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1. A method for providing information to a plurality of users based on the relevancy of the information to the users, the method comprising steps of: (A) receiving an incoming message; (B) generating similarity scores indicating similarities of the incoming message to features of a plurality of messages previously received, wherein each similarity score is generated based on a comparison of the incoming message to one of the plurality of messages and indicates a degree of similarity between the incoming message and the one of the plurality of messages; (C) generating relevancy scores for the plurality of users, the relevancy scores indicating relevancies of the incoming message to the plurality of users based on the similarity scores and a plurality of user profiles including information descriptive of the plurality of users' preferences for the features of the plurality of users; and (D) delivering, to at least some of the plurality of users, message information derived from the incoming message, the relevancy scores, and the plurality of user profiles.
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1. A method for providing information to a plurality of users based on the relevancy of the information to the users, the method comprising steps of: (A) receiving an incoming message; (B) generating similarity scores indicating similarities of the incoming message to features of a plurality of messages previously received, wherein each similarity score is generated based on a comparison of the incoming message to one of the plurality of messages and indicates a degree of similarity between the incoming message and the one of the plurality of messages; (C) generating relevancy scores for the plurality of users, the relevancy scores indicating relevancies of the incoming message to the plurality of users based on the similarity scores and a plurality of user profiles including information descriptive of the plurality of users' preferences for the features of the plurality of users; and (D) delivering, to at least some of the plurality of users, message information derived from the incoming message, the relevancy scores, and the plurality of user profiles. 3. The method of claim 1 , wherein the plurality of user profiles include a preference matrix indicating preferences of the plurality of users for the features, and wherein the step (C) comprises a step of: (C)(1) generating the relevancy scores by performing vector multiplication of a vector representing the similarity scores by vectors in the preference matrix.
| 0.502769 |
29. A system comprising: a programmable processor; and a memory storing instructions operable to cause the programmable processor to: receive a first content in a software application, the software application implementing a first operation that is disabled by default; receive a request to operate on the first content using the first operation; in response to the request, retrieve a first enabler from a database, the first enabler specifying to the software application an enablement of the first operation only with respect to the first content; and as a result of the retrieval of the first enabler, enable the first operation to operate on the first content within an operating context specified in the first enabler.
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29. A system comprising: a programmable processor; and a memory storing instructions operable to cause the programmable processor to: receive a first content in a software application, the software application implementing a first operation that is disabled by default; receive a request to operate on the first content using the first operation; in response to the request, retrieve a first enabler from a database, the first enabler specifying to the software application an enablement of the first operation only with respect to the first content; and as a result of the retrieval of the first enabler, enable the first operation to operate on the first content within an operating context specified in the first enabler. 33. The system of claim 29 , wherein to retrieve the first enabler from the database, the processor is operable to query the database for an enabler that enables the first operation to operate on the first content.
| 0.676883 |
1. A machine-implemented method, comprising: determining that a first user of a first mobile communication device is engaged in a call over a communications network; providing an adaptive speech recognition model comprising a speaker-dependent speech recognition model; after providing the adaptive speech recognition model, analyzing an outbound audio channel of a baseband unit of the first mobile communication device to obtain a call audio signal corresponding to audio input from one or more microphones of the first mobile communication device; and updating the adaptive speech recognition model with training data derived from the call audio signal.
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1. A machine-implemented method, comprising: determining that a first user of a first mobile communication device is engaged in a call over a communications network; providing an adaptive speech recognition model comprising a speaker-dependent speech recognition model; after providing the adaptive speech recognition model, analyzing an outbound audio channel of a baseband unit of the first mobile communication device to obtain a call audio signal corresponding to audio input from one or more microphones of the first mobile communication device; and updating the adaptive speech recognition model with training data derived from the call audio signal. 7. The method of claim 1 , wherein updating the adaptive speech recognition model comprises: comparing the call audio signal with the adaptive speech recognition model; generating a confidence score based on the comparison; in accordance with a determination that the confidence score is at or above a predetermined threshold, updating the adaptive speech recognition model with the training data derived from the call audio signal; and in accordance with a determination that the confidence score is below the predetermined threshold, forgoing to update the adaptive speech recognition model.
| 0.566129 |
17. A method for obtaining and rendering audio based on text in an electronic book (eBook), the method comprising: sending, from an eBook reader device, a request to download the eBook; receiving, at the eBook reader device, the eBook, a supplemental pronunciation database, and specified voice information for synthesizing speech in a specified voice; synthesizing a first speech for a first portion of text in the eBook based at least in part on a pronunciation from the supplemental pronunciation database for portions of text which have pronunciations in the supplemental pronunciation database; synthesizing a second speech for a second portion of text in the eBook based at least in part on a pronunciation from a default pronunciation database for portions of text which do not have pronunciations in the supplemental pronunciation database; synthesizing a third speech for a third portion of text in the eBook based at least in part on the specified voice for portions of text which are specified to be synthesized with the specified voice; and synthesizing a fourth speech for a fourth portion of text based at least in part on a default voice for portions of text which do not have any specified voice.
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17. A method for obtaining and rendering audio based on text in an electronic book (eBook), the method comprising: sending, from an eBook reader device, a request to download the eBook; receiving, at the eBook reader device, the eBook, a supplemental pronunciation database, and specified voice information for synthesizing speech in a specified voice; synthesizing a first speech for a first portion of text in the eBook based at least in part on a pronunciation from the supplemental pronunciation database for portions of text which have pronunciations in the supplemental pronunciation database; synthesizing a second speech for a second portion of text in the eBook based at least in part on a pronunciation from a default pronunciation database for portions of text which do not have pronunciations in the supplemental pronunciation database; synthesizing a third speech for a third portion of text in the eBook based at least in part on the specified voice for portions of text which are specified to be synthesized with the specified voice; and synthesizing a fourth speech for a fourth portion of text based at least in part on a default voice for portions of text which do not have any specified voice. 24. The method of claim 17 , further comprising storing the eBook, the supplemental pronunciation database, and the specified voice information on the eBook reader device.
| 0.643505 |
1. A computer-implemented method comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, by one or more computer systems a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining by the one or more computer systems a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation.
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1. A computer-implemented method comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, by one or more computer systems a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining by the one or more computer systems a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation. 15. The method of claim 1 , wherein the selected predefined number of search results include at least the search result that is returned from the second, different search engine and that is associated with the second search engine ranking score or the search result that is returned from the first search engine and that is associated with the first search engine ranking score.
| 0.716741 |
1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object.
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1. A method of visualization of a set of objects in a computer graphic interface, comprising: defining a hierarchy of objects, the hierarchy of objects having hierarchal relationships between a plurality of objects each having associated content, a hierarchal organization of the hierarchy of objects being related to a respective content of an object and being included within the hierarchy based on satisfaction of a set of inclusion criteria; and supplementing the hierarchy with at least one additional object which does not satisfy the set of inclusion criteria, the at least one additional object being selectively placed within the hierarchy of objects based on an associated content of objects within the hierarchy of objects near the placement position of the at least the additional object and an associated content of the respective additional object. 9. The method according to claim 1 , wherein an object or additional object is selected, and the hierarchy is then transformed to place the selected object or additional object at a root node of the hierarchy.
| 0.540469 |
27. A non-transitory computer-readable storage medium for building a trait model for essay evaluation, the computer-readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model.
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27. A non-transitory computer-readable storage medium for building a trait model for essay evaluation, the computer-readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. 35. The non-transitory computer-readable storage medium of claim 27 , wherein the received at least one evaluated essay has been evaluated on 50 or more features.
| 0.722749 |
4. The information handling system of claim 1 wherein the actions further comprise: selecting a leading candidate word from the plurality of candidate words, wherein the leading candidate word corresponds to the leading morpheme; selecting a trailing candidate word from the plurality of candidate words, wherein the trailing candidate word corresponds to the trailing morpheme; and generating a possible meaning of the portmanteau by combining a first meaning that corresponds to the leading candidate word with a second meaning that corresponds to the trailing candidate word, wherein the combined usage is based on the generated possible meaning.
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4. The information handling system of claim 1 wherein the actions further comprise: selecting a leading candidate word from the plurality of candidate words, wherein the leading candidate word corresponds to the leading morpheme; selecting a trailing candidate word from the plurality of candidate words, wherein the trailing candidate word corresponds to the trailing morpheme; and generating a possible meaning of the portmanteau by combining a first meaning that corresponds to the leading candidate word with a second meaning that corresponds to the trailing candidate word, wherein the combined usage is based on the generated possible meaning. 5. The information handling system of claim 4 wherein the actions further comprise: performing the selecting and generating steps for a plurality of leading and trailing candidate words, wherein the information handling system further comprises: scoring a plurality of generated possible meanings of the portmanteau based on a plurality of combinations of leading and trailing candidate words; and further scoring the plurality of generated possible meanings based on a contextual usage score based on comparing the possible meanings with a contextual usage of the portmanteau in the electronic documents, wherein the combined usage is based on a best scored combination of a selected one of the leading candidate words paired with a selected one of the trailing candidate words.
| 0.785949 |
36. The device defined in claim 35 wherein said peripheral device is a computer capable of receiving electric information from said communication port and displaying said electric information on a computer terminal.
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36. The device defined in claim 35 wherein said peripheral device is a computer capable of receiving electric information from said communication port and displaying said electric information on a computer terminal. 37. The device defined in claim 36 wherein said computer is connected to said communication port via a modem.
| 0.961918 |
4. A table-shuffle stream cipher system comprising: physical computing machinery including: a pseudo-random number generator adapted to maintain at least one stream cipher table having N entries, one traversal index and at least one pseudo-random index; a state update module adapted to update a state of the at least one stream cipher table by: determining a new value of the traversal index, the new value of the traversal index being independent of the pseudo-random index and the entries of the at least one stream cipher table; determining a new value of the pseudo-random index based upon at least one of the entries of the at least one stream cipher table such that the new value of the pseudo-random index is at least biased away from at least one undesirable value of the N possible values of the pseudo-random index; and swapping the entry associated with the new value of the traversal index with the entry associated with the new value of the pseudo-random index; and an output word module adapted to generate an output word as a function of the new value of the traversal index and the new value of the pseudo-random index.
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4. A table-shuffle stream cipher system comprising: physical computing machinery including: a pseudo-random number generator adapted to maintain at least one stream cipher table having N entries, one traversal index and at least one pseudo-random index; a state update module adapted to update a state of the at least one stream cipher table by: determining a new value of the traversal index, the new value of the traversal index being independent of the pseudo-random index and the entries of the at least one stream cipher table; determining a new value of the pseudo-random index based upon at least one of the entries of the at least one stream cipher table such that the new value of the pseudo-random index is at least biased away from at least one undesirable value of the N possible values of the pseudo-random index; and swapping the entry associated with the new value of the traversal index with the entry associated with the new value of the pseudo-random index; and an output word module adapted to generate an output word as a function of the new value of the traversal index and the new value of the pseudo-random index. 5. The system according to claim 4 , wherein the state update module is adapted to determine the new value of the pseudo-random index so that the new value of the pseudo-random index excludes the at least one undesirable value.
| 0.618694 |
17. An apparatus for speech parameterization and coding of a continuous speech signal, comprising: at least one input interface for receiving and digitizing said continuous speech signal; at least one processing unit for performing the actions of: receiving a continuous speech signal representing speech recorded by at least one microphone, dividing said continuous speech signal into a plurality of speech frames, and for each one of said plurality of speech frames: modeling said speech frame by a first harmonic model to produce a plurality of frame model parameter values and harmonic model residual, wherein said first harmonic modeling is estimated by computing a cost function between a plurality of sine function signals and said speech frame, wherein each of said plurality of sine function signals comprises one of a plurality of harmonic frequencies, an amplitude value and a phrase value; performing at least one second harmonic modeling analysis on said first harmonic model residual to remove at least one set of second harmonic model component values from said first harmonic model residual signal to produce a harmonically-filtered residual signal; and processing said harmonically-filtered residual signal with analysis by synthesis techniques to produce vectors of codebook indices and corresponding gains, and sending said plurality of harmonic model parameter values and said codebook vector indices and corresponding gains to a speech processor configured to compute at least one of a speech transformation, a signal compression and a conversion to an audible sound output; at least one output interface to send said plurality of speech parameter values and codes; and a housing for containing said at least one input interface, said at least one processing unit, and said at least one output interface, said housing being configured and suitable for the apparatus environment.
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17. An apparatus for speech parameterization and coding of a continuous speech signal, comprising: at least one input interface for receiving and digitizing said continuous speech signal; at least one processing unit for performing the actions of: receiving a continuous speech signal representing speech recorded by at least one microphone, dividing said continuous speech signal into a plurality of speech frames, and for each one of said plurality of speech frames: modeling said speech frame by a first harmonic model to produce a plurality of frame model parameter values and harmonic model residual, wherein said first harmonic modeling is estimated by computing a cost function between a plurality of sine function signals and said speech frame, wherein each of said plurality of sine function signals comprises one of a plurality of harmonic frequencies, an amplitude value and a phrase value; performing at least one second harmonic modeling analysis on said first harmonic model residual to remove at least one set of second harmonic model component values from said first harmonic model residual signal to produce a harmonically-filtered residual signal; and processing said harmonically-filtered residual signal with analysis by synthesis techniques to produce vectors of codebook indices and corresponding gains, and sending said plurality of harmonic model parameter values and said codebook vector indices and corresponding gains to a speech processor configured to compute at least one of a speech transformation, a signal compression and a conversion to an audible sound output; at least one output interface to send said plurality of speech parameter values and codes; and a housing for containing said at least one input interface, said at least one processing unit, and said at least one output interface, said housing being configured and suitable for the apparatus environment. 20. The apparatus of claim 17 , wherein said at least one output interface is any member of the group comprising: a digital communication interface; and an audio output interface.
| 0.55373 |
1. A system comprising: one or more devices configured to: receive a first search query; determine that the first search query includes a first entity name and that the first entity name does not correspond to one of a plurality of common words or phrases; rewrite the first search query to include a first restrict identifier that restricts a search, based on the rewritten first search query, to a first domain associated with the first entity name, in response to determining that the first search query includes a first entity name and that the first entity name does not correspond to one of the plurality of common words or phrases; perform a search, based on the rewritten first search query, to obtain first search results; and present the first search results.
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1. A system comprising: one or more devices configured to: receive a first search query; determine that the first search query includes a first entity name and that the first entity name does not correspond to one of a plurality of common words or phrases; rewrite the first search query to include a first restrict identifier that restricts a search, based on the rewritten first search query, to a first domain associated with the first entity name, in response to determining that the first search query includes a first entity name and that the first entity name does not correspond to one of the plurality of common words or phrases; perform a search, based on the rewritten first search query, to obtain first search results; and present the first search results. 8. The system of claim 1 , where at least one of the one or more devices is further to: obtain entity names from one or more of an online directory, a group posting, or a corpus of documents, and where, when determining that the first search query includes a first entity name, at least one of the one or more devices is to: determine that the first search query includes a first entity name based on the obtained entity names.
| 0.578345 |
7. The method of claim 1 , wherein the sending comprises: identifying, for the at least one topic, a connection among those of the users who are associated with the at least one topic.
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7. The method of claim 1 , wherein the sending comprises: identifying, for the at least one topic, a connection among those of the users who are associated with the at least one topic. 8. The method of claim 7 , wherein the identifying the connection comprises: filtering the one or more interactions according to the at least one topic.
| 0.917794 |
1. A network device, comprising: a transceiver to send and receive data over a network; and a processor that is operative on the received data to perform actions, including: receiving a message having at least one attachment; using a machine learning model to select at least one sentence from within the message to be relevant to the at least one attachment based on a set of predefined sentence level features; identifying from within the relevant sentence at least one keyword determined to be further relevant to the at least one attachment; and associating the at least one keyword to the at least one attachment, such that the association is useable for at least one of indexing or searching of the at least one attachment.
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1. A network device, comprising: a transceiver to send and receive data over a network; and a processor that is operative on the received data to perform actions, including: receiving a message having at least one attachment; using a machine learning model to select at least one sentence from within the message to be relevant to the at least one attachment based on a set of predefined sentence level features; identifying from within the relevant sentence at least one keyword determined to be further relevant to the at least one attachment; and associating the at least one keyword to the at least one attachment, such that the association is useable for at least one of indexing or searching of the at least one attachment. 5. The network device of claim 1 , wherein the at least one attachment includes at least one of a spreadsheet file, an image file, a video file, an audio file, or a word processing document file.
| 0.874198 |
28. The computer program product of claim 27 , further comprising computer-readable instruction means for iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished.
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28. The computer program product of claim 27 , further comprising computer-readable instruction means for iteratively repeating the search using the refined classifier and feature/attention model until the search goal is accomplished. 29. The computer program product of claim 28 , wherein in a case where the domain knowledge database contains no feature/attention models relating to the search goal, searching is performed using unbiased, center-surround type saliency algorithms.
| 0.896552 |
10. A computer-readable storage medium for storing computer-readable instructions to instruct a processor of a processing system to execute a computer implemented method of providing a user interface for a search method, the search method aided by a set of topics, the topics not necessarily having a hierarchy, each topic having at least one attachment to at least one information item of a plurality of information items, the method comprising: causing a first user interface to be displayed to a first searcher, the user interface providing for the searcher to input search request information including at least one of the group consisting of a search phrase and a subset of one or more search topics of the set of topics; carrying out the search method, the search method including: accepting the search request information input by the first searcher; identifying one or more information items of the plurality of information items according to the accepted search request information; and determining one or more suggested topics from the set of topics, the suggested topics being determined according to the attachments of the suggested topics to the one or more identified information items; and as a result of carrying out the search method, causing a second user interface to be displayed to the first searcher, the second user interface including at least some of the identified information items and at least one of the suggested topics, the second user interface providing for the first searcher the ability to select one of the suggested topics, wherein the suggested topics include one or more refinement topics determined from the set of topics according to a refinement topic criterion using a refinement selection method, such that the first searcher selecting one of the suggested topics using the displayed second user interface generates additional results.
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10. A computer-readable storage medium for storing computer-readable instructions to instruct a processor of a processing system to execute a computer implemented method of providing a user interface for a search method, the search method aided by a set of topics, the topics not necessarily having a hierarchy, each topic having at least one attachment to at least one information item of a plurality of information items, the method comprising: causing a first user interface to be displayed to a first searcher, the user interface providing for the searcher to input search request information including at least one of the group consisting of a search phrase and a subset of one or more search topics of the set of topics; carrying out the search method, the search method including: accepting the search request information input by the first searcher; identifying one or more information items of the plurality of information items according to the accepted search request information; and determining one or more suggested topics from the set of topics, the suggested topics being determined according to the attachments of the suggested topics to the one or more identified information items; and as a result of carrying out the search method, causing a second user interface to be displayed to the first searcher, the second user interface including at least some of the identified information items and at least one of the suggested topics, the second user interface providing for the first searcher the ability to select one of the suggested topics, wherein the suggested topics include one or more refinement topics determined from the set of topics according to a refinement topic criterion using a refinement selection method, such that the first searcher selecting one of the suggested topics using the displayed second user interface generates additional results. 11. A storage medium as recited in claim 10 , wherein at most a pre-determined number of refinement topics are displayed to the viewer.
| 0.545904 |
17. The computer-readable medium of claim 16, wherein said instructions for executing the step of selecting a first training document to be a least-relevant document comprise instructions for executing the steps of: determining an absolute relevance score of each of said plurality of training documents in said first set of training data, each absolute relevance score being indicative of an extent to which said training document includes preferred content; sorting said plurality of training documents in said first set of training data on the basis of their absolute relevance scores to form a sorted list; and specifying a least relevant training document in said sorted list.
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17. The computer-readable medium of claim 16, wherein said instructions for executing the step of selecting a first training document to be a least-relevant document comprise instructions for executing the steps of: determining an absolute relevance score of each of said plurality of training documents in said first set of training data, each absolute relevance score being indicative of an extent to which said training document includes preferred content; sorting said plurality of training documents in said first set of training data on the basis of their absolute relevance scores to form a sorted list; and specifying a least relevant training document in said sorted list. 18. The computer-readable medium of claim 17, wherein said sorted list includes a most relevant document having an absolute relevance score higher than said absolute relevance scores of all other training documents in said sorted list and a least relevant document having an absolute relevance score lower than said absolute relevance scores of all other training documents in said sorted list, and wherein said step of performing a binary search comprises the step of comparing said absolute relevance score of said newly-received document with a statistical average of said absolute relevance scores of said most relevant document and said least relevant document.
| 0.670434 |
11. A system comprising: one or more computers configured to perform operations comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was extracted identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values.
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11. A system comprising: one or more computers configured to perform operations comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was extracted identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values. 15. The system of claim 11 , wherein using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values includes comparing a plurality of candidate pairings of candidate attributes with candidate values to attributes on the expanded attribute whitelist.
| 0.872851 |
1. A method comprising: transforming an input audio training signal, using one or more processors of a system, into a sequence of feature vectors, each feature vector of the sequence bearing quantitative measures of acoustic properties of the input audio training signal; processing the sequence of feature vectors with an auto-encoder implemented by the one or more processors to generate (i) an encoded form of the quantitative measures, and (ii) a recovered form of the quantitative measures based on an inverse operation by the auto-encoder on the encoded form of the quantitative measures; processing a duplicate copy of the sequence of feature vectors with a normalizer implemented by the one or more processors to generate a normalized form of the quantitative measures in which supra-phonetic acoustic properties of the input audio training signal are reduced in comparison with phonetic acoustic properties of the input audio training signal; determining an error signal based on a difference between the normalized form of the quantitative measures and the recovered form of the quantitative measures; providing the error signal to the auto-encoder; and by adjusting parameters of the auto-encoder to reduce the magnitude of the error signal, training the auto-encoder to compensate for supra-phonetic acoustic properties of input audio signals.
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1. A method comprising: transforming an input audio training signal, using one or more processors of a system, into a sequence of feature vectors, each feature vector of the sequence bearing quantitative measures of acoustic properties of the input audio training signal; processing the sequence of feature vectors with an auto-encoder implemented by the one or more processors to generate (i) an encoded form of the quantitative measures, and (ii) a recovered form of the quantitative measures based on an inverse operation by the auto-encoder on the encoded form of the quantitative measures; processing a duplicate copy of the sequence of feature vectors with a normalizer implemented by the one or more processors to generate a normalized form of the quantitative measures in which supra-phonetic acoustic properties of the input audio training signal are reduced in comparison with phonetic acoustic properties of the input audio training signal; determining an error signal based on a difference between the normalized form of the quantitative measures and the recovered form of the quantitative measures; providing the error signal to the auto-encoder; and by adjusting parameters of the auto-encoder to reduce the magnitude of the error signal, training the auto-encoder to compensate for supra-phonetic acoustic properties of input audio signals. 9. The method of claim 1 , wherein providing the error signal to the auto-encoder comprises providing the error signal to the auto-encoder concurrently with processing the sequence of feature vectors with the auto-encoder.
| 0.693182 |
1. A system comprising: at least one processor; at least one navigation application, executable by the at least one processor, configured to cause a current page to be displayed on a device, the current page comprising a plurality of user-selectable functional options that include a functional option configured to lead to a first different page and a functional option configured to lead to a second different page, the first and second different pages being different from each other and from the current page, the first different page comprising a plurality of functional options respectively configured to be acted upon by a user; and at least one contextual breadcrumb application, executable by the at least one processor, configured to cause contextual breadcrumbs to be displayed on the current page, the contextual breadcrumbs comprising: a simplified representation of the first different page, the simplified representation of the first different page comprising context information that comprises a visual representation of the plurality of functional options of the first different page, and the simplified representation of the first different page excluding at least some content of the first different page, at least one of the contextual breadcrumbs being configured to enable the user to act upon the plurality of functional options of the first different page from the current page; a simplified representation of the second different page, the second different page having not yet been displayed on the device in response to user selection of a corresponding one of the plurality of functional options of the current page, the simplified representation of the second different page excluding at least some content of the second different page and including one or more actionable interface elements selectable by the user from the current page to act upon respectively corresponding functional options of the second different page; and a flow from the simplified representation of the current page to the simplified representation of the second different page.
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1. A system comprising: at least one processor; at least one navigation application, executable by the at least one processor, configured to cause a current page to be displayed on a device, the current page comprising a plurality of user-selectable functional options that include a functional option configured to lead to a first different page and a functional option configured to lead to a second different page, the first and second different pages being different from each other and from the current page, the first different page comprising a plurality of functional options respectively configured to be acted upon by a user; and at least one contextual breadcrumb application, executable by the at least one processor, configured to cause contextual breadcrumbs to be displayed on the current page, the contextual breadcrumbs comprising: a simplified representation of the first different page, the simplified representation of the first different page comprising context information that comprises a visual representation of the plurality of functional options of the first different page, and the simplified representation of the first different page excluding at least some content of the first different page, at least one of the contextual breadcrumbs being configured to enable the user to act upon the plurality of functional options of the first different page from the current page; a simplified representation of the second different page, the second different page having not yet been displayed on the device in response to user selection of a corresponding one of the plurality of functional options of the current page, the simplified representation of the second different page excluding at least some content of the second different page and including one or more actionable interface elements selectable by the user from the current page to act upon respectively corresponding functional options of the second different page; and a flow from the simplified representation of the current page to the simplified representation of the second different page. 9. The system of claim 1 , wherein the current page and the first different page are web pages.
| 0.546061 |
11. The method as claimed in claim 9 comprising the steps of: identifying the candidate text string comprising the highest rating; comparing the said highest rating with a second threshold value; determining whether to create the label based upon the said comparison.
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11. The method as claimed in claim 9 comprising the steps of: identifying the candidate text string comprising the highest rating; comparing the said highest rating with a second threshold value; determining whether to create the label based upon the said comparison. 12. The method as claimed in claim 11 comprising the step of: creating the label based upon the candidate text string with the highest rating if the said rating exceeds the second threshold value.
| 0.876022 |
14. A non-transitory computer-readable medium having instructions stored thereon that, in response to execution, cause a system including a processor to perform operations comprising: inferring a first industrial programming language of a plurality of industrial programming languages to use for programming an industrial controller and a second industrial programming language of the plurality of industrial programming languages to use in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and merging at least a portion of the first industrial programming language for programming with at least another portion of the second industrial programming language to form the custom programming language for programming the industrial controller, wherein the first industrial programming language, the second industrial programming language and the custom programming language are not identical.
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14. A non-transitory computer-readable medium having instructions stored thereon that, in response to execution, cause a system including a processor to perform operations comprising: inferring a first industrial programming language of a plurality of industrial programming languages to use for programming an industrial controller and a second industrial programming language of the plurality of industrial programming languages to use in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and merging at least a portion of the first industrial programming language for programming with at least another portion of the second industrial programming language to form the custom programming language for programming the industrial controller, wherein the first industrial programming language, the second industrial programming language and the custom programming language are not identical. 15. The non-transitory computer-readable medium of claim 14 , wherein at least one of the first industrial programming language, the second industrial programming language, or the third programming language is at least one of a structured text (ST), an instruction list (IL), a ladder diagram (LD), a function block diagram (FBD), a sequential function chart (SFC), a function chart (FC), C, or C++.
| 0.5 |
23. A voice controlled wireless communications system, comprising: a central computing device unit; one or more concentrators coupled to the central computing device unit over a link wherein each network concentrator communicates with the central computing device unit, each network concentrator having a coverage range; a plurality of wireless devices that wirelessly communicate with a network concentrator when the wireless device is in the coverage range of the network concentrator; and the central computing device unit further comprising a voice command interpreter having a speech recognition engine and one or more pieces of grammar associated with the speech recognition engine wherein the one or more pieces of grammar contains a word and an artificial ambiguity about one or more homonyms for the word that are inserted into the one or more pieces of grammar of the speech recognition engine for the word to create an ambiguity between the word and the one or more homonyms; and the voice command interpreter identifies a correct interpretation for a received word that has the one or more homonyms based on the received word and the one or more pieces of grammar for the word that includes the inserted information about the one or more homonyms.
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23. A voice controlled wireless communications system, comprising: a central computing device unit; one or more concentrators coupled to the central computing device unit over a link wherein each network concentrator communicates with the central computing device unit, each network concentrator having a coverage range; a plurality of wireless devices that wirelessly communicate with a network concentrator when the wireless device is in the coverage range of the network concentrator; and the central computing device unit further comprising a voice command interpreter having a speech recognition engine and one or more pieces of grammar associated with the speech recognition engine wherein the one or more pieces of grammar contains a word and an artificial ambiguity about one or more homonyms for the word that are inserted into the one or more pieces of grammar of the speech recognition engine for the word to create an ambiguity between the word and the one or more homonyms; and the voice command interpreter identifies a correct interpretation for a received word that has the one or more homonyms based on the received word and the one or more pieces of grammar for the word that includes the inserted information about the one or more homonyms. 32. The system of claim 23 further comprising a homonym detection unit that detects if a word in the one or more pieces of grammar associated with the speech recognition engine has one or more homonyms.
| 0.594012 |
1. At least one machine accessible, non-transitory storage medium having instructions stored thereon, the instructions when executed on a machine, cause the machine to: receive vulnerability definition data, using a hardware processor, including, for each of a plurality of vulnerabilities, an indication of the vulnerability, an identification of one or more countermeasures that reduce a risk associated with possession of the vulnerability by an asset, an indication of a level of protection potentially afforded by each countermeasure for the vulnerability, and applicability information describing one or more configurations of assets to which the vulnerability applies; receive vulnerability detection data, countermeasure detection data, and configuration data for each of one or more assets, wherein the vulnerability detection data for each asset identifies vulnerabilities applicable to the asset, the countermeasure detection data for each asset identifying one or more countermeasures protecting the asset, and the configuration data for each asset describes a configuration of the asset; and determine a respective risk metric for each of the one or more assets for each of the one or more vulnerabilities, wherein determining the risk metric includes, for each asset and each vulnerability: identifying a standardized vulnerability score for the vulnerability, wherein the standardized vulnerability score indicates a relative level of risk associated with the vulnerability relative to other vulnerabilities in the plurality of vulnerabilities; determining a vulnerability detection score for the asset from the vulnerability detection data for the asset; determining a vulnerability composite score for the particular asset to the particular vulnerability, wherein the vulnerability composite score is derived from the standardized vulnerability score and the vulnerability detection score; determining a countermeasure component score from the vulnerability definition data and the countermeasure detection data, wherein determining the countermeasure component score includes analyzing the level of protection afforded by each countermeasure identified in both the vulnerability definition data for the vulnerability and in the countermeasure data as protecting the asset; and determining the risk metric for the asset and the vulnerability from the vulnerability composite score and the countermeasure component score.
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1. At least one machine accessible, non-transitory storage medium having instructions stored thereon, the instructions when executed on a machine, cause the machine to: receive vulnerability definition data, using a hardware processor, including, for each of a plurality of vulnerabilities, an indication of the vulnerability, an identification of one or more countermeasures that reduce a risk associated with possession of the vulnerability by an asset, an indication of a level of protection potentially afforded by each countermeasure for the vulnerability, and applicability information describing one or more configurations of assets to which the vulnerability applies; receive vulnerability detection data, countermeasure detection data, and configuration data for each of one or more assets, wherein the vulnerability detection data for each asset identifies vulnerabilities applicable to the asset, the countermeasure detection data for each asset identifying one or more countermeasures protecting the asset, and the configuration data for each asset describes a configuration of the asset; and determine a respective risk metric for each of the one or more assets for each of the one or more vulnerabilities, wherein determining the risk metric includes, for each asset and each vulnerability: identifying a standardized vulnerability score for the vulnerability, wherein the standardized vulnerability score indicates a relative level of risk associated with the vulnerability relative to other vulnerabilities in the plurality of vulnerabilities; determining a vulnerability detection score for the asset from the vulnerability detection data for the asset; determining a vulnerability composite score for the particular asset to the particular vulnerability, wherein the vulnerability composite score is derived from the standardized vulnerability score and the vulnerability detection score; determining a countermeasure component score from the vulnerability definition data and the countermeasure detection data, wherein determining the countermeasure component score includes analyzing the level of protection afforded by each countermeasure identified in both the vulnerability definition data for the vulnerability and in the countermeasure data as protecting the asset; and determining the risk metric for the asset and the vulnerability from the vulnerability composite score and the countermeasure component score. 8. The non-transitory storage medium of claim 1 , wherein the countermeasure component score is derived from at least the countermeasure protection data and the countermeasure detection data.
| 0.679694 |
5. The method of claim 1 , further comprising: generating a copy of the second document represented by an additional flat data structure having a plurality of additional flat data structure elements; and establishing an additional bridge between the copy and the second document, such that an edit to the second document is applied to the copy.
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5. The method of claim 1 , further comprising: generating a copy of the second document represented by an additional flat data structure having a plurality of additional flat data structure elements; and establishing an additional bridge between the copy and the second document, such that an edit to the second document is applied to the copy. 6. The method of claim 5 , wherein the edit to the first document is applied to the second document via the bridge, and is applied from the second document to the copy via the additional bridge.
| 0.896147 |
1. A computer-readable storage, having stored thereon a computer program for processing speech audio in a network connected client device, said computer program having a plurality of code sections executable by said client device for causing the client device to perform the steps of: selecting a speech grammar for use in a speech recognition system in the network connected client device; characterizing said selected speech grammar, wherein said characterization comprises determining a size and a complexity of said selected grammar and a preferred processing location is specified in said selected grammar; determining a processing power of said client device and of a remote speech server, a speed of a network connection between said client device and said speech server, and a feedback requirement for said speech recognition system; and, based on the characterization of said selected speech grammar, said determined network connection speed, said determined processing power of the network connected client device and the remote speech server, and said feedback requirements, electing whether to process the entire selected speech grammar in said preferred location or another location different from said preferred location before processing the speech audio, wherein said preferred location specifies the network connected client device or the speech server, wherein if said preferred location specifies said speech server, said client device elects said client device if real-time feedback is required by said speech recognition system and a processing power of said client device is sufficient for said client device to process said selected grammar in real-time based on said size and said complexity of said selected grammar, and wherein if said preferred location specifies said client device, said client device elects said remote speech server if a latency in processing said selected speech grammar based on said network speed and said remote speech server processing power is sufficient to meet a feedback requirement of said speech recognition system.
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1. A computer-readable storage, having stored thereon a computer program for processing speech audio in a network connected client device, said computer program having a plurality of code sections executable by said client device for causing the client device to perform the steps of: selecting a speech grammar for use in a speech recognition system in the network connected client device; characterizing said selected speech grammar, wherein said characterization comprises determining a size and a complexity of said selected grammar and a preferred processing location is specified in said selected grammar; determining a processing power of said client device and of a remote speech server, a speed of a network connection between said client device and said speech server, and a feedback requirement for said speech recognition system; and, based on the characterization of said selected speech grammar, said determined network connection speed, said determined processing power of the network connected client device and the remote speech server, and said feedback requirements, electing whether to process the entire selected speech grammar in said preferred location or another location different from said preferred location before processing the speech audio, wherein said preferred location specifies the network connected client device or the speech server, wherein if said preferred location specifies said speech server, said client device elects said client device if real-time feedback is required by said speech recognition system and a processing power of said client device is sufficient for said client device to process said selected grammar in real-time based on said size and said complexity of said selected grammar, and wherein if said preferred location specifies said client device, said client device elects said remote speech server if a latency in processing said selected speech grammar based on said network speed and said remote speech server processing power is sufficient to meet a feedback requirement of said speech recognition system. 2. The computer-readable storage of claim 1 , wherein the selecting step comprises: establishing a communications session with said remote speech server; and, querying said remote speech server for a speech grammar over said established communications session.
| 0.509461 |
1. A computer-implemented method for executing structured queries on unstructured data, the method comprising: receiving a structured query in a structured query language; determining a schema that defines a structure for unstructured data, wherein the schema identifies a plurality of fields in the unstructured data; conducting a pilot query on the unstructured data, wherein the pilot query is conducted using the schema, and wherein conducting the pilot query identifies one or more fields in the unstructured data; converting the structured query in the structured query language into an unstructured query in an unstructured query language, wherein the conversion is done using the one or more fields identified by conducting the pilot query, and wherein the unstructured query is used to access the unstructured data; conducting a search on the unstructured data using the unstructured query; caching the one or more fields identified by conducting the pilot query; conducting a new pilot query on the unstructured data, wherein conducting the new pilot query identifies one or more new fields in the unstructured data; and merging the one or more cached fields with the one or more new fields.
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1. A computer-implemented method for executing structured queries on unstructured data, the method comprising: receiving a structured query in a structured query language; determining a schema that defines a structure for unstructured data, wherein the schema identifies a plurality of fields in the unstructured data; conducting a pilot query on the unstructured data, wherein the pilot query is conducted using the schema, and wherein conducting the pilot query identifies one or more fields in the unstructured data; converting the structured query in the structured query language into an unstructured query in an unstructured query language, wherein the conversion is done using the one or more fields identified by conducting the pilot query, and wherein the unstructured query is used to access the unstructured data; conducting a search on the unstructured data using the unstructured query; caching the one or more fields identified by conducting the pilot query; conducting a new pilot query on the unstructured data, wherein conducting the new pilot query identifies one or more new fields in the unstructured data; and merging the one or more cached fields with the one or more new fields. 5. The computer-implemented method of claim 1 , further comprising: conducting a new pilot query on the unstructured data, wherein the new pilot query identifies one or more new fields in the unstructured data.
| 0.791502 |
12. The method of claim 1 , wherein said semantic expansion comprises a list of search patterns relevant to said formal semantic representation of said user query problem description.
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12. The method of claim 1 , wherein said semantic expansion comprises a list of search patterns relevant to said formal semantic representation of said user query problem description. 13. The method of claim 12 , wherein at least one search pattern from said list of patterns includes a relevance value representing a degree of relevance of said search pattern to said formal semantic representation of said user query problem description.
| 0.954814 |
2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern.
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2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern. 21. A continuous speech recognition system according to claim 2, wherein said asymptotic calculating means is provided with a plurality of similarity measure registers to store similarity measures at predetermined plural time points n, a plurality of path information registers to store path information at said predetermined plural time points n, a comparator to select and output a minimum value from among the values stored in said plurality of similarity measure registers and also to output a signal indicating a time point n corresponding to said selected similarity measure stored in the similarity measure register, an adder to output an added result as a newly obtained similarity measure with said minimum similarity measure as one input and the distance information obtained through said distance calculating means as another input, and means to output the contents stored in said path information register corresponding to said time point n as new path information.
| 0.5743 |
1. An apparatus for testing speech recognition in a new vehicle, said apparatus comprising: a laptop computer; a speaker arrangement which propagates a speech output based on a known text previously recorded by a human; wherein the text is comprised of a set of commands of interest, said speech output being stored digitally in a laptop computer; a testing arrangement adapted to test the acceptability of installed speech recognition systems in vehicles while the vehicles are being operated on a roadway at speeds of 0, 30, and 60 miles per hour, wherein the acceptability of a particular vehicular speech recognition system is based upon a comparison of pre-specified standards of recognition accuracy and signal-to-noise ratio values with a recognition accuracy value and a signal-to-noise ratio value produced by the particular vehicular speech recognition system, based on the text recognized from the speech output and the testing arrangement is located separate from the vehicle being tested, the propagated speech output being transmitted to the testing arrangement via a cellular transmission unit located within the vehicle being tested; wherein said speaker arrangement is configured to simulate the propagation of a human voice and is calibrated with respect to an audio input of an installed speech recognition system in a vehicle such that the speech output is propagated at the same pressure and distance from a microphone used to record the human speech; wherein the speech output comprises three recordings of the human voice, one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 0 miles per hour, one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 30 miles, and one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 60 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 0 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 0 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 30 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 30 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 60 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 60 miles per hour; and wherein the apparatus is used to test every one-hundredth car that leaves an assembly line.
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1. An apparatus for testing speech recognition in a new vehicle, said apparatus comprising: a laptop computer; a speaker arrangement which propagates a speech output based on a known text previously recorded by a human; wherein the text is comprised of a set of commands of interest, said speech output being stored digitally in a laptop computer; a testing arrangement adapted to test the acceptability of installed speech recognition systems in vehicles while the vehicles are being operated on a roadway at speeds of 0, 30, and 60 miles per hour, wherein the acceptability of a particular vehicular speech recognition system is based upon a comparison of pre-specified standards of recognition accuracy and signal-to-noise ratio values with a recognition accuracy value and a signal-to-noise ratio value produced by the particular vehicular speech recognition system, based on the text recognized from the speech output and the testing arrangement is located separate from the vehicle being tested, the propagated speech output being transmitted to the testing arrangement via a cellular transmission unit located within the vehicle being tested; wherein said speaker arrangement is configured to simulate the propagation of a human voice and is calibrated with respect to an audio input of an installed speech recognition system in a vehicle such that the speech output is propagated at the same pressure and distance from a microphone used to record the human speech; wherein the speech output comprises three recordings of the human voice, one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 0 miles per hour, one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 30 miles, and one recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 60 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 0 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 0 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 30 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 30 miles per hour; wherein the recording having been made while the human wore a headset playing noise typical of an automobile operating on a roadway at a speed of 60 miles per hour is played during the test when the vehicle is being operated on a roadway at a speed of 60 miles per hour; and wherein the apparatus is used to test every one-hundredth car that leaves an assembly line. 9. The apparatus according to claim 1 , wherein said speaker arrangement is adapted to propagate prerecorded speech output.
| 0.519935 |
17. A computer for generating an application, comprising: a transceiver for communicating over the network; a memory for storing at least instructions; and a processor device that executes instructions performing actions, including: responsive to encountering a multi-size type during compilation of an intermediate language version of the application into a machine code version of the application, performing actions, including: determining architecture information of a target computer, wherein the architecture information includes at least a word size of the target computer; determining at least one data type associated with the target computer that corresponds to the multi-sized type based on the architecture information; determining one or more native codes call that perform actions associated with an intermediate language code call, wherein parameters to the one or more native codes call match the one or more data types; generating a machine code version of the intermediate language code call that at least corresponds to the one or more determined native code calls and also corresponds to the architecture information; when the target computer enables just-in-time compiling, executing the generated machine code version of the intermediate language code call with one or more values correspondent to the multi-size type and the one or more data types by executing the one or more determined native code calls using the one or more determined data types that correspond to the architecture information; and when the target computer disables just-in-time compiling, inserting the generated machine code version of the intermediate language code call in the machine code version of the application with the one or more values correspondent to the multi-size type and the one or more data types, wherein the generated machine code version includes instructions to execute the one or more determined native code calls.
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17. A computer for generating an application, comprising: a transceiver for communicating over the network; a memory for storing at least instructions; and a processor device that executes instructions performing actions, including: responsive to encountering a multi-size type during compilation of an intermediate language version of the application into a machine code version of the application, performing actions, including: determining architecture information of a target computer, wherein the architecture information includes at least a word size of the target computer; determining at least one data type associated with the target computer that corresponds to the multi-sized type based on the architecture information; determining one or more native codes call that perform actions associated with an intermediate language code call, wherein parameters to the one or more native codes call match the one or more data types; generating a machine code version of the intermediate language code call that at least corresponds to the one or more determined native code calls and also corresponds to the architecture information; when the target computer enables just-in-time compiling, executing the generated machine code version of the intermediate language code call with one or more values correspondent to the multi-size type and the one or more data types by executing the one or more determined native code calls using the one or more determined data types that correspond to the architecture information; and when the target computer disables just-in-time compiling, inserting the generated machine code version of the intermediate language code call in the machine code version of the application with the one or more values correspondent to the multi-size type and the one or more data types, wherein the generated machine code version includes instructions to execute the one or more determined native code calls. 19. The computer of claim 17 , wherein the generated machine code version of the intermediate language code call, further comprises, a portion of machine code that corresponds to a calling convention supported by the target computer.
| 0.77497 |
1. A lighting system comprising a luminaire that includes: a plurality of light channels that respectively produce different spectral distributions of light; a drive circuit coupled to the light channels and programmable to control relative intensities of light output from the light channels; and an interpreter module that processes a script to generate operating parameters for the drive circuit, wherein the script comprises a plurality of descriptors in a sequence that represents that a lighting scenario changes over time and wherein programming the drive circuit with the operating parameters results in the light channels producing the lighting scenario.
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1. A lighting system comprising a luminaire that includes: a plurality of light channels that respectively produce different spectral distributions of light; a drive circuit coupled to the light channels and programmable to control relative intensities of light output from the light channels; and an interpreter module that processes a script to generate operating parameters for the drive circuit, wherein the script comprises a plurality of descriptors in a sequence that represents that a lighting scenario changes over time and wherein programming the drive circuit with the operating parameters results in the light channels producing the lighting scenario. 7. The system of claim 1 , wherein the luminaire further comprises a communication interface through which the luminaire receives scripts.
| 0.628713 |
13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification.
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13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification. 14. The method of claim 13 wherein the selected configuration parameter comprises at least one of a number of sensor features utilized or a frequency of classification.
| 0.650875 |
13. A computer-implemented method for interacting with content, the computer-implemented method comprising performing computer-implemented operations for: receiving the content from a source; identifying at least one input indicator in the content, the at least one input indicator indicating that the content supports multi-mode input, the input indicator including explicit meta tags, flags, implicit keywords, or form elements, the input indicator associated with a form element; determining a context associated with the form element if the input indicator indicates that the form element supports multi-mode input; determining a type of information to be captured from a plurality of types of information by the computer based on the context for the form element; activating one or more non-textual input devices associated with the computer according to the type of information to be captured; capturing multi-mode input, via the one or more non-textual input devices, for interacting with the content, wherein the multi-mode input includes one or more of camera, speech, and touch input; converting the multi-mode input to text; and submitting the text to the source.
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13. A computer-implemented method for interacting with content, the computer-implemented method comprising performing computer-implemented operations for: receiving the content from a source; identifying at least one input indicator in the content, the at least one input indicator indicating that the content supports multi-mode input, the input indicator including explicit meta tags, flags, implicit keywords, or form elements, the input indicator associated with a form element; determining a context associated with the form element if the input indicator indicates that the form element supports multi-mode input; determining a type of information to be captured from a plurality of types of information by the computer based on the context for the form element; activating one or more non-textual input devices associated with the computer according to the type of information to be captured; capturing multi-mode input, via the one or more non-textual input devices, for interacting with the content, wherein the multi-mode input includes one or more of camera, speech, and touch input; converting the multi-mode input to text; and submitting the text to the source. 16. The method of claim 13 , wherein identifying the at least one input indicator comprises identifying at least one input field in the content, analyzing the at least one input field to identify a type of input, and determining that a non-textual input device is available for entering the input.
| 0.5 |
1. A method comprising: maintaining a URL database comprising a plurality of URLs; retrieving, without user intervention, a first document associated with a first URL from the plurality of URLs; parsing, using at least one processor, the first document to identify one or more additional URLs within the first document; comparing the one or more additional URLs to the URL database to determine if the URL database includes the one or more additional URLs; if it is determined that the URL database does not include the one or more additional URLs, updating the URL database to include the one or more additional URLs; determining if the one or more additional URLs are root URLs based on a set of predefined rules; when it is determined that the one or more additional URLs are root URLs, classifying the one or more additional URLs as root URLs in the URL database and updating the URL database to add the classification that the one or more additional URLs are root URLs; querying a third-party database for additional information associated with the one or more additional URLs; updating the URL database to include the additional information associated with the one or more additional URLs; and repeating the steps of retrieving, parsing, comparing, and updating for each of the one or more additional URLs.
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1. A method comprising: maintaining a URL database comprising a plurality of URLs; retrieving, without user intervention, a first document associated with a first URL from the plurality of URLs; parsing, using at least one processor, the first document to identify one or more additional URLs within the first document; comparing the one or more additional URLs to the URL database to determine if the URL database includes the one or more additional URLs; if it is determined that the URL database does not include the one or more additional URLs, updating the URL database to include the one or more additional URLs; determining if the one or more additional URLs are root URLs based on a set of predefined rules; when it is determined that the one or more additional URLs are root URLs, classifying the one or more additional URLs as root URLs in the URL database and updating the URL database to add the classification that the one or more additional URLs are root URLs; querying a third-party database for additional information associated with the one or more additional URLs; updating the URL database to include the additional information associated with the one or more additional URLs; and repeating the steps of retrieving, parsing, comparing, and updating for each of the one or more additional URLs. 5. The method of claim 1 , wherein determining if the one or more additional URLs are root URLs based on a set of predefined rules comprises: parsing the one or more additional URLs into a domain name and a directory path; determining that multiple IP addresses are associated with the domain name; and identifying that the directory path is one directory level below the domain name.
| 0.5 |
1. A method for dynamically generating a survey result(s) comprising: storing and managing each registered user's one or more profile(s), preferences and relational connections or dynamic relationships at a central server; allowing each user to manage a Human Operating System (HOS) including one or more profiles, activities, applications, services, actions, transactions, groups, searching, sharing, communication, contents and connections; presenting one or more domain or subject or taxonomy specific survey forms to user; receiving, via categories survey forms, a plurality of categories survey data or selections from the user, wherein survey data or selections relate or map, for each of plurality of different categories of user data for sharing with one or more other connected users who can access that category of user data and customization, personalization and configuration data utilize for customization of the user's Human Operating System (HOS) including dynamically creating one or more social networks, establishing communication and sharing selective one or more user resources or profiles with one or more other connected users, customize searching and matching, e-commerce, receiving customized advertisements, applications and services lists and contents; updating survey data and survey analysis to the related categories profile(s) of the user for applying or use the survey data for customization, personalization and configuration of each user's Human Operating System (HOS); and generating and presenting a survey results to the user, wherein survey results comprises a details of customization, personalization and configuration of each user's Human Operating System (HOS) and which other connected users can access which categories of user data based on the survey data or selections.
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1. A method for dynamically generating a survey result(s) comprising: storing and managing each registered user's one or more profile(s), preferences and relational connections or dynamic relationships at a central server; allowing each user to manage a Human Operating System (HOS) including one or more profiles, activities, applications, services, actions, transactions, groups, searching, sharing, communication, contents and connections; presenting one or more domain or subject or taxonomy specific survey forms to user; receiving, via categories survey forms, a plurality of categories survey data or selections from the user, wherein survey data or selections relate or map, for each of plurality of different categories of user data for sharing with one or more other connected users who can access that category of user data and customization, personalization and configuration data utilize for customization of the user's Human Operating System (HOS) including dynamically creating one or more social networks, establishing communication and sharing selective one or more user resources or profiles with one or more other connected users, customize searching and matching, e-commerce, receiving customized advertisements, applications and services lists and contents; updating survey data and survey analysis to the related categories profile(s) of the user for applying or use the survey data for customization, personalization and configuration of each user's Human Operating System (HOS); and generating and presenting a survey results to the user, wherein survey results comprises a details of customization, personalization and configuration of each user's Human Operating System (HOS) and which other connected users can access which categories of user data based on the survey data or selections. 4. The method as claimed in claim 1 , wherein said survey forms types comprising major taxonomy wise survey forms, user's personal information survey forms, Human Service Network System and Human Operating System related survey forms, private or advertisement and ecommerce related survey forms and customized survey forms.
| 0.638727 |
2. The method of claim 1 , wherein the selectable thumbnail images are grouped according to a type of relationship the person shares with the individual, the types of relationships comprising one or more of: a manager relationship; a peer relationship; a directs relationship; a working with relationship; and a we both work with relationship.
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2. The method of claim 1 , wherein the selectable thumbnail images are grouped according to a type of relationship the person shares with the individual, the types of relationships comprising one or more of: a manager relationship; a peer relationship; a directs relationship; a working with relationship; and a we both work with relationship. 3. The method of claim 2 , wherein selectable thumbnail images grouped according to a we both work with relationship comprises selectable thumbnail images of people whose nodes are connected to both the first individual's node and the user's node by relationship edges.
| 0.916318 |
6. A method comprising: receiving a model from a user device, the receiving being performed by a computing device; executing the model, the executing being performed by the computing device; determining whether the model is functional based on executing the model, the determining being performed by the computing device; causing the model to be made available to one or more users when the model is functional, the causing the model to be made available when the model is functional being performed by the computing device; causing information to be presented at the user device when the model is not functional, the information indicating that the model is not functional, the causing the information to be presented at the user device being performed by the computing device; receiving, from the user device, a response to the information indicating that the model is not functional, the response indicating that the model, that is not functional, is to be made available to the one or more users, the receiving the response being performed by the computing device; and causing the model, that is not functional, to be made available to the one or more users based on receiving the response indicating that the model, that is not functional, is to be made available to the one or more users, the causing the model to be made available when the model is not functional being performed by the computing device.
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6. A method comprising: receiving a model from a user device, the receiving being performed by a computing device; executing the model, the executing being performed by the computing device; determining whether the model is functional based on executing the model, the determining being performed by the computing device; causing the model to be made available to one or more users when the model is functional, the causing the model to be made available when the model is functional being performed by the computing device; causing information to be presented at the user device when the model is not functional, the information indicating that the model is not functional, the causing the information to be presented at the user device being performed by the computing device; receiving, from the user device, a response to the information indicating that the model is not functional, the response indicating that the model, that is not functional, is to be made available to the one or more users, the receiving the response being performed by the computing device; and causing the model, that is not functional, to be made available to the one or more users based on receiving the response indicating that the model, that is not functional, is to be made available to the one or more users, the causing the model to be made available when the model is not functional being performed by the computing device. 9. The method of claim 6 , where the information is transmitted, to the user device, via an instant message.
| 0.705617 |
16. A system for processing contextual information relating to an exchange of a conversation on a communication channel between a first client and a second client, comprising: a processor and a memory storing instructions that when executed perform actions, comprising: establishing between the first client and the second client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit contextual information before and after the communication channel is established; obtaining first contextual information relating to the first client; wherein the first contextual information is packetized and arranged according to the predefined structured hierarchy; wherein the contextual information comprises client preferences, a set of rules, and device functionality; determining a set of rules by processing the obtained first contextual information; obtaining second contextual information relating to the second client; determining conditions of the second client by processing the second contextual information; comparing the set of rules with the conditions of the second client; if the conditions of the second client satisfy the set of rules, establishing, or maintaining a communication channel connection as indicated by the set of rules; and after establishing the communication channel as indicated by the set of rules performing operations comprising: obtaining additional contextual information; determining current conditions of the second client by processing the additional contextual information; comparing the set of rules with the additional conditions of the second client; and providing a notification of terminating the communication channel when at least one rule of the set of rules does not satisfy a connection condition with the first client based on the condition of the second client, wherein the connection condition is at least one of a desired mood; a desired subject of the conversation; and a desired location.
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16. A system for processing contextual information relating to an exchange of a conversation on a communication channel between a first client and a second client, comprising: a processor and a memory storing instructions that when executed perform actions, comprising: establishing between the first client and the second client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit contextual information before and after the communication channel is established; obtaining first contextual information relating to the first client; wherein the first contextual information is packetized and arranged according to the predefined structured hierarchy; wherein the contextual information comprises client preferences, a set of rules, and device functionality; determining a set of rules by processing the obtained first contextual information; obtaining second contextual information relating to the second client; determining conditions of the second client by processing the second contextual information; comparing the set of rules with the conditions of the second client; if the conditions of the second client satisfy the set of rules, establishing, or maintaining a communication channel connection as indicated by the set of rules; and after establishing the communication channel as indicated by the set of rules performing operations comprising: obtaining additional contextual information; determining current conditions of the second client by processing the additional contextual information; comparing the set of rules with the additional conditions of the second client; and providing a notification of terminating the communication channel when at least one rule of the set of rules does not satisfy a connection condition with the first client based on the condition of the second client, wherein the connection condition is at least one of a desired mood; a desired subject of the conversation; and a desired location. 19. The system of claim 16 , wherein the rules include a set of rules relating to a group of allowed callers.
| 0.525617 |
5. The method of claim 1 , wherein the plurality of MLA classifiers includes: the first MLA classifier; the second MLA classifier; a third MLA classifier, and a fourth MLA classifier.
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5. The method of claim 1 , wherein the plurality of MLA classifiers includes: the first MLA classifier; the second MLA classifier; a third MLA classifier, and a fourth MLA classifier. 11. The method of claim 5 , wherein the fourth MLA classifier is a text-based classifier.
| 0.955267 |
1. A method, comprising: identifying a first form; creating a second form based on the first form, the first form and the second form being defined in extended markup language (XML), wherein a definition of the second form is provided inheritance from a definition of the first form such that the definition of the second form further includes only the difference between the first form and the second form, which are changes made to the first form; receiving a request for the first form; in response to the receipt of the request for the first form: identifying at least one factor associated with at least one of the request for the first form and a system via which the first form is requested; selecting the second form in response to: identifying at least one rule associated with the second form, the at least one rule predefined by a user; determining at least one factor indicated by the at least one rule; and matching the at least one determined factor indicated by the at least one rule to the at least one identified factor associated with the at least one of the request for the first form and the system via which the first form is requested; and returning the selected second form as a response to the request for the first form.
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1. A method, comprising: identifying a first form; creating a second form based on the first form, the first form and the second form being defined in extended markup language (XML), wherein a definition of the second form is provided inheritance from a definition of the first form such that the definition of the second form further includes only the difference between the first form and the second form, which are changes made to the first form; receiving a request for the first form; in response to the receipt of the request for the first form: identifying at least one factor associated with at least one of the request for the first form and a system via which the first form is requested; selecting the second form in response to: identifying at least one rule associated with the second form, the at least one rule predefined by a user; determining at least one factor indicated by the at least one rule; and matching the at least one determined factor indicated by the at least one rule to the at least one identified factor associated with the at least one of the request for the first form and the system via which the first form is requested; and returning the selected second form as a response to the request for the first form. 14. The method of claim 1 , further comprising automatically updating the second form in response to an update of the first form.
| 0.530695 |
16. The computer-readable medium of claim 15 , wherein the operations further comprise: in response to determining that the request is not supported by the fast query service engine, directing the request to the primary data server; and determining whether the request modifies data on the primary data server.
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16. The computer-readable medium of claim 15 , wherein the operations further comprise: in response to determining that the request is not supported by the fast query service engine, directing the request to the primary data server; and determining whether the request modifies data on the primary data server. 17. The computer-readable medium of claim 16 , wherein the operations further comprise: in response to determining that the request modifies data on the primary data server, notifying the fast query service engine that contents of an answer set referencing the modified data, as maintained in the in-memory data storage at the fast query service engine, has become invalid.
| 0.893384 |
9. The system of claim 8 , wherein the processor is further configured for selecting a job listing for injection into the content web page, based on user profile information of a user requesting the content web page.
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9. The system of claim 8 , wherein the processor is further configured for selecting a job listing for injection into the content web page, based on user profile information of a user requesting the content web page. 10. The system of claim 9 , wherein the user profile information includes one or more of a network, OS, a browser of the user, a language of the user, an education level of the user, a work experience of the user, and a demographic characteristic of the user.
| 0.918955 |
16. The apparatus of claim 1 , wherein the URL rules detector is further configured to send an object retrieval request to a Website associated with the candidate URL if the candidate URL is a valid URL.
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16. The apparatus of claim 1 , wherein the URL rules detector is further configured to send an object retrieval request to a Website associated with the candidate URL if the candidate URL is a valid URL. 19. The apparatus of claim 16 , wherein: the digital dictionary, script parser, and URL rules detector are elements of a proxy server configured to intercept content served by a server device, and the executable script object is part of content served by the server device.
| 0.781216 |
14. A query processing system, comprising: a search system receiving information of a request, selecting a human assistant, delivering an interface to the human assistant, presenting a phrase in the interface, receiving a modification to the phrase, presenting a query in an order based on a ranking of the query based on the modification and providing a response; a user system submitting a request for information; and an expediter system receiving information of the request, selecting a resource, and processing the request.
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14. A query processing system, comprising: a search system receiving information of a request, selecting a human assistant, delivering an interface to the human assistant, presenting a phrase in the interface, receiving a modification to the phrase, presenting a query in an order based on a ranking of the query based on the modification and providing a response; a user system submitting a request for information; and an expediter system receiving information of the request, selecting a resource, and processing the request. 15. The system of claim 14 , comprising: a resource system receiving formatted information and providing the response; and a searcher system receiving the query and providing a search result.
| 0.843929 |
7. A computer-implemented method, comprising: accessing code of an application stored in a memory, the code defining a plurality of media components of the application and at least one scripting action; providing, by a processor, output to generate a design view in a graphical user interface, the design view comprising a timeline view of activity that occurs over time during execution of the application, wherein the timeline view comprises a plurality of cells and a plurality of tracks, each track providing a temporal view of a respective media component by populating a plurality of cells extending in a first direction in the timeline view, wherein the tracks are adjacent in a second direction in the timeline view so that cells adjacent in the second direction correspond to activity that occurs at the same time; populating the timeline view with at least one additional track, the at least one additional track comprising a scripting track comprising an action element representing a portion of scripting code defining a series of discrete operations to be performed at a particular time or keyframe by the application, the particular time or keyframe identified by a position of the action element on the timeline, wherein the at least one additional track comprises a label track including a label associated with the keyframe of the timeline; and receiving a selection of a cell of the timeline to define or edit the label to be associated with a selected keyframe of the timeline, wherein the label is used by the scripting code.
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7. A computer-implemented method, comprising: accessing code of an application stored in a memory, the code defining a plurality of media components of the application and at least one scripting action; providing, by a processor, output to generate a design view in a graphical user interface, the design view comprising a timeline view of activity that occurs over time during execution of the application, wherein the timeline view comprises a plurality of cells and a plurality of tracks, each track providing a temporal view of a respective media component by populating a plurality of cells extending in a first direction in the timeline view, wherein the tracks are adjacent in a second direction in the timeline view so that cells adjacent in the second direction correspond to activity that occurs at the same time; populating the timeline view with at least one additional track, the at least one additional track comprising a scripting track comprising an action element representing a portion of scripting code defining a series of discrete operations to be performed at a particular time or keyframe by the application, the particular time or keyframe identified by a position of the action element on the timeline, wherein the at least one additional track comprises a label track including a label associated with the keyframe of the timeline; and receiving a selection of a cell of the timeline to define or edit the label to be associated with a selected keyframe of the timeline, wherein the label is used by the scripting code. 8. The method of claim 7 , wherein the at least one scripting action or the label is defined independently of the media components.
| 0.579137 |
14. A system comprising: a recorder adapted to capture audio recordings from a language environment of a key child; a processor-based device, wherein the recorder provides the audio recordings to the processor-based device, and the processor-based device comprising an application having an audio engine adapted to segment the audio recording into a plurality of segments and identify a segment ID for each of the plurality of segments, wherein at least one of the plurality of segments is associated with a key child segment ID, wherein the audio engine segments the audio recording and identifies a segment ID for each of the plurality of segments using a Minimum Duration Gaussian Mixture Model (MD-GMM), and wherein the segments identified using the MD-GMM are at least a minimum duration D, and any segments with a duration longer than 2*D are broken down into several segments with a duration between D and 2*D, the audio engine being further adapted to: estimate key child segment characteristics based on the at least one of the plurality of segments, wherein the audio engine estimates key child segment characteristics independent of content of the at least one of the plurality of segments, wherein the content is the meaning of the plurality of key child segments; determine at least one metric associated with the language environment using the key child segment characteristics; and output the at least one metric to an output device.
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14. A system comprising: a recorder adapted to capture audio recordings from a language environment of a key child; a processor-based device, wherein the recorder provides the audio recordings to the processor-based device, and the processor-based device comprising an application having an audio engine adapted to segment the audio recording into a plurality of segments and identify a segment ID for each of the plurality of segments, wherein at least one of the plurality of segments is associated with a key child segment ID, wherein the audio engine segments the audio recording and identifies a segment ID for each of the plurality of segments using a Minimum Duration Gaussian Mixture Model (MD-GMM), and wherein the segments identified using the MD-GMM are at least a minimum duration D, and any segments with a duration longer than 2*D are broken down into several segments with a duration between D and 2*D, the audio engine being further adapted to: estimate key child segment characteristics based on the at least one of the plurality of segments, wherein the audio engine estimates key child segment characteristics independent of content of the at least one of the plurality of segments, wherein the content is the meaning of the plurality of key child segments; determine at least one metric associated with the language environment using the key child segment characteristics; and output the at least one metric to an output device. 18. The system of claim 14 wherein the audio engine uses the MD-GMM by: scoring each of the plurality of segments using log-likelihood scoring and a plurality of models; and analyzing the scored plurality of segments to assign the segment ID to each of the plurality of segments.
| 0.632041 |
14. A computing device operative to render an application view and initialize an application's user interface components, comprising: a processor; a memory having computer-executable modules for visually rendering an application view and initializing computational logic of the user interface component, comprising: a graphical rendering module operative to render graphical elements on a computer display associated with the computing device and receive notice of user-generated events, wherein to render graphical elements includes transforming semantic application logic into a format for parsing and rendering by a rendering component executed by the computing device and presented by the computer display associated with the computing device; at least one user interface component associated with semantic application logic used to visually render the user interface component on the computer display and an independently defined runtime object that provides the computational logic to satisfy user-generated events, wherein the semantic application logic used to visually render the at least one user interface component can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and a view module configured to connect graphical elements rendered by the graphical rendering module with computational logic provided by the runtime object, wherein connecting graphical elements with the computational logic includes: registering a listener on a document object model (DOM) object used by a Web browser to render a graphical element; and inserting a unique identifier in the DOM object to associate the graphical element with the runtime object.
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14. A computing device operative to render an application view and initialize an application's user interface components, comprising: a processor; a memory having computer-executable modules for visually rendering an application view and initializing computational logic of the user interface component, comprising: a graphical rendering module operative to render graphical elements on a computer display associated with the computing device and receive notice of user-generated events, wherein to render graphical elements includes transforming semantic application logic into a format for parsing and rendering by a rendering component executed by the computing device and presented by the computer display associated with the computing device; at least one user interface component associated with semantic application logic used to visually render the user interface component on the computer display and an independently defined runtime object that provides the computational logic to satisfy user-generated events, wherein the semantic application logic used to visually render the at least one user interface component can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and a view module configured to connect graphical elements rendered by the graphical rendering module with computational logic provided by the runtime object, wherein connecting graphical elements with the computational logic includes: registering a listener on a document object model (DOM) object used by a Web browser to render a graphical element; and inserting a unique identifier in the DOM object to associate the graphical element with the runtime object. 15. The computing device as recited in claim 14 , wherein the graphical rendering module is a Web Browser and wherein to render graphical elements on a computer display includes performing a transform of XML-formatted data to an HTML format.
| 0.623069 |
1. A non-transitory computer program product comprising a computer useable storage device to store a computer readable program that, when executed on a processor within a computer, causes the computer to perform operations to apply persona styles to written communications, the operations comprising: receive an element of original content from a written communication of a user; receive a selection of a persona style, wherein the selected persona style defines a communication style, the persona style one of a plurality of unique persona style stored in a persona repository, wherein the selected persona style maintains the meaning of a text string while adapting the text string to include an inherent mood, strength, and/or feeling based on the selected persona style and wherein according to the selected persona style, a text string may be dynamically modified to convey the desired style of expression; present a plurality of substitute elements to the user, via the electronic display, wherein each substitute element is compatible with a unique persona style, and at least one substitute element is compatible with the selected persona style, in response to a determination that the element of the original content of the written communication is incompatible with the selected persona style; and replace the element of the original content with the substitute element in response to a selection of the substitute element by the user.
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1. A non-transitory computer program product comprising a computer useable storage device to store a computer readable program that, when executed on a processor within a computer, causes the computer to perform operations to apply persona styles to written communications, the operations comprising: receive an element of original content from a written communication of a user; receive a selection of a persona style, wherein the selected persona style defines a communication style, the persona style one of a plurality of unique persona style stored in a persona repository, wherein the selected persona style maintains the meaning of a text string while adapting the text string to include an inherent mood, strength, and/or feeling based on the selected persona style and wherein according to the selected persona style, a text string may be dynamically modified to convey the desired style of expression; present a plurality of substitute elements to the user, via the electronic display, wherein each substitute element is compatible with a unique persona style, and at least one substitute element is compatible with the selected persona style, in response to a determination that the element of the original content of the written communication is incompatible with the selected persona style; and replace the element of the original content with the substitute element in response to a selection of the substitute element by the user. 3. The non-transitory computer program product of claim 1 , wherein the computer readable program, when executed on the computer, causes the computer to perform an operation to derive a context for the written communication from system properties and application configuration variables.
| 0.54567 |
1. A method performed by data processing apparatus, the method comprising: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource.
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1. A method performed by data processing apparatus, the method comprising: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource. 6. The method of claim 1 , further comprising: receiving a model evaluation request requesting that a model that is defined by the first model rule and the additional model rules be used to classify a set of resources; in response to receiving the model evaluation request, classifying the set of resources; generating an impact list that specifies resources from the set of resources that were classified by the model as violating resources; and providing data that cause presentation of resource identifiers for the resources that were classified as violating resources.
| 0.579069 |
9. A non-transitory computer-readable storage medium having instructions stored thereon that, if executed by a processor, cause the processor to perform operations comprising: receiving a capture of a portion of a rendered document; based on the capture, determining that the rendered document is protected by copyright and determining an electronic counterpart to the rendered document; identifying a plurality of actions not prohibited by the copyright, wherein the plurality of actions include an action for obtaining a license to the rendered document and an action to provide electronic access to the electronic counterpart; and providing instructions for a plurality of display elements, wherein each display element is associated with at least one action of the plurality of actions.
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9. A non-transitory computer-readable storage medium having instructions stored thereon that, if executed by a processor, cause the processor to perform operations comprising: receiving a capture of a portion of a rendered document; based on the capture, determining that the rendered document is protected by copyright and determining an electronic counterpart to the rendered document; identifying a plurality of actions not prohibited by the copyright, wherein the plurality of actions include an action for obtaining a license to the rendered document and an action to provide electronic access to the electronic counterpart; and providing instructions for a plurality of display elements, wherein each display element is associated with at least one action of the plurality of actions. 12. The non-transitory computer-readable storage medium of claim 9 , wherein determining that the rendered document is protected by copyright comprises: determining that the rendered document is protected by copyright based on the electronic counterpart.
| 0.563874 |
18. The computer program product of claim 17 , wherein computing the color transfer function further comprises: applying the color transfer function to the cropped image to generate a transformed cropped image; applying the color transfer function to the indexed image to generate a transformed indexed image; computing a first distance measure between the cropped image and the transformed indexed image; and computing a second distance measure between the indexed image and the transformed cropped image.
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18. The computer program product of claim 17 , wherein computing the color transfer function further comprises: applying the color transfer function to the cropped image to generate a transformed cropped image; applying the color transfer function to the indexed image to generate a transformed indexed image; computing a first distance measure between the cropped image and the transformed indexed image; and computing a second distance measure between the indexed image and the transformed cropped image. 19. The computer program product of claim 18 , wherein ranking the candidate list of indexed images is based on the first distance measure and the second distance measure.
| 0.747982 |
1. A processor-implemented method for disseminating content associated with a plurality of linked subject items in a knowledge base wherein individual subject items are associated with corresponding user-specific understanding values, the method comprising: ranking at least one of a plurality of candidate subject items for presentation to at least one user based on priority values associated with the candidate subject items, wherein the candidacies are determined and the priority values are computed based, at least in part, on: the user-specific understanding values corresponding to the at least one of a plurality of candidate subject items, the user-specific understanding values of at least one of a plurality of basic subject items linked to the at least one candidate subject item, and the user-specific understanding values of at least one of plurality of advanced subject items linked to the at least one candidate subject item.
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1. A processor-implemented method for disseminating content associated with a plurality of linked subject items in a knowledge base wherein individual subject items are associated with corresponding user-specific understanding values, the method comprising: ranking at least one of a plurality of candidate subject items for presentation to at least one user based on priority values associated with the candidate subject items, wherein the candidacies are determined and the priority values are computed based, at least in part, on: the user-specific understanding values corresponding to the at least one of a plurality of candidate subject items, the user-specific understanding values of at least one of a plurality of basic subject items linked to the at least one candidate subject item, and the user-specific understanding values of at least one of plurality of advanced subject items linked to the at least one candidate subject item. 9. The processor-implemented method of claim 1 , wherein user-specific linkage strengths are used to indicate a strength of association between pairs of linked subject items in the knowledge base and the linkage strengths are used in the determination of candidacy and in the computation of the priority values.
| 0.575699 |
2. A voice controlled automatic dialer claimed in claim 1, further comprising sound output means and sound generating means repsonsive to said decision output for supplying an audio frequency signal to said sound output means.
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2. A voice controlled automatic dialer claimed in claim 1, further comprising sound output means and sound generating means repsonsive to said decision output for supplying an audio frequency signal to said sound output means. 7. A voice controlled automatic dialer as claimed in claim 2, wherein said sound generating means comprises a speech synthesizer for generating a synthesized word in response to the entry of an input utterance to said sound input means.
| 0.921231 |
3. An apparatus according to claim 2 , further comprising: a resource file map to store at least two combinations of a layout information file and languages in which the layout strings files store the layout strings; a ranked list of languages specifying a plurality of languages preferred by the user and an order based on the user's preferences; and a selector to select one of the plurality of layout information files and one layout strings file based on the ranked list of languages and the resource file map.
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3. An apparatus according to claim 2 , further comprising: a resource file map to store at least two combinations of a layout information file and languages in which the layout strings files store the layout strings; a ranked list of languages specifying a plurality of languages preferred by the user and an order based on the user's preferences; and a selector to select one of the plurality of layout information files and one layout strings file based on the ranked list of languages and the resource file map. 5. An apparatus according to claim 3 , wherein: each layout information file defines how a particular layout string is displayed in a different language on a different device; and the resource file map stores combinations of layout information files, languages in which the layout strings files store the layout strings, and identities of devices for display of the information.
| 0.747082 |
1. A digital audio-video (AV) information reproducing apparatus for reproducing a file-based AV file, comprising: an instruction interpret unit generating a reproducing signal in response to a user signal, wherein the instruction interpret unit generates a text identification control signal if the user signal containing a text to be searched; an AV index generation unit for analyzing the AV file and generating an AV index, wherein the AV index records relationship of a predetermined time point to a specific logical address of the AV file; a reproducing control unit, connected to the instruction interpret unit and the AV index generation unit, for receiving the reproducing signal, the AV file, and the AV index; a subtitle process module, connected to the reproducing control unit, for processing a subtitle stream outputted from the reproducing control unit; and a data comparison unit, connected to the subtitle process module and the instruction interpret unit, for comparing output of the subtitle process module with the text identification control signal, and providing a setup signal indicating a comparison result including the predetermined time point to the reproducing control unit when the user signal contains the text identification control signal; wherein, the reproducing control unit searches and reproduces a matched part of the AV file corresponding to the predetermined time point based on the AV index and the predetermined time point.
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1. A digital audio-video (AV) information reproducing apparatus for reproducing a file-based AV file, comprising: an instruction interpret unit generating a reproducing signal in response to a user signal, wherein the instruction interpret unit generates a text identification control signal if the user signal containing a text to be searched; an AV index generation unit for analyzing the AV file and generating an AV index, wherein the AV index records relationship of a predetermined time point to a specific logical address of the AV file; a reproducing control unit, connected to the instruction interpret unit and the AV index generation unit, for receiving the reproducing signal, the AV file, and the AV index; a subtitle process module, connected to the reproducing control unit, for processing a subtitle stream outputted from the reproducing control unit; and a data comparison unit, connected to the subtitle process module and the instruction interpret unit, for comparing output of the subtitle process module with the text identification control signal, and providing a setup signal indicating a comparison result including the predetermined time point to the reproducing control unit when the user signal contains the text identification control signal; wherein, the reproducing control unit searches and reproduces a matched part of the AV file corresponding to the predetermined time point based on the AV index and the predetermined time point. 2. The digital AV information reproducing apparatus of claim 1 , wherein, the reproducing control unit further receives a subtitle file, and the reproducing control unit searches and reproduces a matched part of the subtitle file corresponding to the predetermined time point; and the reproducing control unit interprets the AV file and the subtitle file into an AV stream and the subtitle stream.
| 0.633865 |
11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler.
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11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler. 17. The method according to claim 11 , where the received data is ordered so that the sign language video content is received in advance of the data that encodes main program video content at the plurality of locations that are processed to accept substitution of the sign language video content.
| 0.819123 |
18. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being configured for: obtaining a set of text, wherein the set of text includes user-generated content; determining, for the set of text, a numerical value for each of a plurality of objects using the set of text, the numerical value indicating a likelihood that the corresponding one of the plurality of objects could have generated the set of text, each of the plurality of objects representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the set of text were generated from one of the objects, is most likely to have generated the set of text based, at least in part, upon the numerical value corresponding to each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the set of text; associating the set of text with the identified one of the plurality of objects such that a plurality of sets of text associated with the identified one of the plurality of objects includes the set of text; and aggregating information from at least a portion of the plurality of sets of text.
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18. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being configured for: obtaining a set of text, wherein the set of text includes user-generated content; determining, for the set of text, a numerical value for each of a plurality of objects using the set of text, the numerical value indicating a likelihood that the corresponding one of the plurality of objects could have generated the set of text, each of the plurality of objects representing a corresponding one of a plurality of entities; identifying one of the plurality of objects that, if the set of text were generated from one of the objects, is most likely to have generated the set of text based, at least in part, upon the numerical value corresponding to each of the plurality of objects, wherein the identified one of the plurality of objects indicates the one of the plurality of entities that is most likely to be a primary subject of the set of text; associating the set of text with the identified one of the plurality of objects such that a plurality of sets of text associated with the identified one of the plurality of objects includes the set of text; and aggregating information from at least a portion of the plurality of sets of text. 19. The apparatus as recited in claim 18 , further comprising: wherein an object type shared by the plurality of objects indicates a type of entity that is the primary subject of the set of text.
| 0.531496 |
18. The computer-readable medium of claim 17 , wherein the instructions to generate a score comprise generating a score based on: a comparison between a verb of the verb-entity relationship of the first respective statement and a verb of the verb-entity relationship of the second respective statement; and a comparison between an entity of the verb-entity relationship of the first respective statement and an entity of the verb-entity relationship of the second respective statement.
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18. The computer-readable medium of claim 17 , wherein the instructions to generate a score comprise generating a score based on: a comparison between a verb of the verb-entity relationship of the first respective statement and a verb of the verb-entity relationship of the second respective statement; and a comparison between an entity of the verb-entity relationship of the first respective statement and an entity of the verb-entity relationship of the second respective statement. 19. The computer-readable medium of claim 18 , wherein the instructions to generate a score further comprise generating a score based on the verb of the verb-entity relationship of the first respective statement and the verb of the verb-entity relationship of the second respective statement being synonyms.
| 0.846886 |
1. A system for controlling metadata associated with content items as directed by a user of an electronic device, the system comprising: a user interface comprising interface screens displayed on a display of the electronic device; an input mechanism on the electronic device, the input mechanism receiving user instructions through the user interface; a plurality of content items accessible by the electronic device, one or more of the plurality of content items having metadata associated therewith, the plurality of content items comprising original content items and modified content items; an overlay component that places a geolocation overlay indicator on each of the plurality of content items having associated geolocation metadata; a content selection component that displays one or more of the plurality of content items on the display of the electronic device, and enables selection of one or more of the plurality of displayed content items; the content selection component displays the geolocation overlay indicator with each content items having associated geolocation metadata; a plurality of content sharing mechanisms on the electronic device, each of the plurality of content sharing mechanisms for at least one of receiving content items and sending content items over a network accessible by the electronic device; a geotag profile accessible by the electronic device, the geotag profile including profile instructions regarding geolocation metadata control and being directed to at least one of the plurality of content sharing mechanisms; a sharing selection component for selecting a selected content item of the plurality of content items, and for selecting a selected content sharing mechanism of the plurality of content sharing mechanisms, the selected content item having selected content metadata associated therewith; a metadata modification component for modifying metadata associated with the plurality of content items including modifying the selected content metadata before sharing the selected content items, the metadata modification component selecting the geotag profile based on the selected content item and the selected content sharing mechanism, and modifying geolocation metadata of the selected content metadata in accordance with the profile instructions of the geotag profile when the geotag profile is selected; a sharing component for sharing a sharing version of the selected content item with a sharing version of the selected content metadata over a network accessible by the electronic device through the selected content sharing mechanism; wherein metadata associated with the original content items has not been modified by the metadata modification component and metadata associated with the modified content items has been modified by the metadata modification component, and wherein when the metadata modification component modifies selected content metadata before sharing a selected content item and the geotag profile is selected, the metadata modification component modifies the selected content metadata associated with the selected content item in accordance with the profile instructions of the geotag profile to generate the sharing version of the selected content metadata, and the metadata modification component does not modify the selected content metadata associated with the selected content item.
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1. A system for controlling metadata associated with content items as directed by a user of an electronic device, the system comprising: a user interface comprising interface screens displayed on a display of the electronic device; an input mechanism on the electronic device, the input mechanism receiving user instructions through the user interface; a plurality of content items accessible by the electronic device, one or more of the plurality of content items having metadata associated therewith, the plurality of content items comprising original content items and modified content items; an overlay component that places a geolocation overlay indicator on each of the plurality of content items having associated geolocation metadata; a content selection component that displays one or more of the plurality of content items on the display of the electronic device, and enables selection of one or more of the plurality of displayed content items; the content selection component displays the geolocation overlay indicator with each content items having associated geolocation metadata; a plurality of content sharing mechanisms on the electronic device, each of the plurality of content sharing mechanisms for at least one of receiving content items and sending content items over a network accessible by the electronic device; a geotag profile accessible by the electronic device, the geotag profile including profile instructions regarding geolocation metadata control and being directed to at least one of the plurality of content sharing mechanisms; a sharing selection component for selecting a selected content item of the plurality of content items, and for selecting a selected content sharing mechanism of the plurality of content sharing mechanisms, the selected content item having selected content metadata associated therewith; a metadata modification component for modifying metadata associated with the plurality of content items including modifying the selected content metadata before sharing the selected content items, the metadata modification component selecting the geotag profile based on the selected content item and the selected content sharing mechanism, and modifying geolocation metadata of the selected content metadata in accordance with the profile instructions of the geotag profile when the geotag profile is selected; a sharing component for sharing a sharing version of the selected content item with a sharing version of the selected content metadata over a network accessible by the electronic device through the selected content sharing mechanism; wherein metadata associated with the original content items has not been modified by the metadata modification component and metadata associated with the modified content items has been modified by the metadata modification component, and wherein when the metadata modification component modifies selected content metadata before sharing a selected content item and the geotag profile is selected, the metadata modification component modifies the selected content metadata associated with the selected content item in accordance with the profile instructions of the geotag profile to generate the sharing version of the selected content metadata, and the metadata modification component does not modify the selected content metadata associated with the selected content item. 18. The system of claim 1 , wherein the plurality of content items comprises digital content accessible by the electronic device.
| 0.571557 |
14. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity, wherein the instructions for recalculating the first component score comprise instructions for receiving improving the first component score by a predetermined amount; and instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; instructions for receiving a request for the trust score for the first entity from a user device of a third entity in the computer network; instructions for retrieving, using the processing circuitry, data indicating paths in the computer network; and instructions for identifying, based on the retrieved data indicating paths in the computer network, a path connecting the third entity to the second entity in the computer network, the path comprising a number of links that is less than a threshold number of links.
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14. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity, wherein the instructions for recalculating the first component score comprise instructions for receiving improving the first component score by a predetermined amount; and instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; instructions for receiving a request for the trust score for the first entity from a user device of a third entity in the computer network; instructions for retrieving, using the processing circuitry, data indicating paths in the computer network; and instructions for identifying, based on the retrieved data indicating paths in the computer network, a path connecting the third entity to the second entity in the computer network, the path comprising a number of links that is less than a threshold number of links. 17. The non-transitory computer readable medium of claim 14 , the instructions further comprising: instructions for receiving, from the user device of the second entity, an indication of an activity to be performed in the future by the first entity and the second entity, wherein the activity is associated with the attribute associated with the first entity.
| 0.5 |
9. The system of claim 7 , wherein the one or more processors are further configured to: receive the current search key word set; segment the current search key word set into current search key word units; combine the current search key word units into a plurality of current search key word unit groups that correspond to a plurality of current stages, each current stage corresponding to a set of current search key word unit groups, each current search key word unit group in the set having the same number of current search key word units; and use the plurality of search key word tables to identify the current category information that corresponds to the plurality of current search key word unit groups.
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9. The system of claim 7 , wherein the one or more processors are further configured to: receive the current search key word set; segment the current search key word set into current search key word units; combine the current search key word units into a plurality of current search key word unit groups that correspond to a plurality of current stages, each current stage corresponding to a set of current search key word unit groups, each current search key word unit group in the set having the same number of current search key word units; and use the plurality of search key word tables to identify the current category information that corresponds to the plurality of current search key word unit groups. 10. The system of claim 9 , wherein the one or more processors are further configured to: determine a plurality of importance levels of the search key word units; determine, based at least on the plurality of importance levels of the search key word units, a plurality of current importance levels of the current search key word units; select among the current key word units selective current key word units whose importance levels satisfy a precondition; determine, using the plurality of search key word tables corresponding to the plurality of stages, category information that corresponds to the selective current key word unit as the current category information.
| 0.860696 |
2. The method of claim 1 , further comprising retrieving the plurality of documents from a network, wherein scanning the plurality of documents includes scanning each document subsequent to retrieval of the document from the network.
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2. The method of claim 1 , further comprising retrieving the plurality of documents from a network, wherein scanning the plurality of documents includes scanning each document subsequent to retrieval of the document from the network. 3. The method of claim 2 , wherein retrieving the plurality of documents from the network comprises retrieving the plurality of documents from at least one Internet web site in response to a user browsing the at least one Internet web site, and wherein scanning the plurality of documents includes scanning each document upon retrieval of that document from the at least one Internet web site.
| 0.683002 |
1. A method of detecting a malicious URL, said method comprising: retrieving HTML code representing a Web page; scanning said HTML code and identifying at least one embedded URL of said HTML code; identifying layout features of said embedded URL related to the layout of said embedded URL within said HTML code, one of said layout features indicating that said embedded URL is located within the header or the footer of said HTML code; producing a numerical layout vector that indicates the presence of said layout features; processing said numerical layout vector using a classifier algorithm; and outputting a score from said classifier algorithm indicating the likelihood that said embedded URL of said HTML code is a malicious URL.
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1. A method of detecting a malicious URL, said method comprising: retrieving HTML code representing a Web page; scanning said HTML code and identifying at least one embedded URL of said HTML code; identifying layout features of said embedded URL related to the layout of said embedded URL within said HTML code, one of said layout features indicating that said embedded URL is located within the header or the footer of said HTML code; producing a numerical layout vector that indicates the presence of said layout features; processing said numerical layout vector using a classifier algorithm; and outputting a score from said classifier algorithm indicating the likelihood that said embedded URL of said HTML code is a malicious URL. 5. A method as recited in claim 1 further comprising: determining a page rank of a child Web page identified by said URL; producing a numerical referring vector that at least indicates said determined page rank; and inputting said numerical referring vector into said classifier algorithm.
| 0.722576 |
4. The method of claim 1 , wherein the first set of training data comprises a set of individual training examples, and wherein each example represents at least one molecule, and wherein each training example comprises a representation of the at least one molecule and a value for the property of interest modeled by at least one respective molecular property model.
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4. The method of claim 1 , wherein the first set of training data comprises a set of individual training examples, and wherein each example represents at least one molecule, and wherein each training example comprises a representation of the at least one molecule and a value for the property of interest modeled by at least one respective molecular property model. 5. The method of claim 4 , wherein training the more than three molecular property models, comprises: generating a form of each training example for use by a machine learning algorithm; and performing the machine learning algorithm using the set of individual training examples to generate a trained one of the plurality of molecular property models.
| 0.801587 |
39. A computer storage medium storing instructions that, when executed by data processing apparatus, cause the one or more computers to perform operations comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair.
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39. A computer storage medium storing instructions that, when executed by data processing apparatus, cause the one or more computers to perform operations comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair. 56. The computer storage medium of claim 39 , wherein the related text for the text from a text source comprises the text from the text source.
| 0.562763 |
1. A non-transitory computer-readable storage medium comprising computer-readable instructions that, in response to execution, cause a computing system to perform operations, comprising: receiving information indicative of initial entities for content and initial scores associated with the initial entities from one or more content annotation sources; aggregating the information indicative of initial entities for content and initial scores associated with the initial entities received from the one or more content annotation sources; defining a range of values; mapping the initial scores to respective values within the defined range, the mapping producing calibrated scores within the defined range; selecting weights based on joint performance conditions; applying the selected weights to the calibrated scores within the defined range to produce weighted, calibrated scores; selecting a linear aggregation model from among a plurality of linear aggregation models; combining the weighted, calibrated scores based on the selected linear aggregation model to generate a final score; and determining whether to annotate the content with at least one of the initial entities based on a comparison of the final score and a defined threshold value.
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1. A non-transitory computer-readable storage medium comprising computer-readable instructions that, in response to execution, cause a computing system to perform operations, comprising: receiving information indicative of initial entities for content and initial scores associated with the initial entities from one or more content annotation sources; aggregating the information indicative of initial entities for content and initial scores associated with the initial entities received from the one or more content annotation sources; defining a range of values; mapping the initial scores to respective values within the defined range, the mapping producing calibrated scores within the defined range; selecting weights based on joint performance conditions; applying the selected weights to the calibrated scores within the defined range to produce weighted, calibrated scores; selecting a linear aggregation model from among a plurality of linear aggregation models; combining the weighted, calibrated scores based on the selected linear aggregation model to generate a final score; and determining whether to annotate the content with at least one of the initial entities based on a comparison of the final score and a defined threshold value. 7. The non-transitory computer-readable storage medium of claim 1 , wherein the selected linear aggregation model is based on a logarithm of one or more probabilities associated with the initial entities.
| 0.54219 |
6. A computer-implemented method for selecting an answer to a factual query, comprising: receiving a factual query; identifying a set of possible factual answers to the factual query by searching a fact repository that stores factual information extracted from a plurality of documents; determining for each of the possible factual answers a respective score; identifying first answers of the set of possible factual answers to the factual query with best scores; for each of the first answers: identifying, as answers that support the respective first answer, second answers of the set of possible factual answers that are distinct from the respective first answer and support the respective first answer; and determining a supported score by mathematically combining the score of the respective first answer and the scores of the second answers; identifying a third answer of the first answers with a best supported score; and generating a response including the third answer only if the best supported score satisfies a first condition, wherein the first condition includes the best supported score being above a predefined threshold.
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6. A computer-implemented method for selecting an answer to a factual query, comprising: receiving a factual query; identifying a set of possible factual answers to the factual query by searching a fact repository that stores factual information extracted from a plurality of documents; determining for each of the possible factual answers a respective score; identifying first answers of the set of possible factual answers to the factual query with best scores; for each of the first answers: identifying, as answers that support the respective first answer, second answers of the set of possible factual answers that are distinct from the respective first answer and support the respective first answer; and determining a supported score by mathematically combining the score of the respective first answer and the scores of the second answers; identifying a third answer of the first answers with a best supported score; and generating a response including the third answer only if the best supported score satisfies a first condition, wherein the first condition includes the best supported score being above a predefined threshold. 10. The method of claim 6 , further comprising: identifying a fifth answer of the possible answers that is unrelated to the third answer; and determining a supported score for the fifth answer.
| 0.655985 |
3. The method of claim 1 , further comprising: selecting a path in the output memory having a highest likelihood of uniquely identifying an entry in the database; and loading the list memory with reference terms for the selected path, when the list memory has insufficient capacity to load the reference terms of the set of categories.
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3. The method of claim 1 , further comprising: selecting a path in the output memory having a highest likelihood of uniquely identifying an entry in the database; and loading the list memory with reference terms for the selected path, when the list memory has insufficient capacity to load the reference terms of the set of categories. 5. The method of claim 3 , further comprising: eliminating a path in the output memory when no match is found between reference terms in the list memory and a term in the spoken phrase.
| 0.925201 |
6. The method of claim 1 , wherein performing the second iteration of the inner code word error correction process comprises: selecting inner code words to determine selected inner code words; and determining whether errors in the selected inner code words can be corrected by the inner code.
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6. The method of claim 1 , wherein performing the second iteration of the inner code word error correction process comprises: selecting inner code words to determine selected inner code words; and determining whether errors in the selected inner code words can be corrected by the inner code. 7. The method of claim 6 , wherein if the errors in at least one of the selected inner code words fails to be corrected by the inner code, then perform a second iteration of the outer code word error correction process.
| 0.936076 |
13. The system of claim 12 , wherein the processor is further configured to: (i) query the document action requests to determine which are associated with a second document action request type; and (ii) process any of the document action requests of the second document action request type, wherein the document action requests are processed in the order of their associated timestamp, with earlier document action requests of the second document action request type being processed first, wherein the document action requests of the second document action request type are processed only if the document action requests of the first document action request type have been processed.
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13. The system of claim 12 , wherein the processor is further configured to: (i) query the document action requests to determine which are associated with a second document action request type; and (ii) process any of the document action requests of the second document action request type, wherein the document action requests are processed in the order of their associated timestamp, with earlier document action requests of the second document action request type being processed first, wherein the document action requests of the second document action request type are processed only if the document action requests of the first document action request type have been processed. 14. The system of claim 13 , wherein the processor is further configured to: (i) query the document action requests to determine which are associated with a third document action request type; and (ii) process any of the document action requests of the third document action request type, wherein the document action requests are processed in the order of their associated timestamp, with earlier document action requests of the third document action request type being processed first, wherein the document action requests of the third document action request type are processed only if the document action requests of the second document action request type have been processed.
| 0.607726 |
11. A computer system for generating an auto-correct dictionary, the computer system comprising: one or more computer processors; one or more computer readable storage medium; program instructions stored on the computer readable storage medium for execution by at least one of the one or more processors, the program instructions comprising: program instructions to analyze contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; program instructions to identify at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; program instructions to generate a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and program instructions to use the temporary dictionary to carry out auto-correct operations on text included in a second application.
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11. A computer system for generating an auto-correct dictionary, the computer system comprising: one or more computer processors; one or more computer readable storage medium; program instructions stored on the computer readable storage medium for execution by at least one of the one or more processors, the program instructions comprising: program instructions to analyze contents of information accessed by a user via a first application, wherein: the contents of information include at least one of words and phrases that appear in the first application; program instructions to identify at least one of the words and the phrases that appear in the first application and are not included in a first dictionary; program instructions to generate a temporary dictionary based, at least in part, on at least one of the words and the phrases identified in the first application that are not included in the first dictionary; and program instructions to use the temporary dictionary to carry out auto-correct operations on text included in a second application. 14. The computer system of claim 11 , wherein the temporary dictionary of one or both words and phrases includes at least one of: one or both words and phrases that were entered into a field of the first application; one or both words and phrases that were included in the contents of information that appeared in the first application; and one or both words and phrases that are included as part of a description of the first application.
| 0.5 |
22. One or more non-transitory computer-readable storage media storing a data structure, the data structure comprising: one or more concepts associated with a software system; one or more relationship types, respective of the relationship types having one or more terms; for respective of the relationship types, one or more role definitions associated with the one or more terms of the respective relationship type, respective of the role definitions defining the permissible concepts and/or concept instances that can represent the term associated with the respective role definition for the respective relationship type; and one or more relationships based on the one or more concepts and/or the one or more concept instances, the one or more relationships comprising a cross-artifact relationship between a first concept instance of the one or more concept instances and a second concept instance of the one or more concept instances, wherein the cross-artifact relationship specifies a relationship type of the one or more relationship types that relates a concept of the one or more concepts to the first concept instance and the second concept instance.
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22. One or more non-transitory computer-readable storage media storing a data structure, the data structure comprising: one or more concepts associated with a software system; one or more relationship types, respective of the relationship types having one or more terms; for respective of the relationship types, one or more role definitions associated with the one or more terms of the respective relationship type, respective of the role definitions defining the permissible concepts and/or concept instances that can represent the term associated with the respective role definition for the respective relationship type; and one or more relationships based on the one or more concepts and/or the one or more concept instances, the one or more relationships comprising a cross-artifact relationship between a first concept instance of the one or more concept instances and a second concept instance of the one or more concept instances, wherein the cross-artifact relationship specifies a relationship type of the one or more relationship types that relates a concept of the one or more concepts to the first concept instance and the second concept instance. 23. The one or more non-transitory computer-readable storage media of claim 22 , the data structure further comprising: one or more concept instances associated with the at least one or more concepts.
| 0.642734 |
8. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving an electronic document comprising hypertext markup language (HTML) code, body text, and a first raster graphics (RG) image including text-based content, the HTML code providing a format of the body text and the first RG image of the electronic document; identifying one or more textual attributes within the first RG image, the one or more textual attributes including one or more break points located in the text-based content of the first RG image; designating the first RG image for conversion to a vector graphics image (VG image) based at least in part on the identifying of the one or more textual attributes; converting the first RG image to the VG image; determining a body size of a reference character that is located in the VG image; determining a baseline of the VG image relative to the text-based content; segmenting the VG image at the one or more break points to create VG image segments; storing each of the VG image segments as separate but related VG image portions; identifying a second RG image included in the electronic document; determining that the second RG image is free from inclusion of text-based content; preserving the second RG image by refraining from converting the second RG image to a second VG image; and transmitting the electronic document comprising the VG image, the second RG image, and the HTML code to a viewing device for display, wherein the body size and the baseline enable the viewing device to resize and position the text-based content in the VG image to align with adjacent HTML text in the electronic document, and wherein the VG image portions enable the viewing device to reflow at least a portion of the text-based content.
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8. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving an electronic document comprising hypertext markup language (HTML) code, body text, and a first raster graphics (RG) image including text-based content, the HTML code providing a format of the body text and the first RG image of the electronic document; identifying one or more textual attributes within the first RG image, the one or more textual attributes including one or more break points located in the text-based content of the first RG image; designating the first RG image for conversion to a vector graphics image (VG image) based at least in part on the identifying of the one or more textual attributes; converting the first RG image to the VG image; determining a body size of a reference character that is located in the VG image; determining a baseline of the VG image relative to the text-based content; segmenting the VG image at the one or more break points to create VG image segments; storing each of the VG image segments as separate but related VG image portions; identifying a second RG image included in the electronic document; determining that the second RG image is free from inclusion of text-based content; preserving the second RG image by refraining from converting the second RG image to a second VG image; and transmitting the electronic document comprising the VG image, the second RG image, and the HTML code to a viewing device for display, wherein the body size and the baseline enable the viewing device to resize and position the text-based content in the VG image to align with adjacent HTML text in the electronic document, and wherein the VG image portions enable the viewing device to reflow at least a portion of the text-based content. 9. The one or more non-transitory computer-readable media as recited in claim 8 , wherein the acts further comprise storing the baseline and the body size of the reference character located in the text-based content with the VG image.
| 0.562085 |
16. A method performed by a processor of providing companion services to a companion device associated with a media display device, the method comprising: detect video being displayed on the media display device; in response to detecting video being displayed, automatically determining if the video includes an actionable object associated with a product; if the video includes the actionable object associated with the product, performing product-recognition to identify the product represented in the video; providing, at the companion device, access to one or more companion features based on the identified product while playback of the video is being provided on the media display device, wherein providing access to one or more companion features includes adding a referrer identifier to a referrer object list, and wherein the referrer identifier is a link to a website address to associate access of the website address with a referrer, and wherein the referrer object list is a running list of added referrer identifiers that includes referrer identifiers associated with previously identified actionable objects associated with products; and providing instructions to display the added referrer identifiers in the referrer object list based on an order in which the actionable objects associated with the added referrer identifiers were identified in the video.
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16. A method performed by a processor of providing companion services to a companion device associated with a media display device, the method comprising: detect video being displayed on the media display device; in response to detecting video being displayed, automatically determining if the video includes an actionable object associated with a product; if the video includes the actionable object associated with the product, performing product-recognition to identify the product represented in the video; providing, at the companion device, access to one or more companion features based on the identified product while playback of the video is being provided on the media display device, wherein providing access to one or more companion features includes adding a referrer identifier to a referrer object list, and wherein the referrer identifier is a link to a website address to associate access of the website address with a referrer, and wherein the referrer object list is a running list of added referrer identifiers that includes referrer identifiers associated with previously identified actionable objects associated with products; and providing instructions to display the added referrer identifiers in the referrer object list based on an order in which the actionable objects associated with the added referrer identifiers were identified in the video. 17. The method of claim 16 , wherein providing access to the one or more companion features based on the identified product further comprises: providing access to the website address; and providing a selectable option to purchase the product.
| 0.593235 |
1. A tag recommendation system comprising: a computing device; a tag selection element implemented at least in part by the computing device and configured for selecting a plurality of candidate media/tag pairs wherein a candidate tag of each of the candidate media/tag pairs exhibits raw co-occurrence with a target tag of a target media/tag pair; a tag co-occurrence normalization element configured for processing each of the plurality of candidate media/tag pairs against the target media/tag pair resulting in corresponding tag co-occurrence (“TC”) relevance measures wherein the TC relevance measures are in a semantic domain; a visual language modeling element configured for generating a candidate visual language model (“VLM”) for each candidate tag of the plurality of candidate media/tag pairs and a target VLM for a target tag of the target media/tag pair, and further configured for processing each of the candidate VLMs against the target VLM resulting in corresponding tag content correlation (“TCC”) relevance measures wherein such relevance measures are in a visual domain; a visual correlation element configured for processing each of the candidate VLMs against the target VLM resulting in corresponding image-conditioned tag correlation (“ITC”) relevance measures wherein the ITC relevance measures are in a visual domain, wherein the ITC relevance measures are based at least in part on a distance between the target tag and at least one candidate tag, and wherein the distance is an asymmetric distance or a symmetric distance, and wherein the asymmetric distance defined as D ITC a ( t i , t j , x ) = L t i ( x ) · L t j ( x ) L t i ( x ) - L t i ( x ) where x is a target media instance of the target media/tag pair, and where L t i (x)=[ , ], and wherein the symmetric distance defined as D ITC s ( t i , t j , x ) = L t i ( x ) · L t j ( x ) L t i ( x ) L t j ( x ) where x is the target media instance, and where L t i (x)=[ , ], and, for both the asymmetric distance and the symmetric distance, where exponents of 1 indicate a unigram likelihood based on a VLM in a unigram form, and where exponents of 2 indicate a bigram likelihood based on a VLM in a bigram form, and where exponents of 3 indicate a trigram likelihood based on a VLM in a trigram form; and a multi-domain combining element configured for combining one or more TC tag lists indicated by the TC relevance measures with one or more TCC tag lists indicated by the TCC relevance measures and with one or more ITC tag lists indicated by the ITC relevance measures, and further configured for forming a list of recommended tags from the combined one or more TC tags and the one or more TCC tags and the one or more ITC tags.
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1. A tag recommendation system comprising: a computing device; a tag selection element implemented at least in part by the computing device and configured for selecting a plurality of candidate media/tag pairs wherein a candidate tag of each of the candidate media/tag pairs exhibits raw co-occurrence with a target tag of a target media/tag pair; a tag co-occurrence normalization element configured for processing each of the plurality of candidate media/tag pairs against the target media/tag pair resulting in corresponding tag co-occurrence (“TC”) relevance measures wherein the TC relevance measures are in a semantic domain; a visual language modeling element configured for generating a candidate visual language model (“VLM”) for each candidate tag of the plurality of candidate media/tag pairs and a target VLM for a target tag of the target media/tag pair, and further configured for processing each of the candidate VLMs against the target VLM resulting in corresponding tag content correlation (“TCC”) relevance measures wherein such relevance measures are in a visual domain; a visual correlation element configured for processing each of the candidate VLMs against the target VLM resulting in corresponding image-conditioned tag correlation (“ITC”) relevance measures wherein the ITC relevance measures are in a visual domain, wherein the ITC relevance measures are based at least in part on a distance between the target tag and at least one candidate tag, and wherein the distance is an asymmetric distance or a symmetric distance, and wherein the asymmetric distance defined as D ITC a ( t i , t j , x ) = L t i ( x ) · L t j ( x ) L t i ( x ) - L t i ( x ) where x is a target media instance of the target media/tag pair, and where L t i (x)=[ , ], and wherein the symmetric distance defined as D ITC s ( t i , t j , x ) = L t i ( x ) · L t j ( x ) L t i ( x ) L t j ( x ) where x is the target media instance, and where L t i (x)=[ , ], and, for both the asymmetric distance and the symmetric distance, where exponents of 1 indicate a unigram likelihood based on a VLM in a unigram form, and where exponents of 2 indicate a bigram likelihood based on a VLM in a bigram form, and where exponents of 3 indicate a trigram likelihood based on a VLM in a trigram form; and a multi-domain combining element configured for combining one or more TC tag lists indicated by the TC relevance measures with one or more TCC tag lists indicated by the TCC relevance measures and with one or more ITC tag lists indicated by the ITC relevance measures, and further configured for forming a list of recommended tags from the combined one or more TC tags and the one or more TCC tags and the one or more ITC tags. 2. The system of claim 1 further comprising a table generation element configured for generating an inverted tag table wherein the inverted tag table is comprised of the candidate tags wherein each candidate tag is associated with media instances listed as attributes of the candidate tag.
| 0.5 |
1. A method of determining document characteristics prior to processing the document in a document scanner comprising: capturing at least a portion of an input image of documents in an input tray; transmitting said images to a processor; determining characteristics of said documents; processing said documents based on said characteristics; wherein at least one characteristic is related to document condition or content; and detecting whether notes or labels are adhered to the documents; and disabling or enabling ultrasonic zones in at least one location down the document based on said at least one characteristic or the detection of a note or label.
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1. A method of determining document characteristics prior to processing the document in a document scanner comprising: capturing at least a portion of an input image of documents in an input tray; transmitting said images to a processor; determining characteristics of said documents; processing said documents based on said characteristics; wherein at least one characteristic is related to document condition or content; and detecting whether notes or labels are adhered to the documents; and disabling or enabling ultrasonic zones in at least one location down the document based on said at least one characteristic or the detection of a note or label. 4. The method of claim 1 comprising: imaging with a linear sensor.
| 0.879061 |
5. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that classifies text in the text part based on color information of the text, wherein the color information used for classifying is expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a search condition including color information; and a text searching unit that searches the text based on the color information of the search condition.
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5. An image processing apparatus comprising: an extracting unit that extracts a text part from an image; a dividing unit that classifies text in the text part based on color information of the text, wherein the color information used for classifying is expressed in a certain color space, and threshold values are set in components of the certain color space in advance; a search condition specifying unit configured to specify a search condition including color information; and a text searching unit that searches the text based on the color information of the search condition. 9. The image processing apparatus according to claim 5 , further comprising: a compression unit compresses the text part extracted by the extracting unit and other parts individually.
| 0.576923 |
2. The method as in claim 1 wherein prompting the user to type in the phrase includes: instructing the user to write, as the phrase, an expression regarding a particular subject.
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2. The method as in claim 1 wherein prompting the user to type in the phrase includes: instructing the user to write, as the phrase, an expression regarding a particular subject. 3. The method as in claim 2 wherein prompting the user to type in the phrase further includes: prior to instructing the user to write the expression, randomly selecting the particular subject from multiple subjects in a subject database, and presenting the particular subject on the electronic display to the user.
| 0.904719 |
15. The ACM system in accordance with claim 14 wherein said web server configured to receive SOAP/XML requests from said network and transfer the SOAP/XML requests to said SOAP/XML server.
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15. The ACM system in accordance with claim 14 wherein said web server configured to receive SOAP/XML requests from said network and transfer the SOAP/XML requests to said SOAP/XML server. 18. The ACM system in accordance with claim 15 wherein said SOAP/XML server configured to transfer ACM data received from said computer via said network and said web server to said ACM CPU.
| 0.913561 |
1. A machine readable storage having stored thereon a computer program for discussion forum management, the computer program comprising a routine set of instructions which when executed by a machine cause the machine to perform the steps of: receiving externally sourced data for posting in a discussion forum resource; creating a new topic thread for said externally sourced data; and, responsively posting[s] to said externally sourced data in said new topic thread.
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1. A machine readable storage having stored thereon a computer program for discussion forum management, the computer program comprising a routine set of instructions which when executed by a machine cause the machine to perform the steps of: receiving externally sourced data for posting in a discussion forum resource; creating a new topic thread for said externally sourced data; and, responsively posting[s] to said externally sourced data in said new topic thread. 3. The machine readable storage of claim 1 , wherein said externally sourced data comprises data selected from the group consisting of text, audio, imagery and video.
| 0.795343 |
1. An interface for entering electronic text on a touch-sensitive display device, comprising: a virtual keyboard that includes a first key plane and a second, alternate key plane that replaces display of the first key plane, wherein: the first key plane comprises a set of initial phonetic symbols of a single phonetic alphabet; the second key plane comprises a set of final phonetic symbols of the single phonetic alphabet; the first key plane and the second key plane are touch-sensitive and operable to receive user input directed toward each of the phonetic symbols to generate electronic text input; and the virtual keyboard switches between displaying the first key plane and displaying the second key plane in response to predetermined user input triggers received through the virtual keyboard.
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1. An interface for entering electronic text on a touch-sensitive display device, comprising: a virtual keyboard that includes a first key plane and a second, alternate key plane that replaces display of the first key plane, wherein: the first key plane comprises a set of initial phonetic symbols of a single phonetic alphabet; the second key plane comprises a set of final phonetic symbols of the single phonetic alphabet; the first key plane and the second key plane are touch-sensitive and operable to receive user input directed toward each of the phonetic symbols to generate electronic text input; and the virtual keyboard switches between displaying the first key plane and displaying the second key plane in response to predetermined user input triggers received through the virtual keyboard. 7. The interface of claim 1 , wherein the predetermined user input triggers include user selecting one of the set of initial phonetic symbols of the phonetic alphabet on the first key plane.
| 0.69923 |
1. A method for automatically identifying a standalone location, comprising, in a computer, performing the operations of: receiving a term to be evaluated, the term including one or more words; retrieving a non-location score for the term, wherein the non-location score is determined from log data, the log data indicating how frequently the term was entered within a non-location input box, the non-location input box for specifying what a user is searching for in search queries; retrieving a location score for the term, wherein the location score is determined from the log data, the log data indicating how frequently the term was entered within a location input box, the location input box for specifying a geographical location associated with search queries; and determining, at a computer, whether the term is a standalone location based on the non-location score and the location score, wherein a standalone location is a geographic location that is identifiable by its name alone.
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1. A method for automatically identifying a standalone location, comprising, in a computer, performing the operations of: receiving a term to be evaluated, the term including one or more words; retrieving a non-location score for the term, wherein the non-location score is determined from log data, the log data indicating how frequently the term was entered within a non-location input box, the non-location input box for specifying what a user is searching for in search queries; retrieving a location score for the term, wherein the location score is determined from the log data, the log data indicating how frequently the term was entered within a location input box, the location input box for specifying a geographical location associated with search queries; and determining, at a computer, whether the term is a standalone location based on the non-location score and the location score, wherein a standalone location is a geographic location that is identifiable by its name alone. 2. The method of claim 1 , wherein the non-location score for the term is determined from the number of times that the term appears in the non-location box of a search engine interface that includes the non-location box for receiving terms specifying what a user is searching for and the location box for receiving terms specifying a geographic location within which the user is searching.
| 0.558968 |
8. A system for generating a glyphs compliance report, the system comprising: one or more physical processors configured by machine-readable instructions to: obtain, from electronic storage, localized text for a video game, the localized text including one or more glyphs to be displayed during gameplay in the video game, individual glyphs comprising individual parts of individual characters used in a language region, individual combinations of glyphs forming individual characters; compare the one or more glyphs in the localized text to a predetermined list of approved glyphs appropriate for an intended age range of the users of the video game, the comparison being used to determine whether or not the localized text includes any unapproved glyphs that are not on the predetermined list of approved glyphs, the predetermined list of approved glyphs including glyphs that the users of the intended age range are expected to know to facilitate understanding of individual characters including the approved glyphs, the unapproved glyphs including glyphs that the users of the intended age range are not expected to know since understanding of individual characters including the unapproved glyphs is not expected of the users of the intended age range; and generate a glyphs compliance report indicating whether or not the localized text includes at least one unapproved glyph that is not on the predetermined list of approved glyphs.
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8. A system for generating a glyphs compliance report, the system comprising: one or more physical processors configured by machine-readable instructions to: obtain, from electronic storage, localized text for a video game, the localized text including one or more glyphs to be displayed during gameplay in the video game, individual glyphs comprising individual parts of individual characters used in a language region, individual combinations of glyphs forming individual characters; compare the one or more glyphs in the localized text to a predetermined list of approved glyphs appropriate for an intended age range of the users of the video game, the comparison being used to determine whether or not the localized text includes any unapproved glyphs that are not on the predetermined list of approved glyphs, the predetermined list of approved glyphs including glyphs that the users of the intended age range are expected to know to facilitate understanding of individual characters including the approved glyphs, the unapproved glyphs including glyphs that the users of the intended age range are not expected to know since understanding of individual characters including the unapproved glyphs is not expected of the users of the intended age range; and generate a glyphs compliance report indicating whether or not the localized text includes at least one unapproved glyph that is not on the predetermined list of approved glyphs. 11. The system of claim 8 , wherein the one or more physical processors are further configured by machine-readable instructions such that, responsive to a first glyph in the localized text not corresponding to any glyph on the predetermined list of glyphs, the glyphs compliance report specifies that the first glyph in the localized text is not found on the predetermined list of glyphs.
| 0.588946 |
10. The one or more non-transitory machine-readable media of claim 9 , wherein the operations comprise associating, for at least some of the second content items, a respective author restrict with the second content item.
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10. The one or more non-transitory machine-readable media of claim 9 , wherein the operations comprise associating, for at least some of the second content items, a respective author restrict with the second content item. 12. The one or more non-transitory machine-readable media of claim 10 , wherein the operations comprise: updating the search index to associate a searcher restrict comprising data identifying the second entity of the two entities with content authored by the first entity of the two entities.
| 0.92842 |
26. A method of using a candidate selection system that includes at least a first trained machine learning system, the method comprising: receiving, by at least one processor-based system, a number of heuristic values each indicative of a strength of a respective pairing between two entities, the heuristic values generated by at least one machine learning system trained with at least a first entity and a second entity that are a historically successful pairing, and trained with a plurality of hypothetical alternative pairings between the first entity of the historically successful pairing and other entities of a first set of entities based at least in part on at least one value of each of at least one of a plurality of attributes associated with the second entity and based on at least one loosened constraint of a number of constraints applied to matches between the values of at least one of the attributes associated with the second entity; and executing, by the at least one processor-based system, a candidate selection algorithm which employs the received heuristic values and respective values for each of the plurality of attributes for each of a second set of entities to identify prospective candidates.
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26. A method of using a candidate selection system that includes at least a first trained machine learning system, the method comprising: receiving, by at least one processor-based system, a number of heuristic values each indicative of a strength of a respective pairing between two entities, the heuristic values generated by at least one machine learning system trained with at least a first entity and a second entity that are a historically successful pairing, and trained with a plurality of hypothetical alternative pairings between the first entity of the historically successful pairing and other entities of a first set of entities based at least in part on at least one value of each of at least one of a plurality of attributes associated with the second entity and based on at least one loosened constraint of a number of constraints applied to matches between the values of at least one of the attributes associated with the second entity; and executing, by the at least one processor-based system, a candidate selection algorithm which employs the received heuristic values and respective values for each of the plurality of attributes for each of a second set of entities to identify prospective candidates. 35. The method of claim 26 , further comprising: receiving by at least a first processor-based server system information about the plurality of attributes for each of the entities of the second set of entities; and presenting to the first entity a plurality of messages sent to the first entity by other ones of the entities in a ranked order, the ranked order reflecting a strength of a pairing between at least the first entity and the other ones of the entities.
| 0.683201 |
1. A computer-implemented system comprising: a communications module to receive an input, the input specifying a rule expressed in a custom syntax, the custom syntax provided by a rules authoring system; and a translator to translate the rule expressed in the custom syntax into a translated rule, using at least one processor, the translated rule being in a form of a source code suitable for being compiled into an executable module, the translator comprising: a parser to parse the rule expressed in the custom syntax, a validator to utilize one or more validation rules to validate parameters associated with the rule, a validation rule from the one or more validation rules authored using the custom syntax, and a resource generator to extract resources associated with the rule and to process the resources into a format suitable for a runtime environment, the resources comprising one or more keywords; a compiler configured to compile the translated rule into a compiled rule; and a deployment module to publish the compiled rule to the runtime environment.
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1. A computer-implemented system comprising: a communications module to receive an input, the input specifying a rule expressed in a custom syntax, the custom syntax provided by a rules authoring system; and a translator to translate the rule expressed in the custom syntax into a translated rule, using at least one processor, the translated rule being in a form of a source code suitable for being compiled into an executable module, the translator comprising: a parser to parse the rule expressed in the custom syntax, a validator to utilize one or more validation rules to validate parameters associated with the rule, a validation rule from the one or more validation rules authored using the custom syntax, and a resource generator to extract resources associated with the rule and to process the resources into a format suitable for a runtime environment, the resources comprising one or more keywords; a compiler configured to compile the translated rule into a compiled rule; and a deployment module to publish the compiled rule to the runtime environment. 5. The system of claim 1 , comprising a presentation module for presenting the rule expressed in the custom syntax to a viewer.
| 0.5 |
10. An electronic device comprising: a display for displaying a user interface (UI); one or more processors; and, memory comprising instructions which, when executed by one or more of the processors, cause the device to: receive, from a UI client engine associated with an application, a UI component tree for the application, the UI component tree comprising: UI component nodes each having associated predefined contextual rendering information, and a custom rendering element node having associated incomplete contextual rendering information; generate UI rendering instructions in accordance with the UI component tree by: for each UI component node, using the predefined contextual rendering information to generate UI component rendering instructions, for the custom rendering element node, retrieving custom rendering instructions generated by the application and generating incomplete rendering instructions based on the incomplete contextual rendering information, the custom rendering instructions comprises a first part of instructions for rendering a corresponding custom rendering element, and the incomplete rendering instructions comprising a second part of instructions for rendering said corresponding custom rendering element; and combining the UI component rendering instructions, the incomplete rendering instructions and the retrieved custom rendering instructions; and render the UI to the display in accordance with the generated UI rendering instructions.
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10. An electronic device comprising: a display for displaying a user interface (UI); one or more processors; and, memory comprising instructions which, when executed by one or more of the processors, cause the device to: receive, from a UI client engine associated with an application, a UI component tree for the application, the UI component tree comprising: UI component nodes each having associated predefined contextual rendering information, and a custom rendering element node having associated incomplete contextual rendering information; generate UI rendering instructions in accordance with the UI component tree by: for each UI component node, using the predefined contextual rendering information to generate UI component rendering instructions, for the custom rendering element node, retrieving custom rendering instructions generated by the application and generating incomplete rendering instructions based on the incomplete contextual rendering information, the custom rendering instructions comprises a first part of instructions for rendering a corresponding custom rendering element, and the incomplete rendering instructions comprising a second part of instructions for rendering said corresponding custom rendering element; and combining the UI component rendering instructions, the incomplete rendering instructions and the retrieved custom rendering instructions; and render the UI to the display in accordance with the generated UI rendering instructions. 17. The electronic device of claim 10 , wherein the incomplete contextual rendering information comprises at least one of preferred position in a coordinate system, preferred size, and rotation.
| 0.5 |
8. A method of displaying text to a driver of an automobile, the method comprising: displaying by a text display, positioned in the automobile without impairing forward visual attention of the driver, a cursor and a subsequence of a sequence of words, the subsequence having a maximum length and including an active word, the cursor for indicating either the active word or a boundary thereof; in response to receiving, from an occupant of the automobile, an input to adjust the cursor: (a) updating the cursor to indicate a new active word within the sequence, or a boundary thereof, and (b) displaying by the text display the cursor and a second subsequence of the sequence of words, the second subsequence determined based upon the new active word and the maximum length; and in response to receiving, from an occupant of the automobile, an input comprising at least one new word, either: (a) replacing the active word with the at least one new word, if the cursor indicates the active word, or (b) inserting the at least one new word between the active word and an adjacent word, if the cursor indicates a boundary between the active word and the adjacent word.
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8. A method of displaying text to a driver of an automobile, the method comprising: displaying by a text display, positioned in the automobile without impairing forward visual attention of the driver, a cursor and a subsequence of a sequence of words, the subsequence having a maximum length and including an active word, the cursor for indicating either the active word or a boundary thereof; in response to receiving, from an occupant of the automobile, an input to adjust the cursor: (a) updating the cursor to indicate a new active word within the sequence, or a boundary thereof, and (b) displaying by the text display the cursor and a second subsequence of the sequence of words, the second subsequence determined based upon the new active word and the maximum length; and in response to receiving, from an occupant of the automobile, an input comprising at least one new word, either: (a) replacing the active word with the at least one new word, if the cursor indicates the active word, or (b) inserting the at least one new word between the active word and an adjacent word, if the cursor indicates a boundary between the active word and the adjacent word. 9. A method according to claim 8 , further comprising, when the input comprises a navigation operation that followed either a non-navigation operation, or a prior navigation operation in a different direction, updating the cursor to indicate a boundary of the active word.
| 0.60048 |
15. A computer system, comprising: one or more processors; a memory comprising a set of instructions which when executed causes the one or more processors to execute a method, the method comprising: receiving a plurality of comments respectively associated with a plurality of video clips from a plurality of videos stored in a video database; receiving comment metadata regarding each comment of the plurality of comments, including a category of a plurality of categories and one or more time values related to a video clip of the plurality of video clips, one or more computers receiving one or more criteria to apply to the comment metadata, wherein the one or more criteria specify at least a particular category of the plurality of categories; the one or more computers selecting two or more video clips by applying the one or more criteria to the comment metadata to identify video clips with comments that are associated with the particular category, the selecting two or more video clips further comprising: identifying two or more comments on different videos of the plurality of comments where the comment metadata specifies the two or more comments as meeting the one or more criteria; and determining, for each comment of the two or more comments, the video clip associated with the comment based on the one or more time values in the comment metadata corresponding to the comment, wherein, for each comment of the two or more comments, a duration of the video clip associated with the comment is determined based on a user-specified duration of time, a default duration of time, or a duration of time stored in the comment metadata; the one or more computers displaying the two or more video clips by merging the two or more video clips into a compilation video.
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15. A computer system, comprising: one or more processors; a memory comprising a set of instructions which when executed causes the one or more processors to execute a method, the method comprising: receiving a plurality of comments respectively associated with a plurality of video clips from a plurality of videos stored in a video database; receiving comment metadata regarding each comment of the plurality of comments, including a category of a plurality of categories and one or more time values related to a video clip of the plurality of video clips, one or more computers receiving one or more criteria to apply to the comment metadata, wherein the one or more criteria specify at least a particular category of the plurality of categories; the one or more computers selecting two or more video clips by applying the one or more criteria to the comment metadata to identify video clips with comments that are associated with the particular category, the selecting two or more video clips further comprising: identifying two or more comments on different videos of the plurality of comments where the comment metadata specifies the two or more comments as meeting the one or more criteria; and determining, for each comment of the two or more comments, the video clip associated with the comment based on the one or more time values in the comment metadata corresponding to the comment, wherein, for each comment of the two or more comments, a duration of the video clip associated with the comment is determined based on a user-specified duration of time, a default duration of time, or a duration of time stored in the comment metadata; the one or more computers displaying the two or more video clips by merging the two or more video clips into a compilation video. 16. The computer system of claim 15 , wherein each category of the plurality of categories is defined by a taxonomy of a plurality of taxonomies, the one or more criteria specify a particular taxonomy of a plurality of taxonomies, and the comment metadata specifies a taxonomy for comments associated with each video of the plurality of videos.
| 0.506188 |
36. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from an attitude represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the attitude generating with a computer an output communication pertaining to the risk posed by the person from the attitude of the at least one communication.
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36. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from an attitude represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the attitude generating with a computer an output communication pertaining to the risk posed by the person from the attitude of the at least one communication. 47. A method in accordance with claim 36 wherein the output communication includes a responsive action that should be taken in response to the determined risk.
| 0.619554 |
1. A method for managing data organisation for computer programs, the method including the steps of: generating and storing a reference taxonomy, the reference taxonomy comprising information defining a user preference for data organisation; accessing storage associated with a computer program to obtain an application taxonomy, the application taxonomy comprising information defining the organisation of stored data items of the program; comparing the reference taxonomy with the application taxonomy to identify matching and non-matching features of the compared taxonomies; and in response to a selection of a preferred taxonomy based on a result of the comparison, storing the preferred taxonomy as a replacement of at least one of the reference taxonomy and the application taxonomy, wherein the step of storing the preferred taxonomy in response to a selection of the preferred taxonomy includes generating a modified application taxonomy which includes features of the compared reference taxonomy, and wherein the generated reference taxonomy includes nodes representing data structures and information representing relationships between data structures, and wherein the step of generating a modified application taxonomy includes repositioning data structures within the compared application taxonomy, such as that the relationships between the data structures of the modified application taxonomy and nodes of the reference taxonomy are more consistent than the relationships between data structures of the compared application taxonomy and nodes of the reference taxonomy.
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1. A method for managing data organisation for computer programs, the method including the steps of: generating and storing a reference taxonomy, the reference taxonomy comprising information defining a user preference for data organisation; accessing storage associated with a computer program to obtain an application taxonomy, the application taxonomy comprising information defining the organisation of stored data items of the program; comparing the reference taxonomy with the application taxonomy to identify matching and non-matching features of the compared taxonomies; and in response to a selection of a preferred taxonomy based on a result of the comparison, storing the preferred taxonomy as a replacement of at least one of the reference taxonomy and the application taxonomy, wherein the step of storing the preferred taxonomy in response to a selection of the preferred taxonomy includes generating a modified application taxonomy which includes features of the compared reference taxonomy, and wherein the generated reference taxonomy includes nodes representing data structures and information representing relationships between data structures, and wherein the step of generating a modified application taxonomy includes repositioning data structures within the compared application taxonomy, such as that the relationships between the data structures of the modified application taxonomy and nodes of the reference taxonomy are more consistent than the relationships between data structures of the compared application taxonomy and nodes of the reference taxonomy. 10. A method according to claim 1 , wherein said step of generating a reference taxonomy is performed on a first data processing apparatus and is followed by a step of sending at least a part of the reference taxonomy to a second data processing apparatus, and wherein the steps of comparing and storing a selected preferred taxonomy are performed on the second data processing apparatus.
| 0.519494 |
1. A computer-implemented method comprising: providing a database organized according to a relational model; providing a database engine in communication with the database through a language describing the relational model; providing an application comprising an entity-relationship model (ERM), the ERM including a first entity, a second entity, and a relationship between the first entity and the second entity; and causing a query engine of the application to communicate a query to the database engine utilizing a language extension comprising, a first structured entity type including a first key and indicating the first entity, a second structured entity type including a second key and indicating the second entity, and a structured association type reflecting the relationship and including a first parameter clause specifying cardinality information, and including a second parameter clause specifying a combination of alternative key elements in a nested structure comprising an alias name of one alternative key element in a substructure of the second structured entity; and causing the database engine to return a query result to the query engine based upon the language extension.
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1. A computer-implemented method comprising: providing a database organized according to a relational model; providing a database engine in communication with the database through a language describing the relational model; providing an application comprising an entity-relationship model (ERM), the ERM including a first entity, a second entity, and a relationship between the first entity and the second entity; and causing a query engine of the application to communicate a query to the database engine utilizing a language extension comprising, a first structured entity type including a first key and indicating the first entity, a second structured entity type including a second key and indicating the second entity, and a structured association type reflecting the relationship and including a first parameter clause specifying cardinality information, and including a second parameter clause specifying a combination of alternative key elements in a nested structure comprising an alias name of one alternative key element in a substructure of the second structured entity; and causing the database engine to return a query result to the query engine based upon the language extension. 3. The computer-implemented method of claim 1 wherein the query engine communicates to the database engine, the structured association type including further information in a third parameter clause.
| 0.545907 |
34. The method of claim 33 , further comprising: referencing an additional metadata comprising at least one of the content identifier and the advertisement based on a video processing algorithm, wherein the additional meta data is at least one of a title, a description, a thumbnail, a name of an individual, and a historical data, and wherein the additional metadata is determined from a browser history captured from the client device based on a capture policy, and correlating a relevance of the browser history with at least one of the content identifier and the advertisement; constraining an executable environment in a security sandbox; executing the sandboxed application in the executable environment using a processor and a memory; automatically instantiating a connection between the sandboxed application and the unannounced device associated with the networked media device based on the determination that the internet protocol address of the port from the unannounced device is associated with the networked media device; processing an identification data associated with the sandbox reachable service sharing a public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; establishing a communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox; appending a header of a hypertext transfer protocol to permit the networked media device to communicate with the sandboxed application as a permitted origin domain through a Cross-origin resource sharing (CORS) algorithm, wherein the header is either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communications a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server; and automatically regenerating a script embedded in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and sandboxed application based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server.
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34. The method of claim 33 , further comprising: referencing an additional metadata comprising at least one of the content identifier and the advertisement based on a video processing algorithm, wherein the additional meta data is at least one of a title, a description, a thumbnail, a name of an individual, and a historical data, and wherein the additional metadata is determined from a browser history captured from the client device based on a capture policy, and correlating a relevance of the browser history with at least one of the content identifier and the advertisement; constraining an executable environment in a security sandbox; executing the sandboxed application in the executable environment using a processor and a memory; automatically instantiating a connection between the sandboxed application and the unannounced device associated with the networked media device based on the determination that the internet protocol address of the port from the unannounced device is associated with the networked media device; processing an identification data associated with the sandbox reachable service sharing a public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; establishing a communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox; appending a header of a hypertext transfer protocol to permit the networked media device to communicate with the sandboxed application as a permitted origin domain through a Cross-origin resource sharing (CORS) algorithm, wherein the header is either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the sandbox reachable service optionally verifies that the sandboxed application is in the common private network, wherein the sandbox reachable service communications a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to a pairing server; and automatically regenerating a script embedded in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and sandboxed application based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. 40. The method of claim 34 , further comprising: extending the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox; and bypassing a pairing server having the discovery algorithm and the relay algorithm when establishing the connection between the sandboxed application and the sandbox reachable service when the security sandbox is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox.
| 0.805015 |
1. A method programmed in a non-transitory memory of a first device, the method comprising: automatically detecting a comment associated with an entity in a video or audio; in response to automatically detecting the comment associated with the entity, converting the comment into searchable information; comparing the searchable information with information from one or more sources to determine a factual accuracy of the comment; computing an entity validity rating associated with the entity based on the factual accuracy of the comment; causing the entity validity rating to be displayed on a display of a second device.
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1. A method programmed in a non-transitory memory of a first device, the method comprising: automatically detecting a comment associated with an entity in a video or audio; in response to automatically detecting the comment associated with the entity, converting the comment into searchable information; comparing the searchable information with information from one or more sources to determine a factual accuracy of the comment; computing an entity validity rating associated with the entity based on the factual accuracy of the comment; causing the entity validity rating to be displayed on a display of a second device. 2. The method of claim 1 wherein the entity validity rating is displayed in conjunction with the comment associated with the entity.
| 0.71507 |
8. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving a plurality of signals from a plurality of sensors, wherein the plurality of sensors comprises hardware and software sensors of a computing device; determining a plurality of trust levels from the plurality of signals, wherein each of the plurality of trust levels is determined based on one or more of the plurality of signals independently from the determination of any other trust level of the plurality of trust levels and without using any other trust level of the plurality of trust levels, and wherein the determination of at least one of the plurality of trust levels based on one or more of the plurality of signals uses a signal from a hardware sensor; aggregating the plurality of trust levels to determine a first aggregated trust outcome, wherein the first aggregated trust outcome is a granular aggregated trust outcome associated with a first security measure of a computing device; aggregating the plurality of trust levels to determine a second aggregated trust outcome, wherein the second aggregated trust outcome a granular aggregated trust outcome associated with a second security measure of the computing device; wherein the first aggregated trust outcome is determined independent of the second aggregated trust outcome and without using the second aggregated trust outcome; wherein the second aggregated trust outcome is determined independent of the first aggregated trust outcome and without using the first aggregated trust outcome; enabling or disabling the first security measure based on the first granular aggregated trust outcome, wherein the first security measure is not associated with the second granular aggregated trust outcome and the second granular aggregated trust outcome is not used to enable or disable the first security measure; and enabling or disabling the second security measure based on the second granular aggregated trust outcome, wherein the second security measure is not associated with the first granular aggregated trust outcome and the first granular aggregated trust outcome is not used to enable or disable the second security measure.
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8. A computer-implemented method performed by a data processing apparatus, the method comprising: receiving a plurality of signals from a plurality of sensors, wherein the plurality of sensors comprises hardware and software sensors of a computing device; determining a plurality of trust levels from the plurality of signals, wherein each of the plurality of trust levels is determined based on one or more of the plurality of signals independently from the determination of any other trust level of the plurality of trust levels and without using any other trust level of the plurality of trust levels, and wherein the determination of at least one of the plurality of trust levels based on one or more of the plurality of signals uses a signal from a hardware sensor; aggregating the plurality of trust levels to determine a first aggregated trust outcome, wherein the first aggregated trust outcome is a granular aggregated trust outcome associated with a first security measure of a computing device; aggregating the plurality of trust levels to determine a second aggregated trust outcome, wherein the second aggregated trust outcome a granular aggregated trust outcome associated with a second security measure of the computing device; wherein the first aggregated trust outcome is determined independent of the second aggregated trust outcome and without using the second aggregated trust outcome; wherein the second aggregated trust outcome is determined independent of the first aggregated trust outcome and without using the first aggregated trust outcome; enabling or disabling the first security measure based on the first granular aggregated trust outcome, wherein the first security measure is not associated with the second granular aggregated trust outcome and the second granular aggregated trust outcome is not used to enable or disable the first security measure; and enabling or disabling the second security measure based on the second granular aggregated trust outcome, wherein the second security measure is not associated with the first granular aggregated trust outcome and the first granular aggregated trust outcome is not used to enable or disable the second security measure. 12. The computer-implemented method of claim 8 , wherein the first aggregated trust outcome is a confidence level that a mobile computing device is either being used by an authorized user or is in a secure environment.
| 0.616461 |
1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record.
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1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record. 6. The computer-implemented method of claim 1 , further comprising: determining, by the computer, the definition of the target word based on context used within a resource from which the target word originates.
| 0.595933 |
22. The media of claim 20 , wherein execution of the instructions dynamically selects the set of predictions including generating ranked predictions by ordering the plurality of predictions according to descending probability.
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22. The media of claim 20 , wherein execution of the instructions dynamically selects the set of predictions including generating ranked predictions by ordering the plurality of predictions according to descending probability. 23. The media of claim 22 , wherein execution of the instructions dynamically selects the set of predictions by determining a sequential pair of predictions in the ranked predictions between which the difference in corresponding probabilities is greatest relative to any other sequential pair of predictions, wherein the sequential pair of predictions include a first prediction and a second prediction, the first prediction having a higher probability than the second prediction.
| 0.816333 |
3. A computer-implemented method for providing search results for a query, comprising: receiving a search query to obtain a plurality of references to web pages as search results; obtaining the plurality of references to web pages as search results; receiving from a client device a social information domain to be used to rerank the plurality of references to web pages as search results using social information from the social information domain; reranking the plurality of references to web pages using social information; wherein reranking the plurality of references to web pages using social information further comprises generating a bipartite graph with a plurality of users connected by weighted edges to a plurality of terms, wherein the edges are weighted by a number of times the user referenced the term, and generating a dimensional vector of a plurality of users with a plurality of terms from the bipartite graph with the plurality of users connected by weighted edges to the plurality of terms, wherein the edges are weighted by a number of times the user referenced the term; and sending the reranked plurality of references to web pages as search results to a client device for display to a user.
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3. A computer-implemented method for providing search results for a query, comprising: receiving a search query to obtain a plurality of references to web pages as search results; obtaining the plurality of references to web pages as search results; receiving from a client device a social information domain to be used to rerank the plurality of references to web pages as search results using social information from the social information domain; reranking the plurality of references to web pages using social information; wherein reranking the plurality of references to web pages using social information further comprises generating a bipartite graph with a plurality of users connected by weighted edges to a plurality of terms, wherein the edges are weighted by a number of times the user referenced the term, and generating a dimensional vector of a plurality of users with a plurality of terms from the bipartite graph with the plurality of users connected by weighted edges to the plurality of terms, wherein the edges are weighted by a number of times the user referenced the term; and sending the reranked plurality of references to web pages as search results to a client device for display to a user. 5. The method of claim 3 wherein reranking the plurality of references to web pages using social information further comprises computing a similarity between the plurality of references to web pages with a plurality of terms and a plurality of users with a plurality of terms.
| 0.62149 |
2. The computer-implemented method of claim 1 , wherein selecting the subset of the one or more other client computing devices to invite to participate in the communication session comprises: determining which of the one or more other client computing devices are associated with the digital content item; and selecting the one or more other client computing devices are associated with the digital content item.
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2. The computer-implemented method of claim 1 , wherein selecting the subset of the one or more other client computing devices to invite to participate in the communication session comprises: determining which of the one or more other client computing devices are associated with the digital content item; and selecting the one or more other client computing devices are associated with the digital content item. 3. The computer-implemented method of claim 2 , wherein determining which of the one or more other client computing devices are associated with the digital content item comprises: determining whether the one or more other client computing devices have interacted with the digital content item; determining whether one or more users associated with the one or more other client computing devices, respectively, have a proximate geographic association with the digital content item, wherein the proximate geographic association comprises a distance less than a threshold distance between a location associated with the digital content item and a location associated with the one or more other client computing devices; determining whether the one or more users associated with the one or more other client computing devices have been tagged in association with the digital content item, wherein being tagged in association with the digital content item comprises one or more pieces of metadata that identify a user; and determining whether the one or more users of the one or more other client computing devices have specified an interest in a topic associated with the digital content item.
| 0.736111 |
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