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8,418,057 | 14 | 18 |
14. A method for displaying text comprising the steps of: providing a text comprised of a plurality of paragraphs each having a plurality of sentences with each sentence having a plurality of words; arranging said text into a plurality of vertically centered and vertically aligned word clusters having a vertical cluster spacing between consecutive word clusters, each word cluster having a plurality of horizontally extending lines having a vertical line spacing between consecutive lines smaller than said vertical cluster spacing with each line having one or more words, and wherein each word cluster is formed of a thought group defined by a plurality of words linked by a commonality and constrained by an estimate of reader apprehension span, and wherein at least one word in the last line of at least one word cluster has a serif larger than a remainder of said words of said at least one word cluster; and displaying said plurality of word clusters on an electronic display medium.
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14. A method for displaying text comprising the steps of: providing a text comprised of a plurality of paragraphs each having a plurality of sentences with each sentence having a plurality of words; arranging said text into a plurality of vertically centered and vertically aligned word clusters having a vertical cluster spacing between consecutive word clusters, each word cluster having a plurality of horizontally extending lines having a vertical line spacing between consecutive lines smaller than said vertical cluster spacing with each line having one or more words, and wherein each word cluster is formed of a thought group defined by a plurality of words linked by a commonality and constrained by an estimate of reader apprehension span, and wherein at least one word in the last line of at least one word cluster has a serif larger than a remainder of said words of said at least one word cluster; and displaying said plurality of word clusters on an electronic display medium. 18. The method of claim 14 , wherein all of said words in a single the last line of said at least one word cluster have said larger serif.
| 0.802292 |
10,002,124 | 5 | 6 |
5. The method of claim 1 further comprising training the verb/type lookup resource using a type database resource and a corpus of information.
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5. The method of claim 1 further comprising training the verb/type lookup resource using a type database resource and a corpus of information. 6. The method of claim 5 , wherein training the verb/type lookup resource comprises, for each sentence in the corpus of information: annotating the sentence with a verb, a database entity, and a syntactic relation between the verb and the database entity; responsive to determining an entry for the verb and syntactic relation does not exist in the verb/type lookup resource, create an entry for the verb and syntactic relation with a class of the database entity and an integer count of one; and responsive to determining an entry for the verb and syntactic relation exists in the verb/type lookup resource, increment an integer count for a class of the database entity in the entry.
| 0.5 |
8,612,433 | 2 | 6 |
2. The system of claim 1 , further comprising: a personal network setting unit to set, as a personal network of the user, at least one of communities joined by the user, the at least one neighbor, and communities joined by the at least one neighbor.
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2. The system of claim 1 , further comprising: a personal network setting unit to set, as a personal network of the user, at least one of communities joined by the user, the at least one neighbor, and communities joined by the at least one neighbor. 6. The system of claim 2 , wherein the personal network extraction unit is configured to arrange the set personal network of the user based on at least one of an association with the search term and an association with the user, and to extract information corresponding to a neighbor or a community in a ranked personal network.
| 0.566138 |
7,885,815 | 1 | 10 |
1. A system for access to multimedia structures, the system comprising: telephone sets configured to connect to a telephone network; a storage device configured to store a plurality of multimedia structures representing at least one of messages, data and commands; a network access server that is associated with the telephone sets and is separate from the storage device and is comprises: a processor; and; memory storing at least one program that, when executed by the processor, causes the network access server to: receive a telephone call from one of the telephone sets; receive a number from the one telephone set after receiving the telephone call, wherein the number represents a remote hosting site in which the storage device is located; selectively instantiate the multimedia structures via an interconnection network by determining a network address of the remote hosting site using the received number; selectively instantiate the multimedia structures in a directory; download the multimedia structures contained in the directory; and instantiate a voice-recognition and speech-synthesis system that comprises modules for reading files in XML format, for associating these files with an XSL processing module, and for selectively mapping the XML files into the XSL processing module to obtain files in a format that is configured to be interpreted by the voice-recognition and speech-synthesis system.
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1. A system for access to multimedia structures, the system comprising: telephone sets configured to connect to a telephone network; a storage device configured to store a plurality of multimedia structures representing at least one of messages, data and commands; a network access server that is associated with the telephone sets and is separate from the storage device and is comprises: a processor; and; memory storing at least one program that, when executed by the processor, causes the network access server to: receive a telephone call from one of the telephone sets; receive a number from the one telephone set after receiving the telephone call, wherein the number represents a remote hosting site in which the storage device is located; selectively instantiate the multimedia structures via an interconnection network by determining a network address of the remote hosting site using the received number; selectively instantiate the multimedia structures in a directory; download the multimedia structures contained in the directory; and instantiate a voice-recognition and speech-synthesis system that comprises modules for reading files in XML format, for associating these files with an XSL processing module, and for selectively mapping the XML files into the XSL processing module to obtain files in a format that is configured to be interpreted by the voice-recognition and speech-synthesis system. 10. The system defined in claim 1 , further comprising: a development device connected to the interconnection network and configured to produce and store the multimedia structures on the storage device through the interconnection network.
| 0.788256 |
7,855,812 | 1 | 2 |
1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna.
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1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna. 2. The cellular phone of claim 1 , wherein the scanner data processing circuitry further includes circuitry configured with language translation capability to convert image data signals the text data representative to voice audio signals representative of the text data in spoken form, as spoken in a language different from the language of the text data.
| 0.726502 |
4,817,155 | 12 | 13 |
12. The apparatus of claim 9, comprising separate correlation detectors with separate outputs for the low-frequency portion of said speech signal and for the high-frequency portion of said speech signal.
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12. The apparatus of claim 9, comprising separate correlation detectors with separate outputs for the low-frequency portion of said speech signal and for the high-frequency portion of said speech signal. 13. The apparatus of claim 12, in which said synch pulse generating means are operatively connected to said low-frequency correlation detector but not said high-frequency correlation detector.
| 0.5 |
10,097,631 | 1 | 3 |
1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain.
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1. A method comprising: by one or more computing devices of a social-networking system, receiving a reference to a first document, wherein the first document: comprises a content item and a first interactive feature for user posts, wherein the first interactive feature is displayed as a conversation thread; is associated with an entity; and is provided from a first web domain; by the one or more computing devices, selecting a second document that corresponds to the first document, wherein the second document: shares a common content item with the first document; comprises a second interactive feature for user posts, wherein the second interactive feature is displayed as a conversation thread; is provided from a second web domain; and is associated with the entity; by the one or more computing devices, receiving a user post related to the content item, the user post being submitted in connection with the first or the second document; and by the one or more computing devices, updating the first interactive feature and the second interactive feature with the user post, wherein the updating comprises: synchronizing the first interactive feature and the second interactive feature at the same time; and automating a synchronization of a moderation of the user post in connection with both the first and the second documents based on a set of banned words or character strings, wherein automating the synchronization of the moderation comprises: filtering out one or more words of the user post in connection with the first document based on a first moderation rule of the first web domain; and filtering out one or more words of the user post in connection with the second document based on a second moderation rule of the second web domain. 3. The method of claim 1 , wherein the first or second document is located in: a web page associated with the social-networking system; or an application associated with the social-networking system.
| 0.817096 |
9,251,208 | 14 | 15 |
14. An article of manufacture comprising: at least one computer usable non-transitory device having computer readable program code logic tangibly embodied therein to execute instructions in one or more processing units for merging search results, said computer readable program code logic, when executing, performing the following: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results.
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14. An article of manufacture comprising: at least one computer usable non-transitory device having computer readable program code logic tangibly embodied therein to execute instructions in one or more processing units for merging search results, said computer readable program code logic, when executing, performing the following: identifying a query from a user; splitting the query into sub-queries; for each of the sub-queries, determining a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, executing said each sub-query to obtain a search result for said each sub-query, and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combining the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results. 15. The article of manufacture according to claim 14 , wherein: the execution of each of the sub-queries includes identifying a multitude of entities for the at least one of the sub-queries; and the combining includes grouping said multitude of entities into the plurality of clusters, and merging the clusters based on the relevance scores computed for the clusters.
| 0.805408 |
9,704,128 | 1 | 7 |
1. A computer-implemented method for synthesizing and analyzing user input in a collaborative work session, the method comprising: monitoring a plurality of inputs submitted by a group of users in the collaborative work session, wherein at least some of the plurality of inputs include natural language content; algorithmically analyzing the natural language content in real time in order to parse a plurality of ideas from the plurality of inputs; algorithmically identifying similarities among the plurality of ideas; clustering the plurality of ideas into a set of clusters based on the similarities; and presenting the clusters to the group of users during the collaborative work session, wherein the algorithmically analyzing, the algorithmically identifying, and the clustering are each performed at least in part using a processor, and wherein at least one user of the group of users is a synthetic participant that is independent from a moderator for the collaborative work session.
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1. A computer-implemented method for synthesizing and analyzing user input in a collaborative work session, the method comprising: monitoring a plurality of inputs submitted by a group of users in the collaborative work session, wherein at least some of the plurality of inputs include natural language content; algorithmically analyzing the natural language content in real time in order to parse a plurality of ideas from the plurality of inputs; algorithmically identifying similarities among the plurality of ideas; clustering the plurality of ideas into a set of clusters based on the similarities; and presenting the clusters to the group of users during the collaborative work session, wherein the algorithmically analyzing, the algorithmically identifying, and the clustering are each performed at least in part using a processor, and wherein at least one user of the group of users is a synthetic participant that is independent from a moderator for the collaborative work session. 7. The computer-implemented method of claim 1 , wherein the algorithmically identifying is performed using pattern recognition techniques.
| 0.658416 |
9,208,217 | 2 | 8 |
2. A computer-implemented method for providing query results in response to a user-submitted query, the method comprising: receiving from a user a user-submitted query; and analyzing a set of text-based files based on the user-submitted query, wherein the analysis of the set of text-based files includes using text mining techniques to: extract structured information from unstructured or semi-structured text, and present relationships between entities extracted from the unstructured or semi-structured text; and, before all of the text-based files in the set are analyzed, providing to the user partial results that identify a subset of results extracted using at least text mining techniques that satisfy the user-submitted query; wherein analyzing a set of text-based files based on the user-submitted query comprises analyzing query constraints against candidate documents within the set of text files in order to find hits that are written to two or more hit files, wherein each hit file also includes one or more waypoint indicators; and wherein, before all of the text-based files in the set are analyzed, providing to the user partial results that identify a subset of results comprises: reading the two or more hit files until a waypoint indicator in each of the two or more hit files is reached such that one or more hits is identified; and reformulating the identified one or more hits into the subset of results.
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2. A computer-implemented method for providing query results in response to a user-submitted query, the method comprising: receiving from a user a user-submitted query; and analyzing a set of text-based files based on the user-submitted query, wherein the analysis of the set of text-based files includes using text mining techniques to: extract structured information from unstructured or semi-structured text, and present relationships between entities extracted from the unstructured or semi-structured text; and, before all of the text-based files in the set are analyzed, providing to the user partial results that identify a subset of results extracted using at least text mining techniques that satisfy the user-submitted query; wherein analyzing a set of text-based files based on the user-submitted query comprises analyzing query constraints against candidate documents within the set of text files in order to find hits that are written to two or more hit files, wherein each hit file also includes one or more waypoint indicators; and wherein, before all of the text-based files in the set are analyzed, providing to the user partial results that identify a subset of results comprises: reading the two or more hit files until a waypoint indicator in each of the two or more hit files is reached such that one or more hits is identified; and reformulating the identified one or more hits into the subset of results. 8. The method of claim 2 wherein each hit is an instantiation of at least one query constraint.
| 0.895374 |
8,594,420 | 4 | 11 |
4. The apparatus of claim 3 , wherein the labeling each pixel further comprises the processor configured to: determine if each pixel in the image represents an edge; estimate distribution of edge density in a neighborhood of the each pixel in the image; and use the distribution to determine a descriptive type of each pixel and labeling each pixel accordingly.
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4. The apparatus of claim 3 , wherein the labeling each pixel further comprises the processor configured to: determine if each pixel in the image represents an edge; estimate distribution of edge density in a neighborhood of the each pixel in the image; and use the distribution to determine a descriptive type of each pixel and labeling each pixel accordingly. 11. The apparatus of claim 4 , wherein the smoothing is performed only on perceptually significant pixels.
| 0.853994 |
6,049,796 | 17 | 23 |
17. A personal digital assistant device comprising: a storage means having a data base for storing one or more records, each of the records comprising data elements defining an identifier of a party and communication information required for communicating with the party through an electronic communication link; a first user input means, said first user input means being operable by a user for inputting a search key corresponding to at least one of the data elements of at least one of said records; a search engine for comparing at least one of the data elements of at least one of the records to the search key; a display for displaying at least a portion of those ones of said records having at least one data element corresponding to the search key; a second user input means, said second user input means being operable by the user for selecting one of the records having at least one data element corresponding to the search key; and electronic communication means for initiating an electronic communication to the party identified by the identifier defined by data elements of the selected record, using one of a plurality of types of electronic communication.
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17. A personal digital assistant device comprising: a storage means having a data base for storing one or more records, each of the records comprising data elements defining an identifier of a party and communication information required for communicating with the party through an electronic communication link; a first user input means, said first user input means being operable by a user for inputting a search key corresponding to at least one of the data elements of at least one of said records; a search engine for comparing at least one of the data elements of at least one of the records to the search key; a display for displaying at least a portion of those ones of said records having at least one data element corresponding to the search key; a second user input means, said second user input means being operable by the user for selecting one of the records having at least one data element corresponding to the search key; and electronic communication means for initiating an electronic communication to the party identified by the identifier defined by data elements of the selected record, using one of a plurality of types of electronic communication. 23. The personal digital assistant device as in claim 17, wherein at least one of the first and second user input means is comprised of a voice recognition means.
| 0.712766 |
10,102,238 | 1 | 9 |
1. A method for incrementally updating a multi-user document index distributed over a plurality of index servers, the method performed by one or more computing devices, the method comprising: generating an index mutation comprising one or more tokens, wherein the index mutation is based at least in part on one or more identified differences between a new version of a document and a previous version of the document; appending the index mutation and an associated time-based value to a log; reading the time-based value associated with the index mutation from the log and comparing the associated time-based value to a time-based value associated with an index of the document, the index of the document stored at an index server of the plurality of index servers; wherein the time-based value associated with the index of the document stored at the index server represents a last-update time of the index of the document stored at the index server; based at least in part on the reading and the comparing, providing the one or more tokens of the index mutation read from the log to the index server at which the index of the document is stored; and wherein the providing the one or more tokens to the index server causes the index server to use the one or more tokens to update the index of the document stored at the index server.
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1. A method for incrementally updating a multi-user document index distributed over a plurality of index servers, the method performed by one or more computing devices, the method comprising: generating an index mutation comprising one or more tokens, wherein the index mutation is based at least in part on one or more identified differences between a new version of a document and a previous version of the document; appending the index mutation and an associated time-based value to a log; reading the time-based value associated with the index mutation from the log and comparing the associated time-based value to a time-based value associated with an index of the document, the index of the document stored at an index server of the plurality of index servers; wherein the time-based value associated with the index of the document stored at the index server represents a last-update time of the index of the document stored at the index server; based at least in part on the reading and the comparing, providing the one or more tokens of the index mutation read from the log to the index server at which the index of the document is stored; and wherein the providing the one or more tokens to the index server causes the index server to use the one or more tokens to update the index of the document stored at the index server. 9. The method of claim 1 , wherein the document belongs to a document namespace assigned to the index server; wherein the index mutation comprises an identifier of the document namespace; and wherein the providing the one or more tokens of the index mutation to the index server is based, at least in part, on the identifier of the document namespace of the index mutation.
| 0.746947 |
9,421,475 | 1 | 2 |
1. An interactive toy that performs a method for interacting with a user, the method comprising: activating a phrase-detection state in which said toy is configured to receive a first plurality of audible sounds corresponding to text read aloud from a book; receiving, through a microphone embedded in the toy, the first plurality of audible sounds; processing a signal associated with the first plurality of audible sounds to detect one or more triggering phrases, wherein the one or more triggering phrases are a combination of words corresponding to text from the book; detecting a triggering phrase was read aloud by the user reading the book; upon detecting the triggering phrase, switching to a term-detection state in which said toy is configured to receive a second plurality of audible sounds; receiving, through the microphone, the second plurality of audible sounds; processing a signal associated with the second plurality of audible sounds to detect one or more single triggering terms, wherein the one or more single triggering terms are predetermined words or commands; detecting the one or more single triggering terms spoken by the user; and upon detecting the triggering term, activating a response sequence that supplements a story told in the book, wherein the response sequence is determined from a pre-programmed response program.
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1. An interactive toy that performs a method for interacting with a user, the method comprising: activating a phrase-detection state in which said toy is configured to receive a first plurality of audible sounds corresponding to text read aloud from a book; receiving, through a microphone embedded in the toy, the first plurality of audible sounds; processing a signal associated with the first plurality of audible sounds to detect one or more triggering phrases, wherein the one or more triggering phrases are a combination of words corresponding to text from the book; detecting a triggering phrase was read aloud by the user reading the book; upon detecting the triggering phrase, switching to a term-detection state in which said toy is configured to receive a second plurality of audible sounds; receiving, through the microphone, the second plurality of audible sounds; processing a signal associated with the second plurality of audible sounds to detect one or more single triggering terms, wherein the one or more single triggering terms are predetermined words or commands; detecting the one or more single triggering terms spoken by the user; and upon detecting the triggering term, activating a response sequence that supplements a story told in the book, wherein the response sequence is determined from a pre-programmed response program. 2. The method of claim 1 , wherein triggering phrases include a plurality of non-triggering terms.
| 0.850153 |
8,015,131 | 9 | 10 |
9. A system for learning tradeoffs between discriminative power and invariance of classifiers, comprising: a processor and memory; two or more classifiers, each classifier for classifying input and having associated therewith a kernel with a corresponding kernel weight, the kernel specifying an attribute for its associated classifier; a tradeoff learning component configured to combine the two or more classifiers to produce a combined classifier by decreasing a function of the kernel weights, wherein each classifier is a support vector machine incorporating a first tradeoff between discriminative power and invariance, and the produced combined classifier incorporates a second tradeoff between discriminative power that is different from the first tradeoff between discriminative power; and a classifier component configured to receive an input and classifies the received input using the produced combined classifier.
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9. A system for learning tradeoffs between discriminative power and invariance of classifiers, comprising: a processor and memory; two or more classifiers, each classifier for classifying input and having associated therewith a kernel with a corresponding kernel weight, the kernel specifying an attribute for its associated classifier; a tradeoff learning component configured to combine the two or more classifiers to produce a combined classifier by decreasing a function of the kernel weights, wherein each classifier is a support vector machine incorporating a first tradeoff between discriminative power and invariance, and the produced combined classifier incorporates a second tradeoff between discriminative power that is different from the first tradeoff between discriminative power; and a classifier component configured to receive an input and classifies the received input using the produced combined classifier. 10. The system of claim 9 wherein the tradeoff learning component employs a dual formulation to produce the combined classifier.
| 0.687805 |
9,978,365 | 1 | 2 |
1. A method comprising: determining weights for attributes by ranking the attributes based on user interactions with a user terminal; storing the weights for the attributes in a memory of the user terminal; processing, on the user terminal after the storing, a voice input in a first analysis, wherein the first analysis includes identifying one of the attributes; identifying, as a result of the first analysis, one domain of a plurality of domains, wherein the identifying the one domain includes retrieving the stored weight for the identified attribute and identifying the one domain based on the identified attribute and the retrieved weight; processing, on the user terminal, the voice input in a second analysis using specialized information of the one domain, wherein each of the plurality of domains comprises different respective specialized information; and outputting as synthesized speech a response resulting from the second analysis.
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1. A method comprising: determining weights for attributes by ranking the attributes based on user interactions with a user terminal; storing the weights for the attributes in a memory of the user terminal; processing, on the user terminal after the storing, a voice input in a first analysis, wherein the first analysis includes identifying one of the attributes; identifying, as a result of the first analysis, one domain of a plurality of domains, wherein the identifying the one domain includes retrieving the stored weight for the identified attribute and identifying the one domain based on the identified attribute and the retrieved weight; processing, on the user terminal, the voice input in a second analysis using specialized information of the one domain, wherein each of the plurality of domains comprises different respective specialized information; and outputting as synthesized speech a response resulting from the second analysis. 2. The method of claim 1 , further comprising receiving in the voice input a predefined name; and identifying speech in the voice input that immediately follows the predefined name as a query, wherein the first analysis identifies the one of the attributes in the query.
| 0.716981 |
9,501,720 | 3 | 7 |
3. An object detection apparatus comprising: a storage storing, for each of a plurality of part areas forming an area in an input image that is subject to image recognition processing and is referred to as a subject area, image recognition dictionaries that are used to recognize a target object to be detected in the input image and are typed according to variations in appearance of a part of the target object to be detected in the part area; a part score calculator configured to calculate, for each of the part areas forming the subject area cut from the input image, a part score indicative of a degree of similarity between the part area and each of at least some of the image recognition dictionaries stored in the storage; an integrated score calculator configured to calculate an integrated score by selecting, for each of the part areas forming the subject area, one of the scores calculated in the part score calculator and then calculating a weighted sum of the selected part scores for the respective part areas of the subject area; and a determiner configured to determine, on the basis of the integrated score calculated in the integrated score calculator, whether or not the target object is present in the subject area; wherein the integrated score calculator comprises: a candidate score extractor configured to extract, for each of the part areas forming the subject area, scores equal to or greater than a predetermined threshold as candidate scores from the part scores of the part area, and determine the image recognition dictionaries used to calculate the candidate scores for the part area; a temporary integrated score calculator configured to calculate a weighted sum of the candidate part scores for each of combinations of the image recognition dictionaries determined by the candidate score extractor for the respective part areas forming the subject area; and an integrated score selector configured to select, as the integrated score, a maximum of the temporary integrated scores calculated by the temporary integrated score calculator.
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3. An object detection apparatus comprising: a storage storing, for each of a plurality of part areas forming an area in an input image that is subject to image recognition processing and is referred to as a subject area, image recognition dictionaries that are used to recognize a target object to be detected in the input image and are typed according to variations in appearance of a part of the target object to be detected in the part area; a part score calculator configured to calculate, for each of the part areas forming the subject area cut from the input image, a part score indicative of a degree of similarity between the part area and each of at least some of the image recognition dictionaries stored in the storage; an integrated score calculator configured to calculate an integrated score by selecting, for each of the part areas forming the subject area, one of the scores calculated in the part score calculator and then calculating a weighted sum of the selected part scores for the respective part areas of the subject area; and a determiner configured to determine, on the basis of the integrated score calculated in the integrated score calculator, whether or not the target object is present in the subject area; wherein the integrated score calculator comprises: a candidate score extractor configured to extract, for each of the part areas forming the subject area, scores equal to or greater than a predetermined threshold as candidate scores from the part scores of the part area, and determine the image recognition dictionaries used to calculate the candidate scores for the part area; a temporary integrated score calculator configured to calculate a weighted sum of the candidate part scores for each of combinations of the image recognition dictionaries determined by the candidate score extractor for the respective part areas forming the subject area; and an integrated score selector configured to select, as the integrated score, a maximum of the temporary integrated scores calculated by the temporary integrated score calculator. 7. The apparatus of claim 3 , further comprising: an estimator configured to estimate at least one of a scene of the input image and a state of the target object on the basis of the combination of the image recognition dictionaries used to calculate the integrated score.
| 0.734314 |
8,694,959 | 6 | 12 |
6. A system, comprising: a memory that stores at least one computer-executable component; and a processor, communicatively coupled to the memory, that facilitates execution of the at least one computer-executable component, the at least one computer-executable component, comprising: an interface component configured to receive first data from a first programming language and second data from a second programming language, wherein at least one of the first programming language or the second programming language is a graphical programming language; and an editor component configured to: assess an applicability of the first programming language with regard to programming the industrial controller in accord with a programming language standard utilized in programming industrial controllers; assess an applicability of the second programming language with regard to programming the industrial controller in accord with the programming language standard; and combine at least a portion of the first programming language with at least a portion of the second programming language to facilitate creation of a third programming language, wherein the first programming language, the second programming language and the third programming language are disparate and the third programming language is utilized to program the industrial controller in accord with the programming language standard.
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6. A system, comprising: a memory that stores at least one computer-executable component; and a processor, communicatively coupled to the memory, that facilitates execution of the at least one computer-executable component, the at least one computer-executable component, comprising: an interface component configured to receive first data from a first programming language and second data from a second programming language, wherein at least one of the first programming language or the second programming language is a graphical programming language; and an editor component configured to: assess an applicability of the first programming language with regard to programming the industrial controller in accord with a programming language standard utilized in programming industrial controllers; assess an applicability of the second programming language with regard to programming the industrial controller in accord with the programming language standard; and combine at least a portion of the first programming language with at least a portion of the second programming language to facilitate creation of a third programming language, wherein the first programming language, the second programming language and the third programming language are disparate and the third programming language is utilized to program the industrial controller in accord with the programming language standard. 12. The system of claim 6 , wherein the editor component comprises a stencil editor component configured to create at least one of a stencil, or a shape associated with a stencil, as a function of the third programming language being created.
| 0.680739 |
9,600,403 | 12 | 13 |
12. The computerized apparatus of claim 11 : wherein said defining the one or more tags comprises defining a meta tag, wherein possession of the meta tag is dependent on possessions of tags; wherein said processor is further adapted to perform: applying queries corresponding to the meta tag on the set of test cases to determine possession of the meta tag.
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12. The computerized apparatus of claim 11 : wherein said defining the one or more tags comprises defining a meta tag, wherein possession of the meta tag is dependent on possessions of tags; wherein said processor is further adapted to perform: applying queries corresponding to the meta tag on the set of test cases to determine possession of the meta tag. 13. The computerized apparatus of claim 12 , wherein the functional model comprising a hierarchical functional attribute corresponding to the meta tag, wherein a value of the hierarchal functional attribute in a coverage task comprises an identifier of one or more tags which caused the test case to possess the meta tag.
| 0.5 |
8,943,042 | 14 | 16 |
14. A system comprising: one or more processors; and a computer program product tangibly embodied in a computer-readable storage medium and comprising instructions that when executed by a processor perform a method for analyzing and representing interpersonal relations, the method comprising: receiving, by a computer server system and as having been sent from a client device, a request for information that specifies relationships of a first person, wherein the request includes: (i) information that identifies the first person, and (ii) information that indicates a user-specified number of relationship separations extending from the first person from which other persons are to be identified; automatically creating, by the computer server system and in response to receiving the request, a single database query that: (i) when executed, causes a database system to identify a particular group of persons in a relational database that are related to the first person due to the particular group of persons being within the user-specified number of relationship separations from the first person, and (ii) is structured to cause the database system to identify the particular group of persons by: (a) identifying a first group of persons in the relational database to include in the particular group of persons, the identifying of the first group of persons including an identification of persons who are directly related, through a single relationship type from among multiple relationship types, to the first person, and (b) identifying additional persons in the relational database to add to the particular group of persons by performing, for each relationship separation in the user-specified number of relationship separations that extend from the identified first group of persons, a database left join operation that joins a respective additional group of persons in the relational database who are directly related, through the single relationship type, to any person in a previously joined group of persons until the number of relationship separations extending from the first person, through the single relationship type, is determined to satisfy the user-specified number of relationship separations indicated in the request, wherein performing a first of the database left join operations comprises identifying a first additional group of multiple persons to add to the particular group of persons, wherein the first additional group of multiple persons are identified for addition to the particular group of persons based on the first additional group of multiple persons being directly related to the persons in the first group of persons and also being indirectly related to the first person; providing, by the computer server system and to the database system in response to receiving the request, the single database query for execution by the database system, and in response, receiving results obtained by the database system from execution of the single database query, wherein the results specify the particular group of persons, wherein the database system is configured to execute the single database query in-memory; generating, by the computer server system and based on the results obtained by the database system, the information that specifies the relationships of the first person; and providing, by the computer server system and to the client device in response to receiving the request, the information that specifies the relationships of the first person for display.
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14. A system comprising: one or more processors; and a computer program product tangibly embodied in a computer-readable storage medium and comprising instructions that when executed by a processor perform a method for analyzing and representing interpersonal relations, the method comprising: receiving, by a computer server system and as having been sent from a client device, a request for information that specifies relationships of a first person, wherein the request includes: (i) information that identifies the first person, and (ii) information that indicates a user-specified number of relationship separations extending from the first person from which other persons are to be identified; automatically creating, by the computer server system and in response to receiving the request, a single database query that: (i) when executed, causes a database system to identify a particular group of persons in a relational database that are related to the first person due to the particular group of persons being within the user-specified number of relationship separations from the first person, and (ii) is structured to cause the database system to identify the particular group of persons by: (a) identifying a first group of persons in the relational database to include in the particular group of persons, the identifying of the first group of persons including an identification of persons who are directly related, through a single relationship type from among multiple relationship types, to the first person, and (b) identifying additional persons in the relational database to add to the particular group of persons by performing, for each relationship separation in the user-specified number of relationship separations that extend from the identified first group of persons, a database left join operation that joins a respective additional group of persons in the relational database who are directly related, through the single relationship type, to any person in a previously joined group of persons until the number of relationship separations extending from the first person, through the single relationship type, is determined to satisfy the user-specified number of relationship separations indicated in the request, wherein performing a first of the database left join operations comprises identifying a first additional group of multiple persons to add to the particular group of persons, wherein the first additional group of multiple persons are identified for addition to the particular group of persons based on the first additional group of multiple persons being directly related to the persons in the first group of persons and also being indirectly related to the first person; providing, by the computer server system and to the database system in response to receiving the request, the single database query for execution by the database system, and in response, receiving results obtained by the database system from execution of the single database query, wherein the results specify the particular group of persons, wherein the database system is configured to execute the single database query in-memory; generating, by the computer server system and based on the results obtained by the database system, the information that specifies the relationships of the first person; and providing, by the computer server system and to the client device in response to receiving the request, the information that specifies the relationships of the first person for display. 16. The system of claim 14 , wherein the request further includes information that identifies a second person in the relational database, and wherein the single database query is further structured to identify only those persons in the relational database who are related to the first person through a relationship with the second person within the user-specified number of relationship separations.
| 0.731494 |
8,335,687 | 10 | 15 |
10. 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: receiving, by a speech recognition model training system and from a client device, a request to generate a new speech recognition model for the client device, wherein the request includes: (i) one or more features extracted from speech data by a feature extractor on the client device, and (ii) metadata regarding the speech recognition model to be generated; generating, by the speech recognition model training system and using the one or more features extracted from speech data by the feature extractor on the client device, the new speech recognition model according to the metadata; and transmitting, by the speech recognition model training system and to the client device, at least a portion of the new speech recognition model.
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10. 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: receiving, by a speech recognition model training system and from a client device, a request to generate a new speech recognition model for the client device, wherein the request includes: (i) one or more features extracted from speech data by a feature extractor on the client device, and (ii) metadata regarding the speech recognition model to be generated; generating, by the speech recognition model training system and using the one or more features extracted from speech data by the feature extractor on the client device, the new speech recognition model according to the metadata; and transmitting, by the speech recognition model training system and to the client device, at least a portion of the new speech recognition model. 15. The system of claim 10 , wherein the metadata identifies an existing speech recognition model to be updated.
| 0.819355 |
8,452,596 | 9 | 10 |
9. A speaker selecting method to be executed by a computer comprising: storing a plurality of speaker models in advance; calculating a feature value from received voice signals; calculating a first likelihood and a second likelihood based on the voice signals of two relatively different time lengths, for each of the plurality of speaker models stored with respect to the calculated feature value and selecting speakers using the calculated likelihood, the method comprising: selecting speakers corresponding to a predetermined speaker models the first likelihood of which is high; narrowing speakers selected as the speakers corresponding to the predetermined number of speaker models the first likelihood of which is high, down to speaker models the number of which is smaller than the predetermined number and the second likelihood of which is high; and sequentially outputting information corresponding to speakers narrowed down to the speaker models the number of which is smaller than the predetermined number and the second likelihood of which is high.
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9. A speaker selecting method to be executed by a computer comprising: storing a plurality of speaker models in advance; calculating a feature value from received voice signals; calculating a first likelihood and a second likelihood based on the voice signals of two relatively different time lengths, for each of the plurality of speaker models stored with respect to the calculated feature value and selecting speakers using the calculated likelihood, the method comprising: selecting speakers corresponding to a predetermined speaker models the first likelihood of which is high; narrowing speakers selected as the speakers corresponding to the predetermined number of speaker models the first likelihood of which is high, down to speaker models the number of which is smaller than the predetermined number and the second likelihood of which is high; and sequentially outputting information corresponding to speakers narrowed down to the speaker models the number of which is smaller than the predetermined number and the second likelihood of which is high. 10. The speaker selecting method according to claim 9 , wherein in calculating the first likelihood and the second likelihood, a long-time likelihood based on a voice signal of a relatively long time is calculated as the first likelihood, and a short-time likelihood based on a voice signal of a relatively short time is calculated as the second likelihood, in selecting the speakers corresponding to the predetermined number of speaker models the first likelihood of which is high, speakers corresponding to a predetermined number of speaker models the long-time likelihood of which is high are selected, and in narrowing down to the speaker models the second likelihood of which is high, speakers the number of which is smaller than the predetermined number and the short-time likelihood of which is high are selected.
| 0.518779 |
9,131,045 | 31 | 34 |
31. A system for providing captioned services to an assisted user communicating with a hearing person, the system comprising: a relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a captioned device processor; a visual display in communication with the captioned device processor; a microphone; a speaker; an activator in communication with the caption device processor, the activator selectable by an assisted user to indicate that a captioned service should be invoked; the captioned device enabling a user to use the device to facilitate communications via the first communication link between the user and the hearing person and configured to perform the steps of: (i) receiving words spoken by the hearing person on the first communication link during a voice conversation between the assisted user and the hearing person and broadcasting the hearing person's words via the speaker upon reception; (ii) while receiving words spoken by a hearing person on the first communication link, receiving an indication via the activator on the captioned device that a captioning service should be invoked; (iii) upon receiving the indication that a captioning service should be invoked, providing the words spoken by the hearing person over the second communication link to the relay so that the relay can convert the words spoken by the hearing person into text; (iv) receiving text corresponding to the converted words transmitted from the relay; and (v) displaying the received text on a display within sight of the assisted user; the relay configured to perform the steps of: (i) generating a text message stream corresponding to the words spoken by the hearing person; (ii) displaying the text message stream on the relay display screen; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device.
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31. A system for providing captioned services to an assisted user communicating with a hearing person, the system comprising: a relay including a relay computer, a relay input device and a relay display screen; a captioned device that is linkable to at least first and second communication links, the captioned device comprising: a captioned device processor; a visual display in communication with the captioned device processor; a microphone; a speaker; an activator in communication with the caption device processor, the activator selectable by an assisted user to indicate that a captioned service should be invoked; the captioned device enabling a user to use the device to facilitate communications via the first communication link between the user and the hearing person and configured to perform the steps of: (i) receiving words spoken by the hearing person on the first communication link during a voice conversation between the assisted user and the hearing person and broadcasting the hearing person's words via the speaker upon reception; (ii) while receiving words spoken by a hearing person on the first communication link, receiving an indication via the activator on the captioned device that a captioning service should be invoked; (iii) upon receiving the indication that a captioning service should be invoked, providing the words spoken by the hearing person over the second communication link to the relay so that the relay can convert the words spoken by the hearing person into text; (iv) receiving text corresponding to the converted words transmitted from the relay; and (v) displaying the received text on a display within sight of the assisted user; the relay configured to perform the steps of: (i) generating a text message stream corresponding to the words spoken by the hearing person; (ii) displaying the text message stream on the relay display screen; (iii) receiving corrections to the text message stream entered by a call assistant using the relay input device to generate corrected text; and (iv) transmitting the corrected text to the captioned device. 34. The system of claim 31 wherein the captioned device is further programmed to perform the step of, upon receiving the indication that a captioning service should be invoked, initiating a connection over the second communication link.
| 0.765408 |
7,558,733 | 8 | 11 |
8. The system of claim 1 , wherein said dialog delivery system includes a dialog analysis processor.
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8. The system of claim 1 , wherein said dialog delivery system includes a dialog analysis processor. 11. The system of claim 8 , wherein said dialog analysis processor provides a tree representation of said dialog identifying paths and logic associated with decisions within the tree.
| 0.5 |
9,137,577 | 1 | 23 |
1. A method, in a television system, for responding to user selection of an object in television programming, the method comprising: determining, by the television system, an identity of a user-selected object in a television program being presented by receiving the identity of the user-selected object from a remote server, in response to the user-selected object being selected by a television controller by selection of a location of the user-selected object on a television screen of the television system, and the user-selected object corresponds to a person; determining, based at least in part on the determined identity, one or more actions to perform related to the user-selected object within the television program, the determined one or more actions comprise starting a two-way video conference communication, using a display of the television controller, between the user and the person, the person being remote from the television system; and performing, the determined one or more actions.
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1. A method, in a television system, for responding to user selection of an object in television programming, the method comprising: determining, by the television system, an identity of a user-selected object in a television program being presented by receiving the identity of the user-selected object from a remote server, in response to the user-selected object being selected by a television controller by selection of a location of the user-selected object on a television screen of the television system, and the user-selected object corresponds to a person; determining, based at least in part on the determined identity, one or more actions to perform related to the user-selected object within the television program, the determined one or more actions comprise starting a two-way video conference communication, using a display of the television controller, between the user and the person, the person being remote from the television system; and performing, the determined one or more actions. 23. The method of claim 1 , wherein the two way video conference communication further uses a television screen.
| 0.8 |
9,167,274 | 16 | 17 |
16. A system for decoding encoded video content, comprising: at least one memory that stores computer executable components; and at least one processor that executes the following computer executable components stored in the at least one memory: a far-end decoder component configured to decode the encoded video content received from a near-end encoder component; and a far-end dictionary management component configured to identify one or more dictionaries that the far-end decoder component has in common with the near-end encoder component to synchronize common dictionaries between the far-end decoder component and the near-end encoder component, based at least in part on respective unique identifiers associated with respective dictionaries, to facilitate the decoding of the encoded video content, wherein the one or more dictionaries are sparse coding dictionaries, wherein the far-end dictionary management component is further configured to generate a unique identifier, of the respective unique identifiers, wherein the unique identifier is configured to contain a first tier comprising respective terminal addresses of a near-end terminal associated with the near-end encoder component and a far-end terminal associated with the far-end decoder component, and a second tier comprising a dictionary sub-identifier assigned to a dictionary associated with the unique identifier, to facilitate distinguishing the dictionary from other dictionaries associated with the near-end terminal and the far-end terminal.
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16. A system for decoding encoded video content, comprising: at least one memory that stores computer executable components; and at least one processor that executes the following computer executable components stored in the at least one memory: a far-end decoder component configured to decode the encoded video content received from a near-end encoder component; and a far-end dictionary management component configured to identify one or more dictionaries that the far-end decoder component has in common with the near-end encoder component to synchronize common dictionaries between the far-end decoder component and the near-end encoder component, based at least in part on respective unique identifiers associated with respective dictionaries, to facilitate the decoding of the encoded video content, wherein the one or more dictionaries are sparse coding dictionaries, wherein the far-end dictionary management component is further configured to generate a unique identifier, of the respective unique identifiers, wherein the unique identifier is configured to contain a first tier comprising respective terminal addresses of a near-end terminal associated with the near-end encoder component and a far-end terminal associated with the far-end decoder component, and a second tier comprising a dictionary sub-identifier assigned to a dictionary associated with the unique identifier, to facilitate distinguishing the dictionary from other dictionaries associated with the near-end terminal and the far-end terminal. 17. The system of claim 16 , wherein the far-end dictionary management component is further configured to receive from the near-end encoder component a first subset of unique identifiers associated with a first subset of dictionaries maintained by the near-end encoder component, and transmit to the near-end encoder component a second subset of unique identifiers associated with a second subset of dictionaries maintained by the far-end decoder component, to facilitate the synchronization of the common dictionaries.
| 0.522099 |
8,732,595 | 16 | 17 |
16. A condition editor in accordance with claim 15 , wherein the parser module is further adapted to check the syntax, compile the file extension, and check the type of each condition object.
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16. A condition editor in accordance with claim 15 , wherein the parser module is further adapted to check the syntax, compile the file extension, and check the type of each condition object. 17. A condition editor in accordance with claim 16 , further comprising a persistence mechanism to store each condition object on a relational database.
| 0.5 |
5,586,319 | 8 | 9 |
8. The method of claim 6 wherein said plurality of user commands includes a disconnect command that disconnects all signal nets connected to a specified instance connector of an instance.
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8. The method of claim 6 wherein said plurality of user commands includes a disconnect command that disconnects all signal nets connected to a specified instance connector of an instance. 9. The method of claim 8 wherein the disconnect command has as parameters an instance name and an instance connector name.
| 0.5 |
9,049,222 | 1 | 7 |
1. A method of preventing an e-mail from infecting a computing device, the method comprising: viewing the e-mail in a browser on the computing device; creating a document object model (DOM) tree from the e-mail, wherein the DOM tree contains known and unknown elements and wherein known elements are known to be safe and wherein unknown elements potentially include malicious Javascripts and HTML elements wherein the DOM tree includes a plurality of branches, the plurality of branches including at least one branch having only known elements; applying a first filter to the DOM tree, the first filter excluding the at least one branch in the DOM tree having only known elements, thereby creating a modified DOM tree wherein the excluding of the at least one branch from the DOM tree is performed such that remaining branches of the DOM tree are still connected with one another; filtering the modified DOM tree using a script analyzer filter wherein the script analyzer filter intercepts unknown elements in the modified DOM tree; and emulating execution of the unknown elements in the modified DOM tree to determine which unknown elements are malicious.
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1. A method of preventing an e-mail from infecting a computing device, the method comprising: viewing the e-mail in a browser on the computing device; creating a document object model (DOM) tree from the e-mail, wherein the DOM tree contains known and unknown elements and wherein known elements are known to be safe and wherein unknown elements potentially include malicious Javascripts and HTML elements wherein the DOM tree includes a plurality of branches, the plurality of branches including at least one branch having only known elements; applying a first filter to the DOM tree, the first filter excluding the at least one branch in the DOM tree having only known elements, thereby creating a modified DOM tree wherein the excluding of the at least one branch from the DOM tree is performed such that remaining branches of the DOM tree are still connected with one another; filtering the modified DOM tree using a script analyzer filter wherein the script analyzer filter intercepts unknown elements in the modified DOM tree; and emulating execution of the unknown elements in the modified DOM tree to determine which unknown elements are malicious. 7. A method as recited in claim 1 wherein branches having abnormal or unknown elements and scripts remain in the DOM tree.
| 0.924318 |
10,083,227 | 4 | 5 |
4. The computer system of claim 1 , wherein the determining comprises, for a given database table of the plural available database tables: checking whether, according to a data definition of the given database table in the description information, any field text of fields of the given database table in the description information contains the at least a portion of the search area string.
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4. The computer system of claim 1 , wherein the determining comprises, for a given database table of the plural available database tables: checking whether, according to a data definition of the given database table in the description information, any field text of fields of the given database table in the description information contains the at least a portion of the search area string. 5. The computer system of claim 4 , wherein the data definition of the given database table indicates names and data formats of the fields, respectively, of the given database table.
| 0.5 |
8,769,397 | 5 | 6 |
5. The method of claim 1 , further comprising: parsing the snippet to generate a Document Object Model (DOM) tree and a parsed Javascript expression tree; determining a target portion in the snippet based, at least in part, on the editing rules and the DOM tree and the parsed Javascript expression tree; and modifying the target portion in accordance with the editing rules.
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5. The method of claim 1 , further comprising: parsing the snippet to generate a Document Object Model (DOM) tree and a parsed Javascript expression tree; determining a target portion in the snippet based, at least in part, on the editing rules and the DOM tree and the parsed Javascript expression tree; and modifying the target portion in accordance with the editing rules. 6. The method of claim 5 , wherein the target portion is determined based, at least in part, on one of a path, an address or a definition in a hierarchy.
| 0.5 |
9,009,292 | 11 | 12 |
11. The method of claim 1 , wherein the executing step further comprises packaging the dataset with metadata describing data contained within the dataset.
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11. The method of claim 1 , wherein the executing step further comprises packaging the dataset with metadata describing data contained within the dataset. 12. The method of claim 11 , wherein the executing step further comprises packaging, by the application, the dataset with metadata that assists with display of data contained within the dataset.
| 0.5 |
8,250,529 | 12 | 20 |
12. A non-transitory computer readable medium including executable instructions to generate procedural language code for extracting data from an operational system, comprising executable instructions to: accept a declarative specification; and generate procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification.
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12. A non-transitory computer readable medium including executable instructions to generate procedural language code for extracting data from an operational system, comprising executable instructions to: accept a declarative specification; and generate procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification. 20. The computer readable medium of claim 12 including executable instructions to: integrate an IDOC intermediate document with relational tables; and generate ABAP code to extract data from integrated intermediate documents and relational tables.
| 0.674142 |
9,134,816 | 1 | 6 |
1. A method for analyzing a virtual face, comprising: providing a virtual face of a body on a screen associated with a communication device having a cursor; dragging a facial component of the virtual face with the cursor from a first position to a second position to change the virtual face from having a first expression to a second expression, the second expression being different from the first expression; providing a measurement device for determining coordinates of facial components of expressions of feelings; the measurement device determining a direction, speed and acceleration of the facial component on the virtual face; determining physiological data of the body, the physiological data consisting essentially of skin temperature, skin conductivity, brain frequency and pupil size; the communication device matching the coordinates and measured data of the facial component and physiological data with expression coordinates and data of facial components and physiological data stored in a database, the expression coordinates representing previously stored expression of feelings displayed by the virtual face; associating a written or oral description with the identified facial expression coordinates.
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1. A method for analyzing a virtual face, comprising: providing a virtual face of a body on a screen associated with a communication device having a cursor; dragging a facial component of the virtual face with the cursor from a first position to a second position to change the virtual face from having a first expression to a second expression, the second expression being different from the first expression; providing a measurement device for determining coordinates of facial components of expressions of feelings; the measurement device determining a direction, speed and acceleration of the facial component on the virtual face; determining physiological data of the body, the physiological data consisting essentially of skin temperature, skin conductivity, brain frequency and pupil size; the communication device matching the coordinates and measured data of the facial component and physiological data with expression coordinates and data of facial components and physiological data stored in a database, the expression coordinates representing previously stored expression of feelings displayed by the virtual face; associating a written or oral description with the identified facial expression coordinates. 6. The method according to claim 1 wherein the method further comprises the steps of training a user to identify facial expression.
| 0.766904 |
9,633,004 | 39 | 55 |
39. A non-transitory computer-readable storage medium comprising computer-executable instructions for: receiving an audio input comprising user speech; converting the user speech of the audio input into a textual representation of the user speech; determining a primary user intent for the textual representation; identifying a first type of concept referred to by the primary user intent; identifying a first substring from the textual representation corresponding to the first type of concept; determining a secondary user intent for the first substring; and performing a task flow comprising one or more tasks based at least in part on the primary user intent for the textual representation and the secondary user intent for the first substring.
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39. A non-transitory computer-readable storage medium comprising computer-executable instructions for: receiving an audio input comprising user speech; converting the user speech of the audio input into a textual representation of the user speech; determining a primary user intent for the textual representation; identifying a first type of concept referred to by the primary user intent; identifying a first substring from the textual representation corresponding to the first type of concept; determining a secondary user intent for the first substring; and performing a task flow comprising one or more tasks based at least in part on the primary user intent for the textual representation and the secondary user intent for the first substring. 55. The computer-readable storage medium of claim 39 , wherein performing the task flow comprises: identifying a primary task flow to accomplish the primary user intent; identifying one or more constraints associated with the primary task flow; identifying one or more queries, programs, computer-readable storage mediums, services, or APIs that satisfy the one or more constraints associated with the primary task flow; and generating the task flow from the primary task flow and the identified one or more queries, programs, methods, services, or APIs.
| 0.5 |
10,133,827 | 18 | 20 |
18. The computer of claim 16 wherein the first plurality of software instructions comprise a plurality of scalar assignments and a plurality of scalar expressions, wherein each scalar assignment writes one of a plurality of variables, wherein each scalar expression reads at least one of the plurality of variables, wherein the detecting comprises identify the plurality of scalar assignments and the plurality of scalar expressions, wherein the generating comprises: generate a vector element assignment for each scalar assignment, and generate a vector element expression for each scalar expression.
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18. The computer of claim 16 wherein the first plurality of software instructions comprise a plurality of scalar assignments and a plurality of scalar expressions, wherein each scalar assignment writes one of a plurality of variables, wherein each scalar expression reads at least one of the plurality of variables, wherein the detecting comprises identify the plurality of scalar assignments and the plurality of scalar expressions, wherein the generating comprises: generate a vector element assignment for each scalar assignment, and generate a vector element expression for each scalar expression. 20. The computer of claim 18 wherein the generating a vector element assignment comprises generate an element assignment of a vector, wherein a size of the vector is based on a cache line size of a CPU.
| 0.623134 |
9,224,384 | 6 | 7 |
6. A method for acoustic signal processing comprising: receiving acoustic features obtained from an input analog signal representing an incoming voice signal; pruning one or more Hidden Markov Model (HMM) states based on one or more current HMM pruning thresholds to generate one or more active HMM states; pre-pruning the one or more active HMM states based on an adjustable pre-pruning threshold to generate active HMM states output of the pre-pruning unit, wherein the adjustable pre-pruning threshold is based on one or more prior pruning thresholds, and wherein the active HMM states output of the pre-pruning unit each indicate a phoneme of the incoming voice signal and are each associated with a HMM state score; calculating the adjustable pre-pruning threshold based on an HMM state score from a previous frame of data and a senone score, wherein the pre-pruning follows the pruning for a current frame the incoming voice signal and precedes the pruning for a next frame; transferring the phonemes and their associated HMM state scores to a further speech recognition stage; and generating recognized speech corresponding to the incoming voice signal at the further speech recognition stage.
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6. A method for acoustic signal processing comprising: receiving acoustic features obtained from an input analog signal representing an incoming voice signal; pruning one or more Hidden Markov Model (HMM) states based on one or more current HMM pruning thresholds to generate one or more active HMM states; pre-pruning the one or more active HMM states based on an adjustable pre-pruning threshold to generate active HMM states output of the pre-pruning unit, wherein the adjustable pre-pruning threshold is based on one or more prior pruning thresholds, and wherein the active HMM states output of the pre-pruning unit each indicate a phoneme of the incoming voice signal and are each associated with a HMM state score; calculating the adjustable pre-pruning threshold based on an HMM state score from a previous frame of data and a senone score, wherein the pre-pruning follows the pruning for a current frame the incoming voice signal and precedes the pruning for a next frame; transferring the phonemes and their associated HMM state scores to a further speech recognition stage; and generating recognized speech corresponding to the incoming voice signal at the further speech recognition stage. 7. The method according to claim 6 , wherein the HMM state score comprises a best HMM state score from the previous frame of data.
| 0.608434 |
8,335,719 | 3 | 27 |
3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword.
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3. A method in a computing device for automatically identifying keywords for advertisement placement, the method comprising: extracting one or more keywords from a data feed, the data feed providing information about one or more content data; for each extracted keyword, identifying, facilitated by a computer processor, a category of products to advertise with the extracted keyword from among a plurality of categories of products, the products being related to the keyword but the category being independent of a subject of the keyword, the identification based at least in part on (1) an expected benefit of advertising in a first of the plurality of categories of products and (2) at least one attribute of text contained in at least one product of a second of the plurality of categories of products, the identification including selecting from among the first and the second of the plurality of categories of products based at least in part on scores determined for the expected benefit and the text, the scores normalized to facilitate comparison; generating a link for a landing page for the extracted keyword, the landing page for displaying search results of a query of the identified category based at least in part on the extracted keyword; and generating a creative for the extracted keyword; and submitting to an advertisement placement service an extracted keyword, the link for the extracted keyword, and the creative for the extracted keyword. 27. The method of claim 3 , wherein the ranking of one or more attributes of the category comprises a ranking based at least in part on a statistical conversion rate of advertisements for products in the category.
| 0.540948 |
8,515,984 | 1 | 10 |
1. A method in a search term suggestion engine of a computing device, the method comprising: receiving characters of user data as the characters are input, wherein the user data is at least part of a search term to be provided to a first application to search for the search term, wherein the first application is one of multiple applications on the computing device; receiving, from the first application, an indication of multiple suggestion sources; obtaining, from each of two or more of the multiple suggestion sources, one or more suggested search terms based on the received characters; combining the one or more suggested search terms into a combined set of suggested search terms; and returning the combined set of suggested search terms to a search user interface for presentation to a user, the returning including returning first suggested search terms received from a first one or more of the multiple suggestion sources within a threshold amount of time, waiting until second suggested search terms are received from a second one or more of the multiple suggestion sources, and returning, after returning the first suggested search terms, the second suggested search terms to the search user interface.
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1. A method in a search term suggestion engine of a computing device, the method comprising: receiving characters of user data as the characters are input, wherein the user data is at least part of a search term to be provided to a first application to search for the search term, wherein the first application is one of multiple applications on the computing device; receiving, from the first application, an indication of multiple suggestion sources; obtaining, from each of two or more of the multiple suggestion sources, one or more suggested search terms based on the received characters; combining the one or more suggested search terms into a combined set of suggested search terms; and returning the combined set of suggested search terms to a search user interface for presentation to a user, the returning including returning first suggested search terms received from a first one or more of the multiple suggestion sources within a threshold amount of time, waiting until second suggested search terms are received from a second one or more of the multiple suggestion sources, and returning, after returning the first suggested search terms, the second suggested search terms to the search user interface. 10. A method as recited in claim 1 , wherein combining the one or more suggested search terms comprises: removing duplicate suggested search terms from the suggested search terms obtained from the two or more suggestion sources; and ordering the suggested search terms in the combined set of suggested search terms based on the suggestion sources from which the suggested search terms are obtained.
| 0.5 |
10,114,891 | 7 | 9 |
7. A system comprising: an input unit for receiving a textual query; a processing unit for retrieving a preliminary audio sample from an auxiliary audio database by matching the textual query with semantic information associated to the auxiliary audio database, and one of: retrieving a target audio sample from a target audio database by matching the preliminary audio sample with the target audio database and performing an audio-source separation technique on the retrieved target audio sample for separating the retrieved target audio sample into a plurality of audio source signals, wherein retrieving the target audio sample from the target audio database and performing the audio-source separation technique on the retrieved target audio sample are performed jointly, retrieving the target audio sample from the target audio database by the processing unit including comparing the target audio sample with a negative data set stored in a storing unit of said system; and performing an audio-source separation technique on an audio source mixture for separating a target source signal described by said textual query from said audio source mixture by matching the preliminary audio sample with the audio mixture.
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7. A system comprising: an input unit for receiving a textual query; a processing unit for retrieving a preliminary audio sample from an auxiliary audio database by matching the textual query with semantic information associated to the auxiliary audio database, and one of: retrieving a target audio sample from a target audio database by matching the preliminary audio sample with the target audio database and performing an audio-source separation technique on the retrieved target audio sample for separating the retrieved target audio sample into a plurality of audio source signals, wherein retrieving the target audio sample from the target audio database and performing the audio-source separation technique on the retrieved target audio sample are performed jointly, retrieving the target audio sample from the target audio database by the processing unit including comparing the target audio sample with a negative data set stored in a storing unit of said system; and performing an audio-source separation technique on an audio source mixture for separating a target source signal described by said textual query from said audio source mixture by matching the preliminary audio sample with the audio mixture. 9. The system of claim 7 , wherein the processing unit reviews the preliminary audio sample retrieved from the auxiliary audio database upon receipt of a user input in the input unit.
| 0.5 |
8,620,899 | 1 | 16 |
1. A method for generating a set of one or more materialized query table (MQT) candidates for a workload, wherein the method comprises: receiving a workload, wherein the workload comprises a set of one or more queries; generating one or more best matching MQTs (BMQTs) based on one or more query blocks of the one or more queries by removing syntax that is not qualified for a MQT re-write; determining one or more frequently used multi-joins in the workload, wherein said multi-join is a group of tables, wherein any one of the tables in said group of tables is joined to at least one other table within the group of tables, and wherein any table in the group of tables can be accessed from any other table in the group of tables by traversing a path that contains one or more tables in the group and one or more joins that link the tables in the group of tables; using the one or more BMQTs and the one or more frequently used multi-joins to generate a set of one or more workload MQTs (WMQTs); and grouping one or more WMQTs and one or more BMQTs into one or more groups to merge into a set of a smaller number of MQTs and to cover the workload.
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1. A method for generating a set of one or more materialized query table (MQT) candidates for a workload, wherein the method comprises: receiving a workload, wherein the workload comprises a set of one or more queries; generating one or more best matching MQTs (BMQTs) based on one or more query blocks of the one or more queries by removing syntax that is not qualified for a MQT re-write; determining one or more frequently used multi-joins in the workload, wherein said multi-join is a group of tables, wherein any one of the tables in said group of tables is joined to at least one other table within the group of tables, and wherein any table in the group of tables can be accessed from any other table in the group of tables by traversing a path that contains one or more tables in the group and one or more joins that link the tables in the group of tables; using the one or more BMQTs and the one or more frequently used multi-joins to generate a set of one or more workload MQTs (WMQTs); and grouping one or more WMQTs and one or more BMQTs into one or more groups to merge into a set of a smaller number of MQTs and to cover the workload. 16. The method of claim 1 , further comprising modeling one or more join patterns.
| 0.934921 |
8,239,185 | 17 | 18 |
17. A method, comprising: a) obtaining in digital form a choice of an interviewer language; b) obtaining in digital form a choice of an interviewee language that is distinct from the interviewer language including the following steps; (i) defining a geographic map at a current resolution to be a current map, (ii) displaying the current map on the interviewee graphics screen, (iii) receiving a signal through a graphical user interface on the interviewee graphics screen that selects a current point on the current map, (iv) determining by logic whether the current map has sufficient resolution for a human user to distinguish among regions, shown by the current map, where different languages are spoken, and (v) if the determining step indicates that the current map does not have sufficient resolution, then selecting by logic a higher resolution than the current resolution to be a new current resolution, and a map centered on the current point having the new current resolution to be the new current map, and repeating steps (ii) through (v); otherwise, choosing an interviewee language by associating the current point with a language spoken at the geographic location of the current point and causing the interviewee language to be stored in electronic digital storage; c) receiving by logic a topic from a user interface on an interviewer digital electronic system; d) on an interviewee digital electronic system, causing a first information item associated with the topic to be obtained from a database, said first information item being expressed in the interviewee language; e) on the interviewer digital electronic system, causing a second information item associated with the topic to be obtained from a database, said second information item being expressed in the interviewer language and being distinct in meaning from the first information item; f) presenting the first information item in audio form using an interviewee sound device or in visual form using an interviewee graphics screen; g) presenting the second information item in audio form using an interviewer sound device or in visual form using an interviewer graphics screen.
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17. A method, comprising: a) obtaining in digital form a choice of an interviewer language; b) obtaining in digital form a choice of an interviewee language that is distinct from the interviewer language including the following steps; (i) defining a geographic map at a current resolution to be a current map, (ii) displaying the current map on the interviewee graphics screen, (iii) receiving a signal through a graphical user interface on the interviewee graphics screen that selects a current point on the current map, (iv) determining by logic whether the current map has sufficient resolution for a human user to distinguish among regions, shown by the current map, where different languages are spoken, and (v) if the determining step indicates that the current map does not have sufficient resolution, then selecting by logic a higher resolution than the current resolution to be a new current resolution, and a map centered on the current point having the new current resolution to be the new current map, and repeating steps (ii) through (v); otherwise, choosing an interviewee language by associating the current point with a language spoken at the geographic location of the current point and causing the interviewee language to be stored in electronic digital storage; c) receiving by logic a topic from a user interface on an interviewer digital electronic system; d) on an interviewee digital electronic system, causing a first information item associated with the topic to be obtained from a database, said first information item being expressed in the interviewee language; e) on the interviewer digital electronic system, causing a second information item associated with the topic to be obtained from a database, said second information item being expressed in the interviewer language and being distinct in meaning from the first information item; f) presenting the first information item in audio form using an interviewee sound device or in visual form using an interviewee graphics screen; g) presenting the second information item in audio form using an interviewer sound device or in visual form using an interviewer graphics screen. 18. The method of claim 17 , wherein the interviewee graphics screen and the interviewer graphics screen are included in the same device.
| 0.5 |
7,568,171 | 42 | 43 |
42. The computer program product of claim 41 , wherein moving the element is based at least in part on the direction of the stroke.
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42. The computer program product of claim 41 , wherein moving the element is based at least in part on the direction of the stroke. 43. The computer program product of claim 42 , wherein the direction of the stroke is used to determine a tilt of the element relative to the screen space.
| 0.5 |
8,190,595 | 6 | 7 |
6. The method of claim 5 , further comprising: determining whether the OP node satisfies subtree constraints of a tree pattern of the result; if not, then determining that no unique matching is possible and that no candidate match can be derived; and if so, then determining that a tree pattern of the result has a constraint on an order.
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6. The method of claim 5 , further comprising: determining whether the OP node satisfies subtree constraints of a tree pattern of the result; if not, then determining that no unique matching is possible and that no candidate match can be derived; and if so, then determining that a tree pattern of the result has a constraint on an order. 7. The method of claim 6 , further comprising: determining whether the order is satisfied by the OP node and its subtrees; if not, then determining that no unique matching is possible and that no candidate match can be derived; and if so, then determining that the result is a full match.
| 0.5 |
7,860,705 | 14 | 17 |
14. A context adaptable speech-to-speech translation system comprising: a memory at least one processor implementing: a plurality of classifiers, wherein each of the plurality of classifiers receives a corresponding input signal and generates a corresponding set of paralinguistic attribute values; a fusion module that receives a plurality of sets of paralinguistic attribute values from the plurality of classifiers and generates a final set of paralinguistic attribute values; and speech-to-speech translation modules comprising a speech recognition module, a translation module, and a text-to-speech module, wherein performance of at least one of the speech recognition module, the translation module and the text-to-speech module are modified in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier generates is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values performed by the fusion module comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest.
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14. A context adaptable speech-to-speech translation system comprising: a memory at least one processor implementing: a plurality of classifiers, wherein each of the plurality of classifiers receives a corresponding input signal and generates a corresponding set of paralinguistic attribute values; a fusion module that receives a plurality of sets of paralinguistic attribute values from the plurality of classifiers and generates a final set of paralinguistic attribute values; and speech-to-speech translation modules comprising a speech recognition module, a translation module, and a text-to-speech module, wherein performance of at least one of the speech recognition module, the translation module and the text-to-speech module are modified in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier generates is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values performed by the fusion module comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest. 17. The context adaptable speech-to-speech translation system of claim 14 , wherein the speech-to-speech translation modules access an expression database to generate appropriate expression in the text-to-speech module based on the final set of paralinguistic attribute values.
| 0.742565 |
7,899,807 | 5 | 6 |
5. The method of claim 4 , wherein the step of estimating the impact of fetching the particular uncrawled web page further comprises combining a query-based estimate and a query-independent estimate for said particular uncrawled web page by computing a weighted average of said query-based estimate and said query-independent estimate for said particular uncrawled web page; wherein said query-based estimate for said particular uncrawled web page indicates how well said particular uncrawled web page meets neediness and relevance requirements of the needy queries and is determined based, at least in part, on the anchortext and the URL that point to the particular uncrawled web page; wherein said query-independent estimate of said particular uncrawled web page is determined based on query-independent features of said particular uncrawled web page.
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5. The method of claim 4 , wherein the step of estimating the impact of fetching the particular uncrawled web page further comprises combining a query-based estimate and a query-independent estimate for said particular uncrawled web page by computing a weighted average of said query-based estimate and said query-independent estimate for said particular uncrawled web page; wherein said query-based estimate for said particular uncrawled web page indicates how well said particular uncrawled web page meets neediness and relevance requirements of the needy queries and is determined based, at least in part, on the anchortext and the URL that point to the particular uncrawled web page; wherein said query-independent estimate of said particular uncrawled web page is determined based on query-independent features of said particular uncrawled web page. 6. The method of claim 5 , wherein the step of estimating the impact of fetching the particular uncrawled web page further comprises creating query sketches, for said needy queries, by computing an expected impact score for the particular uncrawled web page and expected impact scores for the previously crawled web pages that match said needy queries, and uses the query sketches to determine the query-based estimate and the query-independent estimate for the particular uncrawled web page.
| 0.5 |
9,396,240 | 1 | 3 |
1. A computer-implemented method comprising: receiving a request for an input schema to feed to a data specification language (DaSL) and a metadata outline of typed objects exposed by a database view identified in the request, the database view associated with the database selected using a graphical user interface; requesting extraction of the input schema and metadata outline from the database; creating an instance of a DaSL compiler based upon the input schema; generating, by a computer, a DaSL query corresponding to objects selected from the metadata outline, the DaSL query including low-level primitive queries compiled into a computing language construct supported by the database, mapped to a specific DaSL operator, dynamically compiled at query runtime, and executed to retrieve data from the database conforming to the request; requesting compilation of the DaSL query; receiving a calculation plan and topology cursors responsive to the compilation of the DaSL query; and initiating visualization of a dataset responsive to the execution of the calculation plan using the topology cursors.
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1. A computer-implemented method comprising: receiving a request for an input schema to feed to a data specification language (DaSL) and a metadata outline of typed objects exposed by a database view identified in the request, the database view associated with the database selected using a graphical user interface; requesting extraction of the input schema and metadata outline from the database; creating an instance of a DaSL compiler based upon the input schema; generating, by a computer, a DaSL query corresponding to objects selected from the metadata outline, the DaSL query including low-level primitive queries compiled into a computing language construct supported by the database, mapped to a specific DaSL operator, dynamically compiled at query runtime, and executed to retrieve data from the database conforming to the request; requesting compilation of the DaSL query; receiving a calculation plan and topology cursors responsive to the compilation of the DaSL query; and initiating visualization of a dataset responsive to the execution of the calculation plan using the topology cursors. 3. The method of claim 1 , further comprising transmitting the metadata outline for display.
| 0.673759 |
8,412,525 | 1 | 6 |
1. A method, comprising: converting a plurality of feature vectors that represents a speech utterance into a plurality of log probability sets, the converting using a classifier ensemble including a plurality of classifiers; transforming the plurality of log probability sets into a plurality of output symbol sequences; combining the plurality of output symbol sequences, using an iterative a priori probability calculation algorithm, into a fusion output symbol sequence; and retrieving one or more speech utterances from a speech database using the plurality of output symbol sequences.
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1. A method, comprising: converting a plurality of feature vectors that represents a speech utterance into a plurality of log probability sets, the converting using a classifier ensemble including a plurality of classifiers; transforming the plurality of log probability sets into a plurality of output symbol sequences; combining the plurality of output symbol sequences, using an iterative a priori probability calculation algorithm, into a fusion output symbol sequence; and retrieving one or more speech utterances from a speech database using the plurality of output symbol sequences. 6. The method of claim 1 , wherein at least two classifiers in the classifier ensemble include different number and types of classification classes.
| 0.802139 |
10,007,662 | 28 | 29 |
28. The method of claim 1 , wherein the step of receiving the input sequence comprises the step of receiving over a continuous time variation elements of the input sequence.
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28. The method of claim 1 , wherein the step of receiving the input sequence comprises the step of receiving over a continuous time variation elements of the input sequence. 29. The method of claim 28 , wherein the step of receiving over the continuous time variation elements of the input sequence comprises the step of utilizing a coupling function 2 (t0-t1) , where t 0 and t 1 are the times at which two elements of the input sequence occurred.
| 0.5 |
9,594,835 | 25 | 26 |
25. The method as recited in claim 1 , wherein upon receiving a selection of one of the set of bookmarks, providing a set of links to a set of documents that have previously been selected via the web browser in association with the search query identified by the corresponding bookmark and an indication of a frequency with which each of the set of one or more documents has been selected via the web browser.
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25. The method as recited in claim 1 , wherein upon receiving a selection of one of the set of bookmarks, providing a set of links to a set of documents that have previously been selected via the web browser in association with the search query identified by the corresponding bookmark and an indication of a frequency with which each of the set of one or more documents has been selected via the web browser. 26. The method as recited in claim 25 , wherein the indication is provided via a set of display characteristics associated with the selected bookmark.
| 0.5 |
8,860,752 | 24 | 32 |
24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation.
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24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation. 32. The method of claim 24 , wherein the process for manipulating multimedia items further comprises the steps of: a first process requesting a filter from a second process; said first process defining a relationship between said filter and said multimedia item, said related filter and multimedia item comprising a program, said second process compiling said program, yielding a compiled program; and running at least a portion of said compiled program to apply a function of said filter to said multimedia item.
| 0.5 |
7,941,386 | 20 | 21 |
20. A computer implemented method for enterprise-wide forensic data analysis, the method comprising: providing a search pack exchange server programmed to provide search packs to one or more external systems; storing, in a nontransitory computer readable storage module, a plurality of search packs in a search pack repository, wherein the search packs are generated by different agencies within the enterprise; providing a search pack editor module adapted to create, edit and delete search packs; extracting unknown raw data from a plurality of raw data sources and providing the extracted unknown raw data as output; receiving the extracted unknown raw data from the data extraction module; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying suspect data from among the extracted unknown raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and storing findings reports in a findings report repository; and exchanging search packs and the findings reports between multiple, different agencies within the enterprise.
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20. A computer implemented method for enterprise-wide forensic data analysis, the method comprising: providing a search pack exchange server programmed to provide search packs to one or more external systems; storing, in a nontransitory computer readable storage module, a plurality of search packs in a search pack repository, wherein the search packs are generated by different agencies within the enterprise; providing a search pack editor module adapted to create, edit and delete search packs; extracting unknown raw data from a plurality of raw data sources and providing the extracted unknown raw data as output; receiving the extracted unknown raw data from the data extraction module; determining which one or more search packs to send the unknown raw data to wherein the determination is based on categories of data; automatically identifying suspect data from among the extracted unknown raw data by applying a hash function to the extracted raw data to generate an extracted data hash value, and comparing the extracted data hash value to find identical and similar suspect data features; and storing findings reports in a findings report repository; and exchanging search packs and the findings reports between multiple, different agencies within the enterprise. 21. The method of claim 20 , further comprising providing an interface to permit an external system coupled to the enterprise to conduct a forensic data analysis using search packs created by different agencies.
| 0.552966 |
9,509,818 | 1 | 4 |
1. A method for categorizing contacts, comprising: generating a quality of experience (QoE) vector space for each of one or more contacts associated with a user; monitoring multiple communications between the user and each of the one or more contacts; collecting one or more physiological signals from the user during each of the multiple monitored communications; classifying each of the multiple monitored communications into multiple predetermined classifications; updating the QoE vector space for each of the one or more contacts based on the collected physiological signals; categorizing the one or more contacts into multiple contact groups in accordance with the updated QoE vector spaces, the categorizing including: randomly selecting multiple QoE vector spaces, from the updated QoE vector spaces, as multiple centers, computing a distance value between each unselected QoE vector space and each of the multiple centers, clustering each unselected QoE vector space to one of the multiple centers that corresponds to a minimum one of the computed distance values to form the multiple contact groups, calculating a new center for each of the multiple contact groups, calculating a mean square value for each of the multiple contact groups, reverting to the computing of the distance value if the calculated mean square value is larger than a predetermined mean square value, and validating the categorizing if the calculated mean square value is less than or equal to the predetermined mean square value; and sorting the categorized contact groups based on the updated QoE vector spaces.
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1. A method for categorizing contacts, comprising: generating a quality of experience (QoE) vector space for each of one or more contacts associated with a user; monitoring multiple communications between the user and each of the one or more contacts; collecting one or more physiological signals from the user during each of the multiple monitored communications; classifying each of the multiple monitored communications into multiple predetermined classifications; updating the QoE vector space for each of the one or more contacts based on the collected physiological signals; categorizing the one or more contacts into multiple contact groups in accordance with the updated QoE vector spaces, the categorizing including: randomly selecting multiple QoE vector spaces, from the updated QoE vector spaces, as multiple centers, computing a distance value between each unselected QoE vector space and each of the multiple centers, clustering each unselected QoE vector space to one of the multiple centers that corresponds to a minimum one of the computed distance values to form the multiple contact groups, calculating a new center for each of the multiple contact groups, calculating a mean square value for each of the multiple contact groups, reverting to the computing of the distance value if the calculated mean square value is larger than a predetermined mean square value, and validating the categorizing if the calculated mean square value is less than or equal to the predetermined mean square value; and sorting the categorized contact groups based on the updated QoE vector spaces. 4. The method of claim 1 , wherein the multiple monitored communications include at least one of telephone conversation, a text message exchange, an email exchange, or a video chat.
| 0.662313 |
9,372,681 | 2 | 4 |
2. The method of claim 1 , further comprising: configuring the web browser on the user's computing device to: in response to a navigation event on the user's computing device which leads to a navigated-to-document URL, determine if the navigated-to-document URL conforms to the declared document URL type in the manifest of the application and accordingly redirect the navigated-to-document URL to the application for opening a document associated with the navigated-to-document URL.
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2. The method of claim 1 , further comprising: configuring the web browser on the user's computing device to: in response to a navigation event on the user's computing device which leads to a navigated-to-document URL, determine if the navigated-to-document URL conforms to the declared document URL type in the manifest of the application and accordingly redirect the navigated-to-document URL to the application for opening a document associated with the navigated-to-document URL. 4. The method of claim 2 , wherein the navigation event includes any one of (1) a direct click by a user on a link in a web page or other document and (2) a script-driven navigation event.
| 0.568807 |
8,527,491 | 9 | 15 |
9. A non-transitory computer-readable medium storing instructions, the instructions comprising: a plurality of instructions which, when executed by one or more processors, cause the one or more processors to: provide a list of search results obtained based on a search query that includes one or more keywords, a particular search result, in the list of search results, including: a reference to a search result document, and a snippet of text obtained from content of the search result document; receive a request associated with detecting a cursor being placed over an area associated with the particular search result; provide, based on the received request, an expanded snippet of text, the expanded snippet of text comprising text, from the content of the search result document, that includes: at least one of the one or more keywords, and additional text, different than the snippet of text, from the content of the search result document, the expanded snippet of text comprising less than all of the content of the search result document, and the expanded snippet of text being provided for display, within one of an overlay or a frame, with the list of search results; and provide an option to remove the expanded snippet of text, the particular search result being presented without the expanded snippet of text based on receiving selection of the option to remove the expanded snippet of text.
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9. A non-transitory computer-readable medium storing instructions, the instructions comprising: a plurality of instructions which, when executed by one or more processors, cause the one or more processors to: provide a list of search results obtained based on a search query that includes one or more keywords, a particular search result, in the list of search results, including: a reference to a search result document, and a snippet of text obtained from content of the search result document; receive a request associated with detecting a cursor being placed over an area associated with the particular search result; provide, based on the received request, an expanded snippet of text, the expanded snippet of text comprising text, from the content of the search result document, that includes: at least one of the one or more keywords, and additional text, different than the snippet of text, from the content of the search result document, the expanded snippet of text comprising less than all of the content of the search result document, and the expanded snippet of text being provided for display, within one of an overlay or a frame, with the list of search results; and provide an option to remove the expanded snippet of text, the particular search result being presented without the expanded snippet of text based on receiving selection of the option to remove the expanded snippet of text. 15. The non-transitory computer-readable medium of claim 9 , where the one or more instructions to provide the expanded snippet of text include: one or more instructions to visually distinguish the at least one of the one or more keywords within the expanded snippet of text.
| 0.769682 |
9,471,885 | 12 | 15 |
12. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer, wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured as a separate domain-specific knowledgebase segment and is further configured to perform a method comprising the steps of: determining that a predictor case base containing predictor rules having predictor antecedents and associated predictor consequents does not contain a predictor rule having a predictor antecedent covered by an acquired predictor context; creating one or more least-generalized predictor antecedents that are covered by the acquired predictor context; creating a corrector context using the predictor consequents associated with the one or more least-generalized predictor antecedents; determining that a corrector case base containing corrector rules having corrector antecedents and associated corrector consequents contains a corrector rule having a corrector antecedent covered by the corrector context; and firing the corrector consequent associated with the corrector antecedent covered by the corrector context.
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12. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer, wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured as a separate domain-specific knowledgebase segment and is further configured to perform a method comprising the steps of: determining that a predictor case base containing predictor rules having predictor antecedents and associated predictor consequents does not contain a predictor rule having a predictor antecedent covered by an acquired predictor context; creating one or more least-generalized predictor antecedents that are covered by the acquired predictor context; creating a corrector context using the predictor consequents associated with the one or more least-generalized predictor antecedents; determining that a corrector case base containing corrector rules having corrector antecedents and associated corrector consequents contains a corrector rule having a corrector antecedent covered by the corrector context; and firing the corrector consequent associated with the corrector antecedent covered by the corrector context. 15. The system of claim 12 , wherein each of the plurality of distributed processors are configured to create the corrector context by using the union of predictor consequents associated with the least-generalized predictor antecedents.
| 0.839674 |
9,348,479 | 2 | 5 |
2. The computer storage medium of claim 1 , further comprising ascertaining an operation scenario type of the application, the operation scenario type corresponding to a usage formality of the application, wherein the selecting includes selecting a skin package for a user interface of the application based on the emotional state and the operation scenario type.
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2. The computer storage medium of claim 1 , further comprising ascertaining an operation scenario type of the application, the operation scenario type corresponding to a usage formality of the application, wherein the selecting includes selecting a skin package for a user interface of the application based on the emotional state and the operation scenario type. 5. The computer storage medium of claim 2 , wherein the operation scenario type is one of a plurality of operation scenario types that include an online chat scenario and a document authoring scenario.
| 0.798597 |
8,589,457 | 6 | 7 |
6. The system of claim 1 , wherein the operations further comprise: in response to receiving the query through a search interface, identifying a plurality of images responsive to the query; applying the scoring model to each of the plurality of images to determine a respective score for each image; and presenting images from the plurality of images in the search interface, wherein the images are presented in an order according to the respective score for each image.
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6. The system of claim 1 , wherein the operations further comprise: in response to receiving the query through a search interface, identifying a plurality of images responsive to the query; applying the scoring model to each of the plurality of images to determine a respective score for each image; and presenting images from the plurality of images in the search interface, wherein the images are presented in an order according to the respective score for each image. 7. The system of claim 6 , wherein the scoring model is query specific and the operations further comprise: updating and storing a query specific scoring model each of the plurality of queries.
| 0.5 |
8,806,320 | 1 | 5 |
1. A method, comprising: receiving, via a network, a media selection in connection with a first media associated with a media file; receiving, via the network, a media selection in connection with a second media associated with a media file; receiving, via the network, a multi-sync request associated with the media selection for the first media and the media selection for the second media; and when the multi-sync request is a time-based multi-sync request, then receive, via the network, a selection of a segment of the first media and a selection of a segment of the second media; automatically detect whether a duration of the segment of the first media is equal to a duration of the segment of the second media; when the duration of the segment of the first media is detected as being equal to the duration of the segment of the second media, then automatically enable time-based synching as a default to generate a dynamic media link and multi-sync data based on the selection of the segment of the first media and the selection of the segment of the second media, without affecting an integrity of the first media and an integrity of the second media, the dynamic media link being a hyperlink; send the multi-sync data such that the multi-sync data is stored in a relational database at a relational database server after the multi-sync data is generated; and send, via the network, the dynamic media link such that the segment of the first media and the segment of the second media are displayed and synchronously played side-by-side in a user-editable form based on the multi-sync data stored in the relational database, after receiving an indication that the dynamic media link was selected, the user-editable form being received from a media server, the user-editable form allowing a user to edit synchronization points between the first media and the second media.
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1. A method, comprising: receiving, via a network, a media selection in connection with a first media associated with a media file; receiving, via the network, a media selection in connection with a second media associated with a media file; receiving, via the network, a multi-sync request associated with the media selection for the first media and the media selection for the second media; and when the multi-sync request is a time-based multi-sync request, then receive, via the network, a selection of a segment of the first media and a selection of a segment of the second media; automatically detect whether a duration of the segment of the first media is equal to a duration of the segment of the second media; when the duration of the segment of the first media is detected as being equal to the duration of the segment of the second media, then automatically enable time-based synching as a default to generate a dynamic media link and multi-sync data based on the selection of the segment of the first media and the selection of the segment of the second media, without affecting an integrity of the first media and an integrity of the second media, the dynamic media link being a hyperlink; send the multi-sync data such that the multi-sync data is stored in a relational database at a relational database server after the multi-sync data is generated; and send, via the network, the dynamic media link such that the segment of the first media and the segment of the second media are displayed and synchronously played side-by-side in a user-editable form based on the multi-sync data stored in the relational database, after receiving an indication that the dynamic media link was selected, the user-editable form being received from a media server, the user-editable form allowing a user to edit synchronization points between the first media and the second media. 5. The method of claim 1 , wherein: the selection of the first media is a first selection of the first media, the selection of the second media is a first selection of the second media, the dynamic media link is a first dynamic media link, the multi-sync data is first multi-sync data, if an authorized user request is received to edit the first selection of the first media and the first selection of the second media: receiving a second selection of the first media and a second selection of the second media; generating a second dynamic media link and second multi-sync data based on the second selection of the first media and the second selection of the second media, without affecting the integrity of the first media and the integrity of the second media; storing the second multi-sync data in the relational database after the second multi-sync data is generated; and sending a signal such that the second segment of the first media and the second selection of the second media are synchronously displayed based on the second multi-sync data.
| 0.5 |
8,849,652 | 20 | 22 |
20. A computer-implemented method of processing natural language utterances where recognized words of the natural language utterances alone are insufficient to completely determine one or more commands or requests, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: generating, by the one or more physical processors, a first context set associated with a first device, the first context set comprising context information that corresponds to a plurality of prior utterances; synchronizing the first context set with a second context set associated with a second device such that the context information of the first context set is updated based on related context information of the second context set; receiving, at the one or more physical processors, a natural language utterance associated with a command or request; determining, by the one or more physical processors, one or more words of the natural language utterance by performing speech recognition on the natural language utterance; and determining, by the one or more physical processors, the command or request based on the one or more words and the updated context information.
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20. A computer-implemented method of processing natural language utterances where recognized words of the natural language utterances alone are insufficient to completely determine one or more commands or requests, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: generating, by the one or more physical processors, a first context set associated with a first device, the first context set comprising context information that corresponds to a plurality of prior utterances; synchronizing the first context set with a second context set associated with a second device such that the context information of the first context set is updated based on related context information of the second context set; receiving, at the one or more physical processors, a natural language utterance associated with a command or request; determining, by the one or more physical processors, one or more words of the natural language utterance by performing speech recognition on the natural language utterance; and determining, by the one or more physical processors, the command or request based on the one or more words and the updated context information. 22. The method of claim 20 , wherein the first context set includes a plurality of context entries, the method further comprising: identifying, by the one or more physical processors, from among the plurality of context entries, one or more context entries that correspond to the one or more words, wherein the updated context information includes the one or more context entries.
| 0.650735 |
9,645,999 | 1 | 6 |
1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory.
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1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory. 6. The method of claim 1 , wherein determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount comprises: determining a ratio of a first value to a second value, the first value and the second value both being based on the first amount.
| 0.862881 |
9,817,897 | 5 | 6 |
5. The method of claim 4 , wherein the method further involves receiving one or more answers from at least another user in response to providing the third question; and wherein the answer to the third question provided to the first user is at least one of the one or more received answers.
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5. The method of claim 4 , wherein the method further involves receiving one or more answers from at least another user in response to providing the third question; and wherein the answer to the third question provided to the first user is at least one of the one or more received answers. 6. The method of claim 5 , wherein, after receiving the one or more answers and prior to providing the answer to the first user, the method further involves performing content-dependent processing of the one or more received answers based on the tax-information data sections.
| 0.5 |
9,083,731 | 3 | 4 |
3. The medium of claim 2 , wherein the backref-NFA further comprises, for each pair of brackets in the backref-regex, a corresponding pair of edges labeled to identify respectively a beginning bracket and an ending bracket, the edges extending from a sub-backref-NFA corresponding to a sub-backref-regex embedded inside the each pair of brackets.
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3. The medium of claim 2 , wherein the backref-NFA further comprises, for each pair of brackets in the backref-regex, a corresponding pair of edges labeled to identify respectively a beginning bracket and an ending bracket, the edges extending from a sub-backref-NFA corresponding to a sub-backref-regex embedded inside the each pair of brackets. 4. The medium of claim 3 , wherein the edges of the backref-NFA corresponding to the brackets of the backref-regex represent epsilon transitions.
| 0.5 |
9,461,966 | 1 | 9 |
1. A method comprising: 1) identifying, at a client terminal, a Uniform Resource Identifier and at least three separate components of the Uniform Resource Identifier; 2) sending a query to a rating server over an IP network, the query including as a query string at least a first component of the identified Uniform Resource Identifier or a derivative of that first component; 3) receiving the query at the rating server and determining whether or not a rating exists for the query string and that a further query is required; 4) sending a response including a determined rating, or an indication that no rating exists, to the client terminal, the response including an indication that a further query is required; 5) in response to receiving the response at the client terminal, sending a further query to the rating server, the further query including as a query string said at least a first component and a further component of the identified Uniform Resource Identifier, or a derivative of the first and second components; 6) receiving the further query at the rating server and determining whether or not a rating exists for the query string; 7) in response to determining that a further query is required, repeating steps 4) to 6) through one or more further iterations, determining after each iteration whether or not a further query is required, until a query is received at the rating server for which no further query is required, adding for each iteration a further component of the Uniform Resource Identifier to the query string; and 8) in response to determining that no further query is required, sending a response including a determined rating, or an indication that no rating exists, to the client terminal; and receiving the response at the client terminal.
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1. A method comprising: 1) identifying, at a client terminal, a Uniform Resource Identifier and at least three separate components of the Uniform Resource Identifier; 2) sending a query to a rating server over an IP network, the query including as a query string at least a first component of the identified Uniform Resource Identifier or a derivative of that first component; 3) receiving the query at the rating server and determining whether or not a rating exists for the query string and that a further query is required; 4) sending a response including a determined rating, or an indication that no rating exists, to the client terminal, the response including an indication that a further query is required; 5) in response to receiving the response at the client terminal, sending a further query to the rating server, the further query including as a query string said at least a first component and a further component of the identified Uniform Resource Identifier, or a derivative of the first and second components; 6) receiving the further query at the rating server and determining whether or not a rating exists for the query string; 7) in response to determining that a further query is required, repeating steps 4) to 6) through one or more further iterations, determining after each iteration whether or not a further query is required, until a query is received at the rating server for which no further query is required, adding for each iteration a further component of the Uniform Resource Identifier to the query string; and 8) in response to determining that no further query is required, sending a response including a determined rating, or an indication that no rating exists, to the client terminal; and receiving the response at the client terminal. 9. A method according to claim 1 , wherein the client terminal comprises a web browser and the method further comprises displaying in a web browser window a determined rating.
| 0.678309 |
8,983,990 | 3 | 4 |
3. A system for performing a query, the system comprising: a non-transitory computer readable medium that includes: a query rewrite module that receives a user graph query and that rewrites the user graph query as a new query based on a query policy expressed in a graph query language, the user graph query being user generated, the query policy being expressed as a set of one or more views, where each view includes a first query that evaluates whether the query policy applies to the user and a second query that determines graph data that is viewable to the user through the view, wherein the new query comprises a union of conjunctive queries wherein each query in the union is a result of considering one combination from a Cartesian product of the user graph query and the set of one or more views; the query rewrite module further configured to create an optimized query by removing redundant views from the new query, removing any empty views from the new query, and removing any empty sub-query of the new query; and a query module that performs the optimized query on a graph data to obtain a result, wherein the graph data includes a set of triples, wherein the query rewrite module rewrites the user query by: identifying a plurality of views in the query policy; separating the plurality of views into groups based on a query predicate; considering one view from each of the groups as a rewritten query based on a query predicate; and generating the new query based on a union of the rewritten queries.
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3. A system for performing a query, the system comprising: a non-transitory computer readable medium that includes: a query rewrite module that receives a user graph query and that rewrites the user graph query as a new query based on a query policy expressed in a graph query language, the user graph query being user generated, the query policy being expressed as a set of one or more views, where each view includes a first query that evaluates whether the query policy applies to the user and a second query that determines graph data that is viewable to the user through the view, wherein the new query comprises a union of conjunctive queries wherein each query in the union is a result of considering one combination from a Cartesian product of the user graph query and the set of one or more views; the query rewrite module further configured to create an optimized query by removing redundant views from the new query, removing any empty views from the new query, and removing any empty sub-query of the new query; and a query module that performs the optimized query on a graph data to obtain a result, wherein the graph data includes a set of triples, wherein the query rewrite module rewrites the user query by: identifying a plurality of views in the query policy; separating the plurality of views into groups based on a query predicate; considering one view from each of the groups as a rewritten query based on a query predicate; and generating the new query based on a union of the rewritten queries. 4. The system of claim 3 wherein the graph query language is at least one of SPARQL, RDQL, and RQL.
| 0.5 |
8,880,519 | 7 | 8 |
7. The method of claim 1 , said generating comprising: creating a constituent word list comprising at least one constituent word that is a respective dictionary word appearing in the service name as a result of parsing the service name into a set of dictionary words by the name parser; associating a respective weight to each constituent word of the at least one constituent word; producing a respective synonym list for each constituent word as a result of running the dictionary, the respective synonym list comprising at least one synonym of each constituent word as located in the dictionary; associating a respective weight to each synonym in the respective synonym list for each constituent word; composing at least one alternative service name by combining the at least one constituent word from the constituent word list and the at least one synonym from the respective synonym list pursuant to a sequence in the service name by use of the name composer; calculating a respective rank for the at least one alternative service name by adding the respective weights of all words employed in each alternative service name from said composing; rendering the ranked service name list by associating the respective rank with each alternative service name.
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7. The method of claim 1 , said generating comprising: creating a constituent word list comprising at least one constituent word that is a respective dictionary word appearing in the service name as a result of parsing the service name into a set of dictionary words by the name parser; associating a respective weight to each constituent word of the at least one constituent word; producing a respective synonym list for each constituent word as a result of running the dictionary, the respective synonym list comprising at least one synonym of each constituent word as located in the dictionary; associating a respective weight to each synonym in the respective synonym list for each constituent word; composing at least one alternative service name by combining the at least one constituent word from the constituent word list and the at least one synonym from the respective synonym list pursuant to a sequence in the service name by use of the name composer; calculating a respective rank for the at least one alternative service name by adding the respective weights of all words employed in each alternative service name from said composing; rendering the ranked service name list by associating the respective rank with each alternative service name. 8. The method of claim 7 , wherein the respective weight for each constituent word is predefined in a first range of positive integers greater than one hundred (100), and wherein the respective weight for each synonym of each constituent word is predefined in a second range of zero (0) and positive integers less than five (5) such that a first alternative service name comprising more constituent words ranks higher than a second alternative service name comprising more synonyms in place of constituent words of the service name input by the user.
| 0.5 |
8,417,695 | 11 | 14 |
11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform.
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11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform. 14. The apparatus of claim 11 wherein the one or more processors are further configured to associate a penalty with concept term position switching, number mismatch, and character correction.
| 0.647601 |
8,635,094 | 7 | 9 |
7. A computer hardware system for role-based personalization of a collaborative space comprising: a processor; a memory; a plurality of user interface components disposed in the collaborative space, each user interface component being selected based upon role information extracted from a workflow; a workflow engine coupled to the collaborative space and configured to process the workflow; and, an event engine logically disposed, within the processor and between the user interface components and the workflow engine, the event engine configured to obtain role-based information for an interacting user that has been defined by an underlying business process model in the workflow; and generate the collaborative space utilizing the role-based information, including: parsing the workflow to extract a role model; generating a collaborative space domain model from the role model; selecting a plurality of user interface components based upon the role model, wherein mapping rules are defined to transform role information aggregated in the role model to user interface components for incorporation in the collaborative space domain model, and wherein the mapping rules include user-specified mapping rules between a group of workflow tasks and existing user interface components where existing user interface components exist when the collaborative space is created, and suggested mapping rules obtained by segmenting the workflow based upon role-assignment or a control-flow structure where user interface components do not exist when the collaborative space is created; organize the selected user interface components in the collaborative space; and render the collaborative space.
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7. A computer hardware system for role-based personalization of a collaborative space comprising: a processor; a memory; a plurality of user interface components disposed in the collaborative space, each user interface component being selected based upon role information extracted from a workflow; a workflow engine coupled to the collaborative space and configured to process the workflow; and, an event engine logically disposed, within the processor and between the user interface components and the workflow engine, the event engine configured to obtain role-based information for an interacting user that has been defined by an underlying business process model in the workflow; and generate the collaborative space utilizing the role-based information, including: parsing the workflow to extract a role model; generating a collaborative space domain model from the role model; selecting a plurality of user interface components based upon the role model, wherein mapping rules are defined to transform role information aggregated in the role model to user interface components for incorporation in the collaborative space domain model, and wherein the mapping rules include user-specified mapping rules between a group of workflow tasks and existing user interface components where existing user interface components exist when the collaborative space is created, and suggested mapping rules obtained by segmenting the workflow based upon role-assignment or a control-flow structure where user interface components do not exist when the collaborative space is created; organize the selected user interface components in the collaborative space; and render the collaborative space. 9. The system of claim 7 , wherein the user interface components comprise portlets.
| 0.5 |
8,214,392 | 5 | 6 |
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.
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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. 6. The method of claim 5 , all the limitations of which are incorporated herein by reference, further comprising: setting a maximum number of combination of said data attributes to be presented in said at least one presentation report; setting a maximum number of datapoints in said data set to be presented in said at least one presentation report; setting a maximum number of said domain metrics; and computing a total number of combination of the tagged data attributes based on said data grouping attributes and data measure attributes.
| 0.5 |
8,660,969 | 16 | 20 |
16. A non-transitory computer readable medium storing a plurality of instructions that cause a computer to perform a method comprising: receiving a first dataset including a first given source and a corresponding first given target; parsing the first given source to determine a first parsed target output in accordance with a parsing model having a first parsing parameter; determining an intrinsic loss based upon an intrinsic loss function, the first parsed target and the first given target; receiving a second dataset containing a second given source and a corresponding second given target; parsing the second given source input to generate k-best parses in accordance with the parsing model having a second parsing parameter, the k-best parses including a 1-best parse; determining a lowest cost parse among the k-best parses; determining an extrinsic loss based upon an extrinsic loss function, the lowest cost parse and the 1-best parse; modifying the first parsing parameter based on the determining the intrinsic loss; and modifying the second parsing parameter based on the determining the extrinsic loss, or modifying the first parameter based on the determining the intrinsic loss and modifying the second parsing parameter based on the determining the extrinsic loss.
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16. A non-transitory computer readable medium storing a plurality of instructions that cause a computer to perform a method comprising: receiving a first dataset including a first given source and a corresponding first given target; parsing the first given source to determine a first parsed target output in accordance with a parsing model having a first parsing parameter; determining an intrinsic loss based upon an intrinsic loss function, the first parsed target and the first given target; receiving a second dataset containing a second given source and a corresponding second given target; parsing the second given source input to generate k-best parses in accordance with the parsing model having a second parsing parameter, the k-best parses including a 1-best parse; determining a lowest cost parse among the k-best parses; determining an extrinsic loss based upon an extrinsic loss function, the lowest cost parse and the 1-best parse; modifying the first parsing parameter based on the determining the intrinsic loss; and modifying the second parsing parameter based on the determining the extrinsic loss, or modifying the first parameter based on the determining the intrinsic loss and modifying the second parsing parameter based on the determining the extrinsic loss. 20. The non-transitory computer readable medium of claim 16 , wherein the first parsing parameter is the same as the second parsing parameter.
| 0.904826 |
9,997,161 | 1 | 8 |
1. A speech recognition device for accurate transformation of acoustic utterances into text, the speech recognition device comprising: an acoustic sensor configured to receive one or more acoustic utterances; one or more memory devices configured to receive and store a set of one or more acoustic models having trained one or more confidence classifiers and to store one or more acceptance metrics defining at least one recognition acceptance condition; automatic speech recognition circuitry including at least one processor unit for executing confidence classifier circuitry, the confidence classifier circuitry being configured to generate a first speech recognition confidence classifier score corresponding to the one or more received acoustic utterances and recognized text based on a first confidence classifier and to generate a second speech recognition confidence classifier score corresponding to the one or more received acoustic utterances and the recognized text based on a second confidence classifier; normalization circuitry connected to the automatic speech recognition circuitry to receive the first and second speech recognition confidence classifier scores from the confidence classifier circuitry and to map a distribution within an output range of the second confidence classifier to a distribution within an output range of the first confidence classifier, the mapped distribution including a mapped speech recognition confidence classifier score for the second confidence classifier that more accurately satisfies the recognition acceptance condition than a corresponding score from the first confidence classifier; and a text output interface connected to receive new recognized text from the automatic speech recognition circuitry for a newly-received acoustic utterance and to output a signal representing the new recognized text as accepted text responsive to a determination that a mapped speech recognition confidence classifier score of the second confidence classifier for the newly-received acoustic utterance satisfies the recognition acceptance condition.
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1. A speech recognition device for accurate transformation of acoustic utterances into text, the speech recognition device comprising: an acoustic sensor configured to receive one or more acoustic utterances; one or more memory devices configured to receive and store a set of one or more acoustic models having trained one or more confidence classifiers and to store one or more acceptance metrics defining at least one recognition acceptance condition; automatic speech recognition circuitry including at least one processor unit for executing confidence classifier circuitry, the confidence classifier circuitry being configured to generate a first speech recognition confidence classifier score corresponding to the one or more received acoustic utterances and recognized text based on a first confidence classifier and to generate a second speech recognition confidence classifier score corresponding to the one or more received acoustic utterances and the recognized text based on a second confidence classifier; normalization circuitry connected to the automatic speech recognition circuitry to receive the first and second speech recognition confidence classifier scores from the confidence classifier circuitry and to map a distribution within an output range of the second confidence classifier to a distribution within an output range of the first confidence classifier, the mapped distribution including a mapped speech recognition confidence classifier score for the second confidence classifier that more accurately satisfies the recognition acceptance condition than a corresponding score from the first confidence classifier; and a text output interface connected to receive new recognized text from the automatic speech recognition circuitry for a newly-received acoustic utterance and to output a signal representing the new recognized text as accepted text responsive to a determination that a mapped speech recognition confidence classifier score of the second confidence classifier for the newly-received acoustic utterance satisfies the recognition acceptance condition. 8. The speech recognition device of claim 1 wherein the text output interface outputs the signal representing the accepted text to a display.
| 0.783742 |
5,585,793 | 2 | 3 |
2. The method of claim 1 further comprising associating a unique encoding with each set, and substituting, for each token of each output string, the unique encoding associated with the set which includes the leading sub-string which produced the token, to encode the input strings.
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2. The method of claim 1 further comprising associating a unique encoding with each set, and substituting, for each token of each output string, the unique encoding associated with the set which includes the leading sub-string which produced the token, to encode the input strings. 3. The method of claim 2 wherein the input strings comprise characters of a first alphabet, the encodings comprise characters of a second alphabet, and further comprising arranging the predetermined range of the sub-strings of each set according to a predetermined order of the first alphabet, and arranging the unique encodings according to another predetermined order of the second alphabet, there being a one-to-one correspondence between the sets and the encodings to translate the input strings.
| 0.5 |
8,326,601 | 14 | 15 |
14. A system translated between a first language and a second language in an online chat room, comprising: a processor configured for: receiving a message from a first client written in the first language, temporarily persisting the message in a first queue that is specific to the first language, translating the first language of the message into the second language, and supplying the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language; and a memory coupled to the processor for persisting data.
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14. A system translated between a first language and a second language in an online chat room, comprising: a processor configured for: receiving a message from a first client written in the first language, temporarily persisting the message in a first queue that is specific to the first language, translating the first language of the message into the second language, and supplying the message in the second language to a second queue for subsequent delivery to a second client, the second queue being specific to the second language; and a memory coupled to the processor for persisting data. 15. The system of claim 14 , wherein the processor is further configured for monitoring the first queue periodically prior to translating the first language of the message into the second language.
| 0.670569 |
8,375,008 | 1 | 4 |
1. A method, performed by a computer system, for managing information associated with an enterprise, the method comprising the steps of: obtaining original data from a plurality of different electronic data sources including at least two electronic data sources including a backup tape data source and a networked data source, wherein the original data includes a plurality of files having content portions and metadata portions; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions and the metadata portions by hashing the content portions of the information extracted and the other original data to form hashed values using a de-duplication engine and comparing the hashed values using the de-duplication engine; placing, into a collective database, at least a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information on where the files were obtained; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query is other than a search for duplicate portions of the data; using the rule, which includes a logical operation to segregate the targeted data and the compliant data from other data, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the collective database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the collective database.
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1. A method, performed by a computer system, for managing information associated with an enterprise, the method comprising the steps of: obtaining original data from a plurality of different electronic data sources including at least two electronic data sources including a backup tape data source and a networked data source, wherein the original data includes a plurality of files having content portions and metadata portions; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions and the metadata portions by hashing the content portions of the information extracted and the other original data to form hashed values using a de-duplication engine and comparing the hashed values using the de-duplication engine; placing, into a collective database, at least a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information on where the files were obtained; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query is other than a search for duplicate portions of the data; using the rule, which includes a logical operation to segregate the targeted data and the compliant data from other data, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the collective database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the collective database. 4. The method of claim 1 , wherein the data source comprises a network, and further comprising deleting the other data from the network.
| 0.870476 |
9,418,151 | 10 | 12 |
10. A non-transitory computer readable storage device including instructions stored thereon, the instructions, which when executed by a machine, cause the machine to perform operations comprising; receiving, a non-lexical code and a non-lexical code descriptor, the non-lexical code and the non-lexical code descriptor from structured data; determining a lexical code and a lexical code descriptor based on the received non-lexical code and non-lexical code descriptor; lexically combining the lexical code with the lexical code descriptor based on a template that indicates how to lexically combine the lexical code and the lexical code descriptor, wherein the instructions for lexically combining the lexical code with the lexical code descriptor include instructions for constraining the lexical combination by an ontological relationship between the lexical code and the lexical code descriptor; and associating the lexically combined lexical code and lexical code descriptor with the non-lexical code and the non-lexical code descriptor in a keyword database.
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10. A non-transitory computer readable storage device including instructions stored thereon, the instructions, which when executed by a machine, cause the machine to perform operations comprising; receiving, a non-lexical code and a non-lexical code descriptor, the non-lexical code and the non-lexical code descriptor from structured data; determining a lexical code and a lexical code descriptor based on the received non-lexical code and non-lexical code descriptor; lexically combining the lexical code with the lexical code descriptor based on a template that indicates how to lexically combine the lexical code and the lexical code descriptor, wherein the instructions for lexically combining the lexical code with the lexical code descriptor include instructions for constraining the lexical combination by an ontological relationship between the lexical code and the lexical code descriptor; and associating the lexically combined lexical code and lexical code descriptor with the non-lexical code and the non-lexical code descriptor in a keyword database. 12. The storage device of claim 10 , wherein the instructions for receiving the non-lexical code include instructions for receiving an element that includes the non-lexical code and the non-lexical code descriptor; and wherein the instructions for lexically combining the lexical code with the lexical code descriptor include instructions for looking up a code descriptor template in a lexical enrichment database as a function of the non-lexical code descriptor and the lexical code to determine the lexical code descriptor.
| 0.548193 |
9,779,632 | 1 | 2 |
1. A method comprising: storing data in a learning graph, the learning graph comprising nodes and edges, wherein a plurality of content nodes represent learning content and a plurality of person nodes represent individuals and wherein edges between nodes comprise association types defining particular relationships between particular nodes, wherein a first edge between a particular content node and a particular person node establishes a first association type, the first edge indicating that learning content corresponding to the particular content node has been consumed by an individual corresponding to the particular person node; adaptively deriving, from the learning graph, a customized learning path for the particular person node, the customized learning path specifying a plurality of content nodes in the learning graph; and associating the customized learning path with the particular person node to specify content to be consumed by particular individuals corresponding to the particular person node.
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1. A method comprising: storing data in a learning graph, the learning graph comprising nodes and edges, wherein a plurality of content nodes represent learning content and a plurality of person nodes represent individuals and wherein edges between nodes comprise association types defining particular relationships between particular nodes, wherein a first edge between a particular content node and a particular person node establishes a first association type, the first edge indicating that learning content corresponding to the particular content node has been consumed by an individual corresponding to the particular person node; adaptively deriving, from the learning graph, a customized learning path for the particular person node, the customized learning path specifying a plurality of content nodes in the learning graph; and associating the customized learning path with the particular person node to specify content to be consumed by particular individuals corresponding to the particular person node. 2. The method of claim 1 wherein the learning graph further comprises a plurality of learning collection nodes, wherein the learning collection nodes have a plurality of edges to content nodes.
| 0.82675 |
8,667,007 | 8 | 14 |
8. A computer program product for providing recommendations to improve a query, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category Levels; and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the calculated keyword relevance indicators, wherein the query relevance indicator is calculated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query.
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8. A computer program product for providing recommendations to improve a query, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category Levels; and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the calculated keyword relevance indicators, wherein the query relevance indicator is calculated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. 14. The computer program product of claim 8 , wherein the computer readable program code, when executed by the processor of the computer, is configured to perform: executing the query in a current form; and providing a list of one or more services.
| 0.797716 |
9,608,916 | 1 | 3 |
1. A method for performing collaborative application classification in a system including a classification aggregator communicatively coupled to a plurality of traffic classifiers, the plurality of traffic classifiers including a first and second traffic classifier, the method comprising: receiving, at the classification aggregator, classification information from the first traffic classifier, the classification information including a destination Internet protocol (IP) address, a destination port number, a protocol and a first application name associated with a first communication flow classified by the first traffic classifier; storing the classification information in a data store of the classification aggregator, the data store containing multiple entries, each of the entries mapping a group of characteristics, including a destination IP address, a destination port number and a protocol, to a corresponding application name; receiving, at the classification aggregator, a query requesting an application name associated with a second communication flow from a second classifier; and providing the first application name, in response to determining that the second communication flow is associated with the first application name, to the second classifier, wherein determining that the second communication flow is associated with the first application name is based on one or more of the entries of the data store of the classification aggregator.
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1. A method for performing collaborative application classification in a system including a classification aggregator communicatively coupled to a plurality of traffic classifiers, the plurality of traffic classifiers including a first and second traffic classifier, the method comprising: receiving, at the classification aggregator, classification information from the first traffic classifier, the classification information including a destination Internet protocol (IP) address, a destination port number, a protocol and a first application name associated with a first communication flow classified by the first traffic classifier; storing the classification information in a data store of the classification aggregator, the data store containing multiple entries, each of the entries mapping a group of characteristics, including a destination IP address, a destination port number and a protocol, to a corresponding application name; receiving, at the classification aggregator, a query requesting an application name associated with a second communication flow from a second classifier; and providing the first application name, in response to determining that the second communication flow is associated with the first application name, to the second classifier, wherein determining that the second communication flow is associated with the first application name is based on one or more of the entries of the data store of the classification aggregator. 3. The method of claim 1 , wherein the classification information is received at the classification aggregator each time the first traffic classifier generates new classification information.
| 0.753866 |
8,843,434 | 1 | 8 |
1. A computer implemented method comprising: providing a search system, the search system comprising a plurality of documents, a plurality of knowledge dimensions, each knowledge dimension comprising a plurality of documents, one or more knowledge dimension maps representing the plurality of knowledge dimensions, and a plurality of concepts, the plurality of knowledge dimensions being characterized by the plurality of concepts, and the plurality of concepts being based on the content of the plurality of documents in each knowledge dimension; receiving a query of the search system from a user; presenting search results to the user based on the query, the search results comprising at least a portion of one or more of the plurality of knowledge dimensions, the plurality of documents, the plurality of knowledge dimension maps and the plurality of concepts; receiving a user selection of one or more of: one or more knowledge dimensions; one or more knowledge dimension maps; one or more concepts; and one or more documents, wherein the one or more knowledge dimensions, one or more knowledge dimension maps, one or more concepts, and one or more documents are presented in the search results; creating a personalized knowledge dimension that is personalized to the user based on the user selection, wherein creating the personalized knowledge dimension comprises associating the one or more knowledge dimensions, one or more knowledge dimension maps, one or more concepts and one or more documents that are selected by the user with the user; and storing a representation of the personalized knowledge dimension that is personalized to the user based on the user selection in the search system with the plurality of knowledge dimensions.
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1. A computer implemented method comprising: providing a search system, the search system comprising a plurality of documents, a plurality of knowledge dimensions, each knowledge dimension comprising a plurality of documents, one or more knowledge dimension maps representing the plurality of knowledge dimensions, and a plurality of concepts, the plurality of knowledge dimensions being characterized by the plurality of concepts, and the plurality of concepts being based on the content of the plurality of documents in each knowledge dimension; receiving a query of the search system from a user; presenting search results to the user based on the query, the search results comprising at least a portion of one or more of the plurality of knowledge dimensions, the plurality of documents, the plurality of knowledge dimension maps and the plurality of concepts; receiving a user selection of one or more of: one or more knowledge dimensions; one or more knowledge dimension maps; one or more concepts; and one or more documents, wherein the one or more knowledge dimensions, one or more knowledge dimension maps, one or more concepts, and one or more documents are presented in the search results; creating a personalized knowledge dimension that is personalized to the user based on the user selection, wherein creating the personalized knowledge dimension comprises associating the one or more knowledge dimensions, one or more knowledge dimension maps, one or more concepts and one or more documents that are selected by the user with the user; and storing a representation of the personalized knowledge dimension that is personalized to the user based on the user selection in the search system with the plurality of knowledge dimensions. 8. The method of claim 1 , further comprising allowing the user to define a plurality of personal concepts based on a repository of documents associated with the user, and associating the plurality of personal concepts with the personalized knowledge dimension.
| 0.511236 |
7,523,137 | 15 | 19 |
15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event.
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15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. 19. The method of claim 15 , further comprising: determining an event type based on the article; creating the event object of the event type, including an event description from the article; and storing the event object in an event database.
| 0.5 |
10,047,970 | 1 | 15 |
1. A thermostat configured to control one or more HVAC components of an HVAC system, the thermostat comprising: a housing, the housing configured to house: a control module configured to provide one or more control signals to control one or more HVAC components of an HVAC system in accordance with a thermostat control algorithm; a microphone; a speaker; a display; a voice recognition module, wherein the voice recognition module is configured to receive via the microphone a first distinct voice stream that includes a predetermined audible trigger followed by a help phrase, and to recognize the predetermined audible trigger and the help phrase in the first distinct voice stream; and wherein the control module is further configured to execute a help command that corresponds to the help phrase by entering a voice control mode and automatically providing one or more natural language audio clips via the speaker and/or one or more video clips via the display for assisting a user in operating the thermostat in response to the voice recognition module recognizing the predetermined audible trigger and the help phrase in the first distinct voice stream.
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1. A thermostat configured to control one or more HVAC components of an HVAC system, the thermostat comprising: a housing, the housing configured to house: a control module configured to provide one or more control signals to control one or more HVAC components of an HVAC system in accordance with a thermostat control algorithm; a microphone; a speaker; a display; a voice recognition module, wherein the voice recognition module is configured to receive via the microphone a first distinct voice stream that includes a predetermined audible trigger followed by a help phrase, and to recognize the predetermined audible trigger and the help phrase in the first distinct voice stream; and wherein the control module is further configured to execute a help command that corresponds to the help phrase by entering a voice control mode and automatically providing one or more natural language audio clips via the speaker and/or one or more video clips via the display for assisting a user in operating the thermostat in response to the voice recognition module recognizing the predetermined audible trigger and the help phrase in the first distinct voice stream. 15. The thermostat of claim 1 , further comprising: a memory; and a processor in communication with the memory; and wherein the memory includes instructions executable by the processor to operate the voice recognition module.
| 0.842877 |
7,711,725 | 15 | 19 |
15. A computing device configured to perform operations comprising: monitoring one or more actions taken by a user while browsing a website; automatically assigning one or more search terms to at least one of the one or more actions taken by the user based upon, at least in part, metadata associated with said one or more actions; assigning one or more complementary terms that define one or more products/services that complement the one or more actions taken by the user; in response to at least one of the actions, executing a query on a datastore based on at least a portion of the one or more search terms and at least a portion of the one or more complementary terms to generate a result set; and displaying the result set including a link to an ecommerce website that offers for sale the one or more products/services, the link embedded with a referring party identifier configured to identify a referring party to a merchant operating the ecommerce website for payment of a referral fee.
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15. A computing device configured to perform operations comprising: monitoring one or more actions taken by a user while browsing a website; automatically assigning one or more search terms to at least one of the one or more actions taken by the user based upon, at least in part, metadata associated with said one or more actions; assigning one or more complementary terms that define one or more products/services that complement the one or more actions taken by the user; in response to at least one of the actions, executing a query on a datastore based on at least a portion of the one or more search terms and at least a portion of the one or more complementary terms to generate a result set; and displaying the result set including a link to an ecommerce website that offers for sale the one or more products/services, the link embedded with a referring party identifier configured to identify a referring party to a merchant operating the ecommerce website for payment of a referral fee. 19. The computing device of claim 15 , wherein the computing device is further configured to perform operations comprising: facilitating the sale of the one or more products/services that complement the one or more actions taken by the user.
| 0.74086 |
8,886,624 | 41 | 42 |
41. The method of claim 40 , wherein numerically expressing the association as the associated score comprises calculating a single associated score by applying an individual weight to the association indicator.
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41. The method of claim 40 , wherein numerically expressing the association as the associated score comprises calculating a single associated score by applying an individual weight to the association indicator. 42. The method of claim 41 , wherein numerically expressing the association as the associated score comprises calculating a plural keyword associated score based on the single keyword associated score, and the plural keyword associated score corresponds to a score calculated by numerically expressing an association between the associated keyword or the extended keyword and the other keywords.
| 0.5 |
8,442,813 | 11 | 19 |
11. A computer system for assessing the quality of computer-generated text, comprising: a processor for executing computer program instructions; a computer-readable storage medium storing executable computer program instructions, the computer program instructions comprising: a language-conditional character probability module executable to: receive a plurality of characters generated from an image of a document; and determine, for the plurality of characters generated from the image of the document, language-conditional character probabilities based on a set of language models and an ordering of the characters, a language-conditional character probability for a target character in the plurality of characters describing a degree to which the target character and an ordered set of characters preceding the target character concord with a given language model in the set of language models; and a local language-conditional likelihood module executable to: identify, for the target character, neighbor characters proximate to a location of the target character in the image of the document, wherein the neighbor characters have associated language-conditional character probabilities and are within a defined distance from the location of the target character in the image of the document; combine the language-conditional character probabilities associated with the neighbor characters and the language-conditional character probabilities associated with the target character to generate a local language-conditional likelihood for the target character, and store the local language-conditional likelihood for the target character.
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11. A computer system for assessing the quality of computer-generated text, comprising: a processor for executing computer program instructions; a computer-readable storage medium storing executable computer program instructions, the computer program instructions comprising: a language-conditional character probability module executable to: receive a plurality of characters generated from an image of a document; and determine, for the plurality of characters generated from the image of the document, language-conditional character probabilities based on a set of language models and an ordering of the characters, a language-conditional character probability for a target character in the plurality of characters describing a degree to which the target character and an ordered set of characters preceding the target character concord with a given language model in the set of language models; and a local language-conditional likelihood module executable to: identify, for the target character, neighbor characters proximate to a location of the target character in the image of the document, wherein the neighbor characters have associated language-conditional character probabilities and are within a defined distance from the location of the target character in the image of the document; combine the language-conditional character probabilities associated with the neighbor characters and the language-conditional character probabilities associated with the target character to generate a local language-conditional likelihood for the target character, and store the local language-conditional likelihood for the target character. 19. The system of claim 11 , wherein the language-conditional character probability module is further executable to receive information specifying locations of the plurality of characters within the image of the document, the information comprising two-dimensional coordinates, the defined distance between the neighbor characters and the target character is determined based on the two-dimensional coordinates, and the local language-conditional likelihood is associated with a location of the target character in the image of the document specified by the two-dimensional coordinates.
| 0.57101 |
9,112,972 | 10 | 15 |
10. A method comprising: converting, at a call routing system, an audio input of a call to text; determining a first set of objects and a second set of actions from the text at the call routing system; determining, at the call routing system, that a particular action of the second set is included in a first portion of a synonym table; replacing, at the call routing system, the particular action in the second set with a synonym for the particular action from the synonym table to form a modified second set; pairing, at the call routing system, an object from the first set with an action from the modified second set to form an object-action pair; and routing the call at the call routing system based on the object-action pair.
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10. A method comprising: converting, at a call routing system, an audio input of a call to text; determining a first set of objects and a second set of actions from the text at the call routing system; determining, at the call routing system, that a particular action of the second set is included in a first portion of a synonym table; replacing, at the call routing system, the particular action in the second set with a synonym for the particular action from the synonym table to form a modified second set; pairing, at the call routing system, an object from the first set with an action from the modified second set to form an object-action pair; and routing the call at the call routing system based on the object-action pair. 15. The method of claim 10 , wherein the call is a voice over Internet protocol call.
| 0.812775 |
9,984,069 | 16 | 17 |
16. An input method for completing a missing text or a phrase on a display of a terminal, comprising: displaying, by the terminal, a first text inputted by a user; displaying, by the terminal, a comma after the first text, the comma being directly to the right of the first text; displaying, by the terminal, a second text inputted by the user, the second text being directly to the right of the comma; displaying, by the terminal, a cursor at a first location, the first location being directly to the right of the second text; querying, by the terminal, for a first prediction text from a word library in a memory of the terminal by using one or more words within the second text as a context; displaying, by the terminal, the first prediction text directly to the right of the second text; displaying, by the terminal, the cursor at a second location, the second location of the cursor being to the left of the end of the first prediction text and to the right of the comma; querying, by the terminal, for a second prediction text from the word library in the memory of the terminal by using one or more words within text between the comma and the second location of the cursor as a context, displaying, by the terminal, the second prediction text.
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16. An input method for completing a missing text or a phrase on a display of a terminal, comprising: displaying, by the terminal, a first text inputted by a user; displaying, by the terminal, a comma after the first text, the comma being directly to the right of the first text; displaying, by the terminal, a second text inputted by the user, the second text being directly to the right of the comma; displaying, by the terminal, a cursor at a first location, the first location being directly to the right of the second text; querying, by the terminal, for a first prediction text from a word library in a memory of the terminal by using one or more words within the second text as a context; displaying, by the terminal, the first prediction text directly to the right of the second text; displaying, by the terminal, the cursor at a second location, the second location of the cursor being to the left of the end of the first prediction text and to the right of the comma; querying, by the terminal, for a second prediction text from the word library in the memory of the terminal by using one or more words within text between the comma and the second location of the cursor as a context, displaying, by the terminal, the second prediction text. 17. The input method according to claim 16 , wherein the first text is a phrase or a sentence.
| 0.505263 |
9,122,722 | 11 | 13 |
11. A system for optimizing a query in a multi-tenant database system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; generating an index corresponding to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; and optimizing the query request using the transformed query request, receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field.
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11. A system for optimizing a query in a multi-tenant database system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: receiving a query request with a query predicate to filter data returned in response to the query request, wherein the query predicate comprises a formula; generating an index corresponding to one tenant of the multi-tenant database system; preprocessing the formula in the query predicate based upon the generated index for the tenant to create a transformed query request, wherein the preprocessing includes: applying the generated index to a database field referenced in the formula, replacing at least one reference to a database field within the formula with a reference to a second database field based upon the generated index; and optimizing the query request using the transformed query request, receiving a query request with a reference to a first database field in the query predicate, wherein the first database field comprises the formula in the query predicate, wherein the formula comprises a reference to a second database field; and transforming the query request to a transformed query request by replacing the reference to the first database field within the query request with at least one reference to the second database field. 13. The system for optimizing a query in a database system of claim 11 , wherein the formula has a nested formula and the formula is flattened during preprocessing.
| 0.730263 |
8,281,149 | 1 | 13 |
1. A computer-implemented method of allowing user-selected anonymous and pseudonymous access for a user to a relying party (RP), mediated by an identity provider (IdP), comprising: registering with an IdP to establish a first pseudonym; upon successful proof of possession of the first pseudonym to the IdP, receiving a first representation of an access token from the IdP for accessing the RP; transforming, by a processor, the first representation of the access token to obtain a second representation of the access token, the second representation of the access token being a valid access token and is unlinkable to the first representation of the access token by the IdP; receiving a request from the user to access the RP; determining whether the request is for accessing the RP anonymously or pseudonymously; if the request is for anonymous access, providing the second representation of the access token to the RP anonymously; and gaining access to the RP upon verification of the second representation of the access token, the anonymous access being unlinkable to any previous and any future access at the RP, and unlinkable to the IdP's interaction with any particular user; if the request is for pseudonymous access, providing to the RP the second representation of the access token and proof of possession of a second pseudonym that is previously registered with the RP; and gaining access to the RP upon successful verification of the second representation of the access token and proof of possession of the second pseudonym, wherein the pseudonymous access is linkable to the second pseudonym, unlinkable to the IdP's interaction with any particular user, and unlinkable to any past and future access to the RP that does not employ the second pseudonym.
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1. A computer-implemented method of allowing user-selected anonymous and pseudonymous access for a user to a relying party (RP), mediated by an identity provider (IdP), comprising: registering with an IdP to establish a first pseudonym; upon successful proof of possession of the first pseudonym to the IdP, receiving a first representation of an access token from the IdP for accessing the RP; transforming, by a processor, the first representation of the access token to obtain a second representation of the access token, the second representation of the access token being a valid access token and is unlinkable to the first representation of the access token by the IdP; receiving a request from the user to access the RP; determining whether the request is for accessing the RP anonymously or pseudonymously; if the request is for anonymous access, providing the second representation of the access token to the RP anonymously; and gaining access to the RP upon verification of the second representation of the access token, the anonymous access being unlinkable to any previous and any future access at the RP, and unlinkable to the IdP's interaction with any particular user; if the request is for pseudonymous access, providing to the RP the second representation of the access token and proof of possession of a second pseudonym that is previously registered with the RP; and gaining access to the RP upon successful verification of the second representation of the access token and proof of possession of the second pseudonym, wherein the pseudonymous access is linkable to the second pseudonym, unlinkable to the IdP's interaction with any particular user, and unlinkable to any past and future access to the RP that does not employ the second pseudonym. 13. The method of claim 1 , further comprising: generating a temporary pseudonym based on the second pseudonym; interactively proving to the RP possession of the second pseudonym using the temporary pseudonym; and expunging linkage between the temporary pseudonym and the second pseudonym.
| 0.657583 |
9,009,022 | 10 | 15 |
10. A portable electronic system for language acquisition, the system comprising: at least one display screen operable to display on a first region of the at least one display screen a target language character group from a target language E-book comprising a target language; activating means operable to activate a user selection of the target language character group comprising a user selected location in the target language E-book book to provide a user selected target language; a pre-translated primary language electronic resource module operable to access a pre-translated primary language electronic resource in response to receiving the user selection to allocate a pre-translated primary language E-book comprising a pre-translated version of the target language E-book in a primary language to provide a pre-translated primary language character group; a searcher module operable to: estimate an estimated location of the pre-translated primary language character group in the pre-translated primary language E-book based on calculation of at least one parameter corresponding to the user selected location of the target language character group in the target language E-book; and instantly map the user selected target language in its entirety to the pre-translated primary language character group; a synchronization module operable to: receive a visual control by the user of movement of the pre-translated primary language character group in a second region of the at least one display screen by receiving activation of the at least one display screen based entirely on an input from the user; receive from the user a relative alignment coordination control of the pre-translated primary language character group to the target language character group based on the estimated location and the user selected location; and synchronize interactively by the user on the at least one display screen the pre-translated primary language character group in the second region to the target language character group in the first region on the at least one display screen to obtain a synchronized pre-translated primary language character group; and the at least one display screen further operable to: display only one instant of the pre-translated primary language character group comprising only the primary language in the second region of the at least one display screen separate from the target language in the first region and in proximity of the user selected target language in response to the user selection, the first region and the second region bounded within the at least one display screen; and simultaneously display on their respective separate regions of the at least one display screen the synchronized pre-translated primary language character group and the target language character group only at one display location near the user selected location of the target language E-book in response to a user interaction.
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10. A portable electronic system for language acquisition, the system comprising: at least one display screen operable to display on a first region of the at least one display screen a target language character group from a target language E-book comprising a target language; activating means operable to activate a user selection of the target language character group comprising a user selected location in the target language E-book book to provide a user selected target language; a pre-translated primary language electronic resource module operable to access a pre-translated primary language electronic resource in response to receiving the user selection to allocate a pre-translated primary language E-book comprising a pre-translated version of the target language E-book in a primary language to provide a pre-translated primary language character group; a searcher module operable to: estimate an estimated location of the pre-translated primary language character group in the pre-translated primary language E-book based on calculation of at least one parameter corresponding to the user selected location of the target language character group in the target language E-book; and instantly map the user selected target language in its entirety to the pre-translated primary language character group; a synchronization module operable to: receive a visual control by the user of movement of the pre-translated primary language character group in a second region of the at least one display screen by receiving activation of the at least one display screen based entirely on an input from the user; receive from the user a relative alignment coordination control of the pre-translated primary language character group to the target language character group based on the estimated location and the user selected location; and synchronize interactively by the user on the at least one display screen the pre-translated primary language character group in the second region to the target language character group in the first region on the at least one display screen to obtain a synchronized pre-translated primary language character group; and the at least one display screen further operable to: display only one instant of the pre-translated primary language character group comprising only the primary language in the second region of the at least one display screen separate from the target language in the first region and in proximity of the user selected target language in response to the user selection, the first region and the second region bounded within the at least one display screen; and simultaneously display on their respective separate regions of the at least one display screen the synchronized pre-translated primary language character group and the target language character group only at one display location near the user selected location of the target language E-book in response to a user interaction. 15. The system according to claim 10 , wherein the search module is further operable to search the pre-translated primary language E-book to map the pre-translated primary language character group from the pre-translated primary language E-book corresponding to the user selection of the target language character group in the target language E-book by estimating the estimated location, wherein the at least one parameter comprises: a chapter location, a section location, a position of a highlighted sentence, a number of starting sentences prior to highlighting a sentence, a previous synchronization position, a page number, or a combination thereof.
| 0.5 |
9,081,767 | 9 | 16 |
9. A non-transitory computer readable medium configured to store instructions for browsing a datastore of data objects, the instructions when executed by a processor perform steps comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence.
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9. A non-transitory computer readable medium configured to store instructions for browsing a datastore of data objects, the instructions when executed by a processor perform steps comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence. 16. The non-transitory computer readable medium of claim 9 , wherein providing, for display in a second region of the interface, one or more attributes of the first data object comprises providing, for display in the second region of the interface, one or more attributes of the first data object that are fewer than all the attributes of the first data object.
| 0.5 |
8,606,788 | 1 | 4 |
1. A system comprising: a dictionary manager embodied via executable instructions stored on a computer-readable storage medium, the dictionary manager including: an item input engine configured to obtain a plurality of item character strings, each item character string representing an item in a catalog, each item associated with a category; a brand input engine configured to obtain a plurality of brand character strings associated with the category; a brand matching engine configured to determine, for each item character string included in the plurality of item character strings, whether a matched substring of the each item character string represents a match with one of the obtained brand character strings; a matching indicator engine configured to generate a matching indicator indicating that the each item character string includes a match with the one of the obtained brand character strings, based on a match result of the matching determination by the brand matching engine; a correlated segment engine configured to obtain, for each one of the obtained brand character strings, and for each one of the item character strings that includes a match with the each one of the obtained brand character strings, one or more correlated segments, other than the matched substring, of the each one of the item character strings that includes a match with the each one of the obtained brand character strings, based on determining that the obtained correlated segments are correlated, greater than a predetermined correlation threshold, with the each one of the obtained brand character strings; a hierarchy generator configured to generate a dictionary hierarchy based on the obtained correlated segments; a catalog input engine configured to obtain the catalog, the catalog including a list of items represented by item character strings; a brand expansion engine configured to request an expanded list of brand values based on an initial list of brand values associated with the category; and a category determination engine configured to request a determination of the category associated with the plurality of item character strings, the item input engine configured to obtain the plurality of item character strings, each item character string representing an item in the catalog, each item associated with the category, based on the determination of the category determined by the category determination engine.
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1. A system comprising: a dictionary manager embodied via executable instructions stored on a computer-readable storage medium, the dictionary manager including: an item input engine configured to obtain a plurality of item character strings, each item character string representing an item in a catalog, each item associated with a category; a brand input engine configured to obtain a plurality of brand character strings associated with the category; a brand matching engine configured to determine, for each item character string included in the plurality of item character strings, whether a matched substring of the each item character string represents a match with one of the obtained brand character strings; a matching indicator engine configured to generate a matching indicator indicating that the each item character string includes a match with the one of the obtained brand character strings, based on a match result of the matching determination by the brand matching engine; a correlated segment engine configured to obtain, for each one of the obtained brand character strings, and for each one of the item character strings that includes a match with the each one of the obtained brand character strings, one or more correlated segments, other than the matched substring, of the each one of the item character strings that includes a match with the each one of the obtained brand character strings, based on determining that the obtained correlated segments are correlated, greater than a predetermined correlation threshold, with the each one of the obtained brand character strings; a hierarchy generator configured to generate a dictionary hierarchy based on the obtained correlated segments; a catalog input engine configured to obtain the catalog, the catalog including a list of items represented by item character strings; a brand expansion engine configured to request an expanded list of brand values based on an initial list of brand values associated with the category; and a category determination engine configured to request a determination of the category associated with the plurality of item character strings, the item input engine configured to obtain the plurality of item character strings, each item character string representing an item in the catalog, each item associated with the category, based on the determination of the category determined by the category determination engine. 4. The system of claim 1 , further comprising: a partition initialization engine configured to initialize a plurality of brand partition sets, each brand partition set associated with one of the obtained brand character strings, wherein the matching indicator engine is configured to generate the matching indicator based on updating the brand partition set associated with the one of the obtained brand character strings that matches the matched substring to indicate an addition of the item associated with the each item character string, based on a match result of the matching determination by the brand matching engine.
| 0.5 |
9,473,587 | 1 | 4 |
1. A method for generating an aggregated social feed, the method comprising: receiving a plurality of feeds, each feed including a plurality of content items and received from a social networking service; determining a relevance score for each of the plurality of content items based on one or more relevance factors; adjusting the relevance scores for each of one or more of the content items based on the social networking service from which the content item was received, where the adjusting comprises reducing or increasing the relevance score of the content item based on a number of other content items received from the same social networking service; ranking the content items based on the relevance scores thereof; selecting a plurality of the ranked content items based on ranking; and sending for display to a client device the selected content items in the aggregated social feed.
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1. A method for generating an aggregated social feed, the method comprising: receiving a plurality of feeds, each feed including a plurality of content items and received from a social networking service; determining a relevance score for each of the plurality of content items based on one or more relevance factors; adjusting the relevance scores for each of one or more of the content items based on the social networking service from which the content item was received, where the adjusting comprises reducing or increasing the relevance score of the content item based on a number of other content items received from the same social networking service; ranking the content items based on the relevance scores thereof; selecting a plurality of the ranked content items based on ranking; and sending for display to a client device the selected content items in the aggregated social feed. 4. The method of claim 1 , further comprising responsive to observing content associated with the plurality of content items, removing duplicate content items from the plurality of content items.
| 0.825269 |
8,214,196 | 8 | 9 |
8. The method of claim 1 , further comprising: generating a second string including the second word at each leaf.
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8. The method of claim 1 , further comprising: generating a second string including the second word at each leaf. 9. The method of claim 8 , further comprising: assigning a translation probability to the second string.
| 0.5 |
9,817,904 | 1 | 8 |
1. A method for providing augmented product specifications based on user reviews, comprising: obtaining input data of specifications and user reviews on a plurality of products, each product corresponding to a plurality of specifications and a plurality of user reviews, each specification including at least a pair of a feature and a feature-value of the product; concatenating the user reviews of the products to form product-documents, each product-document corresponding to the concatenated user reviews of a product; employing a topic model to process the input data and learn topic distributions in the product-documents and word distributions in topics, the topics including specifications of the products, the topic model being a type of statistical model for discovering topics that occur in a collection of product-documents, each product-document containing one or more topics, and each topic existing in one or more documents, the topics including specification-topics and review-topics, comprising: obtaining prior knowledge including known topic distributions in the product-documents and known word distributions in the topics, and obtaining a type of each word, wherein the type of the word identifies whether the word is a product-specific word or a specification word, and the prior knowledge of known topic distributions in the product-documents further includes known specification-topic distributions in the product-documents and known review-topic distribution in the product-documents separately; incorporating the prior knowledge and employing the topic model to process the input data and learn the topic distributions in the product-documents and the word distributions in the topics; and obtaining an outcome from the topic model, the outcome including learned topic distributions in the product-documents and learned word distributions in the topics; and providing augmented specifications to a user based on the topic model, the augmented specifications including one or more of relevant sentences of the feature-value, feature importance information, and product-specific words of the product, wherein providing augmented specifications based on the topic model further comprises: when the user hovers a cursor on a product feature-value, displaying the relevant sentences in a float box according to a position of the cursor; ranking and displaying the feature importance information in a separate column corresponding to the product features; and displaying the product-specific words in a separate row, wherein the font size and color of the word corresponds to how specific the word is to the product; and wherein, provided that, the prior knowledge about a distribution of a specific word w in a feature topic f is denoted as p(w|f), the known word distributions in the feature-topics follows Zipf's law distribution; a new prior pβ²(w|f) for each word w is defined as: p β² β‘ ( w β f ) = { p β‘ ( w β f ) Ξ£ w β v β‘ ( f ) β’ p β‘ ( w β f ) β’ β i = 1 ο v β‘ ( f ) β V ο β’ Zipf β‘ ( i ) if β’ β’ w β v β‘ ( f ) Zipf β‘ ( rank f β‘ ( w ) ) otherwise β’ wherein v(f) is a vocabulary in f, V is a vocabulary in all reviews, rank f (w) is w's rank in p(w|f) excluding words in v(f), and Zipf's law distribution function Zipf(i) is defined as Zipf β‘ ( i ) = 1 / i s β n = 1 ο V ο β’ β’ 1 / n s wherein s is a parameter characterizing the distribution.
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1. A method for providing augmented product specifications based on user reviews, comprising: obtaining input data of specifications and user reviews on a plurality of products, each product corresponding to a plurality of specifications and a plurality of user reviews, each specification including at least a pair of a feature and a feature-value of the product; concatenating the user reviews of the products to form product-documents, each product-document corresponding to the concatenated user reviews of a product; employing a topic model to process the input data and learn topic distributions in the product-documents and word distributions in topics, the topics including specifications of the products, the topic model being a type of statistical model for discovering topics that occur in a collection of product-documents, each product-document containing one or more topics, and each topic existing in one or more documents, the topics including specification-topics and review-topics, comprising: obtaining prior knowledge including known topic distributions in the product-documents and known word distributions in the topics, and obtaining a type of each word, wherein the type of the word identifies whether the word is a product-specific word or a specification word, and the prior knowledge of known topic distributions in the product-documents further includes known specification-topic distributions in the product-documents and known review-topic distribution in the product-documents separately; incorporating the prior knowledge and employing the topic model to process the input data and learn the topic distributions in the product-documents and the word distributions in the topics; and obtaining an outcome from the topic model, the outcome including learned topic distributions in the product-documents and learned word distributions in the topics; and providing augmented specifications to a user based on the topic model, the augmented specifications including one or more of relevant sentences of the feature-value, feature importance information, and product-specific words of the product, wherein providing augmented specifications based on the topic model further comprises: when the user hovers a cursor on a product feature-value, displaying the relevant sentences in a float box according to a position of the cursor; ranking and displaying the feature importance information in a separate column corresponding to the product features; and displaying the product-specific words in a separate row, wherein the font size and color of the word corresponds to how specific the word is to the product; and wherein, provided that, the prior knowledge about a distribution of a specific word w in a feature topic f is denoted as p(w|f), the known word distributions in the feature-topics follows Zipf's law distribution; a new prior pβ²(w|f) for each word w is defined as: p β² β‘ ( w β f ) = { p β‘ ( w β f ) Ξ£ w β v β‘ ( f ) β’ p β‘ ( w β f ) β’ β i = 1 ο v β‘ ( f ) β V ο β’ Zipf β‘ ( i ) if β’ β’ w β v β‘ ( f ) Zipf β‘ ( rank f β‘ ( w ) ) otherwise β’ wherein v(f) is a vocabulary in f, V is a vocabulary in all reviews, rank f (w) is w's rank in p(w|f) excluding words in v(f), and Zipf's law distribution function Zipf(i) is defined as Zipf β‘ ( i ) = 1 / i s β n = 1 ο V ο β’ β’ 1 / n s wherein s is a parameter characterizing the distribution. 8. The method according to claim 1 , wherein providing augmented specifications based on the topic model further comprises: providing that f denotes a product feature, N i denotes number of words in document i, s denotes a specification, z denotes a topic, when feature-value pairs are not separated when generating the prior knowledge, after obtaining the outcome from the topic model, defining the importance of a feature as p β‘ ( f ) = β z β f β’ N s = z N x = 1 when features and feature-values are separated when generating the prior knowledge, after obtaining the outcome from the topic model, defining the importance of a feature as p β‘ ( f ) = N f N x = 1 .
| 0.5 |
8,117,199 | 7 | 8 |
7. The method of 6 , wherein the at least one description for each product comprises marketing information, corresponding to the product offerings, provided by the entity.
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7. The method of 6 , wherein the at least one description for each product comprises marketing information, corresponding to the product offerings, provided by the entity. 8. The method of claim 7 , wherein the marketing information is available via a web page.
| 0.5 |
8,768,910 | 3 | 6 |
3. The method of claim 1 , where identifying that the search query is associated with the type of media includes: determining whether the candidate queries match words in a keyword list associated with the type of media, and identifying, based on the first ratio and the second ratio, that the search query is associated with the type of media when the category matches one of the candidate queries and when the candidate queries match the words in the keyword list.
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3. The method of claim 1 , where identifying that the search query is associated with the type of media includes: determining whether the candidate queries match words in a keyword list associated with the type of media, and identifying, based on the first ratio and the second ratio, that the search query is associated with the type of media when the category matches one of the candidate queries and when the candidate queries match the words in the keyword list. 6. The method of claim 3 , where determining whether the candidate queries match the words in the keyword list includes: determining a sum of values associated with one or more of the words in the keyword list that match one or more words included in the candidate queries, and determining that the candidate queries match the words in the keyword list when the sum of the values is greater than a threshold.
| 0.510791 |
8,506,304 | 6 | 7 |
6. The method of claim 5 wherein the recommendation of a teaching plan includes a student group recommendation for group activities.
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6. The method of claim 5 wherein the recommendation of a teaching plan includes a student group recommendation for group activities. 7. The method of claim 6 wherein the recommendation of a teaching plan includes a recommended lesson plan using resources available to the teacher and students.
| 0.5 |
7,801,942 | 1 | 2 |
1. A network search platform, comprising: a spider structured to surf a network, to collect textual information of at least one webpage of at least one website of the network, and to store the textual information in a database; a robot browser structured to take at least one snap-shot image of the at least one webpage; resolution means for parsing the textual information and queuing a request to the robot browser to take the at least one snap-shot image responsive to the textual information of the at least one webpage; user selectable options configurable to provide first search results responsive to keywords entered by at least one user of the network, the first search results to show at least some of the textual information of the at least one webpage; and user services configurable to collect demographic information of the at least one user of the network, wherein the user selectable options are further configurable to provide the first search results responsive to the demographic information.
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1. A network search platform, comprising: a spider structured to surf a network, to collect textual information of at least one webpage of at least one website of the network, and to store the textual information in a database; a robot browser structured to take at least one snap-shot image of the at least one webpage; resolution means for parsing the textual information and queuing a request to the robot browser to take the at least one snap-shot image responsive to the textual information of the at least one webpage; user selectable options configurable to provide first search results responsive to keywords entered by at least one user of the network, the first search results to show at least some of the textual information of the at least one webpage; and user services configurable to collect demographic information of the at least one user of the network, wherein the user selectable options are further configurable to provide the first search results responsive to the demographic information. 2. A network search platform according to claim 1 , wherein the user selectable options are further configurable to provide second search results to show only the at least one snap-shot image of the at least one webpage.
| 0.5 |
7,613,684 | 1 | 6 |
1. An information retrieval system, comprising: a search query generator, in a computer, responsive to a selection of a level within a hierarchical relationship of terms describing an organizational framework for information, for constructing a search query of terms that are based upon the selected level, and for providing the search query of terms to a search engine to search any of a plurality of information sources selected by a user; and a user interface which provides information about documents located at a user-selected information source by the search engine documents to said user.
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1. An information retrieval system, comprising: a search query generator, in a computer, responsive to a selection of a level within a hierarchical relationship of terms describing an organizational framework for information, for constructing a search query of terms that are based upon the selected level, and for providing the search query of terms to a search engine to search any of a plurality of information sources selected by a user; and a user interface which provides information about documents located at a user-selected information source by the search engine documents to said user. 6. The information retrieval system of claim 1 , wherein said search engine analyzes a selected document among said located documents to determine which of the terms in a hierarchy said selected document most closely relates to, wherein said user interface displays values which identify the relevance of the selected document to levels in the selected hierarchy.
| 0.50274 |
8,571,187 | 2 | 3 |
2. The method according to claim 1 further comprising selecting the message term based on an input.
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2. The method according to claim 1 further comprising selecting the message term based on an input. 3. The method according to claim 2 wherein the input further comprises a cursor near the message term.
| 0.5 |
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