or more cells in the spreadsheet file; asynchronously rendering the first component, the second component, and the third component in a graphical user interface at the client, the asynchronous rendering occurring via a plurality of operations comprising: providing a first notification to a data source listener of the data source that data is required to render the first component; providing a second notification to the data source listener that data is required to render the second component; while the client renders the third component of the dashboard, allowing the data source to perform a single batch fetch operation to fetch both the data required to render the first component and the data required to render the second component; and in response to the data source listener indicating that the data source has fetched the data required to render the first component and the data required to render the second component: receiving, from the data source, the data required to render the first component and the data required to render the second component; executing at least one query based on the data received from the data source; and rendering the first component and the second component of the dashboard using a result of the at least one query.
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1. A method comprising: receiving, at a client from a server, data comprising a dashboard, the dashboard being generated at the server by converting each of a spreadsheet file and a dashboard structure file into a text-based, language-independent data interchange format, wherein the dashboard comprises a first component, a second component, and a third component, wherein a rendering of the first component and the second component is dependent on data from a data source, wherein at least one of the first component and the second component comprise a visual component adapted to provide a visual representation of the data from the data source, wherein the third component comprises a prompt, wherein the prompt is adapted to request, from a user, an input of one or more values, wherein one or more cells in the spreadsheet file are changed based on the one or more values input by the user in response to the prompt, and wherein the data source includes the one or more cells in the spreadsheet file; asynchronously rendering the first component, the second component, and the third component in a graphical user interface at the client, the asynchronous rendering occurring via a plurality of operations comprising: providing a first notification to a data source listener of the data source that data is required to render the first component; providing a second notification to the data source listener that data is required to render the second component; while the client renders the third component of the dashboard, allowing the data source to perform a single batch fetch operation to fetch both the data required to render the first component and the data required to render the second component; and in response to the data source listener indicating that the data source has fetched the data required to render the first component and the data required to render the second component: receiving, from the data source, the data required to render the first component and the data required to render the second component; executing at least one query based on the data received from the data source; and rendering the first component and the second component of the dashboard using a result of the at least one query. 5. A method as in claim 1 , wherein the at least one query includes a filter parameterized by the one or more values.
| 0.581797 |
13. A method of using a portable, real time voice translation, the method comprising: obtaining a translation system for use on a single unit, portable device having a processor and a memory, the translation system having a computer program that is operable for executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase to (i) a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; and, (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language; the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than 0.010 seconds; and, executing the computer program.
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13. A method of using a portable, real time voice translation, the method comprising: obtaining a translation system for use on a single unit, portable device having a processor and a memory, the translation system having a computer program that is operable for executing the following functions: accessing a multilanguage database embodied in a non-transitory computer readable storage medium including a plurality of phrase templates associated with a respective plurality of phrases; selecting a source language from a plurality of source languages and a destination language from a plurality of destination languages; inputting a source phrase; transmitting the source phrase to (i) a speech recognition module embodied in a non-transitory computer readable storage medium for converting the spoken source phrase into a recognized source phrase; (ii) a translation engine embodied in a non-transitory computer readable storage medium for translating the recognized source phrase in the selected source language into a destination phrase in a destination language selected from multiple languages, wherein the plurality of phrases in the multilanguage database include the destination phrase; and, (iii) a template look-up engine embodied in a non-transitory computer readable storage medium for finding the phrase template associated with the destination phrase from among the multiple languages; and, outputting the spoken translation in the selected destination language; the translation system having a total time between the input of the source phrase and output of the destination phrase that is no slower than 0.010 seconds; and, executing the computer program. 24. The method of claim 13 , wherein the executing includes accessing a plurality of phrase templates that represent languages that include at least a combination of English, French, and Spanish; English, Japanese, and Mandarin; English, French, and Portuguese; English, Russian, and Mandarin; English, Hindustani, and Japanese; or, English, Arabic, and Russian.
| 0.587624 |
1. A method for handling events in a distributed computing system including a plurality of devices connected by a network, said method comprising: obtaining, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtaining an address for said remote service within the distributed computing system; automatically constructing, by computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receiving, by the event message endpoint on the client platform in the distributed computing system, indications from one or more client processes registering interest in receiving one or more of the plurality of events generated by the remote service in the distributed computing system; the event message endpoint automatically subscribing to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receiving, by the event message endpoint over a network, a message in a markup language sent to the client platform in the distributed computing system from the remote service in the distributed computing system, wherein the message is received at the event message endpoint from the remote service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the remote service to which the event message endpoint is subscribed; and sending, from the event message endpoint, the markup language representation of the event to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform.
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1. A method for handling events in a distributed computing system including a plurality of devices connected by a network, said method comprising: obtaining, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtaining an address for said remote service within the distributed computing system; automatically constructing, by computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receiving, by the event message endpoint on the client platform in the distributed computing system, indications from one or more client processes registering interest in receiving one or more of the plurality of events generated by the remote service in the distributed computing system; the event message endpoint automatically subscribing to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receiving, by the event message endpoint over a network, a message in a markup language sent to the client platform in the distributed computing system from the remote service in the distributed computing system, wherein the message is received at the event message endpoint from the remote service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the remote service to which the event message endpoint is subscribed; and sending, from the event message endpoint, the markup language representation of the event to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform. 4. The method as recited in claim 1 , further comprising the event message endpoint verifying type correctness of the markup language message according to the markup language schema prior to said sending the markup language representation of the event to the at least one of the one or more client processes.
| 0.738964 |
15. A method for decompressing textual data using a dictionary comprising: receiving the dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the textual data listing one or more of the identifiers, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; replacing each identifier listed within the textual data with the key associated with the identifier within the dictionary, in an iterative manner, until there are no identifiers listed within the textual data; and, outputting the textual data within which the identifiers have been replaced with keys associated with the identifiers within the dictionary.
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15. A method for decompressing textual data using a dictionary comprising: receiving the dictionary, the dictionary having a plurality of keys, each key associated with an identifier, the textual data listing one or more of the identifiers, the keys comprising: a plurality of static word or phrase keys, each static word or phrase key listing one or more unchanging words in a particular order; and, a plurality of dynamic phrase keys, each dynamic phrase key listing a plurality of words and one or more placeholders in a particular order, each placeholder denoting a place where a word or phrase other than the words of the dynamic phrase key is to be inserted; replacing each identifier listed within the textual data with the key associated with the identifier within the dictionary, in an iterative manner, until there are no identifiers listed within the textual data; and, outputting the textual data within which the identifiers have been replaced with keys associated with the identifiers within the dictionary. 18. The method of claim 15 , wherein at least one of the dynamic phrase keys identifies one or more of the words of the dynamic phrase key by identifiers for corresponding static words or phrase keys.
| 0.585027 |
19. The computing device of claim 15 , wherein the dependency graph generator includes: a variable follower configured to generate the dependency graph by following on variables resulting from each code statement of the first syntax tree; and a weight assigner configured to assign weights to the nodes of the dependency graph.
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19. The computing device of claim 15 , wherein the dependency graph generator includes: a variable follower configured to generate the dependency graph by following on variables resulting from each code statement of the first syntax tree; and a weight assigner configured to assign weights to the nodes of the dependency graph. 20. The computing device of claim 19 , the weight assigner is configured to: assign a first weight to nodes of the dependency graph corresponding to code statements that start asynchronous operations; assign a second weight to nodes of the dependency graph corresponding to code statements that await; and assign a third weight to nodes of the dependency graph not assigned the first weight and not assigned the second weight.
| 0.806299 |
14. A system for automatically generating a customer interaction log for an interaction between a customer and agent, the system comprising: at least one processing unit configured to execute components; an analysis component configured to automatically analyze received input corresponding to an interaction in the form of a call transcript between the customer and the agent to generate the customer interaction log using at least one model; a display generation component configured to generate a display of the customer interaction log for agent review at a graphical user interface of an agent computer; a feedback collection component configured to enable the agent to provide agent feedback associated with the displayed generated customer interaction log by way of the graphical user interface; and at least one learning component configured to analyze the agent feedback to determine updating of at least the customer interaction log based on the agent feedback.
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14. A system for automatically generating a customer interaction log for an interaction between a customer and agent, the system comprising: at least one processing unit configured to execute components; an analysis component configured to automatically analyze received input corresponding to an interaction in the form of a call transcript between the customer and the agent to generate the customer interaction log using at least one model; a display generation component configured to generate a display of the customer interaction log for agent review at a graphical user interface of an agent computer; a feedback collection component configured to enable the agent to provide agent feedback associated with the displayed generated customer interaction log by way of the graphical user interface; and at least one learning component configured to analyze the agent feedback to determine updating of at least the customer interaction log based on the agent feedback. 15. The system of claim 14 further comprising a text normalizing component configured to transform the received input comprising at least one of: a disfluency component configured to remove disfluencies from received text; a vocabulary normalizing component configured to normalize vocabulary in the received text; a character normalizing component configured to normalize alphanumeric characters in the received text; a word correction component configured to correct misspellings or incorrectly recognized words in the received text; a sentence detection component configured to detect sentence boundaries in the received text; a sentence capitalization component configured to capitalize letters in sentences in the received text; and a call segment component configured to detect call segment boundaries in the received text.
| 0.5 |
29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of an agent device, including instructions configured to cause a data processing apparatus to: determine availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmit availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detect data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participate in a real-time interaction option as an active relevant agent associated with the topic data.
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29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of an agent device, including instructions configured to cause a data processing apparatus to: determine availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmit availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detect data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participate in a real-time interaction option as an active relevant agent associated with the topic data. 31. The computer-program product of claim 29 , wherein status data is active or inactive, wherein status data is active when a relevant agent associated with the topic is active, and wherein status data is inactive when a relevant agent associated with the topic is inactive.
| 0.506076 |
1. A method comprising: determining, by a processor, one or more metric values for a news source based at least in part on at least one of a number of articles produced by the news source during a first time period, an average length of an article produced by the news source, an amount of coverage that the news source produces in a second time period, a breaking news score, an amount of network traffic to the news source, a human opinion of the news source, circulation statistics of the news source, a size of a staff associated with the news source, a number of bureaus associated with the news source, a number of original named entities in a group of articles associated with the news source, a breadth of coverage by the news source, a number of different countries from which network traffic to the news source originates, or a writing style used by the news source determining, by the processor, an importance metric value representing the amount of coverage that the news source produces in a second time period, where the determining an importance metric includes: determining, by the processor, for each article produced by the news source during the second time period, a number of other non-duplicate articles on a same subject produced by other news sources to produce an importance value for the article, and adding, by the processor, the importance values to obtain the importance metric value; generating, by the processor, a quality value for the news source based at least in part on the determined one or more metric values; and using, by the processor, the quality value to rank an object associated with the news source.
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1. A method comprising: determining, by a processor, one or more metric values for a news source based at least in part on at least one of a number of articles produced by the news source during a first time period, an average length of an article produced by the news source, an amount of coverage that the news source produces in a second time period, a breaking news score, an amount of network traffic to the news source, a human opinion of the news source, circulation statistics of the news source, a size of a staff associated with the news source, a number of bureaus associated with the news source, a number of original named entities in a group of articles associated with the news source, a breadth of coverage by the news source, a number of different countries from which network traffic to the news source originates, or a writing style used by the news source determining, by the processor, an importance metric value representing the amount of coverage that the news source produces in a second time period, where the determining an importance metric includes: determining, by the processor, for each article produced by the news source during the second time period, a number of other non-duplicate articles on a same subject produced by other news sources to produce an importance value for the article, and adding, by the processor, the importance values to obtain the importance metric value; generating, by the processor, a quality value for the news source based at least in part on the determined one or more metric values; and using, by the processor, the quality value to rank an object associated with the news source. 14. The method of claim 1 where in determining the one or more metric values, non-duplicate articles are weighted differently than duplicate articles.
| 0.645967 |
14. The method of claim 1 , further comprising sending one or more of the structured queries for presentation to the first user.
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14. The method of claim 1 , further comprising sending one or more of the structured queries for presentation to the first user. 15. The method of claim 14 , further comprising presenting the one or more sent structured queries to the first user, wherein, for each sent structured query, one or more of the references of the sent structured query is highlighted as presented to indicate the reference corresponds to an identified node or an identified edge.
| 0.872973 |
1. An apparatus comprising: one or more processors; a memory storing a program to be executed by the one or more processors, wherein the program causes the one or more processors to execute; converting input image data to a bitmap data format; extracting feature information of an object of interest in the input image data from the input image data of the bitmap data format; referring to a dictionary and determining a similarity between feature information of an object registered in the dictionary and the feature information of the object of interest extracted from the input image data, wherein, in the dictionary, feature information of a plurality of objects are stored, each feature information is classified into one of a plurality of object-groups based on the similarity, and each feature information is associated with the image data in which an object represented by the feature information is included; registering, in the dictionary, the feature information of the object of the interest extracted from the input image data; determining whether a number of common images between an object-group of interest in the plurality of object-groups and object-groups other than the object-group of interest satisfy a predetermined criterion; and if the number of common images does not satisfy the predetermined criterion, updating the dictionary so that the feature information included in the object-group of interest is unusable when the dictionary is used for determining.
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1. An apparatus comprising: one or more processors; a memory storing a program to be executed by the one or more processors, wherein the program causes the one or more processors to execute; converting input image data to a bitmap data format; extracting feature information of an object of interest in the input image data from the input image data of the bitmap data format; referring to a dictionary and determining a similarity between feature information of an object registered in the dictionary and the feature information of the object of interest extracted from the input image data, wherein, in the dictionary, feature information of a plurality of objects are stored, each feature information is classified into one of a plurality of object-groups based on the similarity, and each feature information is associated with the image data in which an object represented by the feature information is included; registering, in the dictionary, the feature information of the object of the interest extracted from the input image data; determining whether a number of common images between an object-group of interest in the plurality of object-groups and object-groups other than the object-group of interest satisfy a predetermined criterion; and if the number of common images does not satisfy the predetermined criterion, updating the dictionary so that the feature information included in the object-group of interest is unusable when the dictionary is used for determining. 7. The apparatus according to claim 1 , wherein the dictionary is used for identifying a person.
| 0.692961 |
12. A method of investigating a suspicious uniform resource locator to determine whether a server referenced by the uniform resource locator may be involved in fraudulent activity, the method comprising: accessing, by a computer, a data source to obtain data about a suspicious activity; downloading, using the computer, the data from the data source; ascertaining, by using the computer to parse the obtained data, a uniform resource locator involved with the suspicious activity, wherein the uniform resource locator is associated with an anchor, the anchor comprising a displayed address; ascertaining, by the computer, the displayed address indicated by the anchor associated with the uniform resource locator; ascertaining, by the computer, an actual address associated with a server referenced by the uniform resource locator; comparing, by the computer, the displayed address with the actual address associated with the server referenced by the uniform resource locator, wherein the displayed address comprises at least one of a first domain and a first internet protocol (IP) address, and wherein the actual address associated with the server referenced by the uniform resource locator comprises at least one of a second domain and a second IP address, and further wherein comparing the displayed address with the actual address associated with the server referenced by the uniform resource locator comprises determining whether the displayed address is different than the actual address associated with the server referenced by the uniform resource locator by performing at least one of a comparison between the first domain and the second domain, and between the first IP address and the second IP address; obtaining, by the computer, domain information about the displayed address; obtaining, by the computer, WHOIS ownership information about the displayed address; comparing, by the computer, the obtained domain information about the displayed address with the WHOIS ownership information about the displayed address; and determining, by the computer and based on the comparison of the obtained domain information about the displayed address with the WHOIS ownership information about the displayed address and the comparison of the displayed address with the actual address associated with the server referenced by the uniform resource locator, whether the uniform resource locator is fraudulent.
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12. A method of investigating a suspicious uniform resource locator to determine whether a server referenced by the uniform resource locator may be involved in fraudulent activity, the method comprising: accessing, by a computer, a data source to obtain data about a suspicious activity; downloading, using the computer, the data from the data source; ascertaining, by using the computer to parse the obtained data, a uniform resource locator involved with the suspicious activity, wherein the uniform resource locator is associated with an anchor, the anchor comprising a displayed address; ascertaining, by the computer, the displayed address indicated by the anchor associated with the uniform resource locator; ascertaining, by the computer, an actual address associated with a server referenced by the uniform resource locator; comparing, by the computer, the displayed address with the actual address associated with the server referenced by the uniform resource locator, wherein the displayed address comprises at least one of a first domain and a first internet protocol (IP) address, and wherein the actual address associated with the server referenced by the uniform resource locator comprises at least one of a second domain and a second IP address, and further wherein comparing the displayed address with the actual address associated with the server referenced by the uniform resource locator comprises determining whether the displayed address is different than the actual address associated with the server referenced by the uniform resource locator by performing at least one of a comparison between the first domain and the second domain, and between the first IP address and the second IP address; obtaining, by the computer, domain information about the displayed address; obtaining, by the computer, WHOIS ownership information about the displayed address; comparing, by the computer, the obtained domain information about the displayed address with the WHOIS ownership information about the displayed address; and determining, by the computer and based on the comparison of the obtained domain information about the displayed address with the WHOIS ownership information about the displayed address and the comparison of the displayed address with the actual address associated with the server referenced by the uniform resource locator, whether the uniform resource locator is fraudulent. 19. A method as recited in claim 12 , wherein the data source comprises a newsgroup.
| 0.524264 |
16. The method of claim 15 , wherein the sentence parsing further comprises: identifying grammatical sub-components of the segments; identifying grammatical sub-components of the analogy phrase; and matching at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component.
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16. The method of claim 15 , wherein the sentence parsing further comprises: identifying grammatical sub-components of the segments; identifying grammatical sub-components of the analogy phrase; and matching at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component. 17. The method of claim 16 , further comprising assigning the match to the replaced anaphora in the created sentence structure.
| 0.890489 |
1. A method of correcting transcribed text utilizing a computer-processing system, the computer-processing system having a browser-based user interface, the method comprising: receiving a first plurality of audio data sets from one or more audio data sources, wherein at least two of the first plurality of audio data sets are associated with different speakers; transcribing the first plurality of audio data sets based on a voice-independent model to generate a plurality of text data sets, wherein at least two of the plurality of text data sets are associated with different speakers; storing the plurality of text data sets; making the plurality of text data sets available to a plurality of users over at least one computer network through the browser-based user interface; receiving a plurality of corrected text data sets over the at least one computer network from at least one of the plurality of users through the browser-based user interface, wherein the plurality of corrected text data sets are associated with the plurality of text data sets and at least two of the plurality of corrected text data sets are associated with different speakers; updating the voice-independent model based on the plurality of corrected text data sets received through the browser-based interface; and transcribing a second plurality of audio data sets based on the voice-independent model as updated, wherein at least two of the second plurality of audio data sets are associated with different speakers.
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1. A method of correcting transcribed text utilizing a computer-processing system, the computer-processing system having a browser-based user interface, the method comprising: receiving a first plurality of audio data sets from one or more audio data sources, wherein at least two of the first plurality of audio data sets are associated with different speakers; transcribing the first plurality of audio data sets based on a voice-independent model to generate a plurality of text data sets, wherein at least two of the plurality of text data sets are associated with different speakers; storing the plurality of text data sets; making the plurality of text data sets available to a plurality of users over at least one computer network through the browser-based user interface; receiving a plurality of corrected text data sets over the at least one computer network from at least one of the plurality of users through the browser-based user interface, wherein the plurality of corrected text data sets are associated with the plurality of text data sets and at least two of the plurality of corrected text data sets are associated with different speakers; updating the voice-independent model based on the plurality of corrected text data sets received through the browser-based interface; and transcribing a second plurality of audio data sets based on the voice-independent model as updated, wherein at least two of the second plurality of audio data sets are associated with different speakers. 25. The method of claim 1 , further comprising automatically selecting a template for formatting the text data.
| 0.545702 |
6. A system ( 102 ) for automated User Interface (UI) testing through model driven techniques comprising a processor ( 202 ) and memory ( 206 ) coupled to said processor, the system comprising: a selection module ( 210 ) configured to select a UI model; a test case model creation module ( 212 ) configured to create a test case model for the selected UI model and populate the created test case model into a test case editor ( 222 ) wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; a validation module ( 214 ) configured to validate the test case model for the selected UI model; a script generation module ( 216 ) configured to generate a test case script from the test case model for the selected UI model.
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6. A system ( 102 ) for automated User Interface (UI) testing through model driven techniques comprising a processor ( 202 ) and memory ( 206 ) coupled to said processor, the system comprising: a selection module ( 210 ) configured to select a UI model; a test case model creation module ( 212 ) configured to create a test case model for the selected UI model and populate the created test case model into a test case editor ( 222 ) wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; a validation module ( 214 ) configured to validate the test case model for the selected UI model; a script generation module ( 216 ) configured to generate a test case script from the test case model for the selected UI model. 7. The system of claim 6 wherein the test case model for the selected UI model is created as the sequence of UI actions, and wherein the sequence of UI actions comprises at least one of an event-centric approach, and a user-interaction centric approach.
| 0.639509 |
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