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10. A method of providing search results comprising: determining whether a webpage selected by a first user is valid, the validity of the webpage being determined based on analysis of text content of the selected webpage; receiving a search query from a second user, wherein search results obtained in response to the search query comprise the webpage selected by the first user; correcting the search results obtained in response to the search query if it is determined that the webpage is not valid; and providing the second user with the corrected search results. | 10. A method of providing search results comprising: determining whether a webpage selected by a first user is valid, the validity of the webpage being determined based on analysis of text content of the selected webpage; receiving a search query from a second user, wherein search results obtained in response to the search query comprise the webpage selected by the first user; correcting the search results obtained in response to the search query if it is determined that the webpage is not valid; and providing the second user with the corrected search results. 11. The method according to claim 10 , wherein the determining whether the selected webpage is valid comprises: accessing, if it is detected that the webpage is selected by the first user, the selected webpage and analyzing validity of the selected webpage; and storing analysis results. | 0.724291 |
11. A method comprising: receiving stroke data; identifying, by use of a processor, a handwritten character from stroke data; mapping the handwritten character to a user-specific font character based on the stroke data, wherein mapping the handwritten character to a user-specific font character comprises: determining whether the stroke data of the handwritten character matches a font character of a user-specific font set associated with a user inputting the stroke data, selecting a matching font character, in response to the stroke data matching the font character, and generating a new font character based on the stroke data, in response to the stroke data not matching any font character of the font set; and storing, to a file, a character encoding corresponding to the user-specific font character. | 11. A method comprising: receiving stroke data; identifying, by use of a processor, a handwritten character from stroke data; mapping the handwritten character to a user-specific font character based on the stroke data, wherein mapping the handwritten character to a user-specific font character comprises: determining whether the stroke data of the handwritten character matches a font character of a user-specific font set associated with a user inputting the stroke data, selecting a matching font character, in response to the stroke data matching the font character, and generating a new font character based on the stroke data, in response to the stroke data not matching any font character of the font set; and storing, to a file, a character encoding corresponding to the user-specific font character. 15. The method of claim 11 , further comprising displaying a text character indicated by the character encoding using the user-specific font character. | 0.680372 |
13. The method of claim 12, further comprising the step of: providing each one of the plurality of expressions with a predicate and at least one argument, wherein the predicate specifies relationships between the plurality of fields in the plurality of database tables. | 13. The method of claim 12, further comprising the step of: providing each one of the plurality of expressions with a predicate and at least one argument, wherein the predicate specifies relationships between the plurality of fields in the plurality of database tables. 14. The method of claim 13, further comprising the step of: providing the at least one argument with any of a combination of explicit fields and implicit fields and a list of attributes that identify the predicate. | 0.874497 |
15. A system that presents a customized application page in an application, the system comprising: an network adapter that receives an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; and a processor that executes a shell module communicatively coupled to the network adapter, the shell rendering an offering tile on a display by the application, the offering tile displaying a graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus, receiving a target page identifier in response to a user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, the processor further executing a user interface framework coupled to the shell module that renders the customized application page defined by the identified markup data on the display to include at least one resource included in the application package. | 15. A system that presents a customized application page in an application, the system comprising: an network adapter that receives an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; and a processor that executes a shell module communicatively coupled to the network adapter, the shell rendering an offering tile on a display by the application, the offering tile displaying a graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus, receiving a target page identifier in response to a user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, the processor further executing a user interface framework coupled to the shell module that renders the customized application page defined by the identified markup data on the display to include at least one resource included in the application package. 16. The system of claim 15 wherein the network adapter further periodically receives additional application packages from a media information system server to replace the received application package, each received application package sharing a common target page identifier used by the application to reference customized application pages. | 0.589928 |
19. The computer program product of claim 18 , wherein, to process the query against the dimensional model, the program code of the computer program product causes the computer to: for each of the one or more of the plurality of attributes for which a query attribute value is specified, select the rows of the dimension tables corresponding to the attribute that matches the query attribute value; join the selected rows of the dimension tables to the fact table to produce a join result; and generate a query result containing the URLs contained by the rows of the join result. | 19. The computer program product of claim 18 , wherein, to process the query against the dimensional model, the program code of the computer program product causes the computer to: for each of the one or more of the plurality of attributes for which a query attribute value is specified, select the rows of the dimension tables corresponding to the attribute that matches the query attribute value; join the selected rows of the dimension tables to the fact table to produce a join result; and generate a query result containing the URLs contained by the rows of the join result. 20. The computer program product of claim 19 , wherein the generated query result contains one or more attribute values extracted from the webpages corresponding to the URLs contained by the rows of the join result. | 0.694901 |
18. The system of claim 15 , wherein monitoring users navigating the query search results comprises: presenting a given user with search results responsive to a query to a corresponding one of the search queries; monitoring the given user accessing a first one of the information assets identified in the set of search results, and subsequently, accessing a second one of the information assets; and updating a weighted relationship between the first information asset and the second information asset in the semantic graph. | 18. The system of claim 15 , wherein monitoring users navigating the query search results comprises: presenting a given user with search results responsive to a query to a corresponding one of the search queries; monitoring the given user accessing a first one of the information assets identified in the set of search results, and subsequently, accessing a second one of the information assets; and updating a weighted relationship between the first information asset and the second information asset in the semantic graph. 19. The system of claim 18 , wherein a weight specified for the weighted relationship is increased each time one the users navigates from the first information asset to the second information asset, and wherein the operation further comprises, upon determining the weight exceeds a specified threshold, updating the semantic graph with an edge connecting nodes in the semantic graph corresponding to the first information asset and the second information asset. | 0.933256 |
1. An information processing apparatus, comprising: circuitry configured to determine at least one action of a user based on motion data received from a motion sensor, determine at least one event associated with text information, the text information being obtained from at least one of social media content and audio data, generate state information of the user based on the at least one action and the at least one event, and provide information related to the state information to the user, wherein the state information includes an attainment level indicating a current attainment level with respect to a goal, a current value related to a current state of the goal, which is acquired by the at least one action, and a comparison value obtained by comparing the current value related to the current state of the goal and a past value related to a past state of the goal, the comparison value being a value acquired from the at least one action. | 1. An information processing apparatus, comprising: circuitry configured to determine at least one action of a user based on motion data received from a motion sensor, determine at least one event associated with text information, the text information being obtained from at least one of social media content and audio data, generate state information of the user based on the at least one action and the at least one event, and provide information related to the state information to the user, wherein the state information includes an attainment level indicating a current attainment level with respect to a goal, a current value related to a current state of the goal, which is acquired by the at least one action, and a comparison value obtained by comparing the current value related to the current state of the goal and a past value related to a past state of the goal, the comparison value being a value acquired from the at least one action. 2. The information processing apparatus according to claim 1 , wherein the at least one action includes a physical activity undertaken by the user. | 0.86372 |
2. The computer-implemented method of claim 1 , further comprising: at the query converter, identifying a first set of fields in the unstructured data to obtain field identification data from the unstructured data, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes using the identified first set of fields to generate the second query. | 2. The computer-implemented method of claim 1 , further comprising: at the query converter, identifying a first set of fields in the unstructured data to obtain field identification data from the unstructured data, the unstructured data including text records, each of the fields in the first set of fields corresponding to a portion of text extracted from a portion of at least one of the text records; wherein generating the second query in the second query language associated with the unstructured data store includes using the identified first set of fields to generate the second query. 7. The computer-implemented method of claim 2 , wherein the first query comprises a Structured Query Language (“SQL”) query. | 0.955768 |
1. A computer implemented method for enabling an application for Conversational Understanding (CU) using assets in a CU service, comprising: receiving a selection of Application Programming Interfaces (APIs) that are associated with a domain to use in the application; automatically updating models for the CU service based on the selection of the APIs and the determined domain; receiving a Natural Language (“NL”) expression, wherein the NL expression may be used to interact with the application; rephrasing the NL expressions to generate at least one additional expression, wherein the at least one additional expression contains a different, way of expressing a meaning of the NL expression; and automatic updating the models for CU service based on the rephrased NL expressions; making the models available to the CU service. | 1. A computer implemented method for enabling an application for Conversational Understanding (CU) using assets in a CU service, comprising: receiving a selection of Application Programming Interfaces (APIs) that are associated with a domain to use in the application; automatically updating models for the CU service based on the selection of the APIs and the determined domain; receiving a Natural Language (“NL”) expression, wherein the NL expression may be used to interact with the application; rephrasing the NL expressions to generate at least one additional expression, wherein the at least one additional expression contains a different, way of expressing a meaning of the NL expression; and automatic updating the models for CU service based on the rephrased NL expressions; making the models available to the CU service. 9. The method of claim 1 , wherein the detected domain is sports. | 0.839909 |
1. A system including computer executable instructions on a computer storage media and the computer executable instructions being executed by a processing unit to implement one or more components comprising: a node generator configured to receive a parsed natural language sentence or phrase and recover phrasal and constituent nodes and grammatical tags for the phrasal and constituent nodes of the parsed natural language sentence or phrase and the node generator uses a head analysis component to analyze the phrasal and constituent nodes and grammatical tags of the parsed natural language sentence or phrase to generate hierarchical and dependent nodes of a language neutral representation of the parsed natural language sentence or phrase; and a node dependency generator configured to receive the hierarchical and dependent nodes and the grammatical tags of the parsed natural language sentence and create an iterative dependency structure including a preliminary dependency structure including one or more unlabeled dependencies to one or more semantic heads and a secondary dependency structure including semantic or grammatical labels replacing the one or more unlabeled dependencies to generate an unordered hierarchical dependency structure for the hierarchical and dependent nodes and the semantic or grammatical labels representing a language neutral relation between the hierarchical and dependent nodes different from the grammatical tags of the parsed natural language sentence or phrase using a semantic relation between the hierarchical and dependent nodes derived from the grammatical tags of the parsed natural language sentence or phrase. | 1. A system including computer executable instructions on a computer storage media and the computer executable instructions being executed by a processing unit to implement one or more components comprising: a node generator configured to receive a parsed natural language sentence or phrase and recover phrasal and constituent nodes and grammatical tags for the phrasal and constituent nodes of the parsed natural language sentence or phrase and the node generator uses a head analysis component to analyze the phrasal and constituent nodes and grammatical tags of the parsed natural language sentence or phrase to generate hierarchical and dependent nodes of a language neutral representation of the parsed natural language sentence or phrase; and a node dependency generator configured to receive the hierarchical and dependent nodes and the grammatical tags of the parsed natural language sentence and create an iterative dependency structure including a preliminary dependency structure including one or more unlabeled dependencies to one or more semantic heads and a secondary dependency structure including semantic or grammatical labels replacing the one or more unlabeled dependencies to generate an unordered hierarchical dependency structure for the hierarchical and dependent nodes and the semantic or grammatical labels representing a language neutral relation between the hierarchical and dependent nodes different from the grammatical tags of the parsed natural language sentence or phrase using a semantic relation between the hierarchical and dependent nodes derived from the grammatical tags of the parsed natural language sentence or phrase. 7. The system of claim 1 wherein the node dependency generator is configured to create the unordered hierarchical dependency structure to represent logical scope and relation of constituents of a noun phrase or verb phrase using the grammatical tags and syntax of the parsed natural language sentence or phase and scope assignment criteria. | 0.53125 |
1. A method comprising: determining, based on a dynamic characteristic of a mobile device of a user, a current device context value of at least one of a plurality of device context parameters; receiving, at the mobile device and over a communications network, context information from each client device of a plurality of client devices, wherein each client device corresponds to a different social contact of a plurality of social contacts of the user, wherein the context information received from each client device comprises information relating to a social context of the client device of the social contact, wherein the information relating to the social context of the client device of the social contact relates to historical application usage information of a plurality of applications of the client device of the social contact; determining, based on the context information received from each client device of the plurality of social contacts of the user, a current social context value of at least one of a plurality of social context parameters; for each of a plurality of applications previously downloaded and stored on the mobile device, calculating, by the mobile device, an application relevance score as a function of the current device context value and the current social context value; identifying at least one of the plurality of applications downloaded to the mobile device as a pinned application; and dynamically updating a display of a plurality of application representations on a graphical user interface (GUI) of the mobile device, such that the application representations are arranged according at least to the application relevance scores, each application representation corresponding to one of the plurality of applications downloaded to the mobile device, the arranging comprising removing at least one application representation of the plurality of application representations according to a frequency of use of each of the plurality of application representations, reordering one or more application representations of the plurality of application representations according to the frequency of use of each such application representation, and listing an application representation corresponding to a most recently used application of the plurality of applications downloaded to the mobile device in a user-designated location of the GUI for the most recently used application, wherein the arrangement of the application representation of the pinned application is fixed and is not affected by changes in the application relevance scores. | 1. A method comprising: determining, based on a dynamic characteristic of a mobile device of a user, a current device context value of at least one of a plurality of device context parameters; receiving, at the mobile device and over a communications network, context information from each client device of a plurality of client devices, wherein each client device corresponds to a different social contact of a plurality of social contacts of the user, wherein the context information received from each client device comprises information relating to a social context of the client device of the social contact, wherein the information relating to the social context of the client device of the social contact relates to historical application usage information of a plurality of applications of the client device of the social contact; determining, based on the context information received from each client device of the plurality of social contacts of the user, a current social context value of at least one of a plurality of social context parameters; for each of a plurality of applications previously downloaded and stored on the mobile device, calculating, by the mobile device, an application relevance score as a function of the current device context value and the current social context value; identifying at least one of the plurality of applications downloaded to the mobile device as a pinned application; and dynamically updating a display of a plurality of application representations on a graphical user interface (GUI) of the mobile device, such that the application representations are arranged according at least to the application relevance scores, each application representation corresponding to one of the plurality of applications downloaded to the mobile device, the arranging comprising removing at least one application representation of the plurality of application representations according to a frequency of use of each of the plurality of application representations, reordering one or more application representations of the plurality of application representations according to the frequency of use of each such application representation, and listing an application representation corresponding to a most recently used application of the plurality of applications downloaded to the mobile device in a user-designated location of the GUI for the most recently used application, wherein the arrangement of the application representation of the pinned application is fixed and is not affected by changes in the application relevance scores. 4. The method of claim 1 , wherein the at least one device context parameter relates to at least one of: current geographical location of the mobile device; current network usage; current application usage; or current time. | 0.90872 |
35. The method as described in claim 34 , wherein said patent indices and said non-linear transformation are chosen so as to satisfy the following: tending of any one of said patent indices substantially to a respective minimal value, independent of values of other patent indices, results in said Patent Quality index tending substantially to one of the following: the PQ min ; the PQ max . | 35. The method as described in claim 34 , wherein said patent indices and said non-linear transformation are chosen so as to satisfy the following: tending of any one of said patent indices substantially to a respective minimal value, independent of values of other patent indices, results in said Patent Quality index tending substantially to one of the following: the PQ min ; the PQ max . 36. The method as described in claim 35 , comprising selecting the PQ min equal to zero. | 0.934803 |
1. A tabulation device comprising: a grid structure retaining means which maintains text strings composing a table and grid structure; text field size threshold providing means for providing at least a value of one of the width and the height at a plurality of discontinuous points output of a line-breaking function on said text strings composing a table, said line breaking function of a text maps a width/height to a height/width of a rectangular area whose height/width is minimum for laying out the text in said rectangular area; text field size retaining means for retaining a relationship between said text string composing said table and the size of a rectangular area provided by said text field size threshold providing means in response to said text; table layout means for acquiring one of said sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said text and said one of the sizes of rectangular area acquired by said table lay out means, based on said grid structure; and evaluating means responsive to the result of comparison of the tabulation by said table lay out means with predetermined conditions for directing said table layout means to acquire another one of the sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said another one of the sizes of rectangular area and said text. | 1. A tabulation device comprising: a grid structure retaining means which maintains text strings composing a table and grid structure; text field size threshold providing means for providing at least a value of one of the width and the height at a plurality of discontinuous points output of a line-breaking function on said text strings composing a table, said line breaking function of a text maps a width/height to a height/width of a rectangular area whose height/width is minimum for laying out the text in said rectangular area; text field size retaining means for retaining a relationship between said text string composing said table and the size of a rectangular area provided by said text field size threshold providing means in response to said text; table layout means for acquiring one of said sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said text and said one of the sizes of rectangular area acquired by said table lay out means, based on said grid structure; and evaluating means responsive to the result of comparison of the tabulation by said table lay out means with predetermined conditions for directing said table layout means to acquire another one of the sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said another one of the sizes of rectangular area and said text. 5. A tabulation device according to claim 1, wherein: given by defining a group of text strings in a given row or column composing a table as T.sub.1, . . . , T.sub.m, and a group of the sizes of rectangular area retained in the means for retaining the sizes of text field and corresponding to said group of text strings L.sub.1, . . . , L.sub.m, said table lay out means lays out said group of text strings such that the size of rectangular area which is equal to the maximum value of the height or width of said group of the sizes of rectangular area or most approximate to the maximum value among the sizes of rectangular area supplied from the means for providing the size of text field in response to the text string T.sub.i becomes the size L.sub.i of rectangular area for said text string T.sub.i. | 0.5 |
30. A process for selectable input based on motion of a pointing device in relation to a region having a plurality of selectable characters, the process comprising the steps of: tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; determining which of the selected positions along the device path correspond to at least one of the selectable characters; and detecting a characteristic motion of the pointing device, the characteristic motion corresponding to at least one of the selected positions along the device path that correspond to at least one of the selectable characters. | 30. A process for selectable input based on motion of a pointing device in relation to a region having a plurality of selectable characters, the process comprising the steps of: tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; determining which of the selected positions along the device path correspond to at least one of the selectable characters; and detecting a characteristic motion of the pointing device, the characteristic motion corresponding to at least one of the selected positions along the device path that correspond to at least one of the selectable characters. 39. The process of claim 30 , wherein the tracked motion is limited to motion of the pointing device on a planar surface of the region. | 0.780681 |
5. A computer-implemented method for executing an action based on audio data, the computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating first speech processing results comprising a first semantic representation of at least a portion of a first user utterance, the first speech processing results generated using a speech processing system and audio data regarding at least the portion of the first user utterance; determining that a second semantic representation of at least a portion of a second user utterance relates to a correction to the first semantic representation; generating, using the first semantic representation, one or more lexical representations associated with a meaning corresponding to the first semantic representation; storing correction information in an error list separate from the first speech processing results and separate from second speech processing results comprising the second semantic representation, wherein the correction information indicates that the one or more lexical representations are erroneous; determining, using the correction information, that at least a portion of a first speech processing hypothesis, of a plurality of speech processing hypotheses for a third user utterance, corresponds to a lexical representation of the one or more lexical representations; removing the first speech processing hypothesis from the plurality of speech processing hypotheses based at least partly on the determining that at least the portion of the first speech processing hypothesis corresponds to the lexical representation; generating a third semantic representation of at least a portion of the third user utterance using a second speech processing hypothesis of the plurality of speech processing hypotheses instead of the first speech processing hypothesis based at least partly on the second speech processing hypothesis remaining in the plurality of speech processing hypotheses after the first speech processing hypothesis is removed, wherein the first speech processing hypothesis is associated with a first executable action, and wherein the second speech processing hypotheses is associated with a second executable action distinct from the first executable action; and executing the second executable action. | 5. A computer-implemented method for executing an action based on audio data, the computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating first speech processing results comprising a first semantic representation of at least a portion of a first user utterance, the first speech processing results generated using a speech processing system and audio data regarding at least the portion of the first user utterance; determining that a second semantic representation of at least a portion of a second user utterance relates to a correction to the first semantic representation; generating, using the first semantic representation, one or more lexical representations associated with a meaning corresponding to the first semantic representation; storing correction information in an error list separate from the first speech processing results and separate from second speech processing results comprising the second semantic representation, wherein the correction information indicates that the one or more lexical representations are erroneous; determining, using the correction information, that at least a portion of a first speech processing hypothesis, of a plurality of speech processing hypotheses for a third user utterance, corresponds to a lexical representation of the one or more lexical representations; removing the first speech processing hypothesis from the plurality of speech processing hypotheses based at least partly on the determining that at least the portion of the first speech processing hypothesis corresponds to the lexical representation; generating a third semantic representation of at least a portion of the third user utterance using a second speech processing hypothesis of the plurality of speech processing hypotheses instead of the first speech processing hypothesis based at least partly on the second speech processing hypothesis remaining in the plurality of speech processing hypotheses after the first speech processing hypothesis is removed, wherein the first speech processing hypothesis is associated with a first executable action, and wherein the second speech processing hypotheses is associated with a second executable action distinct from the first executable action; and executing the second executable action. 6. The computer-implemented method of claim 5 , wherein the correction information comprises at least a portion of the first semantic representation. | 0.637267 |
6. A system for classifying a sentence as to sentiment, the system comprising: one or more application servers; and a quote extraction module executing on the one or more application servers and configured to acquire training data comprising a plurality of sentences labeled as to sentiment, pre-process the plurality of labeled sentences from the training data, generate a list of terms from the plurality of labeled sentences, determine sentiment scores for the terms in the list of terms based on the plurality of labeled sentences, receive the sentence to be classified, pre-process the sentence, and classify the sentence as having a neutral sentiment, a positive sentiment, or a negative sentiment utilizing a machine learning technique trained on the sentiment scores determined for the terms in the list of terms. | 6. A system for classifying a sentence as to sentiment, the system comprising: one or more application servers; and a quote extraction module executing on the one or more application servers and configured to acquire training data comprising a plurality of sentences labeled as to sentiment, pre-process the plurality of labeled sentences from the training data, generate a list of terms from the plurality of labeled sentences, determine sentiment scores for the terms in the list of terms based on the plurality of labeled sentences, receive the sentence to be classified, pre-process the sentence, and classify the sentence as having a neutral sentiment, a positive sentiment, or a negative sentiment utilizing a machine learning technique trained on the sentiment scores determined for the terms in the list of terms. 12. The system of claim 6 , wherein determining sentiment scores for the terms in the list of terms comprises determining a positive sentiment score, a negative sentiment score, a mixed sentiment score, and a neutral sentiment score for each term in the list of terms utilizing a machine learning technique based on the plurality of labeled sentences. | 0.677955 |
9. A non-transitory computer program product for communication monitoring based on sentiment, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to monitor a new communication prior to sending created by a sender to a recipient, wherein the new communication comprises text input by the sender; program instructions to analyze the text of the new communication using sentiment analysis and program instructions to determine a sentiment score on a scale between negative sentiment and positive sentiment; program instructions to reference an overall relationship score based on past communications between the sender and the recipient in response to the sentiment score for the text of the new communication being on a negative side of a first predefined threshold on the scale; program instructions to hold a transmission of the new communication or activating another action in response to the overall relationship score being on the negative side of a second predefined threshold in response to the overall relationship score being on the negative side of a second predefined threshold; and program instructions to send a notification to at least one of the sender or a supervisor of the sender in response to the overall relationship score being on the negative side of the second predefined threshold. | 9. A non-transitory computer program product for communication monitoring based on sentiment, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to monitor a new communication prior to sending created by a sender to a recipient, wherein the new communication comprises text input by the sender; program instructions to analyze the text of the new communication using sentiment analysis and program instructions to determine a sentiment score on a scale between negative sentiment and positive sentiment; program instructions to reference an overall relationship score based on past communications between the sender and the recipient in response to the sentiment score for the text of the new communication being on a negative side of a first predefined threshold on the scale; program instructions to hold a transmission of the new communication or activating another action in response to the overall relationship score being on the negative side of a second predefined threshold in response to the overall relationship score being on the negative side of a second predefined threshold; and program instructions to send a notification to at least one of the sender or a supervisor of the sender in response to the overall relationship score being on the negative side of the second predefined threshold. 10. The computer program product as claimed in claim 9 , wherein the overall relationship score is generated by program instructions to perform sentiment analysis on text content of past communications between the sender and the recipient and program instructions to determine the sentiment score on the scale between negative sentiment and positive sentiment. | 0.538291 |
1. A computer-implemented method comprising: receiving, by a computer system, a request to predict a next word to occur in a phrase being uttered by a first user in a dialog between the first user and a second user; accessing, by the computer system, a neural network comprising i) an input layer that includes a first portion representing a local context for the phrase and a second portion representing a semantic context for the phrase, ii) one or more hidden layers that are at least partially interconnected with the input layer by first connections, and iii) an output layer that represents a vocabulary of candidate words and that is at least partially interconnected with at least one of the one or more hidden layers by second connections; identifying, by the computer system, the local context for the phrase being uttered by the first user; identifying, by the computer system, text of one or more previous messages communicated (i) between the first user and the second user, and (ii) before initiation of the dialog between the first user and the second user; determining, by the computer system and based at least on the identified text of the one or more previous messages, at least one vector that represent the semantic context for the phrase, the at least one vector including values for a plurality of dimensions; applying, by the computer system, input to the input layer of the neural network, the input comprising i) the local context of the phrase and ii) the values for the plurality of dimensions of the at least one vector that represents the semantic context of the phrase; generating, by the computer system, probability values for at least a portion of the candidate words in the vocabulary of the output layer based on propagation of the input through the neural network using, at least, the first connections and the second connections between layers of the neural network; using, by the computer system, the generated probability values to determine a transcription for the phrase uttered by the first user; and providing, by the computer system and as output of an automated speech recognizer, the transcription determined using the generated probability values. | 1. A computer-implemented method comprising: receiving, by a computer system, a request to predict a next word to occur in a phrase being uttered by a first user in a dialog between the first user and a second user; accessing, by the computer system, a neural network comprising i) an input layer that includes a first portion representing a local context for the phrase and a second portion representing a semantic context for the phrase, ii) one or more hidden layers that are at least partially interconnected with the input layer by first connections, and iii) an output layer that represents a vocabulary of candidate words and that is at least partially interconnected with at least one of the one or more hidden layers by second connections; identifying, by the computer system, the local context for the phrase being uttered by the first user; identifying, by the computer system, text of one or more previous messages communicated (i) between the first user and the second user, and (ii) before initiation of the dialog between the first user and the second user; determining, by the computer system and based at least on the identified text of the one or more previous messages, at least one vector that represent the semantic context for the phrase, the at least one vector including values for a plurality of dimensions; applying, by the computer system, input to the input layer of the neural network, the input comprising i) the local context of the phrase and ii) the values for the plurality of dimensions of the at least one vector that represents the semantic context of the phrase; generating, by the computer system, probability values for at least a portion of the candidate words in the vocabulary of the output layer based on propagation of the input through the neural network using, at least, the first connections and the second connections between layers of the neural network; using, by the computer system, the generated probability values to determine a transcription for the phrase uttered by the first user; and providing, by the computer system and as output of an automated speech recognizer, the transcription determined using the generated probability values. 9. The computer-implemented method of claim 1 , wherein the at least one vector that represents the semantic context for the phrase comprises at least one vector generated using a latent dirichlet allocation (LDA) model. | 0.580494 |
8. A method for generating answers to questions, comprising: receiving an input query; obtaining, from an unstructured data source, a plurality of candidate answers to the input query; performing context independent answer processing to produce a first score for each of the candidate answers; computing specified information about each of the candidate answers during the context independent answer processing; sending the candidate answers to a model selection module; using the model selection module to use the specified information computed about the candidate answers during the context independent answer processing, to select one of a plurality of scoring models; sending each of the candidate answers to the selected one of the scoring models; using the selected one of the scoring models for weighting the first scores for the candidate answers to determine an answer score for each of the candidate answers; and generating at least one answer to the input query based on the answer scores. | 8. A method for generating answers to questions, comprising: receiving an input query; obtaining, from an unstructured data source, a plurality of candidate answers to the input query; performing context independent answer processing to produce a first score for each of the candidate answers; computing specified information about each of the candidate answers during the context independent answer processing; sending the candidate answers to a model selection module; using the model selection module to use the specified information computed about the candidate answers during the context independent answer processing, to select one of a plurality of scoring models; sending each of the candidate answers to the selected one of the scoring models; using the selected one of the scoring models for weighting the first scores for the candidate answers to determine an answer score for each of the candidate answers; and generating at least one answer to the input query based on the answer scores. 11. The method according to claim 8 , wherein the computed specified information is intrinsic to the candidate answers. | 0.874739 |
10. A computer-implemented method, comprising: receiving social media data from a plurality of remote data sources, the received social media data being associated with a plurality of topics; analyzing the received social media data to identify a trending hot topic, the trending hot topic being at least one of a topic rising in citations and a topic rising in use; comparing the trending hot topic with a database of topical terms, the database of topical terms including terms relevant to a predetermined topic associated with a particular topic of interest and wherein the topical terms in the database of topical terms are derived from data in a content database; determining that the trending hot topic is relevant to the predetermined topic; querying the content database using the trending hot topic to identify a caption to be associated with the trending hot topic; appending the caption to the trending hot topic, the appended caption providing an indication of context for the trending hot topic; and storing the trending hot topic and the caption in a database. | 10. A computer-implemented method, comprising: receiving social media data from a plurality of remote data sources, the received social media data being associated with a plurality of topics; analyzing the received social media data to identify a trending hot topic, the trending hot topic being at least one of a topic rising in citations and a topic rising in use; comparing the trending hot topic with a database of topical terms, the database of topical terms including terms relevant to a predetermined topic associated with a particular topic of interest and wherein the topical terms in the database of topical terms are derived from data in a content database; determining that the trending hot topic is relevant to the predetermined topic; querying the content database using the trending hot topic to identify a caption to be associated with the trending hot topic; appending the caption to the trending hot topic, the appended caption providing an indication of context for the trending hot topic; and storing the trending hot topic and the caption in a database. 17. The computer-implemented method of claim 10 , wherein the content database includes content published by a single publishing entity. | 0.838824 |
1. A method for constructing a post-transform template for use with a markup language security message in a light weight data model, comprising: a computer receiving an input byte array associated with the markup language security message, wherein the markup language security message includes a security element and encrypted message data; the computer determining whether a template corresponding to all of the markup language security message or a portion of the markup language security message is located in an automaton; responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is located in the automaton: the computer retrieving a cached lightweight data model corresponding to the markup language security message and a transition sequence that represents all of the markup language security message; the computer parsing the transition sequence using a delta parsing engine, to create a first result; the computer generating the post-transform template using the first result of the delta parsing engine with cached transforms; and the computer storing the post-transform template in the automaton; and responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is not located in the automaton: the computer calling transformers corresponding to transform information stored in the cached lightweight data model to construct the post-transform template, wherein a first process calling a transform using an expression conforming to Xpath produces a first transform result and a second process calling a canonicalization transform using the first transform result produces the post-transform template; the computer storing the post-transform template in the automaton; the computer populating the post-transform template with corresponding actual variable values of the input byte array; and the computer performing a serialization operation using the post transform template as populated to form a serialized byte array. | 1. A method for constructing a post-transform template for use with a markup language security message in a light weight data model, comprising: a computer receiving an input byte array associated with the markup language security message, wherein the markup language security message includes a security element and encrypted message data; the computer determining whether a template corresponding to all of the markup language security message or a portion of the markup language security message is located in an automaton; responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is located in the automaton: the computer retrieving a cached lightweight data model corresponding to the markup language security message and a transition sequence that represents all of the markup language security message; the computer parsing the transition sequence using a delta parsing engine, to create a first result; the computer generating the post-transform template using the first result of the delta parsing engine with cached transforms; and the computer storing the post-transform template in the automaton; and responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is not located in the automaton: the computer calling transformers corresponding to transform information stored in the cached lightweight data model to construct the post-transform template, wherein a first process calling a transform using an expression conforming to Xpath produces a first transform result and a second process calling a canonicalization transform using the first transform result produces the post-transform template; the computer storing the post-transform template in the automaton; the computer populating the post-transform template with corresponding actual variable values of the input byte array; and the computer performing a serialization operation using the post transform template as populated to form a serialized byte array. 5. The method of claim 1 , wherein when one template in the automaton that matches a format or structure of the markup language security message is identified in the automaton, then the transition sequence and data model corresponding to the template identified as a match are also stored in the automaton. | 0.747117 |
7. A system for utilizing a computer for finding infringement of at least one patent, the system comprising: a memory device for storing a program for finding infringement of the at least one patent; and a processor, functionally coupled to the memory device, the processor being responsive to computer-executable instructions contained in the program and operative to: receive patent information related to the at least one patent, associated patent support data relating to the patent information, and reference materials, analyze the patent information, the associated patent support data relating to the patent information, and the reference materials, create a patent search profile based at least in part on analysis of the patent information, the associated patent support data relating to the patent information, and the reference materials, the patent search profile at least including keywords associated with the at least one patent, analyze claim structure of the at least one patent to determine a dependency relationship among at least two claims of the at least one patent, based on analysis of the claim structure of the at least one patent, utilize the keywords of the patent search profile determined to be included in the at least two claims having the dependency relationship together when conducting a search for possible patent infringers, utilize the patent search profile to conduct the search of sources of public information for the possible patent infringers of the at least one patent and to provide patent search results identifying possible patent infringement of the at least one patent, and utilize the patent search results to provide a patent search results report. | 7. A system for utilizing a computer for finding infringement of at least one patent, the system comprising: a memory device for storing a program for finding infringement of the at least one patent; and a processor, functionally coupled to the memory device, the processor being responsive to computer-executable instructions contained in the program and operative to: receive patent information related to the at least one patent, associated patent support data relating to the patent information, and reference materials, analyze the patent information, the associated patent support data relating to the patent information, and the reference materials, create a patent search profile based at least in part on analysis of the patent information, the associated patent support data relating to the patent information, and the reference materials, the patent search profile at least including keywords associated with the at least one patent, analyze claim structure of the at least one patent to determine a dependency relationship among at least two claims of the at least one patent, based on analysis of the claim structure of the at least one patent, utilize the keywords of the patent search profile determined to be included in the at least two claims having the dependency relationship together when conducting a search for possible patent infringers, utilize the patent search profile to conduct the search of sources of public information for the possible patent infringers of the at least one patent and to provide patent search results identifying possible patent infringement of the at least one patent, and utilize the patent search results to provide a patent search results report. 8. The system of claim 7 , wherein the processor is further operative to analyze the patent search profile, the patent information, the associated patent support data, and the reference materials, to create a new patent search profile, and wherein the processor is further operative to utilize previous patent search results. | 0.724597 |
10. A speech recognition method for a speech recognition system comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value; and (d) adjusting an amount of prompting provided to the user based upon said user's level of experience to assist the user in delivering speech commands to the system wherein the adjusting includes providing users having less experience with automatic speech recognition with prompting that is more detailed than that provided for users having more experience with automatic speech recognition. | 10. A speech recognition method for a speech recognition system comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value; and (d) adjusting an amount of prompting provided to the user based upon said user's level of experience to assist the user in delivering speech commands to the system wherein the adjusting includes providing users having less experience with automatic speech recognition with prompting that is more detailed than that provided for users having more experience with automatic speech recognition. 19. The speech recognition method of claim 10 , further comprising the step of determining the user's experience level with a group of commands. | 0.629949 |
13. A device according to claim 12 , wherein said displayable items are web pages, the display control arrangement comprising a web browser for viewing the web pages. | 13. A device according to claim 12 , wherein said displayable items are web pages, the display control arrangement comprising a web browser for viewing the web pages. 16. A device according to claim 13 , wherein the transport-control elements are part of a currently displayed web page. | 0.943013 |
11. A computing platform comprising a processor with access to a computer-readable medium embodying program components, the program components comprising: a text engine configured to provide text data comprising a plurality of glyphs; a text placement engine configured to perform the operations of: starting from a first end of a path, iteratively placing along the path each of a first subset of the plurality of glyphs in a first visual order based on determining that each of the first subset of glyphs has a first directional value indicating a first level of bidirectional embedding of the glyph, wherein the first visual order is the order in which the first subset of glyphs are displayed for reading; determining that one of a second subset of the plurality of glyphs has a second directional value indicating a second level of bidirectional embedding of the glyph; starting from a second end of the path that is opposite to the first end of the path, iteratively placing along the path each of the second subset of glyphs in a second visual order, wherein the second visual order is the order in which the second subset of glyphs are displayed for reading; and redetermining placement points for the second subset of glyphs by, starting from a start point on the path adjacent to the first subset of glyphs as placed on the path, iteratively placing the second subset of glyphs along the path such that the second visual order of the second subset of glyphs is maintained. | 11. A computing platform comprising a processor with access to a computer-readable medium embodying program components, the program components comprising: a text engine configured to provide text data comprising a plurality of glyphs; a text placement engine configured to perform the operations of: starting from a first end of a path, iteratively placing along the path each of a first subset of the plurality of glyphs in a first visual order based on determining that each of the first subset of glyphs has a first directional value indicating a first level of bidirectional embedding of the glyph, wherein the first visual order is the order in which the first subset of glyphs are displayed for reading; determining that one of a second subset of the plurality of glyphs has a second directional value indicating a second level of bidirectional embedding of the glyph; starting from a second end of the path that is opposite to the first end of the path, iteratively placing along the path each of the second subset of glyphs in a second visual order, wherein the second visual order is the order in which the second subset of glyphs are displayed for reading; and redetermining placement points for the second subset of glyphs by, starting from a start point on the path adjacent to the first subset of glyphs as placed on the path, iteratively placing the second subset of glyphs along the path such that the second visual order of the second subset of glyphs is maintained. 12. The computing platform of claim 11 , wherein the text placement engine is configured to perform the operation of iteratively placing each glyph by: identifying a first point on the path, determining a path segment to be occupied by the glyph and extending from the first point of the path to a second point on the path, associating the glyph with a point on the path segment, and truncating the path by removing the path segment occupied by the glyph. | 0.5 |
12. The method of claim 10 , wherein a node in a tree hierarchy representation of a document represents a document object. | 12. The method of claim 10 , wherein a node in a tree hierarchy representation of a document represents a document object. 13. The method of claim 12 , wherein a key is associated with a node in the tree hierarchy and the node represents a document object corresponding to the key. | 0.946211 |
16. A method for selecting and printing desired ideographs from a list of available ideographs comprising coding the available ideographs by at least a portion of the phonetic spelling of their commonly used names, coding the available ideographs by a descriptive characteristic of each available ideograph, storing the codes as coded information representing the available ideographs, inputing information representing at least a portion of the phonetic spelling of a desired ideograph, inputing information representing the descriptive characteristic of the desired ideograph, comparing the inputed information representing the phonetic spelling and descriptive characteristic of the desired ideograph with the stored coded information of the available ideographs, selecting the desired ideograph based on the stored coded information and the input information and visually reproducing the selected indeograph thereby permitting the use of a conventional keyboard by a person without special training to uniquely identify and print each desired ideograph. | 16. A method for selecting and printing desired ideographs from a list of available ideographs comprising coding the available ideographs by at least a portion of the phonetic spelling of their commonly used names, coding the available ideographs by a descriptive characteristic of each available ideograph, storing the codes as coded information representing the available ideographs, inputing information representing at least a portion of the phonetic spelling of a desired ideograph, inputing information representing the descriptive characteristic of the desired ideograph, comparing the inputed information representing the phonetic spelling and descriptive characteristic of the desired ideograph with the stored coded information of the available ideographs, selecting the desired ideograph based on the stored coded information and the input information and visually reproducing the selected indeograph thereby permitting the use of a conventional keyboard by a person without special training to uniquely identify and print each desired ideograph. 23. The method of claim 16 additionally including coding at least one of the most frequently used ideographs by a single key stroke in order to maximize typing speed. | 0.64931 |
1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor. | 1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor. 11. The article of claim 1 , wherein the second parameter indicates that hyperlinks that point from any document in the linked set of documents to documents whose hyperlink addresses are outside a given domain are to be excluded from the linked set of documents. | 0.675676 |
16. The method of claim 15 further including a step: automatically soliciting input on content for said event by the computing system from persons located near said event as determined by said site data. | 16. The method of claim 15 further including a step: automatically soliciting input on content for said event by the computing system from persons located near said event as determined by said site data. 17. The method of claim 16 wherein said temporal value is adjusted by the computing system based on contributions computed from said persons located near said event. | 0.947489 |
13. A non-transitory computer-readable medium storing a set of instructions, which when executed by a processor, perform a method of creating a ranked join index for ordered data entries, comprising: mapping a dominating set of the ordered data entries according to rank attributes; determining a separating vector for each set of adjacent mapped data entries of the dominating set of ordered data entries; and ordering the ordered data entries according to a separating point associated with each of the separating vectors. | 13. A non-transitory computer-readable medium storing a set of instructions, which when executed by a processor, perform a method of creating a ranked join index for ordered data entries, comprising: mapping a dominating set of the ordered data entries according to rank attributes; determining a separating vector for each set of adjacent mapped data entries of the dominating set of ordered data entries; and ordering the ordered data entries according to a separating point associated with each of the separating vectors. 14. The non-transitory computer-readable medium of claim 13 , wherein the ordering the ordered data entries, comprises: sweeping a vector across a plane of the adjacent mapped data entries, wherein each time the vector crosses a separating vector, a current composition of highest ranked data entries changes by swapping a data entry in a respective set of the adjacent mapped data entries if it causes a change in the index; and wherein each time a data entry in a respective set of adjacent mapped data entries is swapped, the highest ranked data entries are materialized and a new index entry is initiated. | 0.5 |
10. The method of claim 2, wherein the providing step includes providing a user denizen which modifies itself in response to the result of executing at least a portion of the received instructions. | 10. The method of claim 2, wherein the providing step includes providing a user denizen which modifies itself in response to the result of executing at least a portion of the received instructions. 11. The method of claim 10, wherein the modifying step uses a neural net learning method. | 0.907324 |
16. A system for selecting digital content related to a portion of a block of text, the system comprising: means for receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; the block of text is accessible via a web interface; and the digital content comprises still or moving digital images; means for segmenting the one or more words included in the block of text into one or more segments comprising phrases or individual words, wherein the segmenting includes automatically removing one or more phrases or individual words that are less likely to result in finding images; means for searching a database of digital content based on the one or more segmented phrases or individual words, wherein: the means for searching is coupled to the means for receiving; means for retrieving from the database one or more digital content items or identifiers associated with the one or more digital content items, wherein: the digital content items are related to the one or more segmented phrases or individual words; and the means for retrieving is coupled to the means for searching; means for determining whether a licensing agreement is active with respect to the one or more retrieved digital content items or identifiers associated with the one or more digital content items; means for providing the retrieved digital content items or identifiers to the user only if a licensing agreement is active with respect to the retrieved digital content items or identifiers, wherein the means for providing is coupled to the means for retrieving; means for receiving a selection of one or more of the provided digital content items or identifiers from the user, wherein the means for receiving is coupled to the means for providing; and means for associating for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text, wherein: the means for associating is coupled to the means for receiving; and the block of text and the one or more selected digital content items are accessible via the web interface. | 16. A system for selecting digital content related to a portion of a block of text, the system comprising: means for receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; the block of text is accessible via a web interface; and the digital content comprises still or moving digital images; means for segmenting the one or more words included in the block of text into one or more segments comprising phrases or individual words, wherein the segmenting includes automatically removing one or more phrases or individual words that are less likely to result in finding images; means for searching a database of digital content based on the one or more segmented phrases or individual words, wherein: the means for searching is coupled to the means for receiving; means for retrieving from the database one or more digital content items or identifiers associated with the one or more digital content items, wherein: the digital content items are related to the one or more segmented phrases or individual words; and the means for retrieving is coupled to the means for searching; means for determining whether a licensing agreement is active with respect to the one or more retrieved digital content items or identifiers associated with the one or more digital content items; means for providing the retrieved digital content items or identifiers to the user only if a licensing agreement is active with respect to the retrieved digital content items or identifiers, wherein the means for providing is coupled to the means for retrieving; means for receiving a selection of one or more of the provided digital content items or identifiers from the user, wherein the means for receiving is coupled to the means for providing; and means for associating for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text, wherein: the means for associating is coupled to the means for receiving; and the block of text and the one or more selected digital content items are accessible via the web interface. 23. The system of claim 16 wherein the digital content comprises at least one of audio information or video information. | 0.698529 |
52. The apparatus in claim 37 further comprises a training phase wherein the processor, in response to the stored instructions: detects whether each one of a plurality of predetermined features exists in each message of a training set of m messages belonging to the first class so as to yield a feature matrix containing feature data for all of the training messages, wherein the plurality of predetermined features defines a predefined n-element feature space and each of the training messages has been previously classified as belonging to the first class; reduces the feature matrix in size to yield a reduced feature matrix having said N features (where n, N and m are integers with n>N); and applies the reduced feature matrix and the known classifications of each of said training messages to the classifier and training the classifier to recognize the N features in the m-message training set. | 52. The apparatus in claim 37 further comprises a training phase wherein the processor, in response to the stored instructions: detects whether each one of a plurality of predetermined features exists in each message of a training set of m messages belonging to the first class so as to yield a feature matrix containing feature data for all of the training messages, wherein the plurality of predetermined features defines a predefined n-element feature space and each of the training messages has been previously classified as belonging to the first class; reduces the feature matrix in size to yield a reduced feature matrix having said N features (where n, N and m are integers with n>N); and applies the reduced feature matrix and the known classifications of each of said training messages to the classifier and training the classifier to recognize the N features in the m-message training set. 58. The apparatus in claim 52 wherein the classes comprise a plurality of sub-classes and said one class is one of said sub-classes. | 0.716798 |
13. A machine implemented method for effectuating in situ search for active note taking, comprising: receiving and recognizing a gesture from an input device identifying at least one inked text; generating an embeddable graphical object and associating the embeddable graphical object with the at least one handwritten script, the embeddable graphical object being associated with recognized query text and/or a number of results returned in response to the recognized query text and additional embeddable graphical objects, the additional embeddable graphical objects being associated with disparate functions; employing a tracking menu comprising: a scroll ring that receives pseudo-circular motion from the input device and translates the motion into vertical or horizontal scrolling in a focus application of a system manager window; a capture tool that allows a user to circumscribe an area of a display; a close box that dismisses the tracking menu; and a move handle for dragging the tracking menu to a new position, the tracking menu providing cross application functionality between disparate applications; digitizing and analyzing the at least one handwritten script; initiating a search with the digitized and analyzed at least one handwritten script to return results; coupling the results with the embeddable graphical object; and inserting the embeddable graphical object in close proximity to the at least one handwritten script. | 13. A machine implemented method for effectuating in situ search for active note taking, comprising: receiving and recognizing a gesture from an input device identifying at least one inked text; generating an embeddable graphical object and associating the embeddable graphical object with the at least one handwritten script, the embeddable graphical object being associated with recognized query text and/or a number of results returned in response to the recognized query text and additional embeddable graphical objects, the additional embeddable graphical objects being associated with disparate functions; employing a tracking menu comprising: a scroll ring that receives pseudo-circular motion from the input device and translates the motion into vertical or horizontal scrolling in a focus application of a system manager window; a capture tool that allows a user to circumscribe an area of a display; a close box that dismisses the tracking menu; and a move handle for dragging the tracking menu to a new position, the tracking menu providing cross application functionality between disparate applications; digitizing and analyzing the at least one handwritten script; initiating a search with the digitized and analyzed at least one handwritten script to return results; coupling the results with the embeddable graphical object; and inserting the embeddable graphical object in close proximity to the at least one handwritten script. 15. The method of claim 13 , further comprising animating highlighter hints into or out of an interface control utilized for dismissal and retrieval of the highlighter hints by a user. | 0.57516 |
1. A method comprising: storing in a memory an executable graphical model including a plurality of components including hierarchically arranged child components disposed within parent components, the child components configured to send and receive messages during execution of the graphical model in an order, the messages persist for determined time intervals between a model execution start time and a model execution end time, and have payloads that remain fixed for a given send-receive interaction; identifying, by a processor coupled to the memory: the child components configured to send and receive messages, and the determined time intervals of the messages; automatically generating, by the processor, a message view window for the graphical model, the message view window including: an execution time scale corresponding to a time of execution of the graphical model, parent lifelines corresponding to the parent components, the parent lifelines extending across the execution time scale, and a plurality of first graphical affordances associated with the parent lifelines, the plurality of first graphical affordances representing the messages, the plurality of first graphical affordances arranged in the order of the messages; and expanding a given parent lifeline corresponding to a given parent component of the executable graphical model to show child lifelines corresponding to at least two of the child components of the given parent component. | 1. A method comprising: storing in a memory an executable graphical model including a plurality of components including hierarchically arranged child components disposed within parent components, the child components configured to send and receive messages during execution of the graphical model in an order, the messages persist for determined time intervals between a model execution start time and a model execution end time, and have payloads that remain fixed for a given send-receive interaction; identifying, by a processor coupled to the memory: the child components configured to send and receive messages, and the determined time intervals of the messages; automatically generating, by the processor, a message view window for the graphical model, the message view window including: an execution time scale corresponding to a time of execution of the graphical model, parent lifelines corresponding to the parent components, the parent lifelines extending across the execution time scale, and a plurality of first graphical affordances associated with the parent lifelines, the plurality of first graphical affordances representing the messages, the plurality of first graphical affordances arranged in the order of the messages; and expanding a given parent lifeline corresponding to a given parent component of the executable graphical model to show child lifelines corresponding to at least two of the child components of the given parent component. 5. The method of claim 1 wherein one or more of the plurality of first graphical affordances extend between a pair of parent or child lifelines. | 0.636364 |
1. A method comprising: at an electronic device with a display and one or more input devices; displaying on the display of the electronic device, a first text string with a first type style and a second text string with a second type style, wherein the first type style is different than the second type style; the first text string is displayed proximate to the second text string on the display with a first spatial arrangement that is determined based at least in part on the first type style and the second type style; after displaying the first text string and the second text string on the display, receiving, via the one or more input devices, input that changes a font size of the first text string and changes the respective font size of the second text string; in response to receiving the input, dynamically adjusting, by the electronic device, one or more font metrics that determine the spatial arrangement of text in accordance with text layout rules based on the first type style and the second type style; and displaying, on the display of the electronic device, the first text string and the second text string with the respective font size changed and with a second spatial arrangement that is determined based on the first type style, the second type style and the dynamically adjusted one or more font metrics. | 1. A method comprising: at an electronic device with a display and one or more input devices; displaying on the display of the electronic device, a first text string with a first type style and a second text string with a second type style, wherein the first type style is different than the second type style; the first text string is displayed proximate to the second text string on the display with a first spatial arrangement that is determined based at least in part on the first type style and the second type style; after displaying the first text string and the second text string on the display, receiving, via the one or more input devices, input that changes a font size of the first text string and changes the respective font size of the second text string; in response to receiving the input, dynamically adjusting, by the electronic device, one or more font metrics that determine the spatial arrangement of text in accordance with text layout rules based on the first type style and the second type style; and displaying, on the display of the electronic device, the first text string and the second text string with the respective font size changed and with a second spatial arrangement that is determined based on the first type style, the second type style and the dynamically adjusted one or more font metrics. 8. The method of claim 1 , wherein at least one of the text layout rules specifies a linear equation. | 0.582759 |
1. A method for searching a system, the method including: receiving by a processor based device a user context that identifies a search context relative to a personal identity of an individual seeking a search result; identifying by the processor based device a portion of a connection context as relevant to the user context, the connection context identifying relationships between chosen destinations accessible via information sources that are reachable via a network, the chosen destinations including data objects and address identifiers for identified individuals having respective personal identities, each of the relationships having a strength increased by an aggregation of artifacts recorded in the network by the system and that represent accessing of at least a corresponding first and second of the chosen destinations by different individuals having different personal identities, each artifact identifying the corresponding personal identity and the corresponding chosen destination, at least one of the relationships established based on a determined correlation between a first and a second of the artifacts recorded within a time interval, the first artifact recorded in response as a first of the individuals accesses the first chosen destination using a first available user device and the second artifact recorded in response as the first individual accesses the second chosen destination using a second available user device distinct and independent from the first available user device, the strength of the one relationship increased by the aggregation of the associated artifacts, representing the accessing of the first and second chosen destinations by the different individuals, relative to the respective determined correlations; and generating by the processor based device as the search result an ordered list of destination targets, including selected identified individuals identified based on their respective personal identities, including ordering the ordered list according to the portion of the connection context; wherein the first and second available user devices are at a same location. | 1. A method for searching a system, the method including: receiving by a processor based device a user context that identifies a search context relative to a personal identity of an individual seeking a search result; identifying by the processor based device a portion of a connection context as relevant to the user context, the connection context identifying relationships between chosen destinations accessible via information sources that are reachable via a network, the chosen destinations including data objects and address identifiers for identified individuals having respective personal identities, each of the relationships having a strength increased by an aggregation of artifacts recorded in the network by the system and that represent accessing of at least a corresponding first and second of the chosen destinations by different individuals having different personal identities, each artifact identifying the corresponding personal identity and the corresponding chosen destination, at least one of the relationships established based on a determined correlation between a first and a second of the artifacts recorded within a time interval, the first artifact recorded in response as a first of the individuals accesses the first chosen destination using a first available user device and the second artifact recorded in response as the first individual accesses the second chosen destination using a second available user device distinct and independent from the first available user device, the strength of the one relationship increased by the aggregation of the associated artifacts, representing the accessing of the first and second chosen destinations by the different individuals, relative to the respective determined correlations; and generating by the processor based device as the search result an ordered list of destination targets, including selected identified individuals identified based on their respective personal identities, including ordering the ordered list according to the portion of the connection context; wherein the first and second available user devices are at a same location. 7. The method of claim 1 , further comprising: following generation of the search result, receiving artifacts from a system providing services to the user independent of the search result, the artifacts identifying chosen destinations not having been specified as destination targets in the search result; and updating selected relationships identified by the connection context based on the received artifacts. | 0.562476 |
9. The computer-implemented method of claim 1 , wherein the modifier is a negation, wherein the adjusting the mood weight of the identified text that is in proximity to the modifier includes changing a positive mood to a negative mood or changing a negative mood to a positive mood. | 9. The computer-implemented method of claim 1 , wherein the modifier is a negation, wherein the adjusting the mood weight of the identified text that is in proximity to the modifier includes changing a positive mood to a negative mood or changing a negative mood to a positive mood. 10. The computer-implemented method of claim 9 , wherein the adjusting the mood weight of the identified text that is in proximity to the modifier further includes decreasing the mood weight. | 0.946912 |
11. A computer system of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising: a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets; a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events; identifying, by the computer, identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes; receiving, by the computer, a query input from a user identifying an event; obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model; searching, by the computer, the third topic map meta-model for the identification from the query input; displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user. | 11. A computer system of determining an impact of an event identified in a first topic map meta-model will have on at least one asset identified in a second topic map meta-model representative as a weight comprising a computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: creating, by the computer a third topic map meta-model which maps at least one asset from the second topic map meta-model to an event from the first topic map meta-model, the third topic map meta-model comprising: a topic map representation of assets of the second topic map meta-model, the second topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of assets; a topic map representation of events of the first topic map meta-model, the first topic map meta-model further comprising a topic map based index and instance ontology of a meta-model of events; identifying, by the computer, identification of at least one association mapped between an event identified in the first topic map meta-model and at least one asset identified in the second topic map meta-model; and assigning, by the computer, weight associated with the identification to the at least one association between an event identified in a first topic map meta-model and an asset identified in a second topic map meta-model in various scopes; receiving, by the computer, a query input from a user identifying an event; obtaining, by the computer, from the query input, at least an identification of an association between at least one asset and an event in the third topic map meta-model; searching, by the computer, the third topic map meta-model for the identification from the query input; displaying, by the computer, all weights assigned to the association between the event in the first topic map meta-model and at least one asset of the second topic map meta-model in at least one scope to the user. 13. The computer system of claim 11 , further comprising the program instructions to: in response to a new event being added to the topic map meta-model identifying events, the computer re-creating the third topic map meta-model for the new event, adjusting the weight associated with the association in the third topic map meta-model, the re-created third map meta-model including a topic map based index and instance ontology for the new event and the adjusted weight; and storing, by the computer, the re-created third topic map meta-model into a repository. | 0.53821 |
1. A method for processing documents, comprising executing program codes stored in a memory by a processor in a terminal, wherein the terminal is being configured to perform the method, comprising: upon receiving an operation request for a designated document wherein the operation request carries scene information, obtaining constituent information of the designated document, wherein the constituents information comprises a first resource identification of at least one multimedia resource; obtaining, according to the first resource identification of the at least one multimedia resource, the at least one multimedia resource and a location of the at least one multimedia resource within the designated document; obtaining the designated document according to the at least one multimedia resource and the location of the at least one multimedia resource within the designated document; obtaining document type corresponding to the scene information according to the scene information carried by the operation request; generating the document type of the designated document according to the at least one multimedia resource and the location of the designated document; generating a first document type of the designated document, wherein the first document type performs analysis based on preset logic, wherein the generating takes place when the scene information displays a scene and the document type is the first document type, and wherein the generating is according to: the at least one multimedia resource and the location of the at least one multimedia resource within the designated document, and a compilation mode determined by the first document type; or generating a second document type of the designated document, wherein the second document type performs rich text editing, wherein the generating takes place when the scene information is an editing scene and the document type is the second document type, and wherein the generating is according to: the at least one multimedia resource and the location of the at least one multimedia resource within the designated document, and a compilation mode determined by the second document type; and enhancing a loading rate of the designated document by loading and displaying in sequence, the at least one multimedia resource which constitutes the designated document according to a resource loading sequence which is determined by the designated document, such that the loading and displaying sequence enables the designated document starts being displayed without having to wait for a completion of loading and rendering of a whole document which the designated document being one of a plurality of documents or files within the whole document. | 1. A method for processing documents, comprising executing program codes stored in a memory by a processor in a terminal, wherein the terminal is being configured to perform the method, comprising: upon receiving an operation request for a designated document wherein the operation request carries scene information, obtaining constituent information of the designated document, wherein the constituents information comprises a first resource identification of at least one multimedia resource; obtaining, according to the first resource identification of the at least one multimedia resource, the at least one multimedia resource and a location of the at least one multimedia resource within the designated document; obtaining the designated document according to the at least one multimedia resource and the location of the at least one multimedia resource within the designated document; obtaining document type corresponding to the scene information according to the scene information carried by the operation request; generating the document type of the designated document according to the at least one multimedia resource and the location of the designated document; generating a first document type of the designated document, wherein the first document type performs analysis based on preset logic, wherein the generating takes place when the scene information displays a scene and the document type is the first document type, and wherein the generating is according to: the at least one multimedia resource and the location of the at least one multimedia resource within the designated document, and a compilation mode determined by the first document type; or generating a second document type of the designated document, wherein the second document type performs rich text editing, wherein the generating takes place when the scene information is an editing scene and the document type is the second document type, and wherein the generating is according to: the at least one multimedia resource and the location of the at least one multimedia resource within the designated document, and a compilation mode determined by the second document type; and enhancing a loading rate of the designated document by loading and displaying in sequence, the at least one multimedia resource which constitutes the designated document according to a resource loading sequence which is determined by the designated document, such that the loading and displaying sequence enables the designated document starts being displayed without having to wait for a completion of loading and rendering of a whole document which the designated document being one of a plurality of documents or files within the whole document. 25. The method according to claim 1 , wherein the operation request also carries identification of the designated document and/or designated account information. | 0.653702 |
1. A computer-implemented method, comprising: monitoring, via one or more processors, a script being executed to test the functionality of an application, wherein the script includes one or more tags associated with corresponding tags in documentation associated with the application, wherein each corresponding tag indicates a location in the documentation to insert a screenshot of the application; during execution of the script, evaluating text or graphics of one or more content items displayed by the application; upon determining, based on the evaluated text or graphics, that one or more of the content items displayed by the application is associated with a first feature associated with a first tag in the documentation, adding a tag corresponding to the first tag to the script; during execution of the script, when each of the one or more tags is encountered, capturing content items from the application, wherein the captured content items comprise at least a screenshot of the application captured at a point when each respective tag is encountered during the execution of the script; and inserting the captured content items into the documentation at the locations indicated by each of the corresponding tags of the documentation. | 1. A computer-implemented method, comprising: monitoring, via one or more processors, a script being executed to test the functionality of an application, wherein the script includes one or more tags associated with corresponding tags in documentation associated with the application, wherein each corresponding tag indicates a location in the documentation to insert a screenshot of the application; during execution of the script, evaluating text or graphics of one or more content items displayed by the application; upon determining, based on the evaluated text or graphics, that one or more of the content items displayed by the application is associated with a first feature associated with a first tag in the documentation, adding a tag corresponding to the first tag to the script; during execution of the script, when each of the one or more tags is encountered, capturing content items from the application, wherein the captured content items comprise at least a screenshot of the application captured at a point when each respective tag is encountered during the execution of the script; and inserting the captured content items into the documentation at the locations indicated by each of the corresponding tags of the documentation. 7. The method of claim 1 , further comprising, for each inserted content item, inserting an indication in the documentation indicating that the content item was inserted. | 0.59411 |
1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 4. The method of claim 1 , in which the plurality of data sources include open-source data sources that are publically available and closed-source data sources that are not publically accessible. | 0.582395 |
1. A method comprising: providing session data for a presentation, wherein the session data includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; presenting the selected structural element to the user; streaming speech to the user from one or more users participating in the presentation; detecting a total sound level for the user; and displaying a textual transcription of the speech to the user based upon the total sound level detected, wherein the total sound level comprises the streaming speech plus ambient noise, and wherein displaying the textual transcription of the speech further comprises displaying the textual transcription of the speech if a ratio of the total sound level to the ambient noise level is less than a predetermined value. | 1. A method comprising: providing session data for a presentation, wherein the session data includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; presenting the selected structural element to the user; streaming speech to the user from one or more users participating in the presentation; detecting a total sound level for the user; and displaying a textual transcription of the speech to the user based upon the total sound level detected, wherein the total sound level comprises the streaming speech plus ambient noise, and wherein displaying the textual transcription of the speech further comprises displaying the textual transcription of the speech if a ratio of the total sound level to the ambient noise level is less than a predetermined value. 2. The method of claim 1 wherein the total sound level for the user includes ambient noise and the method includes detecting an ambient noise level for the user. | 0.794706 |
17. At a computer system, a method for detecting a column header for a table including one or more rows, the method comprising: constructing a set of candidate column names for the table; for each candidate column name in the set of candidate column names: calculating a candidate column name frequency for the candidate column name by identifying one or more other tables, from among a set of other tables, that also contain the candidate column name as a candidate column name; inferring that a column included in the set of candidate column names is a hypernym of the cell values contained in the column based on the cell values contained in the column; and selecting the row containing the column as a column header for the table based on the inference and the candidate column name frequencies for the candidate column names in the row. | 17. At a computer system, a method for detecting a column header for a table including one or more rows, the method comprising: constructing a set of candidate column names for the table; for each candidate column name in the set of candidate column names: calculating a candidate column name frequency for the candidate column name by identifying one or more other tables, from among a set of other tables, that also contain the candidate column name as a candidate column name; inferring that a column included in the set of candidate column names is a hypernym of the cell values contained in the column based on the cell values contained in the column; and selecting the row containing the column as a column header for the table based on the inference and the candidate column name frequencies for the candidate column names in the row. 18. The method of claim 17 , wherein inferring that a column included in the set of candidate column names is a hypernym of the cell values contained in the column comprises inferring that a column included in the set of candidate column names is a hypernym of the cell values contained in the column through reference to a knowledge base. | 0.700362 |
23. The method of claim 21 , wherein the combination or the permutation is a hypernym. | 23. The method of claim 21 , wherein the combination or the permutation is a hypernym. 29. The method of claim 23 , further comprising: using the updated list of key terms to perform text categorization, wherein text to be categorized is from a social media source. | 0.955317 |
25. An application program interface embodied on one or more computer-readable storage media, the application programming interface comprising: a first method to create a package, wherein the package holds together a plurality of parts that make up a document and which are described in markup that can refer to different representations of the document, wherein at least some of the different representations include the same content, the package further including a plurality of relationship elements, each relationship element being associated with one of the plurality of parts, defining a relationship between the one of the plurality of parts and one or more of another of the plurality of parts, and enabling the relationship to be discoverable independently of an associated part, the package being associated with a plurality of drivers, the plurality of drivers being associated with different document formats and allowing multiple applications to access the package regardless of a document format associated with each of the multiple applications; a second method to add a first part to the package; a third method to retrieve a second part from the package; and a fourth method to identify a stream of data. | 25. An application program interface embodied on one or more computer-readable storage media, the application programming interface comprising: a first method to create a package, wherein the package holds together a plurality of parts that make up a document and which are described in markup that can refer to different representations of the document, wherein at least some of the different representations include the same content, the package further including a plurality of relationship elements, each relationship element being associated with one of the plurality of parts, defining a relationship between the one of the plurality of parts and one or more of another of the plurality of parts, and enabling the relationship to be discoverable independently of an associated part, the package being associated with a plurality of drivers, the plurality of drivers being associated with different document formats and allowing multiple applications to access the package regardless of a document format associated with each of the multiple applications; a second method to add a first part to the package; a third method to retrieve a second part from the package; and a fourth method to identify a stream of data. 30. An application program interface as recited in claim 25 , further comprising a fifth method to delete an existing part from the package. | 0.549491 |
25. A computer-implemented method, comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query relative to the candidate query; determining a navigation score for the revised query; and determining that the quality score for the revised query satisfies a quality score threshold and that the navigation score for the revised query satisfies a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. | 25. A computer-implemented method, comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query relative to the candidate query; determining a navigation score for the revised query; and determining that the quality score for the revised query satisfies a quality score threshold and that the navigation score for the revised query satisfies a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. 26. The computer-implemented method of claim 25 , wherein determining a quality score for the revised query relative to the candidate query comprises: determining a revision time for the revised query, the revision time being measured relative to the entry of the candidate query; and determining the quality score based on the revision time. | 0.783039 |
14. The method of claim 12 , wherein the contextual breadcrumbs further comprise a simplified representation of the current page and a visual representation of a flow from the simplified representation of the first different page to the simplified representation of the current page, the simplified representation of the current page comprising context information regarding a function of the current page. | 14. The method of claim 12 , wherein the contextual breadcrumbs further comprise a simplified representation of the current page and a visual representation of a flow from the simplified representation of the first different page to the simplified representation of the current page, the simplified representation of the current page comprising context information regarding a function of the current page. 15. The method of claim 14 , wherein: the context information regarding a function of the current page comprises a visual representation of the plurality of functional options of the current page. | 0.896306 |
1. A method for facilitating text entry for an electronic device, the method comprising: activating a field for text entry on a display of the electronic device; displaying a current frame on the display associated with a viewfinder of the electronic device concurrently while also displaying the activated field for text entry; determining an area of interest in the current frame; recognizing text in the area of interest associated with the current frame, wherein recognizing text in the area of interest is performed without capturing the current frame in the viewfinder and without persisting in storage the current frame; and displaying text corresponding to the recognized text in the activated field. | 1. A method for facilitating text entry for an electronic device, the method comprising: activating a field for text entry on a display of the electronic device; displaying a current frame on the display associated with a viewfinder of the electronic device concurrently while also displaying the activated field for text entry; determining an area of interest in the current frame; recognizing text in the area of interest associated with the current frame, wherein recognizing text in the area of interest is performed without capturing the current frame in the viewfinder and without persisting in storage the current frame; and displaying text corresponding to the recognized text in the activated field. 16. The method of claim 1 , wherein detecting a selection associated with an area of interest in the current frame in association with the viewfinder is made in an interactive regime of the viewfinder of a camera application. | 0.65915 |
1. A method comprising: identifying, by one or more computers, a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying, by the one or more computers, a structure of a portion of the structured document that includes at least one term of the seed query; generating, by the one or more computers, a query template that specifies the structure and a portion of the structure from which text should be extracted; generating, by the one or more computers, one or more synthetic queries using the query template and one or more other structured documents, the generating comprising: identifying a portion of a particular structured document that includes the structure specified by the query template; and generating a synthetic query using text contained in the portion of the structure of the particular structured document specified by the query template; and storing, by the one or more computers, the one or more synthetic queries in a query store. | 1. A method comprising: identifying, by one or more computers, a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying, by the one or more computers, a structure of a portion of the structured document that includes at least one term of the seed query; generating, by the one or more computers, a query template that specifies the structure and a portion of the structure from which text should be extracted; generating, by the one or more computers, one or more synthetic queries using the query template and one or more other structured documents, the generating comprising: identifying a portion of a particular structured document that includes the structure specified by the query template; and generating a synthetic query using text contained in the portion of the structure of the particular structured document specified by the query template; and storing, by the one or more computers, the one or more synthetic queries in a query store. 2. The method of claim 1 , wherein the query template includes a generative rule that specifies the portion of the structure from which text should be extracted. | 0.881232 |
11. The tangible computer readable medium of claim 10 further comprising: instructions to assign an order to elements of the Include and Exclude rule components to established ordered indices; and instructions to store the rule model in reduced canonical form according to the ordered indices. | 11. The tangible computer readable medium of claim 10 further comprising: instructions to assign an order to elements of the Include and Exclude rule components to established ordered indices; and instructions to store the rule model in reduced canonical form according to the ordered indices. 13. The tangible computer readable medium of claim 11 further comprising: instructions to define elective events according to a predetermined combination of attribute and enumeration values, which events are operative to invoke data processing to effect display of a message or performance of a calculation. | 0.772249 |
10. The method of claim 1 , wherein the validation of the sequence comprises providing for detecting at least one of missing elements and erroneous elements, based on the model. | 10. The method of claim 1 , wherein the validation of the sequence comprises providing for detecting at least one of missing elements and erroneous elements, based on the model. 11. The method of claim 10 , wherein the validation of the sequence comprises providing for detecting missing elements, comprising identifying missing elements of the sequence only in the content of pages where a signature mark is expected, based on the model. | 0.903766 |
10. One or more non-transitory, machine-readable storage media comprising a plurality of instructions stored thereon that, when executed, cause an automatic speech recognition device to: acquire speech data; recognize, based on the speech data, phonemes of the speech data; recognize, based on the phonemes, words of the speech data; parse, based on the words, the speech data to determine a syntactic coherence of the speech data; determine, based on the words, a word statistics end-of-sentence score; determine, based on the syntactic coherence and the word statistics end-of-sentence score, an end of a sentence of the speech data; and determine, based on the determined end of the sentence, a speech recognition result. | 10. One or more non-transitory, machine-readable storage media comprising a plurality of instructions stored thereon that, when executed, cause an automatic speech recognition device to: acquire speech data; recognize, based on the speech data, phonemes of the speech data; recognize, based on the phonemes, words of the speech data; parse, based on the words, the speech data to determine a syntactic coherence of the speech data; determine, based on the words, a word statistics end-of-sentence score; determine, based on the syntactic coherence and the word statistics end-of-sentence score, an end of a sentence of the speech data; and determine, based on the determined end of the sentence, a speech recognition result. 16. The one or more non-transitory, machine-readable storage media of claim 10 , wherein the plurality of instructions further cause the automatic speech recognition device to: determine, based on the syntactic parse, a syntactic coherence end-of-sentence score, and determine, based on the acoustic features, an acoustic end-of-sentence score, wherein to determine the end of the sentence comprises to determine the end of the sentence based on the syntactic coherence end-of-sentence score and the acoustic end-of-sentence score. | 0.590077 |
24. The computer implemented method of claim 23 where the first plurality of intents and the second plurality of intents and the first plurality of sub-entities and the second plurality of sub-entities identify speech included in the media. | 24. The computer implemented method of claim 23 where the first plurality of intents and the second plurality of intents and the first plurality of sub-entities and the second plurality of sub-entities identify speech included in the media. 30. The computer implemented method of claim 24 where the first natural processing engine and the second natural processing engine comprises an automatic speech recognition service. | 0.87683 |
9. One or more computer-readable storage media storing instructions that, when executed by a processor, implement a method comprising: detecting, by a motion detection system coupled to a user device, a body motion of a user to determine a tagging gesture indicating a region within a media content displayed at the user device, the region including an item; based on determining the tagging gesture, providing for display at the user device a representation of the media content indicated by the body motion; based on the tagging gesture, identifying the item and determining the item is a tagged item; identifying tag-item data associated with the tagged item; in response to the tagging gesture, automatically initiating a search for content related to the tagged item, wherein the search is initiated based on a search query, wherein the search query is based on the identified tag-item data and user data, the user data comprising a history of previously tagged items that were tagged by the user associated with the tagging gesture; receiving the content related to the tagged item in response to the search query, wherein the received content related to the tagged item is based on the identified tag-item data and the user data; and causing a presentation of the content related to the tagged item, wherein the content related to the tagged item is presented in association with the tagged item. | 9. One or more computer-readable storage media storing instructions that, when executed by a processor, implement a method comprising: detecting, by a motion detection system coupled to a user device, a body motion of a user to determine a tagging gesture indicating a region within a media content displayed at the user device, the region including an item; based on determining the tagging gesture, providing for display at the user device a representation of the media content indicated by the body motion; based on the tagging gesture, identifying the item and determining the item is a tagged item; identifying tag-item data associated with the tagged item; in response to the tagging gesture, automatically initiating a search for content related to the tagged item, wherein the search is initiated based on a search query, wherein the search query is based on the identified tag-item data and user data, the user data comprising a history of previously tagged items that were tagged by the user associated with the tagging gesture; receiving the content related to the tagged item in response to the search query, wherein the received content related to the tagged item is based on the identified tag-item data and the user data; and causing a presentation of the content related to the tagged item, wherein the content related to the tagged item is presented in association with the tagged item. 13. The media of claim 9 , wherein the content related to the tagged item further comprises an advertisement associated with the tagged item, a recommendation relevant to the tagged item, or information relevant to the tagged item. | 0.527611 |
1. A computerized method for identification of term or phrase pairs that are associative matches, the method comprising: electronically selecting one or more candidate term pairs for the construction of an associative model; electronically labeling the one or more candidate term pairs by matching the one or more candidate terms on the basis of associative criteria, the associative criteria comprising a complementary product relationship, a task relationship, a cultural relationship and temporal relationships; electronically determining one or more features for the one or more candidate term pairs; electronically building a model on the basis of the one or more features; and electronically applying the model to an unlabeled candidate term pair to determine if the pair is an associative match. | 1. A computerized method for identification of term or phrase pairs that are associative matches, the method comprising: electronically selecting one or more candidate term pairs for the construction of an associative model; electronically labeling the one or more candidate term pairs by matching the one or more candidate terms on the basis of associative criteria, the associative criteria comprising a complementary product relationship, a task relationship, a cultural relationship and temporal relationships; electronically determining one or more features for the one or more candidate term pairs; electronically building a model on the basis of the one or more features; and electronically applying the model to an unlabeled candidate term pair to determine if the pair is an associative match. 11. The method of claim 1 wherein applying the model occurs in response to a search query. | 0.697621 |
5. An apparatus for generating a task-based user interface (UI), the apparatus comprising: a task ontology unit configured to maintain task information with respect to the task; a device ontology unit configured to maintain device information with respect to a device; a UI description generator configured to read at least one of the task information and the device information using the task ontology unit or the device ontology unit, respectively, generate UI description information from at least one of the read task information and the read device information, the UI description information being made by a task-based language, and analyze similarity between the devices based on at least one of task semantic information and device semantic information to automatically map the at least one of the task semantic information and the device semantic information; and a UI description parser configured to parse the UI description information to output the task-based UI, wherein at least one of the task ontology unit, the device ontology unit, the UI description generator and the UI description parser is implemented by a processor of the apparatus, and wherein the task-based language includes a device description section configured to describe a relationship with the device, an internal state of the device, and a variable for controlling a function of the device, a task description section configured to describe the task information being the processor configured to provide services to a user, and an interface description section configured to describe the task-based UI corresponding to the device information and the task information. | 5. An apparatus for generating a task-based user interface (UI), the apparatus comprising: a task ontology unit configured to maintain task information with respect to the task; a device ontology unit configured to maintain device information with respect to a device; a UI description generator configured to read at least one of the task information and the device information using the task ontology unit or the device ontology unit, respectively, generate UI description information from at least one of the read task information and the read device information, the UI description information being made by a task-based language, and analyze similarity between the devices based on at least one of task semantic information and device semantic information to automatically map the at least one of the task semantic information and the device semantic information; and a UI description parser configured to parse the UI description information to output the task-based UI, wherein at least one of the task ontology unit, the device ontology unit, the UI description generator and the UI description parser is implemented by a processor of the apparatus, and wherein the task-based language includes a device description section configured to describe a relationship with the device, an internal state of the device, and a variable for controlling a function of the device, a task description section configured to describe the task information being the processor configured to provide services to a user, and an interface description section configured to describe the task-based UI corresponding to the device information and the task information. 6. The apparatus of claim 5 , wherein the UI description generator performs a mapping process with respect to the task semantic information being analyzed using the task information, and with respect to the device semantic information being analyzed using the device information, respectively. | 0.511518 |
1. A business intelligence data testing apparatus comprising: a processor; and a memory communicatively coupled to the processor, wherein the memory comprises processor-executable instructions stored in the memory, which, on execution by the processor, cause the processor to: generate one or more test cases and one or more test scripts, for execution of the test cases, based on a data mapping file associated with a source data repository and a target data repository; execute the test scripts on the source data repository and the target data repository; generate and output a test results report indicative of the outcome of the execution of the test scripts; receive one or more online analytical processing (OLAP) parameters and generate an OLAP cube report for the target data repository based on the parameters, wherein the OLAP cube report is summarized across one or more dimensions based on contents of the target data repository; compare the OLAP cube report and another report, which is to be tested, based on the test cases to determine when one or more fields in the OLAP cube report do not match one or more corresponding fields in the another report; and generate and output a comparison report based on the comparison, wherein the comparison report indicates the one or more fields of the OLAP cube report, when the determining indicates that the one or more fields in the OLAP cube report do not match the one or more corresponding fields in the another report. | 1. A business intelligence data testing apparatus comprising: a processor; and a memory communicatively coupled to the processor, wherein the memory comprises processor-executable instructions stored in the memory, which, on execution by the processor, cause the processor to: generate one or more test cases and one or more test scripts, for execution of the test cases, based on a data mapping file associated with a source data repository and a target data repository; execute the test scripts on the source data repository and the target data repository; generate and output a test results report indicative of the outcome of the execution of the test scripts; receive one or more online analytical processing (OLAP) parameters and generate an OLAP cube report for the target data repository based on the parameters, wherein the OLAP cube report is summarized across one or more dimensions based on contents of the target data repository; compare the OLAP cube report and another report, which is to be tested, based on the test cases to determine when one or more fields in the OLAP cube report do not match one or more corresponding fields in the another report; and generate and output a comparison report based on the comparison, wherein the comparison report indicates the one or more fields of the OLAP cube report, when the determining indicates that the one or more fields in the OLAP cube report do not match the one or more corresponding fields in the another report. 5. The apparatus as claimed in claim 1 , wherein the instructions, on execution by the processor, further cause the processor to: analyze the another report to determine the dimensions of the another report; and generate the OLAP cube report with dimensions corresponding to the determined dimensions of the another report. | 0.743473 |
14. A system comprising: at least one processor; and at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: receive a search query for searching an attribute within a document; provide, for display within a graphical user interface, a plurality of search results matching the attribute in a plurality of snippets, wherein each snippet of the plurality of snippets displays a portion of content from the document, and wherein each portion of content comprises at least one result from the plurality of search results matching the attribute; receive, based on a user interaction with graphical user interface, a first user input with respect to a first snippet of the plurality of snippets, wherein the first snippet comprises a first portion of content from the document, and wherein the first portion of content comprises multiple result instances from the plurality of search results; based on receiving the first user input with respect to the first snippet: determine a proximity within the document between two adjacent result instances of the multiple result instances within the first snippet; and further determine a required display space within the graphical user interface for splitting the first snippet into one or more additional snippets, wherein a given size of a display space is based at least in part on a number of result instances comprised in a given snippet; determine that the proximity between the two adjacent result instances is outside a proximity threshold; determine that the required display space within the graphical user interface is within an acceptable range; based on determining that the proximity between the two adjacent result instances is outside the proximity threshold and further based on determining that the required display space within the graphical user interface is within an acceptable range, split the first snippet into one or more additional snippets; and provide, for display within the graphical user interface, the one or more additional snippets, wherein each of the one or more additional snippets comprises one or more result instances from among the multiple result instances within the first snippet. | 14. A system comprising: at least one processor; and at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: receive a search query for searching an attribute within a document; provide, for display within a graphical user interface, a plurality of search results matching the attribute in a plurality of snippets, wherein each snippet of the plurality of snippets displays a portion of content from the document, and wherein each portion of content comprises at least one result from the plurality of search results matching the attribute; receive, based on a user interaction with graphical user interface, a first user input with respect to a first snippet of the plurality of snippets, wherein the first snippet comprises a first portion of content from the document, and wherein the first portion of content comprises multiple result instances from the plurality of search results; based on receiving the first user input with respect to the first snippet: determine a proximity within the document between two adjacent result instances of the multiple result instances within the first snippet; and further determine a required display space within the graphical user interface for splitting the first snippet into one or more additional snippets, wherein a given size of a display space is based at least in part on a number of result instances comprised in a given snippet; determine that the proximity between the two adjacent result instances is outside a proximity threshold; determine that the required display space within the graphical user interface is within an acceptable range; based on determining that the proximity between the two adjacent result instances is outside the proximity threshold and further based on determining that the required display space within the graphical user interface is within an acceptable range, split the first snippet into one or more additional snippets; and provide, for display within the graphical user interface, the one or more additional snippets, wherein each of the one or more additional snippets comprises one or more result instances from among the multiple result instances within the first snippet. 15. The system as claimed in claim 14 , wherein all of the content from the document is accessible from within each snippet of the plurality of snippets. | 0.588743 |
31. An automated information processing method, comprising: processing inferences about a probability distribution over informational goals given a query, a physical location of a user, and parts of speech containing a focus of attention of the query in accordance with attributes of a user and most appropriate level of detail, wherein the probability distribution is stored in one or more data structures that are comprised in an inference model, wherein parsing the query into the parts of speech facilitates accessing the data structures in the inference model; employing the inferences in at least one of a post-filter process, a reformulation process, a process for dynamically crafting an answer to the query; and a process for driving a dialog in pursuit of refining the probability distribution, and a process for driving dialog in pursuit of a more appropriate query in order to satisfy the informational goals before crafting the answer when at least one of the inferences about the informational goals has a likelihood below a predefined probability threshold wherein one or more of at least an attribute associated with the user or the inference model is refined based upon occurrence of the dialog with the user. | 31. An automated information processing method, comprising: processing inferences about a probability distribution over informational goals given a query, a physical location of a user, and parts of speech containing a focus of attention of the query in accordance with attributes of a user and most appropriate level of detail, wherein the probability distribution is stored in one or more data structures that are comprised in an inference model, wherein parsing the query into the parts of speech facilitates accessing the data structures in the inference model; employing the inferences in at least one of a post-filter process, a reformulation process, a process for dynamically crafting an answer to the query; and a process for driving a dialog in pursuit of refining the probability distribution, and a process for driving dialog in pursuit of a more appropriate query in order to satisfy the informational goals before crafting the answer when at least one of the inferences about the informational goals has a likelihood below a predefined probability threshold wherein one or more of at least an attribute associated with the user or the inference model is refined based upon occurrence of the dialog with the user. 38. The method of claim 31 , the process of for driving a dialog in pursuit of refining the probability distribution further comprises: driving the dialog over states of at least one of informational goals, age, appropriate level of detail, or focus of attention of the query. | 0.584606 |
13. A system for improving speech perception, comprising: a first transducer for receiving a first audio signal; an analysis module configured for: detecting one or more spectral characteristics of the first audio signal, the detected one or more spectral characteristics corresponding to one or more respective non-sonorant sounds; and classifying the one or more respective non-sonorant sounds, based on the detected one or more spectral characteristics of the first audio signal; a synthesis module configured for: selecting a second audio signal from a plurality of audio signals, responsive to at least the classification of the one or more respective non-sonorant sounds; and combining at least a portion of the first audio signal with the second audio signal for output to form a combined audio signal with frequency characteristics audible to the user; and a second transducer for outputting the combined audio signal. | 13. A system for improving speech perception, comprising: a first transducer for receiving a first audio signal; an analysis module configured for: detecting one or more spectral characteristics of the first audio signal, the detected one or more spectral characteristics corresponding to one or more respective non-sonorant sounds; and classifying the one or more respective non-sonorant sounds, based on the detected one or more spectral characteristics of the first audio signal; a synthesis module configured for: selecting a second audio signal from a plurality of audio signals, responsive to at least the classification of the one or more respective non-sonorant sounds; and combining at least a portion of the first audio signal with the second audio signal for output to form a combined audio signal with frequency characteristics audible to the user; and a second transducer for outputting the combined audio signal. 19. The system of claim 13 , wherein the analysis module is further configured for classifying the one or more non-sonorant sounds in the first audio signal as belonging to a first, second, or third group of one of a predetermined plurality of groups having distinct spectral characteristics, based on amplitudes of energy of the first audio signal in one or more predetermined frequency bands. | 0.677814 |
21. The non-transitory machine-accessible medium of claim 20 , wherein the instructions, when executed by the machine, further cause the machine to access a translation utility to access the enhanced local language dictionary. | 21. The non-transitory machine-accessible medium of claim 20 , wherein the instructions, when executed by the machine, further cause the machine to access a translation utility to access the enhanced local language dictionary. 22. The non-transitory machine-accessible medium of claim 21 , wherein the translation utility may be at least one of located on the machine or be coupled to the machine. | 0.92562 |
9. A non-transitory computer-readable storage medium storing one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of: rewriting an original query into a rewritten query, said original query including: a first path-based expression that evaluates to first one or more values, and a second path-based expression; wherein the rewritten query includes a first rewritten expression that causes the first one or more values to be computed using streaming evaluation; wherein the rewritten query includes a second rewritten expression that corresponds to said second path-based expression; computing the first rewritten expression using a streaming evaluation; computing the second rewritten expression using XML index evaluation of an XML index that indexes nodes in a collection of XML documents, wherein each index entry of entries of said XML index contains location data that identifies a location of an element within a representation of an XML document of said collection of XML documents; wherein the second rewritten expression evaluates to an output for location information within a representation of a particular XML document, wherein said output of said second rewritten expression is an input to said first rewritten expression, wherein said location information is derived from location data from an entry in said XML index; and wherein computing the first rewritten expression includes using said location information to locate an element within said representation of said particular XML document using streaming evaluation. | 9. A non-transitory computer-readable storage medium storing one or more sequences of instructions, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform the steps of: rewriting an original query into a rewritten query, said original query including: a first path-based expression that evaluates to first one or more values, and a second path-based expression; wherein the rewritten query includes a first rewritten expression that causes the first one or more values to be computed using streaming evaluation; wherein the rewritten query includes a second rewritten expression that corresponds to said second path-based expression; computing the first rewritten expression using a streaming evaluation; computing the second rewritten expression using XML index evaluation of an XML index that indexes nodes in a collection of XML documents, wherein each index entry of entries of said XML index contains location data that identifies a location of an element within a representation of an XML document of said collection of XML documents; wherein the second rewritten expression evaluates to an output for location information within a representation of a particular XML document, wherein said output of said second rewritten expression is an input to said first rewritten expression, wherein said location information is derived from location data from an entry in said XML index; and wherein computing the first rewritten expression includes using said location information to locate an element within said representation of said particular XML document using streaming evaluation. 12. The non-transitory computer-readable storage medium of claim 9 , wherein the first rewritten expression includes an expression that evaluates to a system-defined function not prescribed by a database language. | 0.647804 |
40. A computer program product comprising computer executable instructions embodied in a computer readable storage medium for performing steps comprising: (a) converting computer program source code into a fact set in a mathematical notation that supports direct expression of semantic reliances between elements of source code and is suitable for inputting into an automated inference engine; (b) providing an elemental design pattern catalog including at least one elemental design pattern for identifying a construct in the source code; (c) providing a rule set defining relationships between elemental design patterns identified as present in the computer program source code; and (d) comparing the fact set to the elemental design pattern catalog and applying the rules in the rule set to identify constructs present in the computer program source code, wherein comparing the fact set to the elemental design pattern catalog and applying the rules includes inputting the fact set, the elemental design pattern catalog, and the rules into an automated inference engine and identifying the construct present in the computer program source code. | 40. A computer program product comprising computer executable instructions embodied in a computer readable storage medium for performing steps comprising: (a) converting computer program source code into a fact set in a mathematical notation that supports direct expression of semantic reliances between elements of source code and is suitable for inputting into an automated inference engine; (b) providing an elemental design pattern catalog including at least one elemental design pattern for identifying a construct in the source code; (c) providing a rule set defining relationships between elemental design patterns identified as present in the computer program source code; and (d) comparing the fact set to the elemental design pattern catalog and applying the rules in the rule set to identify constructs present in the computer program source code, wherein comparing the fact set to the elemental design pattern catalog and applying the rules includes inputting the fact set, the elemental design pattern catalog, and the rules into an automated inference engine and identifying the construct present in the computer program source code. 41. The computer program product of claim 40 wherein converting the computer program source code into a fact set includes using a compiler to convert the source code into a parse tree. | 0.620112 |
3. The electronic device as claimed in claim 1 , wherein the text input interface is capable of switching between modes, the modes corresponding to a plurality of language interfaces, and the processor enables the text input interface to switch the language interfaces when the input signal received by the input device is a first predetermined gesture. | 3. The electronic device as claimed in claim 1 , wherein the text input interface is capable of switching between modes, the modes corresponding to a plurality of language interfaces, and the processor enables the text input interface to switch the language interfaces when the input signal received by the input device is a first predetermined gesture. 11. The electronic device as claimed in claim 3 , wherein, in a fourth mode, the input rule table comprises a Japanese input rule table, and the text input interface has a Japanese default interface when the text input interface operates as a Japanese interface, wherein the first display region is arranged to display a space key and an enter key in the Japanese default interface, and the second display region is arranged to display a first set of a plurality of Japanese consonants in the Japanese default interface. | 0.878836 |
37. A computer-readable non-transitory storage medium storing instructions for accessing a data item stored in a relational database, the computer-readable medium comprising instructions executable by one or more processors to perform steps of: generating, within a database server that manages the relational database, a Uniform Resource Locator (URL) that points to the data item based on where the data item resides within a row of a relational table of the relational database; wherein the URL includes an XPath expression that specifies: (a) the relational table, (b) a particular column of the relational table, and (c) a particular condition on the particular column; the database server providing the URL to an entity that resides outside the database server; receiving, at the database server, the URL; and in response to receiving the URL, resolving the URL within the database server to locate the data item within the row of the relational table; wherein resolving the URL includes converting the XPath expression into a Structured Query Language (SQL) statement that operates only on rows in the relational table where data in the particular column satisfies the particular condition. | 37. A computer-readable non-transitory storage medium storing instructions for accessing a data item stored in a relational database, the computer-readable medium comprising instructions executable by one or more processors to perform steps of: generating, within a database server that manages the relational database, a Uniform Resource Locator (URL) that points to the data item based on where the data item resides within a row of a relational table of the relational database; wherein the URL includes an XPath expression that specifies: (a) the relational table, (b) a particular column of the relational table, and (c) a particular condition on the particular column; the database server providing the URL to an entity that resides outside the database server; receiving, at the database server, the URL; and in response to receiving the URL, resolving the URL within the database server to locate the data item within the row of the relational table; wherein resolving the URL includes converting the XPath expression into a Structured Query Language (SQL) statement that operates only on rows in the relational table where data in the particular column satisfies the particular condition. 38. The computer-readable non-transitory storage medium of claim 37 , wherein the step of generating the URL includes adding to the URL data that indicates a data type associated with the data item. | 0.554552 |
4. The method of claim 1 , wherein the selected partition of the user-term index comprises a plurality of database shards organized by time, and indexing the term of the post and the post identifier into the selected partition of the user-term index comprises: selecting a record in a most recent database shard of the plurality of database shards, the record comprising the user identifier, the term identifier, and a list of post identifiers; and adding the post identifier into the list of post identifiers of the selected record in the most recent database shard. | 4. The method of claim 1 , wherein the selected partition of the user-term index comprises a plurality of database shards organized by time, and indexing the term of the post and the post identifier into the selected partition of the user-term index comprises: selecting a record in a most recent database shard of the plurality of database shards, the record comprising the user identifier, the term identifier, and a list of post identifiers; and adding the post identifier into the list of post identifiers of the selected record in the most recent database shard. 7. The method of claim 4 , wherein the plurality of database shards comprises a shard for each day of the month, a shard for each month of the year, or a shard for each hour of the day. | 0.759381 |
11. One or more computer storage media having stored thereon multiple instructions that, when executed by one or more processors of a computing device, cause the one or more processors to: receive a named entity input from a source; identify a target sense for the named entity input, wherein the target sense is a particular desired usage of the named entity input in a document set; and generate, based at least in part on both the named entity input and the document set, an extraction complexity measurement that indicates a complexity of identifying the named entity input in the document set for the target sense, wherein to generate the extraction complexity measurement is to build an undirected graph based on the named entity input and the document set, the undirected graph including multiple vertices and multiple edges, the multiple vertices comprising co-occurring contexts surrounding occurrences of the named entity input in the set of documents. | 11. One or more computer storage media having stored thereon multiple instructions that, when executed by one or more processors of a computing device, cause the one or more processors to: receive a named entity input from a source; identify a target sense for the named entity input, wherein the target sense is a particular desired usage of the named entity input in a document set; and generate, based at least in part on both the named entity input and the document set, an extraction complexity measurement that indicates a complexity of identifying the named entity input in the document set for the target sense, wherein to generate the extraction complexity measurement is to build an undirected graph based on the named entity input and the document set, the undirected graph including multiple vertices and multiple edges, the multiple vertices comprising co-occurring contexts surrounding occurrences of the named entity input in the set of documents. 16. One or more computer storage media as recited in claim 11 , wherein to generate the extraction complexity measurement is to perform a graph-based clustering technique to refine a language model obtained from performing a graph-based spreading activation technique. | 0.571543 |
8. The method of claim 1 wherein each of the plurality of tree-based structures is associated with a target language model score that depends on the tree-based structure and target language tokens associated with the tree-based structure. | 8. The method of claim 1 wherein each of the plurality of tree-based structures is associated with a target language model score that depends on the tree-based structure and target language tokens associated with the tree-based structure. 9. The method of claim 8 wherein decoding the input sequence of source tokens includes combining target language model scores associated with a plurality of tree-based structures. | 0.907184 |
1. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring first image information using at least one camera of a computing device; storing, for at least a minimum period of time, the first image information in a rolling buffer; acquiring second image information using the at least one camera; detecting, based at least in part on the second image information, one or more fingers of a user within a specified distance of the computing device; determining, using the second image information, movement of the one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the first image information stored in the rolling buffer to detect a second portion of the candidate hand gesture, the second portion having been performed before the first portion of the candidate hand gesture; based at least in part on the first portion of the candidate hand gesture and the second portion of the candidate hand gesture, determining a hand gesture performed by the user; comparing the performed hand gesture to a gesture pattern stored on the computing device; and authenticating an identity of the user as an authorized user, and providing an input to unlock the computing device from a locked state, in response to the hand gesture, performed by the user, being determined to correspond to the gesture stored on the computing device. | 1. A computer-implemented method, comprising: under control of one or more computing devices including executable instructions, acquiring first image information using at least one camera of a computing device; storing, for at least a minimum period of time, the first image information in a rolling buffer; acquiring second image information using the at least one camera; detecting, based at least in part on the second image information, one or more fingers of a user within a specified distance of the computing device; determining, using the second image information, movement of the one or more fingers, the movement corresponding to a first portion of a candidate hand gesture; analyzing the first image information stored in the rolling buffer to detect a second portion of the candidate hand gesture, the second portion having been performed before the first portion of the candidate hand gesture; based at least in part on the first portion of the candidate hand gesture and the second portion of the candidate hand gesture, determining a hand gesture performed by the user; comparing the performed hand gesture to a gesture pattern stored on the computing device; and authenticating an identity of the user as an authorized user, and providing an input to unlock the computing device from a locked state, in response to the hand gesture, performed by the user, being determined to correspond to the gesture stored on the computing device. 3. The computer-implemented method of claim 1 , further comprising: denying the user access to one or more of functionality or data on the computing device when one or more of the identity of the user is unable to be authenticated to correspond to an authorized user. | 0.546172 |
1. A computer-implemented method for controlling operations of a system in an environment using temporal patterns in data sequences, comprising: constructing a hierarchical tree of nodes, the hierarchical tree of nodes including a root node, a plurality of intermediate nodes, and a plurality of leaf nodes, and in which the root node has a plurality of child nodes, each intermediate node has a parent node and a plurality of child nodes, and each leaf node has a parent node; associating each node with a composite hidden Markov model, in which each composite hidden Markov model associated with the root node or an intermediate node has one independent path model corresponding to each child node of the node, and in which each composite hidden Markov model associated with a leaf node has a plurality of independent final path models; acquiring a set of training data sequences representing known temporal patterns of motion of physical objects in an environment; training the composite hidden Markov models using the set of training data sequences, in which the training further comprises: training the composite hidden Markov model associated with the root node with the set of training data sequences; training the composite hidden Markov models associated with each intermediate node with intermediate subsets of the set of training data sequences, each intermediate subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the intermediate node; and training the composite hidden Markov model associated with each leaf node with leaf subsets of the set of training data sequences to produce a plurality of trained final path models, each leaf subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the leaf node; constructing a single final composite hidden Markov model, in which the single final composite hidden Markov model has one independent path model for each trained final path model; acquiring unknown data sequences representing unknown temporal patterns of motion of physical objects in the environment; employing the single final composite hidden Markov model to determine known temporal patterns in the unknown data sequences; and controlling operations of a system in the environment using the determined known temporal patterns. | 1. A computer-implemented method for controlling operations of a system in an environment using temporal patterns in data sequences, comprising: constructing a hierarchical tree of nodes, the hierarchical tree of nodes including a root node, a plurality of intermediate nodes, and a plurality of leaf nodes, and in which the root node has a plurality of child nodes, each intermediate node has a parent node and a plurality of child nodes, and each leaf node has a parent node; associating each node with a composite hidden Markov model, in which each composite hidden Markov model associated with the root node or an intermediate node has one independent path model corresponding to each child node of the node, and in which each composite hidden Markov model associated with a leaf node has a plurality of independent final path models; acquiring a set of training data sequences representing known temporal patterns of motion of physical objects in an environment; training the composite hidden Markov models using the set of training data sequences, in which the training further comprises: training the composite hidden Markov model associated with the root node with the set of training data sequences; training the composite hidden Markov models associated with each intermediate node with intermediate subsets of the set of training data sequences, each intermediate subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the intermediate node; and training the composite hidden Markov model associated with each leaf node with leaf subsets of the set of training data sequences to produce a plurality of trained final path models, each leaf subset of the set of training data sequences including a training data sequence generated by the corresponding independent path model of the parent node of the leaf node; constructing a single final composite hidden Markov model, in which the single final composite hidden Markov model has one independent path model for each trained final path model; acquiring unknown data sequences representing unknown temporal patterns of motion of physical objects in the environment; employing the single final composite hidden Markov model to determine known temporal patterns in the unknown data sequences; and controlling operations of a system in the environment using the determined known temporal patterns. 10. The computer-implemented method of claim 1 , further comprising: retraining the single final composite hidden Markov model using all of the training data sequences. | 0.601263 |
1. A method, comprising: obtaining a collection of clusters of immutable observations about entities, at least a plurality of the clusters each: corresponding to a respective entity, identifying immutable observations determined to describe the respective entity, and having summary attribute-value pairs that summarize the identified observations and collectively describe an inferred current state of the respective entity; receiving a new observation about a given entity; selecting, with one or more processors, a cluster among the collection of clusters based on correspondence of the selected cluster to the given entity; summarizing, with one or more processors, the selected cluster by updating at least some of the summary attribute-value pairs of the selected cluster based on both the new observation and the observations identified by the selected cluster; storing the updated attribute-value pairs in memory in association with the selected cluster; and updating a user interface at a user device using the new observation. | 1. A method, comprising: obtaining a collection of clusters of immutable observations about entities, at least a plurality of the clusters each: corresponding to a respective entity, identifying immutable observations determined to describe the respective entity, and having summary attribute-value pairs that summarize the identified observations and collectively describe an inferred current state of the respective entity; receiving a new observation about a given entity; selecting, with one or more processors, a cluster among the collection of clusters based on correspondence of the selected cluster to the given entity; summarizing, with one or more processors, the selected cluster by updating at least some of the summary attribute-value pairs of the selected cluster based on both the new observation and the observations identified by the selected cluster; storing the updated attribute-value pairs in memory in association with the selected cluster; and updating a user interface at a user device using the new observation. 9. The method of claim 1 , wherein summarizing the selected cluster by updating at least some of the summary attribute-value pairs of the selected cluster comprises: determining that a state of the given entity has changed; and in response to the determination, updating a summary attribute-value pair of the cluster corresponding to the given entity based on a value conveyed by the new observation. | 0.83579 |
7. The system according to claim 1 , wherein the at least one data source comprises an inmate telephone system. | 7. The system according to claim 1 , wherein the at least one data source comprises an inmate telephone system. 8. The system according to claim 7 , wherein the at least one data source further comprises an inmate management system. | 0.969117 |
13. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying different sets of lists for different columns of the document, each column ordered within the document based on a reading order; identifying a first list in a first column of the document that has an open end state; identifying a second list, in a second column of the document subsequent to the first column in the reading order, that has an open start state; determining that the first list in the first column continues as the second list in the second column of the document; and storing the first list and the second list as a single list structure associated with the document. | 13. A non-transitory machine readable medium storing a program which when executed by at least one processing unit analyzes a document comprising a plurality of primitive elements, the program comprising sets of instructions for: identifying different sets of lists for different columns of the document, each column ordered within the document based on a reading order; identifying a first list in a first column of the document that has an open end state; identifying a second list, in a second column of the document subsequent to the first column in the reading order, that has an open start state; determining that the first list in the first column continues as the second list in the second column of the document; and storing the first list and the second list as a single list structure associated with the document. 18. The non-transitory machine readable medium of claim 13 , wherein the second column in the document is immediately after the first column of the document in a reading order of the document. | 0.705499 |
12. A method of presenting speech information comprising producing a sequence of signals representative of speech phonemes; transforming the signals into a sequence of first and second grid patterns of points, the first pattern being a code which identifies the phoneme sound and the second pattern being another code which identifies a mouth form that produces the phoneme sound; and presenting the first and second patterns by activating presenters arranged in a multiple point grid matrix in accordance with said patterns of points. | 12. A method of presenting speech information comprising producing a sequence of signals representative of speech phonemes; transforming the signals into a sequence of first and second grid patterns of points, the first pattern being a code which identifies the phoneme sound and the second pattern being another code which identifies a mouth form that produces the phoneme sound; and presenting the first and second patterns by activating presenters arranged in a multiple point grid matrix in accordance with said patterns of points. 17. The method of claim 12, wherein said presenting comprises presenting the first and second patterns on first and second arrays of presenters. | 0.67093 |
9. The system for annotation of electronic messages with contextual information of claim 1 , wherein said processor further comprises a training set that develops or revises methods for feature extraction and information selection. | 9. The system for annotation of electronic messages with contextual information of claim 1 , wherein said processor further comprises a training set that develops or revises methods for feature extraction and information selection. 10. The system for annotation of electronic messages with contextual information of claim 9 , wherein said processor tracks usage of said one or more contextual information items by said one or more recipients, wherein data received as feedback by said processor is used to revise said methods for feature extraction and information selection. | 0.958753 |
16. The system of claim 11 , wherein the media content is a media program that includes an audio track. | 16. The system of claim 11 , wherein the media content is a media program that includes an audio track. 18. The system of claim 16 , wherein the media guidance data is available in both the alternate language and the preferred language. | 0.930911 |
13. A non-transitory computer-readable storage medium storing executable computer program instructions for correcting textual errors in digital volumes in a corpus, the computer program instructions comprising instructions for: receiving a plurality of candidate volumes comprising a basis volume and a plurality of comparison volumes; comparing the basis volume with the plurality of comparison volumes to identify identical sequences of text that are identical across all of the plurality of candidate volumes and mismatched sequences of text that contain different text in different candidate volumes; resolving at least some of the mismatched sequences by comparing the different text in the different candidate volumes to ascertain correct text for the mismatched sequences by: determining a type of mismatch for a given mismatched sequence that contains different versions of text in different candidate volumes; and applying a resolution technique to the given mismatched sequence selected responsive to the type of mismatch; and correcting errors in the plurality of candidate volumes using the ascertained correct text. | 13. A non-transitory computer-readable storage medium storing executable computer program instructions for correcting textual errors in digital volumes in a corpus, the computer program instructions comprising instructions for: receiving a plurality of candidate volumes comprising a basis volume and a plurality of comparison volumes; comparing the basis volume with the plurality of comparison volumes to identify identical sequences of text that are identical across all of the plurality of candidate volumes and mismatched sequences of text that contain different text in different candidate volumes; resolving at least some of the mismatched sequences by comparing the different text in the different candidate volumes to ascertain correct text for the mismatched sequences by: determining a type of mismatch for a given mismatched sequence that contains different versions of text in different candidate volumes; and applying a resolution technique to the given mismatched sequence selected responsive to the type of mismatch; and correcting errors in the plurality of candidate volumes using the ascertained correct text. 18. The non-transitory computer-readable storage medium of claim 13 , further comprising: determining a proportion of text that a comparison volume of the plurality of comparison volumes has in common with the basis volume; and filtering the comparison volume of the plurality of comparison volumes out of the plurality of candidate volumes responsive to the proportion of text being below a specified threshold proportion. | 0.578864 |
14. One or more tangible computer-readable media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for performing interleaving experiments on blended search results, the method comprising: identifying a plurality of search query categories; for search queries that belong to a first category of search queries of the identified plurality of search query categories, identifying two or more blending algorithms that blend search results produced by two or more ranking systems to generate blended search results; generating two or more sets of the blended search results from the identified two or more blending algorithms; performing the interleaving experiments on the generated two or more sets of the blended search results from the identified two or more blending algorithms to determine an optimal blending algorithm; associating the determined optimal blending algorithm with the first category of search queries: and utilizing the determined optimal blending algorithm to blend search results when a search query in the first category of search queries is received. | 14. One or more tangible computer-readable media storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for performing interleaving experiments on blended search results, the method comprising: identifying a plurality of search query categories; for search queries that belong to a first category of search queries of the identified plurality of search query categories, identifying two or more blending algorithms that blend search results produced by two or more ranking systems to generate blended search results; generating two or more sets of the blended search results from the identified two or more blending algorithms; performing the interleaving experiments on the generated two or more sets of the blended search results from the identified two or more blending algorithms to determine an optimal blending algorithm; associating the determined optimal blending algorithm with the first category of search queries: and utilizing the determined optimal blending algorithm to blend search results when a search query in the first category of search queries is received. 19. The one or more tangible computer-readable media of claim 14 , wherein one or more of the identified plurality of search query categories describe a subject matter of the search queries in the search query category. | 0.643921 |
8. A computer program product for verifying factual assertions in natural language, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to monitor a natural language input, wherein the natural language input includes an audio input; program instructions to process the audio input into a digital input by an audio input processing module; program instructions to transmit the digital input to a transcription module; program instructions to transcribe the digital input into a natural language text input by a speech transcription engine within the transcription module which matches the audio input to one or more acoustic models detailed by an electronic database; program instructions to identify a phrase within the natural language text input, wherein the phrase comprises a subject, an object, and a relation; program instructions to determine if the phrase is a statement of opinion; program instructions to determine if the phrase is an indication of a consequence of a prior statement; program instructions to identify the phrase as a factual assertion if the phase is not a statement of opinion and not an indication of a consequence of a prior statement; program instructions to verify the factual assertion in the natural language text input; and program instructions to output a notification to a user of a result of the verification. | 8. A computer program product for verifying factual assertions in natural language, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to monitor a natural language input, wherein the natural language input includes an audio input; program instructions to process the audio input into a digital input by an audio input processing module; program instructions to transmit the digital input to a transcription module; program instructions to transcribe the digital input into a natural language text input by a speech transcription engine within the transcription module which matches the audio input to one or more acoustic models detailed by an electronic database; program instructions to identify a phrase within the natural language text input, wherein the phrase comprises a subject, an object, and a relation; program instructions to determine if the phrase is a statement of opinion; program instructions to determine if the phrase is an indication of a consequence of a prior statement; program instructions to identify the phrase as a factual assertion if the phase is not a statement of opinion and not an indication of a consequence of a prior statement; program instructions to verify the factual assertion in the natural language text input; and program instructions to output a notification to a user of a result of the verification. 14. The computer program product in accordance with claim 8 , further comprising: program instructions to determine if the factual assertion is ambiguous; and program instructions to resolve the ambiguity using contextual input. | 0.593392 |
1. A computer-implemented method for determining similar users, comprising: receiving information for a source user, at a computer system, the information including at least one topic and a user value for each topic, where: the user value includes a user authority value representing a user expertise related to that topic and a user interest value representing a degree of user association with that topic, and the user value represents how strongly the user is associated with that topic; generating similarity scores based on a user value for each topic for the source user and a user value for the same topic for each user in a set of users, where each user in the set of users is associated with a user value for each topic; selecting one or more similar users based on the generated similarity scores; outputting one or more of the selected users; and outputting the identity of one or more overlapping topics and a value indicating a degree of overlap for each overlapping topic. | 1. A computer-implemented method for determining similar users, comprising: receiving information for a source user, at a computer system, the information including at least one topic and a user value for each topic, where: the user value includes a user authority value representing a user expertise related to that topic and a user interest value representing a degree of user association with that topic, and the user value represents how strongly the user is associated with that topic; generating similarity scores based on a user value for each topic for the source user and a user value for the same topic for each user in a set of users, where each user in the set of users is associated with a user value for each topic; selecting one or more similar users based on the generated similarity scores; outputting one or more of the selected users; and outputting the identity of one or more overlapping topics and a value indicating a degree of overlap for each overlapping topic. 15. The method of claim 1 , wherein the one or more overlapping topics are selected based on a degree of overlap being above a predetermined threshold degree of overlap. | 0.546193 |
1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain. | 1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain. 10. The method of claim 1 , wherein the content item comprises: text; video content; one or more images; audio content; or one or more links. | 0.59359 |
1. A computer-implemented method comprising: identifying, using one or more processors, a creative for processing, the creative including a title portion, a body portion and optionally a reference portion, wherein the title portion constitutes a first line of text, and the body portion includes second and third lines of text; evaluating the body portion including determining when the body portion includes one or more words that can be added to the title portion, wherein evaluating the body portion includes evaluating either or both of the second and the third line of text to identify the one or more words; promoting, using the one or more processors, the one or more words into the title portion; and providing the creative including the title portion with the promoted one or more words. | 1. A computer-implemented method comprising: identifying, using one or more processors, a creative for processing, the creative including a title portion, a body portion and optionally a reference portion, wherein the title portion constitutes a first line of text, and the body portion includes second and third lines of text; evaluating the body portion including determining when the body portion includes one or more words that can be added to the title portion, wherein evaluating the body portion includes evaluating either or both of the second and the third line of text to identify the one or more words; promoting, using the one or more processors, the one or more words into the title portion; and providing the creative including the title portion with the promoted one or more words. 10. The method of claim 1 wherein promoting the one or more words includes constructing a link for the title portion after promotion. | 0.660032 |
13. The computer program product as set forth in claim 12 wherein the automatically performing a crowd sourcing operation comprises performing a historical analysis of similar questions, clues or combination of questions and clues to determine potentially missing information from the received question or received clue, and performing an action to collect the missing information, and wherein the supplying a crowd-sourced enhancement to the deep question-answer computing system comprises including the collected missing information with the a crowd-sourced enhancement. | 13. The computer program product as set forth in claim 12 wherein the automatically performing a crowd sourcing operation comprises performing a historical analysis of similar questions, clues or combination of questions and clues to determine potentially missing information from the received question or received clue, and performing an action to collect the missing information, and wherein the supplying a crowd-sourced enhancement to the deep question-answer computing system comprises including the collected missing information with the a crowd-sourced enhancement. 14. The computer program product as set forth in claim 13 wherein the collection of missing information comprises at least one action selected from the group consisting of prompting a user via a user interface for the missing information, retrieving the missing information from a data repository, and querying one or more domain expert users via communications devices for the missing information, wherein the queried domain expert users are selected from a list of subject domain experts. | 0.787541 |
11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. | 11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. 14. The media processor of claim 11 , wherein the operations further comprise: receiving a blog message; identifying a blog leader associated with the blog message; and directing the blog message to a blog group of the blog leader. | 0.580851 |
21. The system of claim 18 , the operation further comprising: upon determining that the first word of the text input is not validated against at least one of the content corpus and the set of rules, disabling a submit button configured to display the text input in the online chat room, wherein disabling the submit button restricts display of the text input in the online chat room. | 21. The system of claim 18 , the operation further comprising: upon determining that the first word of the text input is not validated against at least one of the content corpus and the set of rules, disabling a submit button configured to display the text input in the online chat room, wherein disabling the submit button restricts display of the text input in the online chat room. 22. The system of claim 21 , wherein disabling the submit button further comprises: replacing the submit button with a selectable element configured to: accept the first approved word as the replacement to the first word; and submit the modified text input to the online chat room for display. | 0.879471 |
13. A non-transitory computer-readable storage medium containing one or more markup language documents for being rendered by a web browser application executing on a computer system, the one or more markup language documents comprising: a hierarchical structure of nodes representing elements of a markup language document and edges connecting the nodes, wherein: a subset of nodes mapped to node types and a root node connected with other nodes via paths comprising nodes and edges; and a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; instructions to a web browser application executing on a computer system for executing handlers in response to an event, the instructions for causing the computer system to: receive a user input associated with a selected node; identify a set of node types encountered in a path connecting the root node with the selected node; identify a set of handlers mapped to the identified set of node types based on the mapping; and execute the handlers in the identified set of handlers. | 13. A non-transitory computer-readable storage medium containing one or more markup language documents for being rendered by a web browser application executing on a computer system, the one or more markup language documents comprising: a hierarchical structure of nodes representing elements of a markup language document and edges connecting the nodes, wherein: a subset of nodes mapped to node types and a root node connected with other nodes via paths comprising nodes and edges; and a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; instructions to a web browser application executing on a computer system for executing handlers in response to an event, the instructions for causing the computer system to: receive a user input associated with a selected node; identify a set of node types encountered in a path connecting the root node with the selected node; identify a set of handlers mapped to the identified set of node types based on the mapping; and execute the handlers in the identified set of handlers. 18. The non-transitory computer readable storage medium of claim 13 , wherein the selected node is displayed in the browser as one of a link, button, or image. | 0.561142 |
16. A method comprising: receiving, by a user device that is physically separate from a speech interface device, information regarding a historical speech interaction conducted at least in part through the speech interface device between a user and a speech interface platform, wherein the information indicates recognized speech from a user utterance and at least one of (a) a user intent that was understood from the recognized speech, (b) text corresponding to speech generated by the speech interface platform in response to the user utterance, or (c) an action performed by the speech interface platform in response to the user utterance; accepting, by the user device that is physically separate from the speech interface device via a first graphical interface displayed at the user device, a selection of a historical interaction record from a plurality of historical interaction records, the historical interaction record associated with the information regarding the historical speech interaction; accepting, by the user device via a second graphical interface, one or more edits or evaluations from the user regarding the historical speech interaction, the second graphical interface presented at least in part based on the selection; and providing, by the user device that is physically separate from the speech interface device and to the speech interface platform, the edits or evaluations regarding the historical speech interaction for use in conjunction with future speech interactions and for improving future speech recognition and intent understanding on a subsequent audio signal received from the speech interface device. | 16. A method comprising: receiving, by a user device that is physically separate from a speech interface device, information regarding a historical speech interaction conducted at least in part through the speech interface device between a user and a speech interface platform, wherein the information indicates recognized speech from a user utterance and at least one of (a) a user intent that was understood from the recognized speech, (b) text corresponding to speech generated by the speech interface platform in response to the user utterance, or (c) an action performed by the speech interface platform in response to the user utterance; accepting, by the user device that is physically separate from the speech interface device via a first graphical interface displayed at the user device, a selection of a historical interaction record from a plurality of historical interaction records, the historical interaction record associated with the information regarding the historical speech interaction; accepting, by the user device via a second graphical interface, one or more edits or evaluations from the user regarding the historical speech interaction, the second graphical interface presented at least in part based on the selection; and providing, by the user device that is physically separate from the speech interface device and to the speech interface platform, the edits or evaluations regarding the historical speech interaction for use in conjunction with future speech interactions and for improving future speech recognition and intent understanding on a subsequent audio signal received from the speech interface device. 21. The method of claim 16 , wherein the one or more edits or evaluations comprise a rating of the speech generated by the speech interface platform. | 0.680836 |
1. A method of performing an input/output (I/O) processing operation at a host computer system configured for communication with a control unit, the method comprising: obtaining information relating to an I/O operation at a channel subsystem in the host computer system, the channel subsystem including at least one channel having a channel processor and a local channel memory, the channel subsystem in communication with a network interface configured to transmit data between the channel subsystem and the control unit during the I/O operation; generating at least one address control word (ACW) specifying at least one host memory location for transfer of the data between the host computer system and the control unit, and storing the at least one ACW in the local channel memory, the at least one ACW including at least one of a data check word generation field and a data check word save field; generating an address control structure for each data transfer specified by the I/O operation and forwarding each address control structure from the at least one channel to the network interface, each address control structure specifying a location in the local channel memory of a corresponding ACW; forwarding an I/O command message to the at least one I/O device via the network interface; responsive to the I/O command message, receiving a data transfer request from the network interface that includes the address control structure; responsive to the data transfer request including input data to be stored in the host memory and at least one received data check word, storing the at least one received data check word in the data check word save field and performing a check of the input data to determine whether the input data has been corrupted, and routing the input data to one of the at least one host memory location specified by the corresponding ACW responsive to determining that the input data has not been corrupted; and responsive to the input data transfer request including a request for output data to be retrieved from the host memory, retrieving the output data from the one or another of the at least one host memory location specified by the corresponding ACW, generating at least one data check word based on the data check word generation field, appending the at least one generated data check word to the output data, and routing the output data and the at least one generated data check word to the network interface. | 1. A method of performing an input/output (I/O) processing operation at a host computer system configured for communication with a control unit, the method comprising: obtaining information relating to an I/O operation at a channel subsystem in the host computer system, the channel subsystem including at least one channel having a channel processor and a local channel memory, the channel subsystem in communication with a network interface configured to transmit data between the channel subsystem and the control unit during the I/O operation; generating at least one address control word (ACW) specifying at least one host memory location for transfer of the data between the host computer system and the control unit, and storing the at least one ACW in the local channel memory, the at least one ACW including at least one of a data check word generation field and a data check word save field; generating an address control structure for each data transfer specified by the I/O operation and forwarding each address control structure from the at least one channel to the network interface, each address control structure specifying a location in the local channel memory of a corresponding ACW; forwarding an I/O command message to the at least one I/O device via the network interface; responsive to the I/O command message, receiving a data transfer request from the network interface that includes the address control structure; responsive to the data transfer request including input data to be stored in the host memory and at least one received data check word, storing the at least one received data check word in the data check word save field and performing a check of the input data to determine whether the input data has been corrupted, and routing the input data to one of the at least one host memory location specified by the corresponding ACW responsive to determining that the input data has not been corrupted; and responsive to the input data transfer request including a request for output data to be retrieved from the host memory, retrieving the output data from the one or another of the at least one host memory location specified by the corresponding ACW, generating at least one data check word based on the data check word generation field, appending the at least one generated data check word to the output data, and routing the output data and the at least one generated data check word to the network interface. 2. The method of claim 1 , wherein the at least one received data check word and the at least one generated data check word are selected from a longitudinal redundancy check word (LRC), a cyclical redundancy check word (CRC) and a Check Sum. | 0.516939 |
10. A non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising: receiving an image of a portion of a document that was captured by a first user using a camera, wherein the image includes text; identifying an electronic document that includes the text; determining, by the one or more computing devices, that there are a plurality of versions related to the identified electronic document, wherein the plurality of versions of the electronic document include a first version that corresponds to the document and a second version that differs from the first version; and providing, in response to the determination, data that present document information informing the first user of the plurality of versions of the electronic document together with information identifying, to the first user, a second user that is currently reading a most recent version of the document. | 10. A non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processor, cause the processor to perform operations comprising: receiving an image of a portion of a document that was captured by a first user using a camera, wherein the image includes text; identifying an electronic document that includes the text; determining, by the one or more computing devices, that there are a plurality of versions related to the identified electronic document, wherein the plurality of versions of the electronic document include a first version that corresponds to the document and a second version that differs from the first version; and providing, in response to the determination, data that present document information informing the first user of the plurality of versions of the electronic document together with information identifying, to the first user, a second user that is currently reading a most recent version of the document. 13. The non-transitory computer-readable storage medium of claim 10 , wherein the first version of the electronic document corresponds to a first publication of the electronic document and the second version of the electronic document corresponds to a second publication of the electronic document. | 0.585147 |
1. A method for instructing a programmable computer, the method comprising: receiving from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, and the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; a declarative specification for controlling the game character in the computer game as a function of the first grouping, wherein the first grouping is a logical implication in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and the game character does not perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; and during the computer game, in response to the declarative specification, allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is positive and not allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. | 1. A method for instructing a programmable computer, the method comprising: receiving from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, and the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; a declarative specification for controlling the game character in the computer game as a function of the first grouping, wherein the first grouping is a logical implication in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and the game character does not perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; and during the computer game, in response to the declarative specification, allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is positive and not allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. 23. The method of claim 1 , further comprising: receiving from the user through the user interface, another adjustment input to move another icon on the screen to a position in which the another icon is touching one or more other icons to form a second grouping separate from the first grouping, the second grouping comprises an icon of a second data indication predicate touching an icon of a second action predicate, the second data indication predicate is positive or negative based on the position of the game character relative to the object in the computer game, the second data indication predicate is positive when the first data indication predicate is negative, and negative when the first data indication predicate is positive; altering the declarative specification for controlling the game character in the computer game as a function of the second grouping; and during the computer game, in response to the declarative specification, causing the game character to perform a respective action identified by the icon of the second action predicate when the second data indication predicate is positive. | 0.528679 |
6. The system of claim 5 , further comprising: a fourth module controlling the processor, after the virtual agent finishes speaking to the user, to receive additional speech data from the user and transmit the additional speech data to the server for speech processing in order to generate a response by the virtual agent to the user. | 6. The system of claim 5 , further comprising: a fourth module controlling the processor, after the virtual agent finishes speaking to the user, to receive additional speech data from the user and transmit the additional speech data to the server for speech processing in order to generate a response by the virtual agent to the user. 7. The system of claim 6 , further comprising: a fifth module controlling the processor, after the user finishes a speech segment, to receive responsive speech from the server for generating a virtual agent response to the user. | 0.825734 |
16. The method of claim 1 , wherein the executing that implements the data network comprises: classifying whether each of a plurality of objects of the data network belongs to the class designated by the domain of the process step; performing the algorithm on each of the plurality of objects that belong to the class; automatically generating a second class that is part of the class network, wherein the domain designates the second class instead of the class; and performing the algorithm on each object of the plurality of objects that belong to the second class. | 16. The method of claim 1 , wherein the executing that implements the data network comprises: classifying whether each of a plurality of objects of the data network belongs to the class designated by the domain of the process step; performing the algorithm on each of the plurality of objects that belong to the class; automatically generating a second class that is part of the class network, wherein the domain designates the second class instead of the class; and performing the algorithm on each object of the plurality of objects that belong to the second class. 17. The method of claim 16 , wherein the executing that implements the data network further comprises: deleting the class from the class network. | 0.77786 |
37. The computer-readable medium recited in claim 31, further containing instructions for causing the computer to create, in response to input from a user, a word list containing information relating to a plurality of words of a vocabulary that represent possible spoken responses that might be recognized by the computer during a speech recognition process. | 37. The computer-readable medium recited in claim 31, further containing instructions for causing the computer to create, in response to input from a user, a word list containing information relating to a plurality of words of a vocabulary that represent possible spoken responses that might be recognized by the computer during a speech recognition process. 38. The computer-readable medium recited in claim 37, wherein the word list is associated with one of said plurality of subsets of prompt definitions. | 0.879603 |
10. A method for supporting multi-user collaborative program development, the method comprising: obtaining a code snippet, wherein the code snippet is software program source code; classifying, automatically, by a processor, the code snippet; storing the classified code snippet in a code repository, wherein the code repository maintains a plurality of classified code snippets of software program source code that are shared among the developers; and providing automated programming assistance by the processor, wherein the automated programming assistance includes one or more classified code snippets in the code repository, wherein providing automated programming assistance comprises, processing the code snippet to identify a code pattern and a quality score; and retrieving from the code repository, at least one different code snippet having a similar code pattern and a higher quality score than the code snippet. | 10. A method for supporting multi-user collaborative program development, the method comprising: obtaining a code snippet, wherein the code snippet is software program source code; classifying, automatically, by a processor, the code snippet; storing the classified code snippet in a code repository, wherein the code repository maintains a plurality of classified code snippets of software program source code that are shared among the developers; and providing automated programming assistance by the processor, wherein the automated programming assistance includes one or more classified code snippets in the code repository, wherein providing automated programming assistance comprises, processing the code snippet to identify a code pattern and a quality score; and retrieving from the code repository, at least one different code snippet having a similar code pattern and a higher quality score than the code snippet. 19. The method of claim 10 , wherein storing the code snippet in the code repository comprises organizing the code snippets in the code repository using a multi-level class hierarchy structure. | 0.58347 |
27. The system for presenting an electronic document of claim 24 wherein the second analysis module further comprises a device accommodation editor that is operative with the reduction engine to combine a plurality of values in the second tagged file to generate a property deliverable file that controls the presentation of the electronic document on a hand held device. | 27. The system for presenting an electronic document of claim 24 wherein the second analysis module further comprises a device accommodation editor that is operative with the reduction engine to combine a plurality of values in the second tagged file to generate a property deliverable file that controls the presentation of the electronic document on a hand held device. 28. The system for presenting an electronic document of claim 27 wherein the hand held device includes at least one of a cellular phone, a pager, and a personal digital assistant. | 0.888179 |
5. The method of claim 1 , wherein the binarized background artifacts include blobs and wherein a sliding mask is utilized to detect and remove the blobs. | 5. The method of claim 1 , wherein the binarized background artifacts include blobs and wherein a sliding mask is utilized to detect and remove the blobs. 6. The method of claim 5 , wherein the blobs that are greater than a predetermined number of pixels in size are removed. | 0.960993 |
14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. | 14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. 15. The method as recited in claim 14 , further comprising compensating for the rotation of the input gesture from which the input gesture data was created prior to taking the plurality of samples. | 0.548502 |
18. Program controlled digital data processing means for locating from a plurality of digital coded candidate words at least one candidate word which is both an acceptable misspelling and an acceptable inflection of a digital coded query word, the query word and each of a plurality of the query words comprising plural characters, the data processing means comprising: (a) programmed digital data processing means for determining characters forming a stem portion and an ending portion of such query word and for determining and forming a suffix class indication of any one of a plurality of classes in which the query word may be included; (b) programmed digital data processing means for comparing the characters forming the stem portion of the query word with characters starting at the beginning of each of a plurality of such candidate words for finding candidate words having beginning portions with acceptable misspelling matches and those with nonacceptable misspelling matches and, for each of individual ones of those candidate words having an acceptable misspelling match, operative for forming an acceptable misspelling class indication representing a value for any one of a plurality of classes in which the acceptable misspelling match for such candidate word may be included; (c) programmed digital data processing means utilizing the acceptable misspelling class indication for each of individual ones of the candidate words to identify an ending portion, if any, in the corresponding candidate word; (d) programmed digital data processing means for utilizing the suffix class indication for the query word to select from among other suffixes a representation of at least one acceptable suffix for the candidate words; and (e) programmed digital data processing means for comparing the characters of said at least one acceptable suffix with the characters of the ending portion in each of individual ones of the candidate words for finding candidate words having acceptable ending portions. | 18. Program controlled digital data processing means for locating from a plurality of digital coded candidate words at least one candidate word which is both an acceptable misspelling and an acceptable inflection of a digital coded query word, the query word and each of a plurality of the query words comprising plural characters, the data processing means comprising: (a) programmed digital data processing means for determining characters forming a stem portion and an ending portion of such query word and for determining and forming a suffix class indication of any one of a plurality of classes in which the query word may be included; (b) programmed digital data processing means for comparing the characters forming the stem portion of the query word with characters starting at the beginning of each of a plurality of such candidate words for finding candidate words having beginning portions with acceptable misspelling matches and those with nonacceptable misspelling matches and, for each of individual ones of those candidate words having an acceptable misspelling match, operative for forming an acceptable misspelling class indication representing a value for any one of a plurality of classes in which the acceptable misspelling match for such candidate word may be included; (c) programmed digital data processing means utilizing the acceptable misspelling class indication for each of individual ones of the candidate words to identify an ending portion, if any, in the corresponding candidate word; (d) programmed digital data processing means for utilizing the suffix class indication for the query word to select from among other suffixes a representation of at least one acceptable suffix for the candidate words; and (e) programmed digital data processing means for comparing the characters of said at least one acceptable suffix with the characters of the ending portion in each of individual ones of the candidate words for finding candidate words having acceptable ending portions. 19. Programmed digital data processing means according to claim 18 comprising means for separating from the rest of the candidate words each of individual ones of those candidate words found by previously recited programmed digital processing means as having both a beginning portion with the acceptable misspelling match and the acceptable ending portion. | 0.576987 |
11. A handheld optical scanner, comprising: an optical imaging component adapted to capture images of text from rendered documents at a first time, convert at least some of the captured images to textual representations at a second time, and compress or delete any converted captured images at a third time; a memory component coupled to the optical imaging component; a universal serial bus port coupled to the memory component; a processor coupled to the memory component; and a battery coupled to the optical imaging component, the memory component, the universal serial bus port, and the processor; wherein the memory component is adapted to receive data from the universal serial bus port, to store data received via the universal serial bus port, and to transmit data via the universal serial bus port to another device, and wherein the memory component is further adapted to receive data derived from images captured by the optical imaging component and store the data derived from images captured the optical imaging component. | 11. A handheld optical scanner, comprising: an optical imaging component adapted to capture images of text from rendered documents at a first time, convert at least some of the captured images to textual representations at a second time, and compress or delete any converted captured images at a third time; a memory component coupled to the optical imaging component; a universal serial bus port coupled to the memory component; a processor coupled to the memory component; and a battery coupled to the optical imaging component, the memory component, the universal serial bus port, and the processor; wherein the memory component is adapted to receive data from the universal serial bus port, to store data received via the universal serial bus port, and to transmit data via the universal serial bus port to another device, and wherein the memory component is further adapted to receive data derived from images captured by the optical imaging component and store the data derived from images captured the optical imaging component. 20. The handheld optical scanner of claim 11 , wherein the memory component is a solid-state storage component. | 0.568079 |
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