sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|
14. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: receive an item, wherein the item indicates a text string comprising a plurality of characters, and a respective preferred font for each character of said plurality of characters; perform a character-by-character font substitution analysis on each character of said text string, wherein performing said analysis comprises: in response to determining that the preferred font is not available for a particular character, resolve the particular character with a particular glyph from a font of a set of multiple safe fonts, wherein said particular glyph matches said particular character, and wherein said set of safe fonts collectively spans a character set; in response to determining that the preferred font is not available for an other character of the same text string, resolve the other character with an other glyph from a different font of said set of safe fonts, wherein said other glyph matches said other character; and generate a resolved text string comprising said particular glyph and said other glyph. | 14. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: receive an item, wherein the item indicates a text string comprising a plurality of characters, and a respective preferred font for each character of said plurality of characters; perform a character-by-character font substitution analysis on each character of said text string, wherein performing said analysis comprises: in response to determining that the preferred font is not available for a particular character, resolve the particular character with a particular glyph from a font of a set of multiple safe fonts, wherein said particular glyph matches said particular character, and wherein said set of safe fonts collectively spans a character set; in response to determining that the preferred font is not available for an other character of the same text string, resolve the other character with an other glyph from a different font of said set of safe fonts, wherein said other glyph matches said other character; and generate a resolved text string comprising said particular glyph and said other glyph. 15. The system of claim 14 , wherein said item indicates dimensions of a bounding box for the text string, wherein the program instructions are executable to scale the size of the resolved text string according to the dimensions of the bounding box. | 0.522291 |
9. A method comprising: providing for display a plurality of options for selecting a sponsored story specification for generating a sponsored story in an online social networking system, the sponsored story comprising promoting a story selected from an organic activity stream of stories in the online social networking system; receiving, from the plurality of options, selection of a request to create a new sponsored story specification; providing for display one or more entities in the online social networking system for use in generating the sponsored story specification related to one of the entities; receiving a first user input selecting a target entity from the one or more entities as a first criterion for the sponsored story specification; providing for display one or more interactions for use in generating the sponsored story specification, each interaction comprising information about a user action with the selected entity taken in the online social networking system; receiving a second user input selecting a target interaction comprising a user action with the selected entity taken in the online social networking system as a second criterion for the sponsored story; generating, by a computer processor, a new sponsored story specification, the sponsored story specification specifying the first and second criteria for identifying, from the organic activity stream of stories in the online social networking system, one or more stories describing the selected interaction taken on the selected target entity in the online social networking system; and receiving input activating the new sponsored story specification. | 9. A method comprising: providing for display a plurality of options for selecting a sponsored story specification for generating a sponsored story in an online social networking system, the sponsored story comprising promoting a story selected from an organic activity stream of stories in the online social networking system; receiving, from the plurality of options, selection of a request to create a new sponsored story specification; providing for display one or more entities in the online social networking system for use in generating the sponsored story specification related to one of the entities; receiving a first user input selecting a target entity from the one or more entities as a first criterion for the sponsored story specification; providing for display one or more interactions for use in generating the sponsored story specification, each interaction comprising information about a user action with the selected entity taken in the online social networking system; receiving a second user input selecting a target interaction comprising a user action with the selected entity taken in the online social networking system as a second criterion for the sponsored story; generating, by a computer processor, a new sponsored story specification, the sponsored story specification specifying the first and second criteria for identifying, from the organic activity stream of stories in the online social networking system, one or more stories describing the selected interaction taken on the selected target entity in the online social networking system; and receiving input activating the new sponsored story specification. 10. The method of claim 9 , wherein the sponsored story comprises an advertisement. | 0.897311 |
11. The method of claim 9 , further comprising determining a listing to promote based on the listing containing the at least one most relevant aspect value for the at least one most relevant aspect name. | 11. The method of claim 9 , further comprising determining a listing to promote based on the listing containing the at least one most relevant aspect value for the at least one most relevant aspect name. 12. The method of claim 11 , further comprising promoting the listing by visually distinguishing the listing containing the most relevant aspect name and aspect value pair from other listings. | 0.930224 |
8. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a first term, a second term, and a third term; determining that a phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of a meaning of the first term, a meaning of the second term, and a meaning of the third term; in response to determining that the phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of the meaning of the first term, the meaning of the second term, and the meaning of the third term: identifying, in a collection of search queries, an original search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, original search query term that is not included in the phrase; determining a number of times that, in the collection of search queries, the original query that includes (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term that is not included in the phrase, is followed by a revised search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, revised search query term that is different than the additional term and that is not included in the phrase; and determining, based on the number of times, whether to revise a subsequently received search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term, to include the additional, revised search query term. | 8. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a first term, a second term, and a third term; determining that a phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of a meaning of the first term, a meaning of the second term, and a meaning of the third term; in response to determining that the phrase that includes the first term, the second term, and the third term has a collective meaning that is different than each of the meaning of the first term, the meaning of the second term, and the meaning of the third term: identifying, in a collection of search queries, an original search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, original search query term that is not included in the phrase; determining a number of times that, in the collection of search queries, the original query that includes (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term that is not included in the phrase, is followed by a revised search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) an additional, revised search query term that is different than the additional term and that is not included in the phrase; and determining, based on the number of times, whether to revise a subsequently received search query that includes: (i) the phrase that includes the first term, the second term, and the third term, and (ii) the additional, original search query term, to include the additional, revised search query term. 14. The non-transitory computer-readable storage medium of claim 8 , wherein determining the collective meaning of the phrase that includes the first term, the second term, and the third term comprises: determining whether the collective meaning of the phrase that includes the first term, the second term, and the third term matches a stored concept. | 0.563488 |
21. The computer readable storage medium of claim 20 , wherein the modified search results webpage includes one or more of: an indication of relevance of each of the first plurality of search results to the first user selection or a suggested search criteria based on the first user selection. | 21. The computer readable storage medium of claim 20 , wherein the modified search results webpage includes one or more of: an indication of relevance of each of the first plurality of search results to the first user selection or a suggested search criteria based on the first user selection. 24. The computer readable storage medium of claim 21 , wherein the one or more sequences of instructions, when executed by the one or more processors further cause receiving a request for a search using one or more of: the suggested search criteria based on the first user selection or a modified search criteria that is a modification of the suggested search criteria by a user. | 0.902991 |
12. The server of claim 11 , wherein the instructions cause the server to: subsequent to detecting the user-initiated interaction with the web document and responsive to determining that a copy of the web document has not previously been analyzed to identify topics to which the web document relates, request and receive a copy of the web document from a content source identified by the URI and perform a textual analysis of the web document to identify the one or more topics to which the web document relates. | 12. The server of claim 11 , wherein the instructions cause the server to: subsequent to detecting the user-initiated interaction with the web document and responsive to determining that a copy of the web document has not previously been analyzed to identify topics to which the web document relates, request and receive a copy of the web document from a content source identified by the URI and perform a textual analysis of the web document to identify the one or more topics to which the web document relates. 13. The server of claim 12 , wherein the instructions cause the server to determine that the URI is not stored in a cache or database. | 0.912005 |
25. A computer-implemented method for providing access to a knowledge base, comprising: receiving a natural language question as input; transmitting the natural language question to the knowledge base for translation to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; and presenting a definitive natural language answer responsive to the natural language question received from the knowledge base and including second knowledge derived from the first knowledge in response to the internal query, the second knowledge not having been stored in the knowledge base prior to transmission of the natural language question to the knowledge base. | 25. A computer-implemented method for providing access to a knowledge base, comprising: receiving a natural language question as input; transmitting the natural language question to the knowledge base for translation to an internal query that represents an interpretation of the natural language question and has an internal format compatible with structured data of the knowledge base, the structured data representing first knowledge; and presenting a definitive natural language answer responsive to the natural language question received from the knowledge base and including second knowledge derived from the first knowledge in response to the internal query, the second knowledge not having been stored in the knowledge base prior to transmission of the natural language question to the knowledge base. 30. The method of claim 25 further comprising transmitting the natural language question to the knowledge base via a network, and receiving the definitive natural language answer from the knowledge base via the network. | 0.8 |
1. A computer-implemented method of determining a common social context comprising: detecting by a computer a collaboration between a plurality of participants; identifying by a computer a plurality of common social contexts; determining by a computer a probability that the collaboration belongs to each of the plurality of common social contexts; and outputting at least one probability and corresponding common social context. | 1. A computer-implemented method of determining a common social context comprising: detecting by a computer a collaboration between a plurality of participants; identifying by a computer a plurality of common social contexts; determining by a computer a probability that the collaboration belongs to each of the plurality of common social contexts; and outputting at least one probability and corresponding common social context. 10. The computer-implemented method of claim 1 , wherein determining a probability further comprises: monitoring the probability the collaboration belongs to a particular common social context; determining when the probability the collaboration belongs to the particular common social context exceeds a minimum threshold level; and outputting an alert when the probability the collaboration belongs to the particular common social context exceeds the minimum threshold level. | 0.705081 |
1. A computer-implemented method for responding to a current message posted in a social media stream, the method comprising: at a server computer, implementing instructions for: monitoring a social media site for at least one current message including select subject matter; in response to identifying a current message, collecting a series of exchanges that form a conversational thread including the current message; determining at least one content attribute of the conversational thread including the current message, including: extracting a set of tags forming the current message by: splitting at least the current message into separate words; filtering and removing irrelevant words so that only contextual information remains; associating each of the remaining words as a tag, forming at least one combination of tags to generate at least one slug, and associating each slug as a content attribute; classifying the current message using at least one key attribute; searching a database for a reference message using a combination of the at least one content and key attributes; determining a previous outcome of a reference thread including the reference message, the determining including: parsing words in a customer-posted response of the reference thread, where the customer-posted response was made after a user's previous solution was posted to the reference thread, and automatically applying the parsed words to a stored dictionary to associate the words as belonging to one of a number of predetermined sentiments; and, in response to the words belonging to a positive sentiment, displaying the user's previous solution for determining a course of action. | 1. A computer-implemented method for responding to a current message posted in a social media stream, the method comprising: at a server computer, implementing instructions for: monitoring a social media site for at least one current message including select subject matter; in response to identifying a current message, collecting a series of exchanges that form a conversational thread including the current message; determining at least one content attribute of the conversational thread including the current message, including: extracting a set of tags forming the current message by: splitting at least the current message into separate words; filtering and removing irrelevant words so that only contextual information remains; associating each of the remaining words as a tag, forming at least one combination of tags to generate at least one slug, and associating each slug as a content attribute; classifying the current message using at least one key attribute; searching a database for a reference message using a combination of the at least one content and key attributes; determining a previous outcome of a reference thread including the reference message, the determining including: parsing words in a customer-posted response of the reference thread, where the customer-posted response was made after a user's previous solution was posted to the reference thread, and automatically applying the parsed words to a stored dictionary to associate the words as belonging to one of a number of predetermined sentiments; and, in response to the words belonging to a positive sentiment, displaying the user's previous solution for determining a course of action. 5. The method of claim 1 , further comprising: categorizing the current message into one of a predetermined set of categories classifying a purpose of the message; and, searching the database using at least the category one key attribute in the combination. | 0.602421 |
1. A method comprising: selecting, via a processor, a pair of anchor words in a media presentation based on automatic speech recognition output of the media presentation and a transcription of the media presentation, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than an anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words. | 1. A method comprising: selecting, via a processor, a pair of anchor words in a media presentation based on automatic speech recognition output of the media presentation and a transcription of the media presentation, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than an anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words. 2. The method of claim 1 , wherein the transcription is human-generated. | 0.737354 |
1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech. | 1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech. 4. The method of claim 1 , wherein suppressing the further output of the text-to-speech engine comprises initiating a reduction in an audio output level of the text-to-speech engine. | 0.708685 |
14. A processor implemented method for provisioning of enhanced interactive constructs or materials, according to approaches used by experienced problem solvers; said method comprising activities implemented through the execution of one or more processors, said activities comprising: receipt or input or both of at least one input item, said input item comprising at least one topic, problem, question, query, conclusion, solution, answer, information construct, analysis construct, or at least one portion of at least one model or specification or enhanced interactive construct, or a combination thereof; evaluation of at least one said input item, said evaluation accomplished at least in part relative to at least one of an exemplary archetype process for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, an exemplary archetype structure for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, a customized archetype process for facilitating exemplary user problem solving, a customized archetype structure for facilitating exemplary user problem solving, archetype expectations, a target enhanced interactive construct, or related archives, or a combination thereof; provisioning in display, output, or storage, or a combination thereof, of at least one portion of at least one enhanced interactive construct. | 14. A processor implemented method for provisioning of enhanced interactive constructs or materials, according to approaches used by experienced problem solvers; said method comprising activities implemented through the execution of one or more processors, said activities comprising: receipt or input or both of at least one input item, said input item comprising at least one topic, problem, question, query, conclusion, solution, answer, information construct, analysis construct, or at least one portion of at least one model or specification or enhanced interactive construct, or a combination thereof; evaluation of at least one said input item, said evaluation accomplished at least in part relative to at least one of an exemplary archetype process for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, an exemplary archetype structure for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, a customized archetype process for facilitating exemplary user problem solving, a customized archetype structure for facilitating exemplary user problem solving, archetype expectations, a target enhanced interactive construct, or related archives, or a combination thereof; provisioning in display, output, or storage, or a combination thereof, of at least one portion of at least one enhanced interactive construct. 17. The processor implemented method of claim 14 comprising incorporation, linkage to or use of, or a combination thereof, of at least one additional electronic item comprising at least one of an information resource, computer system, processor enabled system, search engine, agent, web service, applet, widget, client processor, server processor, display device, input device, output, display, storage, electronic tool, embedded system component, social network, collaboration system, or processing device, or processor executable instructions embodied in at least one of a processor readable medium, memory or device, or a combination thereof. | 0.687322 |
1. A method for voice-based social networking wherein for a temporal sequence of voice message segments, many of which augmented by an associated image file, segments are associated into new or existing conversations, wherein the association of a particular message with a conversation is accomplished through: applying an algorithm to the message data, where said algorithm incorporates a user dependent mathematical weighting of comment subject matters as inferred from text tags, audio tags, automated voice to text comment translation, image filename, image analysis and active users; and, comparing the output of said algorithm for said message to the output of said algorithm for a particular conversation where if the difference is small then the message is deemed part of said conversation. | 1. A method for voice-based social networking wherein for a temporal sequence of voice message segments, many of which augmented by an associated image file, segments are associated into new or existing conversations, wherein the association of a particular message with a conversation is accomplished through: applying an algorithm to the message data, where said algorithm incorporates a user dependent mathematical weighting of comment subject matters as inferred from text tags, audio tags, automated voice to text comment translation, image filename, image analysis and active users; and, comparing the output of said algorithm for said message to the output of said algorithm for a particular conversation where if the difference is small then the message is deemed part of said conversation. 4. The method of claim 1 where the voice message segments are automatically presented in temporal sequence, as they are received and as limited by playback resources, and in addition, a facility is made available for quick reorientation when user needs to regain context, so that the user receiving said message segments can easily infer the context of each voice segment and follow multiple conversations thus permitting said user effective use of said network while allocating significant attention to activities outside of interacting with said network. | 0.5 |
12. The method as recited in claim 1 , including a further step of displaying text of items identified by said step of logically combining results. | 12. The method as recited in claim 1 , including a further step of displaying text of items identified by said step of logically combining results. 13. The method as recited in claim 12 , wherein said text comprises an abstract of an item. | 0.9727 |
2. The method of claim 1 , further comprising: receiving an output message in a CLI format from the routing system responsive to the transmitted CLI command; translating the output message from the CLI format into the XML format having the CLI syntax; and transmitting the output message in the XML format having the CLI syntax to a remote device external from the routing system. | 2. The method of claim 1 , further comprising: receiving an output message in a CLI format from the routing system responsive to the transmitted CLI command; translating the output message from the CLI format into the XML format having the CLI syntax; and transmitting the output message in the XML format having the CLI syntax to a remote device external from the routing system. 3. The method of claim 2 , wherein the translating of the output message includes: parsing the output message to identify one or more nodes in the parse graph, wherein the parse graph includes a set of nodes arranged to represent macroinstructions utilized by the routing system to analyze whether one or more CLI commands input to a CLI prompt have a proper CLI syntax; and comparing the one or more nodes identified to object and attribute definitions in the parse graph. | 0.829496 |
1. A computer-implemented method for identifying data files that have a common characteristic, the method comprising: receiving a plurality of data files, the plurality of data files including one or more data files having the common characteristic; generating, using one or more processors, a list that includes key terms from the plurality of data files; using the list to generate a rule set, the rule set being generated using the one or more processors by: generating a potential rule by selecting one or more key terms from the list that satisfy a term evaluation metric; evaluating the potential rule using a rule evaluation metric configured to determine a relevancy of the potential rule to the one or more data files having the common characteristic, the rule evaluation metric being further configured to determine an applicability of the potential rule to data not included in the plurality of data files; adding the potential rule to the rule set if the rule evaluation metric is satisfied; based upon the potential rule being added to the rule set, removing data files covered by the potential rule from the plurality of data files; and repeating the potential rule generation and evaluation until a stopping criterion is met; and after the stopping criterion has been met, identifying with the rule set, other data files that have the common characteristic using the one or more processors. | 1. A computer-implemented method for identifying data files that have a common characteristic, the method comprising: receiving a plurality of data files, the plurality of data files including one or more data files having the common characteristic; generating, using one or more processors, a list that includes key terms from the plurality of data files; using the list to generate a rule set, the rule set being generated using the one or more processors by: generating a potential rule by selecting one or more key terms from the list that satisfy a term evaluation metric; evaluating the potential rule using a rule evaluation metric configured to determine a relevancy of the potential rule to the one or more data files having the common characteristic, the rule evaluation metric being further configured to determine an applicability of the potential rule to data not included in the plurality of data files; adding the potential rule to the rule set if the rule evaluation metric is satisfied; based upon the potential rule being added to the rule set, removing data files covered by the potential rule from the plurality of data files; and repeating the potential rule generation and evaluation until a stopping criterion is met; and after the stopping criterion has been met, identifying with the rule set, other data files that have the common characteristic using the one or more processors. 4. The method of claim 1 , comprising: receiving the plurality of data files, the plurality of data files including one or more data files that do not have the common characteristic. | 0.602069 |
1. A method of determining a document type associated with a digital document, the method comprising: training, using a first training set comprising a plurality of documents of a first document type, a first machine learning algorithm (MLA) classifier of a plurality of MLA classifiers; responsive to determining that the first MLA classifier confidently identifies the first document type, excluding the first document type from a second training set; training, using the second training set, a second MLA classifier of the plurality of MLA classifiers; acquiring, via a digital document interface, a digital document; executing, by a processor, the first MLA classifier in order to determine a document type for the digital document, the first MLA classifier being associated with a first hierarchical order of execution; responsive to determining that the document type produced by the first MLA classifier is not one of confidently predictable document types associated with the first MLA classifier, executing, by the processor, the second MLA classifier in order to determine the document type for the digital document, the second MLA classifier being associated with a second hierarchical order of execution immediately following the first hierarchical order of execution. | 1. A method of determining a document type associated with a digital document, the method comprising: training, using a first training set comprising a plurality of documents of a first document type, a first machine learning algorithm (MLA) classifier of a plurality of MLA classifiers; responsive to determining that the first MLA classifier confidently identifies the first document type, excluding the first document type from a second training set; training, using the second training set, a second MLA classifier of the plurality of MLA classifiers; acquiring, via a digital document interface, a digital document; executing, by a processor, the first MLA classifier in order to determine a document type for the digital document, the first MLA classifier being associated with a first hierarchical order of execution; responsive to determining that the document type produced by the first MLA classifier is not one of confidently predictable document types associated with the first MLA classifier, executing, by the processor, the second MLA classifier in order to determine the document type for the digital document, the second MLA classifier being associated with a second hierarchical order of execution immediately following the first hierarchical order of execution. 13. The method of claim 1 , wherein the digital document is provided by one of: a rigidly-structured document, a nearly-rigidly-structured document, a semi-structured document, and an un-structured document. | 0.663059 |
2. The method of claim 1 wherein said accumulating step comprises the steps of accumulating for each target pattern second and later required dwell time position, and for each target pattern optional dwell time position, the sum of the accumulated score for the previous target pattern dwell time position during the previous frame time and the present numerical measure associated with the target pattern, accumulating, for each keyword first target pattern, first required dwell time position, the sum of the best accumulated score, during the previous frame time, which is associated with the end of a keyword, and the present numerical measure associated with the keyword first target pattern, and accumulating, for each other target pattern first required dwell time position, the sum of the best ending accumulated score for the previous target pattern of the same keyword and the present numerical measure associated with the target pattern. | 2. The method of claim 1 wherein said accumulating step comprises the steps of accumulating for each target pattern second and later required dwell time position, and for each target pattern optional dwell time position, the sum of the accumulated score for the previous target pattern dwell time position during the previous frame time and the present numerical measure associated with the target pattern, accumulating, for each keyword first target pattern, first required dwell time position, the sum of the best accumulated score, during the previous frame time, which is associated with the end of a keyword, and the present numerical measure associated with the keyword first target pattern, and accumulating, for each other target pattern first required dwell time position, the sum of the best ending accumulated score for the previous target pattern of the same keyword and the present numerical measure associated with the target pattern. 3. The method of claim 2 further comprising the steps of storing in association with each frame time position, the identity and duration, in frame time position, of the keyword having best score and a valid ending at each said frame time position, and wherein said decision generating step comprises the step of tracing back through said stored keyword indentity and duration information for determining each keyword in a word string. | 0.723733 |
2. The system of claim 1 , wherein the feature vector extractor is further configured to: extract a second training set of feature vectors from the set of training data; and extract a second test feature vector from the set of prediction data. | 2. The system of claim 1 , wherein the feature vector extractor is further configured to: extract a second training set of feature vectors from the set of training data; and extract a second test feature vector from the set of prediction data. 18. The system of claim 2 , wherein the second test feature vector and the first test feature vector comprise distinct features. | 0.878578 |
8. A speech analysis and synthesis system comrising: an analyzer including, means for analyzing an electrical speech signal by Cepstrum technique to generate a pitch period parameter, means for analyzing said speech signal to generate a voiced/unvoiced decision parameter, and means for analyzing said speech signal by linear prediction technique to generate a predetermined number of coefficient parameters and a power parameter; and a synthesizer including, pitch pulse generator means for receiving said pitch period parameter and generating pitch pulses having a corresponding pitch period, random noise generator means, switch means connected to said pitch pulsed generator means to said random noise generator means for receiving said voiced/unvoiced decision parameter, an output of said switch means being derived from said pitch pulse generator means if said decision is voiced, and from said random noise generator means if said decision is unvoiced, gain control means connected to said output of said switch means for receiving said power parameter, an output level of said gain control means being dependent upon said power parameter, and linear prediction filter means connected to said output of said gain control means for receiving and applying said coefficient parameters to said filter means to generate a replica or said speech signal at an output of said filter means; wherein said means for analyzing an electrical speech signal by Cepstrum technique includes means for conditioning a Cepstrum signal generated by said Cepstrum technique, said signal conditioning means generating a weighting signal which linearly increases in value during the time span of said Cepstrum and said means for conditioning said Cepstrum further adding said weighting signal to said Cepstrum during said time span to create a weighted Cepstrum signal. | 8. A speech analysis and synthesis system comrising: an analyzer including, means for analyzing an electrical speech signal by Cepstrum technique to generate a pitch period parameter, means for analyzing said speech signal to generate a voiced/unvoiced decision parameter, and means for analyzing said speech signal by linear prediction technique to generate a predetermined number of coefficient parameters and a power parameter; and a synthesizer including, pitch pulse generator means for receiving said pitch period parameter and generating pitch pulses having a corresponding pitch period, random noise generator means, switch means connected to said pitch pulsed generator means to said random noise generator means for receiving said voiced/unvoiced decision parameter, an output of said switch means being derived from said pitch pulse generator means if said decision is voiced, and from said random noise generator means if said decision is unvoiced, gain control means connected to said output of said switch means for receiving said power parameter, an output level of said gain control means being dependent upon said power parameter, and linear prediction filter means connected to said output of said gain control means for receiving and applying said coefficient parameters to said filter means to generate a replica or said speech signal at an output of said filter means; wherein said means for analyzing an electrical speech signal by Cepstrum technique includes means for conditioning a Cepstrum signal generated by said Cepstrum technique, said signal conditioning means generating a weighting signal which linearly increases in value during the time span of said Cepstrum and said means for conditioning said Cepstrum further adding said weighting signal to said Cepstrum during said time span to create a weighted Cepstrum signal. 9. A speech analysis and synthesis system as defined in claim 8 wherein said signal conditioning means includes: means for generating said weighting signal having a first adder with an output connected as an input to a register, said register having an output connected as a first input to said first adder, said first adder having as a second input an incrementing constant connected to said first adder through a first gate, said gate being enabled as an incremental element of said Cepstrum signal is gated through a second gate to a first input to a second adder, whereby said register is incremented for each element of said Cepstrum signal which is gated into said second adder; and means for adding said weighting signal to said Cepstrum by connecting the output of said register as a second input to said second adder, whereby the incremented output of said register is added to each element of said Cepstrum signal and an output of said second adder is said weighted Cepstrum signal. | 0.676279 |
1. A method, comprising: receiving with a computing device digital data representing a string of images, the images representing at least part of a user; processing the data using software to detect therefrom a string of gestures of the user, each gesture represented as a vector; mapping the vectors to a string of phonetic elements; and identifying one or more words in a written language, the one or more words corresponding to the string of the phonetic elements; wherein the written language is a one of a plurality of regional languages, mapping the vectors to the string of phonetic elements comprises selecting each phonetic element in the string of phonetic elements in a manner that is agnostic to any one of the plurality of regional languages, and identifying the one or more words comprises selecting a contextual dictionary specific to a selected one of the plurality of regional languages, the selected one corresponding to the written language, and translating the string of phonetic elements to the selected language; and wherein further each vector comprises a position in n-degree space, and wherein mapping further comprises translating the position in n-degree space to a position in m-degree space, where n>m, and selecting a phonetic element uniquely associated with the position in m-degree space, translating includes accessing a dictionary to map positions in n-degree space to corresponding positions in m-degree space, and the method further comprises using principal components analysis to adaptively learn the dictionary. | 1. A method, comprising: receiving with a computing device digital data representing a string of images, the images representing at least part of a user; processing the data using software to detect therefrom a string of gestures of the user, each gesture represented as a vector; mapping the vectors to a string of phonetic elements; and identifying one or more words in a written language, the one or more words corresponding to the string of the phonetic elements; wherein the written language is a one of a plurality of regional languages, mapping the vectors to the string of phonetic elements comprises selecting each phonetic element in the string of phonetic elements in a manner that is agnostic to any one of the plurality of regional languages, and identifying the one or more words comprises selecting a contextual dictionary specific to a selected one of the plurality of regional languages, the selected one corresponding to the written language, and translating the string of phonetic elements to the selected language; and wherein further each vector comprises a position in n-degree space, and wherein mapping further comprises translating the position in n-degree space to a position in m-degree space, where n>m, and selecting a phonetic element uniquely associated with the position in m-degree space, translating includes accessing a dictionary to map positions in n-degree space to corresponding positions in m-degree space, and the method further comprises using principal components analysis to adaptively learn the dictionary. 7. The method of claim 1 , further comprising displaying the words to the user via a visual display of the computing device. | 0.587255 |
9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining data indicating a set of linguistic features corresponding to a text; providing (i) data indicating the linguistic features and (ii) data indicating the language of the text as input to a neural network that has been trained to provide output indicating prosody information for multiple languages, the neural network having been trained using speech in multiple languages; receiving, from the neural network, output indicating prosody information for the linguistic features; and generating audio data representing the text using the output of the neural network. | 9. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining data indicating a set of linguistic features corresponding to a text; providing (i) data indicating the linguistic features and (ii) data indicating the language of the text as input to a neural network that has been trained to provide output indicating prosody information for multiple languages, the neural network having been trained using speech in multiple languages; receiving, from the neural network, output indicating prosody information for the linguistic features; and generating audio data representing the text using the output of the neural network. 12. The system of claim 9 , wherein the operation further comprise determining a linguistic group that includes a subset of the linguistic features in the set of linguistic features; wherein providing data indicating the linguistic features to the neural network comprises providing data indicating the subset of linguistic features in the linguistic group as input to the neural network; and wherein receiving, from the neural network, output indicating prosody information for the linguistic features comprises receiving, from the neural network, output indicating prosody information for the linguistic group. | 0.727393 |
12. A system comprising: one or more processors; a content monitor executable by the one or more processors and configured to: receive a content item from one or more of a plurality of communication channels, and determine the content item is to be processed further, the content item comprising: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; an analysis engine executable by the one or more processors and configured to determine a commitment score of the individual to attend the event by: identifying the event as a topic of interest in the content item; calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item, calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item, calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel, and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. | 12. A system comprising: one or more processors; a content monitor executable by the one or more processors and configured to: receive a content item from one or more of a plurality of communication channels, and determine the content item is to be processed further, the content item comprising: a communication from an individual, and a statement by the individual, the statement comprising committing language about an intent to attend an event; an analysis engine executable by the one or more processors and configured to determine a commitment score of the individual to attend the event by: identifying the event as a topic of interest in the content item; calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item, calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item, calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel, and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining an action based on the commitment score of the individual to attend the event. 21. The system of claim 12 , wherein the communication channel includes one or more of an electronic mail system, a social networking service, an audio channel, a Really Simple Syndication (RSS) feed, a Twitter feed, a web site, or an Application Program Interface to a second system. | 0.619318 |
1. A computer-implemented method of determining the resemblance of a plurality of data objects, comprising the steps of: parsing each data object into a canonical sequence of tokens; grouping overlapping sequences of the tokens of each data object into shingles; assigning a unique identification element to each shingle; permuting the elements of the data objects to form image sets; selecting a predetermined number of minimum elements from each image to form a sketch; partitioning the selected elements of each sketch into a plurality of groups; and assigning another unique identification to each group to generate the features of each data object to determine a level of resemblance of the plurality of data objects. | 1. A computer-implemented method of determining the resemblance of a plurality of data objects, comprising the steps of: parsing each data object into a canonical sequence of tokens; grouping overlapping sequences of the tokens of each data object into shingles; assigning a unique identification element to each shingle; permuting the elements of the data objects to form image sets; selecting a predetermined number of minimum elements from each image to form a sketch; partitioning the selected elements of each sketch into a plurality of groups; and assigning another unique identification to each group to generate the features of each data object to determine a level of resemblance of the plurality of data objects. 21. The method of claim 1 wherein the unique identifications are fingerprints. | 0.66895 |
13. The tangible non-transitory computer-recordable medium of claim 12 , wherein a first class of the plurality of classes is an accept class, and wherein the desired performance characteristics comprise a desired rate for falsely classifying inputs as belonging to the accept class by the classification model. | 13. The tangible non-transitory computer-recordable medium of claim 12 , wherein a first class of the plurality of classes is an accept class, and wherein the desired performance characteristics comprise a desired rate for falsely classifying inputs as belonging to the accept class by the classification model. 14. The tangible non-transitory computer-recordable medium of claim 13 , wherein a second class of the plurality of classes is a reject class, and wherein the desired performance characteristics further comprise a desired rate for falsely classifying inputs as belonging to the reject class by the classification model. | 0.847425 |
10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a client system, cause the client system to perform a method comprising: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet. | 10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a client system, cause the client system to perform a method comprising: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet. 13. The non-transitory computer readable storage medium of claim 10 , wherein receiving the request to add the cell value comprises entering the request into a spreadsheet cell. | 0.618536 |
10. A method for fault prediction in a home network, comprising: generating context information based on status data collected in real time about components of the home network; generating knowledge rules for fault detection by using specifications of the components of the home network; analyzing if the generated context information meet the generated knowledge rules to classify the context information into normal situation contexts and abnormal situation contexts; generating new knowledge rules based on the abnormal situation contexts and fault rules corresponding to the abnormal situation contexts; and analyzing a correlation between the new knowledge rules and the generated context information thereby predicting faults to be generated. | 10. A method for fault prediction in a home network, comprising: generating context information based on status data collected in real time about components of the home network; generating knowledge rules for fault detection by using specifications of the components of the home network; analyzing if the generated context information meet the generated knowledge rules to classify the context information into normal situation contexts and abnormal situation contexts; generating new knowledge rules based on the abnormal situation contexts and fault rules corresponding to the abnormal situation contexts; and analyzing a correlation between the new knowledge rules and the generated context information thereby predicting faults to be generated. 14. The method of claim 10 , wherein said generating knowledge rules comprises: interpreting the specifications and giving the specifications semantics; establishing a relation between the semantics; and generating the knowledge rules based on functions that affect the establishment of the relation between the specifications of the components. | 0.688363 |
32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. | 32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. 38. The system according to claim 32 , wherein the parser formulates at least one request in accordance with a grammar that the selected domain agent uses to process requests associated with the context for the one or more keywords contained in the utterance. | 0.860084 |
19. The system of claim 11 , wherein each conversational category of the plurality of conversational categories represents a conversation formed by an amalgamation of at least two strings that each, individually, match a respective singleton template, and wherein the control circuitry is further configured to determine that the matching singleton templates, when juxtaposed, form a single query. | 19. The system of claim 11 , wherein each conversational category of the plurality of conversational categories represents a conversation formed by an amalgamation of at least two strings that each, individually, match a respective singleton template, and wherein the control circuitry is further configured to determine that the matching singleton templates, when juxtaposed, form a single query. 20. The system of claim 19 , wherein the first conversation, the second conversation, and the third conversation form the single query based on a respective juxtaposition of the first string, the second string, and the third string. | 0.957104 |
33. The machine recited in claim 31, where the method for discovering trends in a database further comprises: determining whether sets contained in the large itemsets satisfy the predefined constraints; generating a set of candidate itemsets including large itemsets which satisfy the predefined constraints; and using the set of candidate itemsets to output the association rules. | 33. The machine recited in claim 31, where the method for discovering trends in a database further comprises: determining whether sets contained in the large itemsets satisfy the predefined constraints; generating a set of candidate itemsets including large itemsets which satisfy the predefined constraints; and using the set of candidate itemsets to output the association rules. 34. The machine recited in claim 33, where the generating a selected set of items includes pruning non-interesting items from the set. | 0.935517 |
1. A device, comprising: a display; and logic configured to: receive a selection of a first control action associated with an application stored in the device, provide a plurality of choices associated with the first control action, receive a word or a phrase to use as a voice command corresponding to the first control action, wherein the word or phrase is selected from the plurality of choices, associate the word or phrase with the first control action, receive voice input from a user, identify the voice input as corresponding to the word or phrase, and perform the first control action based on the identified voice input. | 1. A device, comprising: a display; and logic configured to: receive a selection of a first control action associated with an application stored in the device, provide a plurality of choices associated with the first control action, receive a word or a phrase to use as a voice command corresponding to the first control action, wherein the word or phrase is selected from the plurality of choices, associate the word or phrase with the first control action, receive voice input from a user, identify the voice input as corresponding to the word or phrase, and perform the first control action based on the identified voice input. 2. The device of claim 1 , further comprising: a memory, and wherein the logic is further configured to: store the received word or phrase in the memory. | 0.80762 |
20. A non-transitory computer-readable storage medium storing instructions for: storing, by a multi-tenant system, data received from a plurality of external systems, each external system associated with a customer of the multi-tenant system, each customer associated with one or more users; monitoring, by the multi-tenant system, user interactions performed by users of the multi-tenant system with reports, the monitoring comprising associating a user interaction with a context in which the user interaction is performed, the context identifying at least a report with which the user interaction was performed; performing, by the multi-tenant system, a sequence of interactions with the user, the performing of each interaction comprising: determining a recommendation comprising a potential sequence of computer-executable actions based on past user interactions performed by users of the multi-tenant system in contexts matching a context of the user, the matching contexts comprising sequences of the past user interactions, wherein the context of the user comprises a present sequence of user interactions performed by the user; determining a recommendation score for the recommendation, wherein determining the recommendation score comprises determining an aggregate value based on the past user interactions; responsive to determining the recommendation score for the recommendation, constructing a computer-actionable widget for the recommendation based on the recommendation score, and configuring a user interface comprising a computer-actionable widget, the widget comprising a compiled graphical user interface element configured to receive one or more user interactions associated with the recommendation and automatically execute the recommended sequence of potential computer-executable actions, the configuring of the user interface comprising: determining a value of an attribute of the widget based on the recommendation score of the recommendation associated with the widget, the attribute specifying one of: a size of the widget; a size of text associated with the widget; or an appearance of the widget; and configuring the computer-actionable widget, comprising, performing at least one of: scaling the size of the widget according to the determined value of the attribute; scaling the size of the text associated with the widget according to the determined value of the attribute; or configuring the appearance of the widget according to the determined value of the attribute; and receiving an interaction from the user based on the computer-actionable widget of the user interface. | 20. A non-transitory computer-readable storage medium storing instructions for: storing, by a multi-tenant system, data received from a plurality of external systems, each external system associated with a customer of the multi-tenant system, each customer associated with one or more users; monitoring, by the multi-tenant system, user interactions performed by users of the multi-tenant system with reports, the monitoring comprising associating a user interaction with a context in which the user interaction is performed, the context identifying at least a report with which the user interaction was performed; performing, by the multi-tenant system, a sequence of interactions with the user, the performing of each interaction comprising: determining a recommendation comprising a potential sequence of computer-executable actions based on past user interactions performed by users of the multi-tenant system in contexts matching a context of the user, the matching contexts comprising sequences of the past user interactions, wherein the context of the user comprises a present sequence of user interactions performed by the user; determining a recommendation score for the recommendation, wherein determining the recommendation score comprises determining an aggregate value based on the past user interactions; responsive to determining the recommendation score for the recommendation, constructing a computer-actionable widget for the recommendation based on the recommendation score, and configuring a user interface comprising a computer-actionable widget, the widget comprising a compiled graphical user interface element configured to receive one or more user interactions associated with the recommendation and automatically execute the recommended sequence of potential computer-executable actions, the configuring of the user interface comprising: determining a value of an attribute of the widget based on the recommendation score of the recommendation associated with the widget, the attribute specifying one of: a size of the widget; a size of text associated with the widget; or an appearance of the widget; and configuring the computer-actionable widget, comprising, performing at least one of: scaling the size of the widget according to the determined value of the attribute; scaling the size of the text associated with the widget according to the determined value of the attribute; or configuring the appearance of the widget according to the determined value of the attribute; and receiving an interaction from the user based on the computer-actionable widget of the user interface. 23. The non-transitory computer-readable storage medium of claim 20 , wherein the recommendation score for the recommendation is determined based on a weighted combination of rate at which a user action associated with the recommendation was taken by one or more of: the user for whom the recommendation is determined; an organization associated with the customer of the user; and a user base based on a plurality of customers. | 0.511825 |
16. A non-transitory computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method for translating an incoming message into a native format, said method comprising: invoking each of a plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the incoming message; identifying, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the incoming message; upon a successful identification of the particular exchange protocol, decoding said incoming message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoking each of a plurality of extensible document protocol plug-ins to identify a particular document format protocol associated with the decoded message; identifying, by a particular one of said plurality of extensible document protocol plug ins, the particular document format protocol associated with the decoded message; upon a successful identification of the particular document format protocol, translating said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of said native format. | 16. A non-transitory computer-readable storage medium storing a plurality of instructions which, when executed by a processor, cause the processor to perform a method for translating an incoming message into a native format, said method comprising: invoking each of a plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the incoming message; identifying, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the incoming message; upon a successful identification of the particular exchange protocol, decoding said incoming message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoking each of a plurality of extensible document protocol plug-ins to identify a particular document format protocol associated with the decoded message; identifying, by a particular one of said plurality of extensible document protocol plug ins, the particular document format protocol associated with the decoded message; upon a successful identification of the particular document format protocol, translating said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of said native format. 22. A non-transitory computer-readable storage medium as described in claim 16 , wherein said received message is encoded with an exchange protocol of one of said plurality of extensible exchange protocol plug-ins and is encoded with a document format protocol of one of said plurality of extensible document format protocol plug-ins. | 0.6064 |
15. At least one non-transitory computer-readable storage medium encoded with a plurality of machine-readable instructions that, when executed by a computer perform a method comprising: processing input speech to determine if clarification of the input speech is desired because the spoken dialog system has returned at least two speech recognition hypotheses having similar confidence values for at least a portion of the input speech; retrieving, if clarification is desired, a first list of items to be played back to the user; identifying acoustically confusable items on the first list of items using at least one measure of confusability; selecting, based, at least in part, on at least one rule in a collection of rules, a disambiguation strategy from a plurality of disambiguation strategies, wherein the disambiguation strategy is selected based on a type of acoustic confusion between the acoustically confusable items on the first list of items, wherein the plurality of disambiguation strategies includes a first disambiguation strategy comprising spelling at least a portion of each of at least two of the items in the first list of items and a second disambiguation strategy comprising repeating at least two of the items in the first list of items and identifying a first letter of a word in each of the at least two of the items; generating a disambiguated list of items by modifying at least one of the acoustically confusable items on the first list according to the disambiguation strategy; and playing a prompt comprising the disambiguated list of items back to the user. | 15. At least one non-transitory computer-readable storage medium encoded with a plurality of machine-readable instructions that, when executed by a computer perform a method comprising: processing input speech to determine if clarification of the input speech is desired because the spoken dialog system has returned at least two speech recognition hypotheses having similar confidence values for at least a portion of the input speech; retrieving, if clarification is desired, a first list of items to be played back to the user; identifying acoustically confusable items on the first list of items using at least one measure of confusability; selecting, based, at least in part, on at least one rule in a collection of rules, a disambiguation strategy from a plurality of disambiguation strategies, wherein the disambiguation strategy is selected based on a type of acoustic confusion between the acoustically confusable items on the first list of items, wherein the plurality of disambiguation strategies includes a first disambiguation strategy comprising spelling at least a portion of each of at least two of the items in the first list of items and a second disambiguation strategy comprising repeating at least two of the items in the first list of items and identifying a first letter of a word in each of the at least two of the items; generating a disambiguated list of items by modifying at least one of the acoustically confusable items on the first list according to the disambiguation strategy; and playing a prompt comprising the disambiguated list of items back to the user. 19. The at least one computer-readable storage medium of claim 15 , wherein the disambiguation strategy is selected based on minimal features to distinguish the acoustically confusable items. | 0.551572 |
12. The system of claim 8 , wherein the string of characters corresponds to a domain name. | 12. The system of claim 8 , wherein the string of characters corresponds to a domain name. 13. The system of claim 12 , wherein the at least one processor is configured to execute the instructions to perform the method further comprising: registering the string of characters as the domain name; and associating the new sound file with the domain name. | 0.942526 |
43. A method for a voice user interface with personality, the method comprising: storing a recognition grammar in a memory, the recognition grammar comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, the recognition grammar being selected based on the personality of the virtual assistant; executing a voice user interface, the voice user interface outputting first voice signals, the voice user interface recognizing speech signals; and controlling the voice user interface to provide the voice user interface with a verbal personality. | 43. A method for a voice user interface with personality, the method comprising: storing a recognition grammar in a memory, the recognition grammar comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, the recognition grammar being selected based on the personality of the virtual assistant; executing a voice user interface, the voice user interface outputting first voice signals, the voice user interface recognizing speech signals; and controlling the voice user interface to provide the voice user interface with a verbal personality. 50. The method as recited in claim 43 wherein the controlling the voice user interface comprises selecting a prompt, the prompt comprising an appropriate temporal prompt. | 0.662379 |
18. The computer program product as claimed in claim 16 wherein each concept of the first graph represents a category of data that exists according to the first source schema. | 18. The computer program product as claimed in claim 16 wherein each concept of the first graph represents a category of data that exists according to the first source schema. 19. The computer program product as claimed in claim 18 wherein each concept of the second graph represents a category of data that exists according to the second source schema, and wherein each concept of the first and second graph is a relation name with an associated set of attributes. | 0.863316 |
37. A machine readable storage medium having instructions stored thereon that when executed by a processor cause a system to: provide a plurality of type repositories, wherein each type repository represents a type system and maintains public information of one or more type definitions associated with the type system, wherein the public information of one or more type definition is accessible by other types; and provide a plurality of name resolution components, wherein each name resolution component is associated with a type repository of the plurality of type repositories, wherein each of the plurality of name resolution components provides private information of one or more type definitions associated with the type system during name resolution. wherein the private information of one or more type definition is not accessible by other types. | 37. A machine readable storage medium having instructions stored thereon that when executed by a processor cause a system to: provide a plurality of type repositories, wherein each type repository represents a type system and maintains public information of one or more type definitions associated with the type system, wherein the public information of one or more type definition is accessible by other types; and provide a plurality of name resolution components, wherein each name resolution component is associated with a type repository of the plurality of type repositories, wherein each of the plurality of name resolution components provides private information of one or more type definitions associated with the type system during name resolution. wherein the private information of one or more type definition is not accessible by other types. 38. The machine readable storage medium of claim 37 , wherein: each of the plurality of type repository determines which portion of name resolution needs to be completed for a type in the type repository to ensure that every type definition in the type repository is fully resolved during compilation. | 0.552653 |
13. The method of claim 10 , wherein said presenting includes displaying the information to a user submitting the search request. | 13. The method of claim 10 , wherein said presenting includes displaying the information to a user submitting the search request. 14. The method of claim 13 , wherein said linking includes parsing content of the query of the search request and generating a profile for the search request, the profile including the property based on the content of the query. | 0.927348 |
12. A device, comprising: a transceiver; and a processor to implement a voice engine, wherein the processor is to receive an incoming call from a caller's device using the transceiver, determine a locale preference associated with the caller's device, dynamically configure the voice engine using locale settings associated with the determined locale preference, send a query message to the caller's device using the transceiver, parse a voice response from the caller to the query message using the voice engine, and process the incoming call in the called device based on the voice response. | 12. A device, comprising: a transceiver; and a processor to implement a voice engine, wherein the processor is to receive an incoming call from a caller's device using the transceiver, determine a locale preference associated with the caller's device, dynamically configure the voice engine using locale settings associated with the determined locale preference, send a query message to the caller's device using the transceiver, parse a voice response from the caller to the query message using the voice engine, and process the incoming call in the called device based on the voice response. 16. The device of claim 12 , wherein the processor is to determine the locale preference based on at least one of a number or a name associated with the caller's device. | 0.640379 |
10. A method for hybrid approach to natural language understanding, comprising the steps of: (a) creating a new natural language understanding model based at least in part by a plurality of user-provided examples using a machine learning service; (b) providing a natural language understanding model dataset comprising at least the new natural language understanding model to other components of the system using the machine learning service; (c) retrieving the natural language understanding model dataset from the machine learning service using an integrated development environment; (d) publishing a runtime solution by combining at least a natural language understanding rule and a natural language understanding model dataset using an integrated development environment; (e) retrieving the runtime solution from the integrated development environment using an interaction engine; (f) receiving a natural language input from an external interface using the interaction engine; (g) processing the natural language input by at least annotating and classifying the input using the interaction engine; (h) generating a log dataset based at least on how the runtime solution and processed input interprets the natural language input using the interaction engine; (i) storing the natural language input, and log dataset to a log storage using the interaction engine; (j) requesting the log dataset from the log storage using the machine learning service; and (k) retraining and improve the natural language understanding model dataset using the machine learning service; wherein the processing of the natural language input uses a hybrid solution comprising both natural language rules and machine learning-based classifiers. | 10. A method for hybrid approach to natural language understanding, comprising the steps of: (a) creating a new natural language understanding model based at least in part by a plurality of user-provided examples using a machine learning service; (b) providing a natural language understanding model dataset comprising at least the new natural language understanding model to other components of the system using the machine learning service; (c) retrieving the natural language understanding model dataset from the machine learning service using an integrated development environment; (d) publishing a runtime solution by combining at least a natural language understanding rule and a natural language understanding model dataset using an integrated development environment; (e) retrieving the runtime solution from the integrated development environment using an interaction engine; (f) receiving a natural language input from an external interface using the interaction engine; (g) processing the natural language input by at least annotating and classifying the input using the interaction engine; (h) generating a log dataset based at least on how the runtime solution and processed input interprets the natural language input using the interaction engine; (i) storing the natural language input, and log dataset to a log storage using the interaction engine; (j) requesting the log dataset from the log storage using the machine learning service; and (k) retraining and improve the natural language understanding model dataset using the machine learning service; wherein the processing of the natural language input uses a hybrid solution comprising both natural language rules and machine learning-based classifiers. 18. The method of claim 10 , wherein an order of processing of the runtime solution can be further adjusted and controlled through both human control as well as through machine learning methods. | 0.637255 |
35. A method of indexing and searching timed media files, as recited in claim 25 , wherein said processed language includes language that is spoken within the timed media file. | 35. A method of indexing and searching timed media files, as recited in claim 25 , wherein said processed language includes language that is spoken within the timed media file. 36. A method of indexing and searching timed media files, as recited in claim 35 , wherein said processing of language that is spoken within the timed media file includes analyzing the logical structure of the language. | 0.889351 |
24. The system of claim 16 , further comprise a video test serving module configured to display a subset of selected frames of the video segment of the video test. | 24. The system of claim 16 , further comprise a video test serving module configured to display a subset of selected frames of the video segment of the video test. 26. The system of claim 24 , wherein the video test serving module is further configured to increment a user trial counter for the user. | 0.967381 |
1. At a computer system including one or more processors and system memory, a method for formulating a collection of set membership conditions for a set, the method comprising: an act of accessing a set definition for a specified set, the set definition defining what resources are to be included in the specified set; an act of accessing a membership condition grammar, the membership condition grammar generally indicating how to translate a set definition for a set into membership conditions indicative of membership in the set; an act of translating the accessed set definition into one or more corresponding membership conditions defined in accordance with the membership condition grammar, each membership condition including one or more membership condition statements, each membership condition statement defining a condition about a resource's attributes that is to be true for the resource to be considered for membership in the set, including for each membership condition statement: an act of decomposing a portion of the accessed set definition into a referent field, an attribute field, an operator field, and a value field that collectively represent the defined membership condition statement, each of the referent field, attribute field, operator field, and value field being defined within the membership condition grammar as: <Referent>::=<Referent Reference><Attribute>, <Attribute>::=a name of an attribute of a resource identified by an expression to its left, <Operator>::=<Relational Operator>|<Inverted Operator>, and <Value>::=<Literal Value>|<Function Value>|<De-referenced Value>, and further: the attribute field naming an attribute, the operator field indicating a relational operator, the value field representing a value, the referent field indicating a referent, the referent referring either directly to the resource currently being evaluated for membership in the set or to another resource that is related in some way to the resource that is currently being evaluated for membership in the set; and an act of storing the one or more corresponding membership conditions for use in subsequently determining resource membership in the set. | 1. At a computer system including one or more processors and system memory, a method for formulating a collection of set membership conditions for a set, the method comprising: an act of accessing a set definition for a specified set, the set definition defining what resources are to be included in the specified set; an act of accessing a membership condition grammar, the membership condition grammar generally indicating how to translate a set definition for a set into membership conditions indicative of membership in the set; an act of translating the accessed set definition into one or more corresponding membership conditions defined in accordance with the membership condition grammar, each membership condition including one or more membership condition statements, each membership condition statement defining a condition about a resource's attributes that is to be true for the resource to be considered for membership in the set, including for each membership condition statement: an act of decomposing a portion of the accessed set definition into a referent field, an attribute field, an operator field, and a value field that collectively represent the defined membership condition statement, each of the referent field, attribute field, operator field, and value field being defined within the membership condition grammar as: <Referent>::=<Referent Reference><Attribute>, <Attribute>::=a name of an attribute of a resource identified by an expression to its left, <Operator>::=<Relational Operator>|<Inverted Operator>, and <Value>::=<Literal Value>|<Function Value>|<De-referenced Value>, and further: the attribute field naming an attribute, the operator field indicating a relational operator, the value field representing a value, the referent field indicating a referent, the referent referring either directly to the resource currently being evaluated for membership in the set or to another resource that is related in some way to the resource that is currently being evaluated for membership in the set; and an act of storing the one or more corresponding membership conditions for use in subsequently determining resource membership in the set. 3. The method as recited in claim 1 , wherein the act of accessing a membership condition grammar comprises an act of accessing a membership grammar that defines membership condition statements to include a referent field, an attribute field, an operator field, and a value field. | 0.798999 |
8. The system of claim 1 , wherein the ensembling is performed as a function of a level of information uncertainty and a confidence level. | 8. The system of claim 1 , wherein the ensembling is performed as a function of a level of information uncertainty and a confidence level. 11. The system of claim 8 , wherein the ensembling produces classification results based on a form of proportional voting in response to the executed model stacks producing intermediate classification results with low confidence levels while operating with a low level of information uncertainty. | 0.962931 |
2. The method of claim 1 , comprising: performing a search assistance task utilizing the query-goal-mission structure. | 2. The method of claim 1 , comprising: performing a search assistance task utilizing the query-goal-mission structure. 3. The method of claim 2 , the performing a search assistance task comprising at least one of: identifying an event recommendation; identifying content associated with a product or service; expanding a query submitted to a search engine; or ranking search results. | 0.934341 |
1. An information processing method comprising the steps of: accepting, as a print setting, a setting for arranging a plurality of pages on one sheet of paper; receiving a selection of either an original-view mode for displaying a preview in which the accepted print setting is not reflected or a print-view mode for displaying a preview in a form to be printed according to the accepted print setting, as a preview mode; and displaying a preview in which one page is arranged on one sheet of paper in a state in which the accepted print setting, which is the setting for arranging the plurality of pages on one sheet of paper, is maintained, in a case where the selection of the original-view mode is received, and displaying a preview in which the plurality of pages are arranged on one sheet of paper in a case where the selection of the print-view mode is received. | 1. An information processing method comprising the steps of: accepting, as a print setting, a setting for arranging a plurality of pages on one sheet of paper; receiving a selection of either an original-view mode for displaying a preview in which the accepted print setting is not reflected or a print-view mode for displaying a preview in a form to be printed according to the accepted print setting, as a preview mode; and displaying a preview in which one page is arranged on one sheet of paper in a state in which the accepted print setting, which is the setting for arranging the plurality of pages on one sheet of paper, is maintained, in a case where the selection of the original-view mode is received, and displaying a preview in which the plurality of pages are arranged on one sheet of paper in a case where the selection of the print-view mode is received. 2. The information processing method according to claim 1 , wherein the plurality of pages are included in document data, which is generated by an application. | 0.694522 |
13. The method of claim 1 , further including a step: selecting one or more second computing systems for separately performing steps (b) and/or (c) based on a performance and/or cost requirement. | 13. The method of claim 1 , further including a step: selecting one or more second computing systems for separately performing steps (b) and/or (c) based on a performance and/or cost requirement. 16. The method of claim 13 wherein said one or more second computing systems are selected based on an auction process in which such one or more second computing systems bid for the right to process said speech utterance. | 0.936804 |
1. A computer-implemented method, comprising: storing a document as discrete parts in electronic form on a computing device, the document including a document configuration that conveys data related to content of at least one discrete part and a document sequence portion that lists the discrete parts; applying a digital signature to the document stored on the computing device based on a digital signing policy to protect the content of the at least one discrete part with the digital signature while leaving the document sequence portion that lists the discrete parts unprotected by the digital signature; invalidating the digital signature when the content in the at least one discrete part is altered; and indicating that the digital signature is valid when the document sequence portion is altered to list an additional discrete part that is added to the document. | 1. A computer-implemented method, comprising: storing a document as discrete parts in electronic form on a computing device, the document including a document configuration that conveys data related to content of at least one discrete part and a document sequence portion that lists the discrete parts; applying a digital signature to the document stored on the computing device based on a digital signing policy to protect the content of the at least one discrete part with the digital signature while leaving the document sequence portion that lists the discrete parts unprotected by the digital signature; invalidating the digital signature when the content in the at least one discrete part is altered; and indicating that the digital signature is valid when the document sequence portion is altered to list an additional discrete part that is added to the document. 6. The computer-implemented method as recited in claim 1 , further comprising indicating that the digital signature is invalid when the data in the at least one discrete part is altered. | 0.588878 |
22. At least one computer-readable recording medium encoded with a plurality of instructions that, when executed by at least one processor, perform a method comprising acts of: establishing a real-time communication session between a text exchange client and a speech enabled application; identifying a translation table that includes a plurality of entries, each entry including a text exchange item and a corresponding conversational translation item; receiving a text exchange message that was entered into a text exchange client; detecting at least one text exchange item in the text exchange message, which corresponds to an entry included in the translation table; in the text exchange message, substituting a corresponding conversational translation item for each detected text exchange item; sending the substitute message to a text input interface of a voice server to be processed; receiving, from the speech enabled application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client, wherein substituting a corresponding conversation translation item for each detected text exchange occurs in a manner transparent to the text exchange client and to the speech enabled application. | 22. At least one computer-readable recording medium encoded with a plurality of instructions that, when executed by at least one processor, perform a method comprising acts of: establishing a real-time communication session between a text exchange client and a speech enabled application; identifying a translation table that includes a plurality of entries, each entry including a text exchange item and a corresponding conversational translation item; receiving a text exchange message that was entered into a text exchange client; detecting at least one text exchange item in the text exchange message, which corresponds to an entry included in the translation table; in the text exchange message, substituting a corresponding conversational translation item for each detected text exchange item; sending the substitute message to a text input interface of a voice server to be processed; receiving, from the speech enabled application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client, wherein substituting a corresponding conversation translation item for each detected text exchange occurs in a manner transparent to the text exchange client and to the speech enabled application. 28. The at least one computer-readable recording of claim 22 , wherein the method further comprises acts of: detecting at least one conversational translation item in the automatic output message, which corresponds to an entry included in the translation table; in the automatic output message, substituting a corresponding text exchange item for each detected conversational translation item to generate the output text. | 0.5 |
1. A method of automatically converting alphabetic text written in a text based language into a non-text based language, comprising: identifying a reading level of a person; when the identified reading level of the person is below a threshold level: parsing the text to identify at least one word; via a processor, identifying within a lexicon database data corresponding to the word, wherein the data corresponding to the word identifies at least one pictograph for each letter or plurality of letters of the word, the at least one pictograph being selected from a group of pictographs that visually look different than the text and comprises an object entity or an action, wherein each pictograph in the group of pictographs corresponds to a unique speech sound of the text based language; rendering the identified at least one word as a phonetic word object in a view, the phonetic word object including the identified at least one pictograph; and monitoring the reading level of the person; when the identified reading level or monitored reading level of the person is at least equal to the threshold level: parsing the text to identify at least one word; via the processor, identifying within the lexicon database data corresponding to the word, wherein the data corresponding to the word identifies at least one symbol for each letter or plurality of letters of the word, the at least one symbol being selected from a group of symbols that visually look more like the letters of the text based language than the pictographs, wherein the group of symbols comprises at least one symbol representing a consonant that has at least one visual attribute representing a particular feature depicted in a corresponding pictograph, wherein each symbol in the group of symbols corresponds to a unique speech sound of the text based language; and rendering the identified at least one word as a phonetic word object in a view, the phonetic word object including the identified at least one symbol. | 1. A method of automatically converting alphabetic text written in a text based language into a non-text based language, comprising: identifying a reading level of a person; when the identified reading level of the person is below a threshold level: parsing the text to identify at least one word; via a processor, identifying within a lexicon database data corresponding to the word, wherein the data corresponding to the word identifies at least one pictograph for each letter or plurality of letters of the word, the at least one pictograph being selected from a group of pictographs that visually look different than the text and comprises an object entity or an action, wherein each pictograph in the group of pictographs corresponds to a unique speech sound of the text based language; rendering the identified at least one word as a phonetic word object in a view, the phonetic word object including the identified at least one pictograph; and monitoring the reading level of the person; when the identified reading level or monitored reading level of the person is at least equal to the threshold level: parsing the text to identify at least one word; via the processor, identifying within the lexicon database data corresponding to the word, wherein the data corresponding to the word identifies at least one symbol for each letter or plurality of letters of the word, the at least one symbol being selected from a group of symbols that visually look more like the letters of the text based language than the pictographs, wherein the group of symbols comprises at least one symbol representing a consonant that has at least one visual attribute representing a particular feature depicted in a corresponding pictograph, wherein each symbol in the group of symbols corresponds to a unique speech sound of the text based language; and rendering the identified at least one word as a phonetic word object in a view, the phonetic word object including the identified at least one symbol. 7. The method of claim 1 , wherein: at least one of the respective symbols in the group of symbols include at least one visual attribute corresponding to a visual attribute of at least one respective letter of the text based language corresponding to the same unique speech sound to which the symbol corresponds; and the at least one symbol includes at least one visual attribute corresponding to visual attribute of a respective pictographs in a group of pictographs corresponding to the same unique speech sound to which the symbol corresponds. | 0.552091 |
20. The computer system of claim 19 , further comprising a step of: if a deadlock is detected at the step of checking, returning to a user a characterization indicative of the detected deadlock via a graphical user interface (GUI). | 20. The computer system of claim 19 , further comprising a step of: if a deadlock is detected at the step of checking, returning to a user a characterization indicative of the detected deadlock via a graphical user interface (GUI). 21. The computer system of claim 20 , further comprising, after returning the characterization indicative of the detected deadlock, a step of: upon receiving user instruction to dismiss a detected deadlock, continuing the labeling by considering: the labels of respective two incoming edges of the AND-join node corresponding to the detected deadlock as equivalent; and the AND-join node corresponding to the detected deadlock as an inclusive OR-join node. | 0.804774 |
1. A method in a content recommendation system, the method comprising: identifying a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising: processing content items to determine semantic information that includes identified entities and relations between the identified entities; storing the identified entities and relations in a repository of the content recommendation system; generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items, wherein generating the cluster includes: finding a candidate cluster of a plurality of clusters that is nearest to one of the multiple related content items by computing a cosine distance between a term vector that represents the one content item and a term vector that represents a content item of the candidate cluster; and determining whether the candidate cluster is a suitable cluster for the one content item, based on all of: cosine distances between the one content item and content items of the candidate cluster, a quantity of common keyterms between the one content item and content items of the candidate cluster, and on whether a sufficiently high percentage of content items of the candidate cluster have a cosine distance to the content item that is below a predetermined threshold; if the candidate cluster is determined to be a suitable cluster, adding the one content item to the candidate cluster; and if the candidate cluster is not determined to be a suitable cluster, creating a new cluster that includes the one content item as a seed; and storing an indication of the identified news story and the generated cluster. | 1. A method in a content recommendation system, the method comprising: identifying a news story about an event, the news story including multiple related content items that each give an account of the event and that each reference multiple entities or categories that are each electronically represented by the content recommendation system, comprising: processing content items to determine semantic information that includes identified entities and relations between the identified entities; storing the identified entities and relations in a repository of the content recommendation system; generating a cluster that includes the multiple related content items, based at least in part on how many entities each of the multiple related content items has in common with one or more other of the multiple related content items, wherein generating the cluster includes: finding a candidate cluster of a plurality of clusters that is nearest to one of the multiple related content items by computing a cosine distance between a term vector that represents the one content item and a term vector that represents a content item of the candidate cluster; and determining whether the candidate cluster is a suitable cluster for the one content item, based on all of: cosine distances between the one content item and content items of the candidate cluster, a quantity of common keyterms between the one content item and content items of the candidate cluster, and on whether a sufficiently high percentage of content items of the candidate cluster have a cosine distance to the content item that is below a predetermined threshold; if the candidate cluster is determined to be a suitable cluster, adding the one content item to the candidate cluster; and if the candidate cluster is not determined to be a suitable cluster, creating a new cluster that includes the one content item as a seed; and storing an indication of the identified news story and the generated cluster. 13. The method of claim 1 wherein identifying the news story includes determining a representative content item for the news story by selecting one of the multiple related content items that is nearest to a centroid of the generated cluster. | 0.56135 |
1. A method, comprising: detecting an event that causes a compiler to generate diagnostic information; storing the diagnostic information for the event in a manner that preserves semantic information associated with the event; receiving diagnostic information at a particular development tool, wherein the diagnostic information was generated by the compiler while compiling source code for a program created using the development tool, wherein the diagnostic information has a structured representation that is configured to be plugged into at least one diagnostic formatter from a set of diagnostic formatters, which comprises: a raw diagnostic formatter that outputs diagnostic information using an internal format of the compiler for diagnostic information; a tunneling diagnostic formatter that encodes the diagnostic information into a structured XML document; a rich diagnostic formatter that performs the following modifications to the diagnostic information: localizing the diagnostic output; shortening a unique name in the diagnostic information while preserving the name's uniqueness; lengthening a clashing name in the diagnostic information to make the clashing name unique; and adding a where clause to the diagnostic information that provides additional type information for variables in the diagnostic information; selecting the raw diagnostic formatter from the set of diagnostic formatters based on a particular output context for the particular development tool; using the raw diagnostic formatter to modify at least a particular part of the diagnostic information before presenting the particular part of the diagnostic information to a user through the particular development tool; selecting the rich diagnostic formatter from the set of diagnostic formatters; tunneling the diagnostic information through one or more intermediate application layers to a subsequent development tool; using the rich diagnostic formatter to modify at least a subsequent part of the diagnostic information before presenting the subsequent part of the diagnostic information to the user through the subsequent development tool; comparing the modified particular part of the diagnostic information or the modified subsequent part of the diagnostic information to a reference diagnostic output generated by a reference compiler; and presenting the modified particular part of the diagnostic information to the user through the particular development tool, the modified subsequent part of the diagnostic information to the user through the subsequent development tool and results of the comparison to the reference diagnostic output. | 1. A method, comprising: detecting an event that causes a compiler to generate diagnostic information; storing the diagnostic information for the event in a manner that preserves semantic information associated with the event; receiving diagnostic information at a particular development tool, wherein the diagnostic information was generated by the compiler while compiling source code for a program created using the development tool, wherein the diagnostic information has a structured representation that is configured to be plugged into at least one diagnostic formatter from a set of diagnostic formatters, which comprises: a raw diagnostic formatter that outputs diagnostic information using an internal format of the compiler for diagnostic information; a tunneling diagnostic formatter that encodes the diagnostic information into a structured XML document; a rich diagnostic formatter that performs the following modifications to the diagnostic information: localizing the diagnostic output; shortening a unique name in the diagnostic information while preserving the name's uniqueness; lengthening a clashing name in the diagnostic information to make the clashing name unique; and adding a where clause to the diagnostic information that provides additional type information for variables in the diagnostic information; selecting the raw diagnostic formatter from the set of diagnostic formatters based on a particular output context for the particular development tool; using the raw diagnostic formatter to modify at least a particular part of the diagnostic information before presenting the particular part of the diagnostic information to a user through the particular development tool; selecting the rich diagnostic formatter from the set of diagnostic formatters; tunneling the diagnostic information through one or more intermediate application layers to a subsequent development tool; using the rich diagnostic formatter to modify at least a subsequent part of the diagnostic information before presenting the subsequent part of the diagnostic information to the user through the subsequent development tool; comparing the modified particular part of the diagnostic information or the modified subsequent part of the diagnostic information to a reference diagnostic output generated by a reference compiler; and presenting the modified particular part of the diagnostic information to the user through the particular development tool, the modified subsequent part of the diagnostic information to the user through the subsequent development tool and results of the comparison to the reference diagnostic output. 2. The method of claim 1 , wherein presenting the diagnostic information a particular diagnostic tool and a subsequent diagnostic tool comprises one of: presenting the diagnostic information through the particular diagnostic tool simultaneously with presenting the diagnostic information through the subsequent diagnostic tool; and presenting the diagnostic information through the subsequent diagnostic tool after presenting the diagnostic information through the particular diagnostic tool. | 0.550836 |
16. A system comprising: one or more hardware processors; and one or more machine-readable media storing instructions which, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising: analyzing contents of a document to identify a plurality of document elements that collectively constitute the contents of the document, and causing, for each of the identified document elements, a respective database entry comprising a unique document-element identifier to be stored; creating a plurality of anchors dispersed throughout the document by causing, for each of a plurality of anchor locations, a respective database entry comprising a unique anchor identifier to be stored; causing a document view to be stored that represents the document as an ordered list of the document-element identifiers of the identified document elements, and causing at least some of the anchor identifiers to be listed in the document view interspersed with or nested within the document-element identifiers; and generating, in response to selection of a portion of the document, a referencing address uniquely identifying the selected portion, the referencing address comprising at least one or more anchor identifiers of one or more respective anchors associated with the selected portion. | 16. A system comprising: one or more hardware processors; and one or more machine-readable media storing instructions which, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising: analyzing contents of a document to identify a plurality of document elements that collectively constitute the contents of the document, and causing, for each of the identified document elements, a respective database entry comprising a unique document-element identifier to be stored; creating a plurality of anchors dispersed throughout the document by causing, for each of a plurality of anchor locations, a respective database entry comprising a unique anchor identifier to be stored; causing a document view to be stored that represents the document as an ordered list of the document-element identifiers of the identified document elements, and causing at least some of the anchor identifiers to be listed in the document view interspersed with or nested within the document-element identifiers; and generating, in response to selection of a portion of the document, a referencing address uniquely identifying the selected portion, the referencing address comprising at least one or more anchor identifiers of one or more respective anchors associated with the selected portion. 23. The system of claim 16 , wherein the operations further comprise including a document key uniquely identifying the document in the referencing address. | 0.551491 |
14. A computer system configured to provide for the collaboration of information comprising: a computer-implemented client associated with each user of the system, the client comprising: an assembly workspace including a sections component and an assembly document representation; and, a data store including memory to store information of a number of participants associated with an assembly document, wherein the information is associated with content, state, relationship with other entities, version, locking behavior, and status; and, a computer-implemented assembly component to: assemble the assembly document, including using a master assembly document to track and maintain user changes, after interacting with the assembly document representation; provide an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions; apply a number of constraints to the assembly document, wherein the number of constraints determine users permitted to interact with a number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; use an assembly document proxy to build the assembly document based in part on the information and an assembly document object to create a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation customized for an end-user user based in part on the information stored in the data store including an associated role and other permission parameters associated with the end-user; and, generate a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. | 14. A computer system configured to provide for the collaboration of information comprising: a computer-implemented client associated with each user of the system, the client comprising: an assembly workspace including a sections component and an assembly document representation; and, a data store including memory to store information of a number of participants associated with an assembly document, wherein the information is associated with content, state, relationship with other entities, version, locking behavior, and status; and, a computer-implemented assembly component to: assemble the assembly document, including using a master assembly document to track and maintain user changes, after interacting with the assembly document representation; provide an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions; apply a number of constraints to the assembly document, wherein the number of constraints determine users permitted to interact with a number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; use an assembly document proxy to build the assembly document based in part on the information and an assembly document object to create a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation customized for an end-user user based in part on the information stored in the data store including an associated role and other permission parameters associated with the end-user; and, generate a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. 15. The system of claim 14 , the assembly document proxy further to provide the manifestation of the assembly document, wherein the assembly document proxy includes the data, metadata, and content to be used to persist the assembly document on the client. | 0.56275 |
7. A system according to claim 6, wherein the readability output includes a linear function of plural basic text units. | 7. A system according to claim 6, wherein the readability output includes a linear function of plural basic text units. 8. A system according to claim 7, wherein a readability output includes a Bormuth Reading Power Score. | 0.951479 |
1. A computer-executable method for generating a product recommendation, comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. | 1. A computer-executable method for generating a product recommendation, comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. 9. The method of claim 1 , further comprising: receiving data indicating a new primitive and input/output arguments of the new primitive; and adding the new primitive to a set of primitives. | 0.928731 |
11. The one or more computer-readable storage memory of claim 7 , the one or more API modules comprising an object-oriented class, the one or more metadata files configured to describe the object-oriented class in an object-oriented manner. | 11. The one or more computer-readable storage memory of claim 7 , the one or more API modules comprising an object-oriented class, the one or more metadata files configured to describe the object-oriented class in an object-oriented manner. 12. The one or more computer-readable storage memory of claim 11 , the object-oriented class comprising a file class. | 0.9123 |
10. A speech recognition output confirmation system, comprising: a decision mechanism configured to decide whether a confirmation is to be performed, said decision mechanism being pre-configured to make said decision employing a mode chosen from the group consisting of a deterministic mode, a random mode, and an integrated mode, wherein the random mode comprises randomly determining whether to perform the automated confirmation to verify a speech recognition result; and a confirmation mechanism, in communication with said decision mechanism, said confirmation mechanism configured to perform the automated confirmation on the speech recognition result having an associated confidence score according to the decision made by said decision mechanism, wherein a confirmation construction mechanism carries out the automated confirmation, and generates a confirmation response. | 10. A speech recognition output confirmation system, comprising: a decision mechanism configured to decide whether a confirmation is to be performed, said decision mechanism being pre-configured to make said decision employing a mode chosen from the group consisting of a deterministic mode, a random mode, and an integrated mode, wherein the random mode comprises randomly determining whether to perform the automated confirmation to verify a speech recognition result; and a confirmation mechanism, in communication with said decision mechanism, said confirmation mechanism configured to perform the automated confirmation on the speech recognition result having an associated confidence score according to the decision made by said decision mechanism, wherein a confirmation construction mechanism carries out the automated confirmation, and generates a confirmation response. 11. The system according to claim 10 , wherein the confirmation mechanism performs a confirmation employing a mode chosen from a group consisting of a manual mode in which a human operator performs the confirmation; and an automated mode in which a speech recognition mechanism is used to confirm the speech recognition result. | 0.612821 |
31. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; and a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets. | 31. A method for storing and retrieving data in a computer system having a memory, a central processing unit and a display, comprising the steps of: configuring said memory according to a logical table, said logical table including: a plurality of cells, each said cell having a first address segment and a second address segment; a plurality of attribute sets, each said attribute set including a series of cells having the same second address segment, each said attribute set including an object identification number (OID) to identify each said attribute set; and a plurality of records, each said record including a series of cells having the same first address segment, each said record including an OID to identify each said record, wherein at least one of said records has an OID equal to the OID of a corresponding one of said attribute sets, and at least one of said records includes attribute set information defining each of said attribute sets. 40. The method of claim 31 wherein said OID's are variable length and include data related to a session identification number and a timestamp. | 0.573874 |
7. The method of claim 5 , wherein determining the respective cost values for each of at least the first key, the second key, and the third key comprises: determining respective physical cost values for each of at least the first key, the second key, and the third key, wherein each of the respective physical cost values represents a probability that at least one physical feature of an alignment point of the group of alignment points indicates at least one physical feature of a key of the plurality of keys; determining respective lexical cost values for each of at least the first key, the second key, and the third key, wherein each of the respective lexical cost values represents a probability that a letter represented by a key of the plurality of keys is included in the candidate word; and determining the respective cost values for each of at least the first key, the second key, and the third key based on the respective physical cost values and the respective lexical cost values for each of at least the first key, the second key, and the third key. | 7. The method of claim 5 , wherein determining the respective cost values for each of at least the first key, the second key, and the third key comprises: determining respective physical cost values for each of at least the first key, the second key, and the third key, wherein each of the respective physical cost values represents a probability that at least one physical feature of an alignment point of the group of alignment points indicates at least one physical feature of a key of the plurality of keys; determining respective lexical cost values for each of at least the first key, the second key, and the third key, wherein each of the respective lexical cost values represents a probability that a letter represented by a key of the plurality of keys is included in the candidate word; and determining the respective cost values for each of at least the first key, the second key, and the third key based on the respective physical cost values and the respective lexical cost values for each of at least the first key, the second key, and the third key. 9. The method of claim 7 , wherein determining the respective lexical cost values for each of at least the first key, the second key, and the third key comprises comparing each of at least the first key, the second key, and the third key with a language model. | 0.71044 |
13. The system of claim 9 , wherein the database language is structured query language or SQL. | 13. The system of claim 9 , wherein the database language is structured query language or SQL. 14. The system of claim 13 , wherein the bean select method uses ejb query language or EJB QL. | 0.96828 |
12. The computer-implemented method of claim 8 , further comprising determining at least one difference between at least two of the plurality of versions of the network resource. | 12. The computer-implemented method of claim 8 , further comprising determining at least one difference between at least two of the plurality of versions of the network resource. 13. The computer-implemented method of claim 12 , wherein the at least one difference comprises a difference in at least a portion of textual content of the at least two of the plurality of versions of the network resource. | 0.924149 |
1. A computer-program product tangibly embodied in a computer-readable storage device, the computer-program product comprising instructions that when executed cause a processor to perform operations for providing a natural-language interface to a repository, the operations comprising: identifying at least one repository from which a new computer-readable ontology is to be created; retrieving information from the at least one repository, wherein the retrieved information includes at least a first value of a first attribute and at least a second value of a second attribute; determining a first data type of the first attribute based on the first value; determining a second data type of the second attribute based on the second value; generating the new computer-readable ontology using the retrieved information, the new computer-readable ontology indicating the first data type of the first attribute and the second data type of the second attribute; and interpreting a user-entered natural-language statement for accessing the at least one repository using the new computer-readable ontology, including: (a) identifying, in the first user-entered natural-language statement, a user-entered attribute name corresponding to the first attribute and the second attribute; (b) identifying, in the first user-entered natural-language statement, a user-entered value associated with the user-entered attribute name; (c) determining a data type of the user-entered value; (d) comparing the data type of the user-entered value to the first data type of the first attribute and the second data type of the second attribute; (e) selecting one of the first attribute and the second attribute based on the comparison; and (f) using the selected attribute and the user-entered value in a predefined operation for accessing the at least one repository. | 1. A computer-program product tangibly embodied in a computer-readable storage device, the computer-program product comprising instructions that when executed cause a processor to perform operations for providing a natural-language interface to a repository, the operations comprising: identifying at least one repository from which a new computer-readable ontology is to be created; retrieving information from the at least one repository, wherein the retrieved information includes at least a first value of a first attribute and at least a second value of a second attribute; determining a first data type of the first attribute based on the first value; determining a second data type of the second attribute based on the second value; generating the new computer-readable ontology using the retrieved information, the new computer-readable ontology indicating the first data type of the first attribute and the second data type of the second attribute; and interpreting a user-entered natural-language statement for accessing the at least one repository using the new computer-readable ontology, including: (a) identifying, in the first user-entered natural-language statement, a user-entered attribute name corresponding to the first attribute and the second attribute; (b) identifying, in the first user-entered natural-language statement, a user-entered value associated with the user-entered attribute name; (c) determining a data type of the user-entered value; (d) comparing the data type of the user-entered value to the first data type of the first attribute and the second data type of the second attribute; (e) selecting one of the first attribute and the second attribute based on the comparison; and (f) using the selected attribute and the user-entered value in a predefined operation for accessing the at least one repository. 2. The computer-program product of claim 1 , wherein the information comprises metadata. | 0.569697 |
1. A method for visually modeling information sought from a set of documents implemented using a computer having a processor and a display, comprising: identifying a set of documents; applying a filter to the set of documents to produce raw text; analyzing the raw text using a lexica module and a POS (part of speech) tagger by operation of the processor; creating a set of POS (part of speech) tagged documents based on the analysis of the raw text, the set of POS (part of speech) tagged documents corresponding to the set of documents; presenting the analysis of the raw text to a user; creating a plurality of concepts based on the analysis of the raw text; creating a visual model comprising visual elements corresponding to the plurality of concepts; presenting the visual model to the user on the display; enabling the user to add a new visual element to the visual model, the new visual element corresponding to a new concept; enabling the user to add a new relation between visual elements in the visual model, the new relation between visual elements representing a new relation between concepts corresponding to the visual elements; receiving a definition of a concept from the user via a selection of a visual model corresponding to the concept; generating extractors, each extractor corresponding to one of the visual elements or the relations between the visual elements in the visual model; based on a user selection of one of the visual elements or the relations, extracting a POS (part of speech) tagged document from the set of POS (part of speech) tagged documents using the corresponding extractor, the extracted POS (part of speech) tagged document containing information related to the concept corresponding to the selected visual element or the selected relation; presenting the extracted POS (part of speech) tagged document to the user; customizing the visual model based on user input in response to the extracted POS (part of speech) tagged document; and exporting the customized model. | 1. A method for visually modeling information sought from a set of documents implemented using a computer having a processor and a display, comprising: identifying a set of documents; applying a filter to the set of documents to produce raw text; analyzing the raw text using a lexica module and a POS (part of speech) tagger by operation of the processor; creating a set of POS (part of speech) tagged documents based on the analysis of the raw text, the set of POS (part of speech) tagged documents corresponding to the set of documents; presenting the analysis of the raw text to a user; creating a plurality of concepts based on the analysis of the raw text; creating a visual model comprising visual elements corresponding to the plurality of concepts; presenting the visual model to the user on the display; enabling the user to add a new visual element to the visual model, the new visual element corresponding to a new concept; enabling the user to add a new relation between visual elements in the visual model, the new relation between visual elements representing a new relation between concepts corresponding to the visual elements; receiving a definition of a concept from the user via a selection of a visual model corresponding to the concept; generating extractors, each extractor corresponding to one of the visual elements or the relations between the visual elements in the visual model; based on a user selection of one of the visual elements or the relations, extracting a POS (part of speech) tagged document from the set of POS (part of speech) tagged documents using the corresponding extractor, the extracted POS (part of speech) tagged document containing information related to the concept corresponding to the selected visual element or the selected relation; presenting the extracted POS (part of speech) tagged document to the user; customizing the visual model based on user input in response to the extracted POS (part of speech) tagged document; and exporting the customized model. 6. The method of claim 1 , wherein customizing comprises: associating a unique identifier selected from the group consisting of a color, a font, and a shape with one of the elements of the visual display. | 0.51412 |
15. A computer program product stored in a non-transitory computer readable storage medium, comprising computer instructions that, when executed by an information handling system, causes the system to analyze concept vectors over time to detect changes in a corpus by performing actions comprising: generating, by the system, at least a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts that are extracted from the corpus and applied to a vector learning component; generating, by the system, at least a second concept vector set V′1, . . . , V′k+b derived from a second set of concept sequences over k old and b new concepts that are extracted from the corpus and applied to the vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences; and performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to detect changes in the corpus over time by analyzing relationship strengths between concepts that persist in the first set of concept sequences and the second set of concept sequences to identify market trends for answering questions submitted to the information handling system by identifying vector changes for one or more concepts included in the first and/or second set of concept sequences, wherein analyzing relationship strengths comprises: computing, by the system, a first cosine distance between each vector pair Vi, Vj from the first concept vector set V1, . . . , Vk for all i≠j, 1≤i, j≤k; computing, by the system, a second cosine distance between each vector pair V′i, V′j from the second concept vector set V1, . . . , V′k+b for all i≠j, 1≤i, j≤k; and identifying concept pairs from the first set of concept sequences whose interrelationship has changed by reporting each concept pair Vi, Vj whereby a subtraction of the second cosine distance from the first cosine distance exceeds a first specified reporting threshold. | 15. A computer program product stored in a non-transitory computer readable storage medium, comprising computer instructions that, when executed by an information handling system, causes the system to analyze concept vectors over time to detect changes in a corpus by performing actions comprising: generating, by the system, at least a first concept vector set V1, . . . , Vk derived from a first set of concept sequences over k concepts that are extracted from the corpus and applied to a vector learning component; generating, by the system, at least a second concept vector set V′1, . . . , V′k+b derived from a second set of concept sequences over k old and b new concepts that are extracted from the corpus and applied to the vector learning component, where the second set of concept sequences is effectively collected after collection of the first set of concept sequences; and performing, by the system, a natural language processing (NLP) analysis of the first concept vector set and second concept vector set to detect changes in the corpus over time by analyzing relationship strengths between concepts that persist in the first set of concept sequences and the second set of concept sequences to identify market trends for answering questions submitted to the information handling system by identifying vector changes for one or more concepts included in the first and/or second set of concept sequences, wherein analyzing relationship strengths comprises: computing, by the system, a first cosine distance between each vector pair Vi, Vj from the first concept vector set V1, . . . , Vk for all i≠j, 1≤i, j≤k; computing, by the system, a second cosine distance between each vector pair V′i, V′j from the second concept vector set V1, . . . , V′k+b for all i≠j, 1≤i, j≤k; and identifying concept pairs from the first set of concept sequences whose interrelationship has changed by reporting each concept pair Vi, Vj whereby a subtraction of the second cosine distance from the first cosine distance exceeds a first specified reporting threshold. 17. The computer program product of claim 15 , wherein performing the NLP analysis comprises detecting an appearance of one or more disruptive concepts in the second set of concept sequences that are related to a specified technology area represented by a sum of a plurality of concept vectors. | 0.53776 |
2. The computer-implemented method of claim 1 , wherein calculating the ranking comprises: applying a pagerank-based algorithm to the at least one data structure encoding the preference graph to calculate the ranking. | 2. The computer-implemented method of claim 1 , wherein calculating the ranking comprises: applying a pagerank-based algorithm to the at least one data structure encoding the preference graph to calculate the ranking. 3. The computer-implemented method of claim 2 , wherein the preference graph comprises a plurality of nodes, wherein each node corresponds to an item in the plurality of items, and calculating the ranking comprises: calculating a pagerank score of at least one node in the plurality of nodes. | 0.90815 |
4. The method of claim 3 , all the limitations of which are incorporated herein by reference, further comprising categorizing each said data relevant to said user query in said dataset into non-overlapping data regions. | 4. The method of claim 3 , all the limitations of which are incorporated herein by reference, further comprising categorizing each said data relevant to said user query in said dataset into non-overlapping data regions. 5. The method of claim 4 , all the limitations of which are incorporated herein by reference, further comprising calculating a number of unique values in said data set associated with a given attribute. | 0.971031 |
4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. 9. The computing system of claim 4 wherein the context identification system comprises: a proximity detector configured to identify other people or things within a given proximity to the computing system. | 0.904417 |
2. The apparatus of claim 1 wherein the dialog comprises part of a telephone conversation between the caller and the automated dialog system. | 2. The apparatus of claim 1 wherein the dialog comprises part of a telephone conversation between the caller and the automated dialog system. 3. The apparatus of claim 2 wherein the agent is compelled to intervene upon a request by the caller. | 0.978607 |
20. A method performed by a control system through interaction with an entertainment system comprising a screen and at least one audio unit, the method comprising: in a remote control device: displaying a language guide on a screen of the remote control device; receiving a user input via the displayed language guide; identifying a first language corresponding to the user input; and responding to the user input by transmitting a control signal triggering delivery of a video portion of a media element to the screen of the entertainment system and an audio portion of the media element in the selected first language to the at least one audio unit of the entertainment system. | 20. A method performed by a control system through interaction with an entertainment system comprising a screen and at least one audio unit, the method comprising: in a remote control device: displaying a language guide on a screen of the remote control device; receiving a user input via the displayed language guide; identifying a first language corresponding to the user input; and responding to the user input by transmitting a control signal triggering delivery of a video portion of a media element to the screen of the entertainment system and an audio portion of the media element in the selected first language to the at least one audio unit of the entertainment system. 21. The method according to claim 20 , further comprising: displaying a media selection guide on the screen of the remote control device; receiving a media selection via the displayed media selection guide; and identifying the media element from a plurality of media elements based on the received media selection. | 0.659566 |
1. A non-transitory computer storage medium storing computer-useable instructions that, when used by at least one computing device, cause the at least one computing device to perform operations comprising: receiving an abstraction of an asset associated with an asset-modifying workflow; determining a contextual identifier based on the received abstraction of the asset; determining a modification to the asset-modifying workflow based on the determined contextual identifier; and communicating a signal operable to apply the determined modification to the asset-modifying workflow. | 1. A non-transitory computer storage medium storing computer-useable instructions that, when used by at least one computing device, cause the at least one computing device to perform operations comprising: receiving an abstraction of an asset associated with an asset-modifying workflow; determining a contextual identifier based on the received abstraction of the asset; determining a modification to the asset-modifying workflow based on the determined contextual identifier; and communicating a signal operable to apply the determined modification to the asset-modifying workflow. 9. The medium of claim 1 , wherein the signal includes at least one of a reference to the identified contextual identifier, a recommendation to modify the asset-modifying workflow, or instructions operable to initiate a modification of the asset-modifying workflow. | 0.801427 |
15. A method for presenting a series of exercise books and a series of story books through a literacy software program, the method being implemented on a computer system including a computer-readable storage medium comprising instructions that when executed by a computer processor the following operations to occur: presenting on a display device, via the computer processor, a first exercise book of the series of exercise books, each exercise book comprising a set of language skills exercises introducing a targeted set of content words and non-content words; and determining, by the computer processor, an associated story book to present based on a shared content property of the associated story book and one or more exercise books including the first exercise book after user completion of the one or more exercise books from the series of exercise books, the shared content property being a story of the associated story book consisting only of those content words and non-content words that were introduced by the one or more previously completed exercise books from the series of exercise books such that the user viewing the associated story book on the display device is exposed only to those content words and non-contents words that were previously introduced with the language skills exercises of the one or more previously completed exercise books. | 15. A method for presenting a series of exercise books and a series of story books through a literacy software program, the method being implemented on a computer system including a computer-readable storage medium comprising instructions that when executed by a computer processor the following operations to occur: presenting on a display device, via the computer processor, a first exercise book of the series of exercise books, each exercise book comprising a set of language skills exercises introducing a targeted set of content words and non-content words; and determining, by the computer processor, an associated story book to present based on a shared content property of the associated story book and one or more exercise books including the first exercise book after user completion of the one or more exercise books from the series of exercise books, the shared content property being a story of the associated story book consisting only of those content words and non-content words that were introduced by the one or more previously completed exercise books from the series of exercise books such that the user viewing the associated story book on the display device is exposed only to those content words and non-contents words that were previously introduced with the language skills exercises of the one or more previously completed exercise books. 26. The method of claim 15 , wherein in response to completing the associated story book, a subsequent exercise book in the series of exercise books is immediately presented on the display device. | 0.602592 |
1. A method for web mining at least one couplet part, the method comprising: parsing, by a computer, a search result resulting from a query based on a search term comprising a first part of a couplet comprising the first part and a second part, wherein each of the first part and the second part include at least one character or word, and wherein the parsing results in a snippet set wherein each snippet in the set comprises at least one returned character or word that matches the query; filtering, by the computer, the resulting snippet set, wherein the filtering results in at least one candidate couplet part; and generating, by the computer, at least one output couplet part, wherein the generating comprises classifying, by a support vector machine classifier, the at least one candidate couplet part, wherein the at least one couplet part comprises the generated at least one output couplet part. | 1. A method for web mining at least one couplet part, the method comprising: parsing, by a computer, a search result resulting from a query based on a search term comprising a first part of a couplet comprising the first part and a second part, wherein each of the first part and the second part include at least one character or word, and wherein the parsing results in a snippet set wherein each snippet in the set comprises at least one returned character or word that matches the query; filtering, by the computer, the resulting snippet set, wherein the filtering results in at least one candidate couplet part; and generating, by the computer, at least one output couplet part, wherein the generating comprises classifying, by a support vector machine classifier, the at least one candidate couplet part, wherein the at least one couplet part comprises the generated at least one output couplet part. 2. The method as recited in claim 1 wherein the search result is obtained by processing the search term using a search engine. | 0.585714 |
25. A word game device with a game objective to find or form words, comprising: a playfield that includes a plurality of playing positions, wherein a playing position is used to display a character of an alphabet, and wherein an initial set of alphabet characters are assigned to playing positions to form at least one game word, and wherein at least one game word is scrambled by having at least one character shifted into a position that does not lie along the same axis common to the other characters in the word, at least one input control mechanism to enable a player to interact with the device, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the device, and a program segment that is responsive to input control mechanism, and which shifts characters along a selected axis on the playfield. | 25. A word game device with a game objective to find or form words, comprising: a playfield that includes a plurality of playing positions, wherein a playing position is used to display a character of an alphabet, and wherein an initial set of alphabet characters are assigned to playing positions to form at least one game word, and wherein at least one game word is scrambled by having at least one character shifted into a position that does not lie along the same axis common to the other characters in the word, at least one input control mechanism to enable a player to interact with the device, a microprocessor with a computer-readable medium encoded with a computer program to control the operation of the device, and a program segment that is responsive to input control mechanism, and which shifts characters along a selected axis on the playfield. 30. A word game device as recited in claim 25 , wherein said plurality of playing positions form a two-dimensional array. | 0.621351 |
1. A method for retrieving information, comprising: receiving a search query within a first information corpus that comprises a first plurality of documents, wherein the first information corpus is a first non World Wide Web-based corpus whose first plurality of documents are not available on the World Wide Web; identifying search results for the search query; generating a score for each of a plurality of data items identified in the search results, wherein the score for a corresponding one of the plurality of data items is based on: a score dependent on the search query within the first information corpus; and at least one score independent of the search query, the at least one score independent of the search query comprising a ranking signal and at least one additional score, the ranking signal being associated with a search of the corresponding one of the plurality of data items using a second information corpus that comprises a second plurality of documents, wherein the second information corpus is a World Wide Web-based corpus whose second plurality of documents are available on an Internet, wherein the first information corpus comprising the first plurality of documents and the second information corpus comprising the second plurality of documents are non-overlapping, the ranking signal including a first score signal based on a number of times the search has been performed over a given period of time, the at least one additional score based on information from a second non World Wide Web-based corpus that includes a geographic location from where the search query originated and whose information is not available on the World Wide Web; and ranking the search results based on the generated score for each of the plurality of data items. | 1. A method for retrieving information, comprising: receiving a search query within a first information corpus that comprises a first plurality of documents, wherein the first information corpus is a first non World Wide Web-based corpus whose first plurality of documents are not available on the World Wide Web; identifying search results for the search query; generating a score for each of a plurality of data items identified in the search results, wherein the score for a corresponding one of the plurality of data items is based on: a score dependent on the search query within the first information corpus; and at least one score independent of the search query, the at least one score independent of the search query comprising a ranking signal and at least one additional score, the ranking signal being associated with a search of the corresponding one of the plurality of data items using a second information corpus that comprises a second plurality of documents, wherein the second information corpus is a World Wide Web-based corpus whose second plurality of documents are available on an Internet, wherein the first information corpus comprising the first plurality of documents and the second information corpus comprising the second plurality of documents are non-overlapping, the ranking signal including a first score signal based on a number of times the search has been performed over a given period of time, the at least one additional score based on information from a second non World Wide Web-based corpus that includes a geographic location from where the search query originated and whose information is not available on the World Wide Web; and ranking the search results based on the generated score for each of the plurality of data items. 8. The method according to claim 1 , wherein the at least one additional score independent of the search query is further based on one or more of: a sell count of the corresponding one of the plurality of data items; a release date of the corresponding one of the plurality of data items; or if the corresponding one of the plurality of data items is a media item, a play count of the corresponding one of the plurality of data items. | 0.54048 |
1. A method performed by one of more processors associated with one or more server devices, the method comprising: receiving, by one or more processors, a search query from a user via a client device; searching, by one or more processors and based on the search query, a plurality of repositories to identify, for each of the plurality of repositories, a set of search results, the plurality of repositories including different types of documents; calculating, for each of the plurality of repositories, a score associated with a likelihood that a corresponding repository, of the plurality of repositories, includes information responsive to the search query, the score being calculated based on: a comparison of information about the search query and information about a plurality of other search queries associated with a plurality of users, the information about the plurality of other search queries including: information regarding a user that provided a search query, information regarding the search query, and information regarding a repository from which search results were provided in response to the search query, a comparison of information, associated with the user, and information about the plurality of users, and selections, by the plurality of users and based on the plurality of search queries, from the corresponding repository; ranking, by one or more processors, the plurality of repositories based on the respective scores; selecting, by one or more processors, at least one of the plurality of repositories based on the rankings; and generating, by one or more processors, a search result document based on the set of search results associated with the selected at least one of the plurality of repositories. | 1. A method performed by one of more processors associated with one or more server devices, the method comprising: receiving, by one or more processors, a search query from a user via a client device; searching, by one or more processors and based on the search query, a plurality of repositories to identify, for each of the plurality of repositories, a set of search results, the plurality of repositories including different types of documents; calculating, for each of the plurality of repositories, a score associated with a likelihood that a corresponding repository, of the plurality of repositories, includes information responsive to the search query, the score being calculated based on: a comparison of information about the search query and information about a plurality of other search queries associated with a plurality of users, the information about the plurality of other search queries including: information regarding a user that provided a search query, information regarding the search query, and information regarding a repository from which search results were provided in response to the search query, a comparison of information, associated with the user, and information about the plurality of users, and selections, by the plurality of users and based on the plurality of search queries, from the corresponding repository; ranking, by one or more processors, the plurality of repositories based on the respective scores; selecting, by one or more processors, at least one of the plurality of repositories based on the rankings; and generating, by one or more processors, a search result document based on the set of search results associated with the selected at least one of the plurality of repositories. 2. The method of claim 1 , where the score is based on a model that determines whether to search the particular repository, of the plurality of repositories, based on information about the previous search queries and the plurality of users, and where calculating the score includes: generating rules for the model. | 0.636559 |
11. A computer program product tangibly embodied on a computer readable storage device, the computer program product for playing content, the computer program product comprising instructions for causing a device to: receive ad-hoc feeds; produce one or more visual items of playable content from the received ad-hoc feeds by instructions to: convert information content from a given one of the ad-hoc feeds into a specified mark-up language format; apply parsing rules to parse the converted information content from the given ad-hoc feed into code functions and data elements to provide one or more datasets comprising one or more of image, text, audio and video portions of the given ad-hoc feed; load a first one of the data elements and code functions of the given ad-hoc feed into a player window of a player to render the one of more datasets into one of the produced visual items of playable content; store the one or more produced visual items of playable content in a computer storage; execute a player engine that plays the one or more visual items of playable content, as images parsed from the ad-hoc feeds, and rendered on a display device; apply one or more user focus tools by a user to one of the visual items of playable content, rendered on the display device, the one or more user focus tools functionally selected according to at least one of context of the user, device and location of the device; produce new content by application of the one or more user focus tools; and cause the new content that results from applying the one or more user focus tools to be rendered on the display device with the rendered visual item. | 11. A computer program product tangibly embodied on a computer readable storage device, the computer program product for playing content, the computer program product comprising instructions for causing a device to: receive ad-hoc feeds; produce one or more visual items of playable content from the received ad-hoc feeds by instructions to: convert information content from a given one of the ad-hoc feeds into a specified mark-up language format; apply parsing rules to parse the converted information content from the given ad-hoc feed into code functions and data elements to provide one or more datasets comprising one or more of image, text, audio and video portions of the given ad-hoc feed; load a first one of the data elements and code functions of the given ad-hoc feed into a player window of a player to render the one of more datasets into one of the produced visual items of playable content; store the one or more produced visual items of playable content in a computer storage; execute a player engine that plays the one or more visual items of playable content, as images parsed from the ad-hoc feeds, and rendered on a display device; apply one or more user focus tools by a user to one of the visual items of playable content, rendered on the display device, the one or more user focus tools functionally selected according to at least one of context of the user, device and location of the device; produce new content by application of the one or more user focus tools; and cause the new content that results from applying the one or more user focus tools to be rendered on the display device with the rendered visual item. 12. The computer program product of claim 11 further comprising instructions to: queue the produced visual items of playable content for playback in a sequence according to criteria specified for playback; and customize the queued visual items of playable content by at least one property of location of the device, time of day, audience intended for the visual items, and activity engaged in by the user. | 0.566991 |
20. The machine readable medium of claim 17 , wherein heuristically identifying ambiguous memory dependencies associated with the memory references of the load and the store instructions in the code segment further comprises identifying non-aliases and must-aliases of the code segment. | 20. The machine readable medium of claim 17 , wherein heuristically identifying ambiguous memory dependencies associated with the memory references of the load and the store instructions in the code segment further comprises identifying non-aliases and must-aliases of the code segment. 24. The machine readable medium of claim 20 , wherein the runtime checks further comprise symbolically computing a value of a register and a value of a memory location referenced by the code segment. | 0.912708 |
1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. | 1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. 8. The system according to claim 1 , wherein the links between IOs are unidirectional. | 0.735588 |
11. A method comprising: receiving, by a computing device, an input data set comprising a document; determining, by the computing device, at least one focus in the input data set, wherein the focus is at least one of a grammatical part of speech or a functional descriptor, and the focus is a portion of the input data set less than the input data set; forming, by the computing device, a term unit matrix from the input data set, the term unit matrix comprising a plurality of numeric integer values, the plurality of numeric integer values corresponding to a plurality of term units of the input data set, wherein the plurality of numeric integer values is a substantially lossless representation of the input data set; filtering, by the computing device, the plurality of term units by removing one or more term units from the plurality of term units based on the focus; forming, by the computing device, a group of combinations of term units that remain after filtering and that are based on an underlying grammatical rule of the input data set, wherein for each term unit of the group of combinations of term units, the underlying grammatical rule is numerically encoded in respective numeric integer values of the group of combinations of term units; identifying, by the computing device, at least one root term unit of the group of combinations of term units that remain after filtering, the at least one root term unit having a plurality of tail term units associated therewith; searching, by the computing device, a data repository that is different from the input data set using the at least one root term unit and the plurality of tail term units; organizing, by the computing device, search results based on the focus indicating presence of the at least one root term unit; and providing, by the computing device, the organized search results. | 11. A method comprising: receiving, by a computing device, an input data set comprising a document; determining, by the computing device, at least one focus in the input data set, wherein the focus is at least one of a grammatical part of speech or a functional descriptor, and the focus is a portion of the input data set less than the input data set; forming, by the computing device, a term unit matrix from the input data set, the term unit matrix comprising a plurality of numeric integer values, the plurality of numeric integer values corresponding to a plurality of term units of the input data set, wherein the plurality of numeric integer values is a substantially lossless representation of the input data set; filtering, by the computing device, the plurality of term units by removing one or more term units from the plurality of term units based on the focus; forming, by the computing device, a group of combinations of term units that remain after filtering and that are based on an underlying grammatical rule of the input data set, wherein for each term unit of the group of combinations of term units, the underlying grammatical rule is numerically encoded in respective numeric integer values of the group of combinations of term units; identifying, by the computing device, at least one root term unit of the group of combinations of term units that remain after filtering, the at least one root term unit having a plurality of tail term units associated therewith; searching, by the computing device, a data repository that is different from the input data set using the at least one root term unit and the plurality of tail term units; organizing, by the computing device, search results based on the focus indicating presence of the at least one root term unit; and providing, by the computing device, the organized search results. 19. The method of claim 11 , wherein the computing device comprises at least one of a computer, a laptop computer, a personal computer, a personal data assistant, a camera, a phone, a cell phone, mobile phone, a computer server, a media server, a music player, a game box, a smart phone, a data storage device, a measuring device, a handheld scanner, a scanning device, a barcode reader, a point-of-sale device, a digital assistant, a desk phone, an IP phone, a solid-state memory device, a tablet, or a memory card. | 0.5 |
17. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying a plurality of different document versions of a particular document; identifying a first type of metadata that is associated with each document version of the plurality of different document versions, wherein the first type of metadata includes data that describes a source that provides each document version of the plurality of different document versions; identifying, by the computer system, at least a second type of metadata that is associated with each document version of the plurality of different document versions, wherein the second type of metadata describes a feature of each document version of the plurality of different document versions other than the source of the document version; for each document version of the plurality of different document versions, applying a priority rule to the first type of metadata and the second type of metadata, to generate a priority value generated for each document version of the plurality of different document versions; selecting a particular document version, of the plurality of different document versions, based on the priority values; and providing the particular document version for presentation. | 17. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying a plurality of different document versions of a particular document; identifying a first type of metadata that is associated with each document version of the plurality of different document versions, wherein the first type of metadata includes data that describes a source that provides each document version of the plurality of different document versions; identifying, by the computer system, at least a second type of metadata that is associated with each document version of the plurality of different document versions, wherein the second type of metadata describes a feature of each document version of the plurality of different document versions other than the source of the document version; for each document version of the plurality of different document versions, applying a priority rule to the first type of metadata and the second type of metadata, to generate a priority value generated for each document version of the plurality of different document versions; selecting a particular document version, of the plurality of different document versions, based on the priority values; and providing the particular document version for presentation. 20. The computer-readable medium of claim 17 , wherein applying the priority rule comprises: identifying a priority associated with the source of each document version of the plurality of different document versions; and determining the priority value for each document version of the plurality of different document versions based on the identified priority associated with the source of each document version of the plurality of document versions. | 0.515089 |
3. The improvement in said synthetic voice generating system of claim 2 wherein said means for utilizing comprises: pitch control means for modifying said glottal pulses to vary the pitch of the glottal pulses, said glottal pulses being modified by uniformly interpolating between sample points of said glottal pulses to produce a modified glottal pulse having more or fewer sample points. | 3. The improvement in said synthetic voice generating system of claim 2 wherein said means for utilizing comprises: pitch control means for modifying said glottal pulses to vary the pitch of the glottal pulses, said glottal pulses being modified by uniformly interpolating between sample points of said glottal pulses to produce a modified glottal pulse having more or fewer sample points. 4. The improvement in said synthetic voice generating system of claim 3 wherein said means for utilizing further comprises: amplitude control means for increasing or decreasing the amplitude of the time-domain glottal pulses modified by said pitch control means. | 0.70884 |
1. A method comprising: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; generating a report comprising, for each result in the group of results, the respective view of data in said each result; and wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; generating a report comprising, for each result in the group of results, the respective view of data in said each result; and wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein the relevance score for a particular field of the common set of fields is based at least in part on a frequency with which null values appear in the results for the particular field. | 0.743529 |
14. The apparatus according to claim 1 , wherein the composition unit comprises an update unit configured to update a filter structure of the composite weak classifier. | 14. The apparatus according to claim 1 , wherein the composition unit comprises an update unit configured to update a filter structure of the composite weak classifier. 15. The apparatus according to claim 14 , wherein the update unit executes the update using a Markov Chain Monte Carlo method. | 0.946922 |
1. A computer-implemented method comprising: receiving a plurality of a particular user's interactions with a plurality of items in a social networking system, each item associated with a category; ranking the items based on the particular user's interactions with the items, each interaction discounted based on a time elapsed since the particular user last interacted with an item; for the particular user, ranking the categories based on the item rankings of the items within each category; for the particular user, generating by the social networking system a bookmark link for each item, each bookmark link providing a link to the corresponding item in the social networking system; and sending the bookmark links grouped by category to the particular user for display, the bookmark links ordered within each category based on the item rankings of the corresponding items within the category, and the categories ordered based on the ranking of the categories. | 1. A computer-implemented method comprising: receiving a plurality of a particular user's interactions with a plurality of items in a social networking system, each item associated with a category; ranking the items based on the particular user's interactions with the items, each interaction discounted based on a time elapsed since the particular user last interacted with an item; for the particular user, ranking the categories based on the item rankings of the items within each category; for the particular user, generating by the social networking system a bookmark link for each item, each bookmark link providing a link to the corresponding item in the social networking system; and sending the bookmark links grouped by category to the particular user for display, the bookmark links ordered within each category based on the item rankings of the corresponding items within the category, and the categories ordered based on the ranking of the categories. 10. The method of claim 1 , wherein an inadvertent interaction with an item by the particular user is not considered when determining the ranking of the item. | 0.570931 |
9. A method performed by at least one electronic device comprising one or more processors, the method comprising: executing, using at least one processor, for each object within a plurality of objects, the following steps: creating a data structure of a first type for the object, wherein the data structure of a first type is created based at least in part on one or more properties associated with the object; and inputting the data structure of a first type for the object into a data structure of a second type; and creating, using at least one processor, an association between a first object and a second object based at least in part on a data structure of a first type for the first object and a data structure of a first type for the second object corresponding to a same bin in the data structure of a second type, wherein the first object comprises a first set of properties, and wherein the second object comprises a second set of properties that include at least a portion of the first set of properties. | 9. A method performed by at least one electronic device comprising one or more processors, the method comprising: executing, using at least one processor, for each object within a plurality of objects, the following steps: creating a data structure of a first type for the object, wherein the data structure of a first type is created based at least in part on one or more properties associated with the object; and inputting the data structure of a first type for the object into a data structure of a second type; and creating, using at least one processor, an association between a first object and a second object based at least in part on a data structure of a first type for the first object and a data structure of a first type for the second object corresponding to a same bin in the data structure of a second type, wherein the first object comprises a first set of properties, and wherein the second object comprises a second set of properties that include at least a portion of the first set of properties. 11. The method of claim 9 , further comprising: causing the data structure of a second type to add each data structure of a first type into a bin in the data structure of a second type, the bin being one of a plurality of bins in the data structure of a second type; and for each bin comprising two or more data structures of a first type: adding the two or more data structures of a first type to a multimap. | 0.606522 |
4. The method of claim 1 , wherein said query expression comprises a first search term associated with a first zone layer and a second search term associated with a second zone layer. | 4. The method of claim 1 , wherein said query expression comprises a first search term associated with a first zone layer and a second search term associated with a second zone layer. 5. The method of claim 4 , wherein the first search term is a primary search term and the second search term is a context search term. | 0.948344 |
1. A system, the system comprising: a memory; a processor; a visual design system having an editor to enable a user to create and edit a visual data structure, said visual data structure based on a hierarchy of components, said components having types as defined by said visual design system; a database to store at least one visual data structure and an associated signature wherein said signature represents at least a semantic composition of said at least one visual data structure; a page analyzer to analyze at least said types and to generate an associated signature for said visual data structure wherein said associated signature for said visual data structure represents at least a semantic composition of said hierarchy of components of said visual data structure; a signature comparer to match a signature of said visual data structure to an associated signature of at least one visual data structure stored in said database and to present multiple versions of alternate visual data structures for said hierarchy of components for selection by a user; a visual data structure adapter and applier to adapt at least the attributes, said component types and content of said visual data structure to a selected visual data structure; and wherein said alternate visual data structures are visually different and semantically similar to each other; and wherein said processor activates said page analyzer, said signature comparer and said adapter and applier. | 1. A system, the system comprising: a memory; a processor; a visual design system having an editor to enable a user to create and edit a visual data structure, said visual data structure based on a hierarchy of components, said components having types as defined by said visual design system; a database to store at least one visual data structure and an associated signature wherein said signature represents at least a semantic composition of said at least one visual data structure; a page analyzer to analyze at least said types and to generate an associated signature for said visual data structure wherein said associated signature for said visual data structure represents at least a semantic composition of said hierarchy of components of said visual data structure; a signature comparer to match a signature of said visual data structure to an associated signature of at least one visual data structure stored in said database and to present multiple versions of alternate visual data structures for said hierarchy of components for selection by a user; a visual data structure adapter and applier to adapt at least the attributes, said component types and content of said visual data structure to a selected visual data structure; and wherein said alternate visual data structures are visually different and semantically similar to each other; and wherein said processor activates said page analyzer, said signature comparer and said adapter and applier. 9. The system according to claim 1 and wherein said visual design system is a native application building system. | 0.572608 |
25. The computer readable medium of claim 19 , wherein the computer executable instructions defining the step of determining a best apex-base plane candidate pair based on the generated joint context using a trained joint context detector comprise computer executable instructions defining the step of: determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector. | 25. The computer readable medium of claim 19 , wherein the computer executable instructions defining the step of determining a best apex-base plane candidate pair based on the generated joint context using a trained joint context detector comprise computer executable instructions defining the step of: determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector. 26. The computer readable medium of claim 25 , wherein the computer executable instructions defining the step of determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector comprise computer executable instructions defining the step of: selecting an apex-base plane candidate with a best probability score:
p=p j *( p a +p b )/2, where p j denotes the probability determined by the joint context detector, p a denotes the probability determined by the apex detector, and p b denotes the probability determined by the base plane detector. | 0.568182 |
10. The text display control method according to claim 8 , further comprising: changing, using an area size changing unit, a size of the text display area, wherein, each time the area size changing unit changes the size of the text display area, the newline insertion unit deletes a previously inserted newline character from the text displayed in the text display area, and wherein the processes performed by the text determination unit, the space selection unit, the partial text determination unit, the newline insertion unit, and the display control unit are performed again on the text from which the newline insertion unit has deleted the newline character. | 10. The text display control method according to claim 8 , further comprising: changing, using an area size changing unit, a size of the text display area, wherein, each time the area size changing unit changes the size of the text display area, the newline insertion unit deletes a previously inserted newline character from the text displayed in the text display area, and wherein the processes performed by the text determination unit, the space selection unit, the partial text determination unit, the newline insertion unit, and the display control unit are performed again on the text from which the newline insertion unit has deleted the newline character. 11. The text display control method according to claim 10 , further comprising: each time the area size changing unit changes the size of the text display area, associating, using a newline position storage unit, a new size of the text display area and a position at which the newline insertion unit has inserted a newline character into the text displayed in the text display area with each other and storing the new size and position, wherein, if the area size changing unit changes the size of the text display area and a position of a newline character corresponding to a new size of the text display area is stored in the newline position storage unit, the newline insertion unit inserts a newline character into the text displayed in the text display area at the position of a newline character corresponding to the new size of the text display area stored in the newline position storage unit. | 0.783496 |
1. A method comprising: receiving, at a server via web service communications from a client, client web service messages comprising data marked according to a markup language; wherein receiving the client web service messages comprises: receiving a first client web service message to request a connection to the server; receiving a second client web service message associated with the connection, wherein the second client web service message encapsulates an XQuery expression as data marked according to the markup language, wherein the XQuery expression conforms to an XQuery language; at the server, extracting the XQuery expression from the second client web service message; at the server, executing the XQuery expression against XML data; sending, from the server to the client via web service communications, a server web service message; wherein the server web service message contains a sequence of items; wherein the sequence of items contains at least part of results from execution of the XQuery expression; wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving, at a server via web service communications from a client, client web service messages comprising data marked according to a markup language; wherein receiving the client web service messages comprises: receiving a first client web service message to request a connection to the server; receiving a second client web service message associated with the connection, wherein the second client web service message encapsulates an XQuery expression as data marked according to the markup language, wherein the XQuery expression conforms to an XQuery language; at the server, extracting the XQuery expression from the second client web service message; at the server, executing the XQuery expression against XML data; sending, from the server to the client via web service communications, a server web service message; wherein the server web service message contains a sequence of items; wherein the sequence of items contains at least part of results from execution of the XQuery expression; wherein the method is performed by one or more computing devices. 10. The method of claim 1 , wherein the second client web service message specifies a maximum number of items to return as the at least part of the results from execution of the XQuery expression, the method further comprising: restricting the sequence of items in the server web service message to the maximum number of items. | 0.671795 |
1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request. | 1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request. 9. The computer-implemented method of claim 1 , wherein searching the one or more databases further includes: ranking the one or more products based at least in part upon weighted combinations of scores for each of the one or more products in the one or more databases. | 0.563248 |
1. A system comprising: a plurality of tags affixed to a plurality of objects, wherein the plurality of tags include a plurality of features such that each tag comprises at least one feature; a plurality of sensors, wherein a location of the plurality of sensors defines a spatial operating environment (SOE) that includes the plurality of objects, wherein the plurality of sensors detect the plurality of features; and an adaptive tracking component (ATC) running on a processor, wherein the ATC receives from each sensor of the plurality of sensors feature data corresponding to each object of the plurality of objects detected by the respective sensor, wherein the ATC generates and maintains a coherent model of relationships between the plurality of objects and the SOE by integrating the feature data from the plurality of sensors. | 1. A system comprising: a plurality of tags affixed to a plurality of objects, wherein the plurality of tags include a plurality of features such that each tag comprises at least one feature; a plurality of sensors, wherein a location of the plurality of sensors defines a spatial operating environment (SOE) that includes the plurality of objects, wherein the plurality of sensors detect the plurality of features; and an adaptive tracking component (ATC) running on a processor, wherein the ATC receives from each sensor of the plurality of sensors feature data corresponding to each object of the plurality of objects detected by the respective sensor, wherein the ATC generates and maintains a coherent model of relationships between the plurality of objects and the SOE by integrating the feature data from the plurality of sensors. 110. The system of claim 1 , wherein a tag comprises a linear-partial-tag (LPT) that includes a plurality of collinear markers. | 0.633306 |
1. A computer-implemented method performed by data processing apparatus, the method comprising: receiving a first query and a plurality of second queries; determining a temporal correlation score between the first query and each second query based on a comparison of a temporal series of occurrences of elements of the first query in a first corpus comprising a first document of a first document type and a temporal series of occurrences of elements of the second query in a second different textual corpus comprising a second document of a second document type that differs from the first document type, wherein the comparison is based on the first document and the second document having timestamps in a same time period; computing a similarity score for the first query and a second query, the similarity score between the first query and a second query being computed based on the temporal correlation score between the first document and the second document; and ranking the second query according to the similarity score. | 1. A computer-implemented method performed by data processing apparatus, the method comprising: receiving a first query and a plurality of second queries; determining a temporal correlation score between the first query and each second query based on a comparison of a temporal series of occurrences of elements of the first query in a first corpus comprising a first document of a first document type and a temporal series of occurrences of elements of the second query in a second different textual corpus comprising a second document of a second document type that differs from the first document type, wherein the comparison is based on the first document and the second document having timestamps in a same time period; computing a similarity score for the first query and a second query, the similarity score between the first query and a second query being computed based on the temporal correlation score between the first document and the second document; and ranking the second query according to the similarity score. 7. The method of claim 1 , wherein ranking the plurality of second queries in an order according to their respective similarity scores comprises determining a Boolean classification of each second query with respect to the first query indicative of a semantic relevance of the second query with respect to the first query. | 0.79633 |
1. A non-transitory computer readable medium for estimating a confidence level of a classification assignment, the non-transitory computer readable medium having instructions configured to cause a processor of a computer to: create a data model having a plurality of classes of records, the data model being based on a set of pre-classified records; assign one of said classes to a new record; obtain a qualitative confidence level for the assignment of said class; obtain a quantitative confidence level for the assignment of said class; and combine the qualitative confidence level and the quantitative confidence level, wherein the quantitative confidence level is obtained by finding a ratio of the probability of said class to a second most likely class, finding a ratio of a complement probability of said second most likely class to a complement probability of said class, and using matchfactors to generate a scaled ratio. | 1. A non-transitory computer readable medium for estimating a confidence level of a classification assignment, the non-transitory computer readable medium having instructions configured to cause a processor of a computer to: create a data model having a plurality of classes of records, the data model being based on a set of pre-classified records; assign one of said classes to a new record; obtain a qualitative confidence level for the assignment of said class; obtain a quantitative confidence level for the assignment of said class; and combine the qualitative confidence level and the quantitative confidence level, wherein the quantitative confidence level is obtained by finding a ratio of the probability of said class to a second most likely class, finding a ratio of a complement probability of said second most likely class to a complement probability of said class, and using matchfactors to generate a scaled ratio. 4. The non-transitory computer readable medium claimed in claim 1 wherein the non-transitory computer readable medium is configured to devise a list of important words for each of said plurality of classes, selecting a set of at least one condition evidentiary of said class, and determining if new record meets said set of at least one conditions. | 0.639136 |
11. A method according to claim 6 , wherein executing the first VM comprises executing a first instance of the first VM using a first programmable hardware component that is associated with a first hardware specification, said method further comprising: programming a second programmable hardware component that is associated with a second hardware specification based on the HDL description; and executing a second instance of the first VM using the second programmable hardware component. | 11. A method according to claim 6 , wherein executing the first VM comprises executing a first instance of the first VM using a first programmable hardware component that is associated with a first hardware specification, said method further comprising: programming a second programmable hardware component that is associated with a second hardware specification based on the HDL description; and executing a second instance of the first VM using the second programmable hardware component. 14. A method according to claim 11 , further comprising: executing a first instance of the software application using the first instance of the first VM; and executing a second instance of the software application using the second instance of the first VM, wherein the software application is certified to execute on the target hardware platform described by the HDL description. | 0.75921 |
2. The method of claim 1 , further including applying the transforms to convert the document from the source document version to the target document version. | 2. The method of claim 1 , further including applying the transforms to convert the document from the source document version to the target document version. 3. The method of claim 2 , wherein the target service identifier is a party/service/action triplet. | 0.932564 |
1. A computer implemented method in a data processing system for transforming source input data using a transformation macro, the computer implemented method comprising computer implemented steps of: executing, by the data processing system using the transformation macro, a transformation macro script; reading, by the data processing system using the transformation macro script, one or more transformation templates, wherein one or more input data source files are contained within the one or more transformation templates; reading, by the data processing system using the transformation macro script, the one or more input data source files contained within the one or more transformation templates; performing, by the data processing system using the transformation macro, logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files; determining, by the data processing system, whether constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid; responsive to a determination by the data processing system that the constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid, transforming, by the data processing system using the transformation macro, the one or more input data source files from a first file format into a second file format; and responsive to determining by the data processing system that transformation of the one or more input data source files from the first file format into the second file format is complete, outputting, by the data processing system, a transformation output. | 1. A computer implemented method in a data processing system for transforming source input data using a transformation macro, the computer implemented method comprising computer implemented steps of: executing, by the data processing system using the transformation macro, a transformation macro script; reading, by the data processing system using the transformation macro script, one or more transformation templates, wherein one or more input data source files are contained within the one or more transformation templates; reading, by the data processing system using the transformation macro script, the one or more input data source files contained within the one or more transformation templates; performing, by the data processing system using the transformation macro, logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files; determining, by the data processing system, whether constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid; responsive to a determination by the data processing system that the constraints generated by the logical processing of the transformation macro script and the one or more transformation templates that contain the one or more input data source files are valid, transforming, by the data processing system using the transformation macro, the one or more input data source files from a first file format into a second file format; and responsive to determining by the data processing system that transformation of the one or more input data source files from the first file format into the second file format is complete, outputting, by the data processing system, a transformation output. 6. The computer implemented method of claim 1 , wherein the first file format is a comma-separated values (CSV) file format and the second file format is a knowledgebase development environment (.kbs) file format. | 0.610256 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.