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4. A system comprising: a network alarm input message processing facility including at least one hardware processor configured to: receive a network alarm message provided by a network element of a wide area network, the network alarm message being in a first message format, and map content of the network alarm message to a plurality of fields of a network universal message format based on a mapping data file associated with the first message format; a network alarm message conversion facility communicatively coupled to the network alarm input message processing facility and configured to: translate the content of the network alarm message in the first message format based on a translation rules data file associated with the first message format, and populate the plurality of fields with the translated content to generate a new network alarm message in the network universal message format; a network alarm output message processing facility communicatively coupled to the network alarm message conversion facility and configured to provide the new network alarm message in the network universal message format to a network surveillance application, wherein the network surveillance application is configured to conduct surveillance of the wide area network by interpreting the new network alarm message in the network universal message format and performing a root-cause analysis based at least in part on the interpreted new network alarm message in the network universal message format; a storage facility communicatively coupled to the network alarm input message processing facility and the network alarm message conversion facility, the storage facility configured to: store the mapping data file and the translation rules data file associated with the first message format, receive a request to add a new mapping data file and a new translation rules data file to the storage facility, the new mapping data file and the new translation rules data file associated with a second message format, and add the new mapping data file and the new translation rules data file to the storage facility for use in translating one or more network alarm messages from the second message format to the network universal message format, wherein the addition of the new mapping data file and the new translation rules data file to the storage facility is performed without interrupting surveillance of the network. | 4. A system comprising: a network alarm input message processing facility including at least one hardware processor configured to: receive a network alarm message provided by a network element of a wide area network, the network alarm message being in a first message format, and map content of the network alarm message to a plurality of fields of a network universal message format based on a mapping data file associated with the first message format; a network alarm message conversion facility communicatively coupled to the network alarm input message processing facility and configured to: translate the content of the network alarm message in the first message format based on a translation rules data file associated with the first message format, and populate the plurality of fields with the translated content to generate a new network alarm message in the network universal message format; a network alarm output message processing facility communicatively coupled to the network alarm message conversion facility and configured to provide the new network alarm message in the network universal message format to a network surveillance application, wherein the network surveillance application is configured to conduct surveillance of the wide area network by interpreting the new network alarm message in the network universal message format and performing a root-cause analysis based at least in part on the interpreted new network alarm message in the network universal message format; a storage facility communicatively coupled to the network alarm input message processing facility and the network alarm message conversion facility, the storage facility configured to: store the mapping data file and the translation rules data file associated with the first message format, receive a request to add a new mapping data file and a new translation rules data file to the storage facility, the new mapping data file and the new translation rules data file associated with a second message format, and add the new mapping data file and the new translation rules data file to the storage facility for use in translating one or more network alarm messages from the second message format to the network universal message format, wherein the addition of the new mapping data file and the new translation rules data file to the storage facility is performed without interrupting surveillance of the network. 9. The system of claim 4 , wherein the network universal message format specifies a plurality of fields comprising at least an alarm source field for data representing a source of an alarm, a sub-node field for data representing at least one sub-node network element affected by the alarm, and an alarm severity field for data representing a severity level of the alarm. | 0.636107 |
19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. | 19. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: identifying two or more consecutive terms in a search query; determining a first quantity of search results that (i) are responsive to the search query, and (ii) have been selected by a user; determining a second quantity of search results that (i) are responsive to the search query, (ii) have been selected by the user, and (iii) have summaries that include the two or more consecutive terms; determining a value using the first quantity and the second quantity; and determining a likelihood that the two or more consecutive terms represent a compound based on the value. 23. The medium of claim 19 , wherein a compound is a combination of terms that has a different meaning in combination than the terms do separately. | 0.710145 |
12. A method for automatically generating grammar for use in the processing of natural language, the method comprising: setting one domain as a target domain to be processed by an intention analysis system using a setting processor; extracting a corpus relevant to the target domain from a collection of corpora using an extractor, dividing the corpus into sentences and tagging the sentences; classifying the extracted corpus into a domain action among one or more domain actions that correspond to the target domain; converting one or more words included in the extracted corpus into classes; and generating a grammar based on the converted classes of the extracted corpus using a generator wherein one or more ungrammatical words or sentences are removed from the corpus. | 12. A method for automatically generating grammar for use in the processing of natural language, the method comprising: setting one domain as a target domain to be processed by an intention analysis system using a setting processor; extracting a corpus relevant to the target domain from a collection of corpora using an extractor, dividing the corpus into sentences and tagging the sentences; classifying the extracted corpus into a domain action among one or more domain actions that correspond to the target domain; converting one or more words included in the extracted corpus into classes; and generating a grammar based on the converted classes of the extracted corpus using a generator wherein one or more ungrammatical words or sentences are removed from the corpus. 17. The method of claim 12 , wherein the collection of corpora include text corpus that is collected from one or more of novels, magazines, dictionaries, and text available on the World Wide Web, and the collection of corpora further includes speech corpus that is collected from one or more of conversations, interviews, and speeches. | 0.601896 |
12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename. | 12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename. 15. The non-transitory computer readable storage medium of claim 12 further comprising generating another data structure comprising each entry from the file once, the another data structure providing metadata for received URLs. | 0.502825 |
11. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a local computing system, a query from a business enterprise computing system, the query comprising data associated with a business enterprise commodity, the data comprising one or more attributes of the business enterprise commodity; matching the one or more attributes of the business enterprise commodity with one or more terms of a plurality of terms in a word matrix, the word matrix comprising: a plurality of nodes that each comprise a term of the plurality of terms; and a plurality of links that each connect two or more nodes and define a similarity between the two or more nodes; generating, based on the matching, a numerical vector for the business enterprise commodity; identifying, based on the numerical vector, one or more classification regions that each define a classification of the business enterprise commodity; and preparing the classifications of the business enterprise commodity of the one or more identified classification regions for display at the business enterprise computing system. | 11. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving, at a local computing system, a query from a business enterprise computing system, the query comprising data associated with a business enterprise commodity, the data comprising one or more attributes of the business enterprise commodity; matching the one or more attributes of the business enterprise commodity with one or more terms of a plurality of terms in a word matrix, the word matrix comprising: a plurality of nodes that each comprise a term of the plurality of terms; and a plurality of links that each connect two or more nodes and define a similarity between the two or more nodes; generating, based on the matching, a numerical vector for the business enterprise commodity; identifying, based on the numerical vector, one or more classification regions that each define a classification of the business enterprise commodity; and preparing the classifications of the business enterprise commodity of the one or more identified classification regions for display at the business enterprise computing system. 16. The computer storage medium of claim 11 , wherein the operations further comprise: transmitting the classifications of the business enterprise commodity of the one or more identified classification regions for display at the business enterprise computing system; receiving a selection of one of the classifications of the business enterprise commodity from the business enterprise computing system; and updating the word matrix based on the received selection. | 0.58311 |
15. A computer device comprising: at least one memory that stores computer-executable instructions; at least one processor configured to access the at least one memory and execute the computer-executable instructions to: receive a scanned image of a source text, the scanned image comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text; generate an image representative of each of the first glyph and the second glyph; determine a first positional reference line indicative of a default positioning of a first character along a horizontal or vertical baseline; determine a second positional reference line indicative of an alignment of characters forming the first word and a third positional reference line indicative of an alignment of characters forming the second word; determine a first distance value between the first positional reference line and the second positional reference line; assign a first numerical identifier to the first glyph; generate first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first distance value; generate a font file configured to be executed by a renderer to render the source text, the font file comprising the image and the first glyph data; and generate a digitally renderable format for the source text based at least in part on the font file and the scanned image. | 15. A computer device comprising: at least one memory that stores computer-executable instructions; at least one processor configured to access the at least one memory and execute the computer-executable instructions to: receive a scanned image of a source text, the scanned image comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text; generate an image representative of each of the first glyph and the second glyph; determine a first positional reference line indicative of a default positioning of a first character along a horizontal or vertical baseline; determine a second positional reference line indicative of an alignment of characters forming the first word and a third positional reference line indicative of an alignment of characters forming the second word; determine a first distance value between the first positional reference line and the second positional reference line; assign a first numerical identifier to the first glyph; generate first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first distance value; generate a font file configured to be executed by a renderer to render the source text, the font file comprising the image and the first glyph data; and generate a digitally renderable format for the source text based at least in part on the font file and the scanned image. 20. The computer device of claim 15 , wherein the image is a vector image. | 0.883567 |
15. The memory device of claim 14 , wherein determining the adjusted query further comprises: determining multiple adjusted queries, each having corresponding interpreted probabilities; and wherein further the inserting the adjustment option comprises inserting multiple adjustment options, each describing one or more of the multiple adjusted queries, at multiple adjustment positions based on the corresponding interpreted probabilities of the one or more adjusted queries described by the multiple adjustment options. | 15. The memory device of claim 14 , wherein determining the adjusted query further comprises: determining multiple adjusted queries, each having corresponding interpreted probabilities; and wherein further the inserting the adjustment option comprises inserting multiple adjustment options, each describing one or more of the multiple adjusted queries, at multiple adjustment positions based on the corresponding interpreted probabilities of the one or more adjusted queries described by the multiple adjustment options. 16. The memory device of claim 15 , wherein a quantity of the multiple adjusted queries described by the inserted multiple adjustment options is limited based on the corresponding interpreted probability of respective ones of the multiple adjusted queries. | 0.90661 |
16. A method for providing search results comprising the steps of: providing sets of data comprising: (a) one or more search engine identifiers of a plurality of search engine identifiers, (b) one or more search engine uniform resource locators of a plurality of search engine uniform resource locators, (c) one or more second placeholder patterns of a plurality of second placeholder patterns, (d) one or more query term separators of a plurality of query term separators, and wherein said search engine identifier of a plurality of search engine identifiers represents a search engine of a plurality of search engines, and wherein said search engine identifier of a plurality of search engines identifiers is linked to components of said sets of data including: (i) said search engine uniform resource locator of a plurality of search engine uniform resource locators, (ii) said second placeholder pattern of a plurality of second placeholder patterns, and (iii) said query term separator of a plurality of query term separators, and wherein said search engine uniform resource locator of a plurality of search engine uniform resource locators includes: (a). a scheme of a plurality of schemes, (b). a host of a plurality of hosts, (c). a path of a plurality of paths, (d). a query of a plurality of queries comprising: a first placeholder pattern of a plurality of first placeholder patterns representing a value of a plurality of values in a name value pair of a plurality of name value pairs, and wherein said second placeholder pattern of a plurality of second placeholder patterns is identical to said first placeholder pattern of a plurality of first placeholder patterns; loading said sets of data; receiving voiced utterances from a user of a plurality of users; converting said voiced utterances into a first data string; matching said first data string to said sets of data, identifying a corresponding said search engine identifier of a plurality of search engine identifiers; retrieving data linked to matched said search engine identifier of a plurality of search engine identifiers; storing retrieved data linked to said matched search engine identifier of a plurality of search engine identifiers in variables; signaling said user of a plurality of users that said first data string matched a corresponding said search engine identifier of a plurality of search engine identifiers; receiving a second set of voiced utterances from said user of a plurality of users specifying a query term to be searched for; converting said second set of voiced utterances into a second data string; modifying said second data string by replacing any spaces in said second data string with retrieved said query term separator linked to said search engine identifier of a plurality of search engine identifiers, creating a modified second data string; replacing said first placeholder pattern of a plurality of placeholder patterns in retrieved said search engine uniform resource locator of a plurality of search engine uniform resource locators with said modified second data string creating a modified search engine uniform resource locator; opening said modified search engine uniform resource locator through a uniform resource locator transmission method of a plurality of uniform resource locator transmission methods; and providing results of the search system. | 16. A method for providing search results comprising the steps of: providing sets of data comprising: (a) one or more search engine identifiers of a plurality of search engine identifiers, (b) one or more search engine uniform resource locators of a plurality of search engine uniform resource locators, (c) one or more second placeholder patterns of a plurality of second placeholder patterns, (d) one or more query term separators of a plurality of query term separators, and wherein said search engine identifier of a plurality of search engine identifiers represents a search engine of a plurality of search engines, and wherein said search engine identifier of a plurality of search engines identifiers is linked to components of said sets of data including: (i) said search engine uniform resource locator of a plurality of search engine uniform resource locators, (ii) said second placeholder pattern of a plurality of second placeholder patterns, and (iii) said query term separator of a plurality of query term separators, and wherein said search engine uniform resource locator of a plurality of search engine uniform resource locators includes: (a). a scheme of a plurality of schemes, (b). a host of a plurality of hosts, (c). a path of a plurality of paths, (d). a query of a plurality of queries comprising: a first placeholder pattern of a plurality of first placeholder patterns representing a value of a plurality of values in a name value pair of a plurality of name value pairs, and wherein said second placeholder pattern of a plurality of second placeholder patterns is identical to said first placeholder pattern of a plurality of first placeholder patterns; loading said sets of data; receiving voiced utterances from a user of a plurality of users; converting said voiced utterances into a first data string; matching said first data string to said sets of data, identifying a corresponding said search engine identifier of a plurality of search engine identifiers; retrieving data linked to matched said search engine identifier of a plurality of search engine identifiers; storing retrieved data linked to said matched search engine identifier of a plurality of search engine identifiers in variables; signaling said user of a plurality of users that said first data string matched a corresponding said search engine identifier of a plurality of search engine identifiers; receiving a second set of voiced utterances from said user of a plurality of users specifying a query term to be searched for; converting said second set of voiced utterances into a second data string; modifying said second data string by replacing any spaces in said second data string with retrieved said query term separator linked to said search engine identifier of a plurality of search engine identifiers, creating a modified second data string; replacing said first placeholder pattern of a plurality of placeholder patterns in retrieved said search engine uniform resource locator of a plurality of search engine uniform resource locators with said modified second data string creating a modified search engine uniform resource locator; opening said modified search engine uniform resource locator through a uniform resource locator transmission method of a plurality of uniform resource locator transmission methods; and providing results of the search system. 19. The method of claim 16 , wherein converting said voiced utterances into data is performed by a speech recognition system. | 0.515277 |
1. A method for selection of a provenance dependency function in a stream-based data processing infrastructure to optimize backtracing performance in response to a provenance query, the method comprising: determining performance of a set of dependency functions associated with an analysis component for determining relevancy of each input event received by the analysis component, wherein each of the dependency functions provides a different, respective method for determining a respective data provenance of a given output event for the analysis component; determining the relevancy of each input event according to each of the dependency functions and storing a record of relevant events according to a recording method; aggregating relevancy results of the dependency functions and ordering the dependency functions according to a criterion indicating the relevancy of the input events provided by the dependency functions; for the given output event, selecting between the dependency functions to obtain a best dependency function from the set of dependency functions based on the ordering; and providing the respective data provenance for the given output event provided by the best dependency function using an input event recording method associated with the best dependency function according to the criterion. | 1. A method for selection of a provenance dependency function in a stream-based data processing infrastructure to optimize backtracing performance in response to a provenance query, the method comprising: determining performance of a set of dependency functions associated with an analysis component for determining relevancy of each input event received by the analysis component, wherein each of the dependency functions provides a different, respective method for determining a respective data provenance of a given output event for the analysis component; determining the relevancy of each input event according to each of the dependency functions and storing a record of relevant events according to a recording method; aggregating relevancy results of the dependency functions and ordering the dependency functions according to a criterion indicating the relevancy of the input events provided by the dependency functions; for the given output event, selecting between the dependency functions to obtain a best dependency function from the set of dependency functions based on the ordering; and providing the respective data provenance for the given output event provided by the best dependency function using an input event recording method associated with the best dependency function according to the criterion. 3. The method as recited in claim 1 , wherein the aggregating relevancy results of the dependency functions and ordering the dependency functions according to a criterion includes computing a relevancy ratio. | 0.575241 |
6. A method to manufacture a system using a user device in communication with a stored data repository, that reduces the background noise from a speech audio signal generated by a user, comprising: providing a user device, with a processor and a memory, receiving a speech audio signal; and providing a noise reduction device, in communication with a stored data repository, and in communication with said user device, is configured to: convert said received speech audio signal to text; generate synthetic speech based on a speech data corpus or speech model data of the user stored in said stored data repository and said converted text; determine the predicted subjective quality of the received speech audio signal if that signal were to be transmitted to a far end listener; determine the predicted subjective quality of said synthetic speech; and transmit, selectively, said speech audio signal or said synthetic speech, whichever has higher predicted quality based on a comparison between the value of objective quality metrics computed for the speech audio signal and the synthetic speech signal. | 6. A method to manufacture a system using a user device in communication with a stored data repository, that reduces the background noise from a speech audio signal generated by a user, comprising: providing a user device, with a processor and a memory, receiving a speech audio signal; and providing a noise reduction device, in communication with a stored data repository, and in communication with said user device, is configured to: convert said received speech audio signal to text; generate synthetic speech based on a speech data corpus or speech model data of the user stored in said stored data repository and said converted text; determine the predicted subjective quality of the received speech audio signal if that signal were to be transmitted to a far end listener; determine the predicted subjective quality of said synthetic speech; and transmit, selectively, said speech audio signal or said synthetic speech, whichever has higher predicted quality based on a comparison between the value of objective quality metrics computed for the speech audio signal and the synthetic speech signal. 9. The claim according to claim 6 , wherein said step of receiving said speech audio signal by said user device further comprises pre-processing said speech audio signal based on using a predetermined noise reduction algorithm. | 0.688787 |
1. A method comprising: receiving a plurality of medical documents, the plurality of medical documents including a first set of medical documents in a first format and a second set of medical documents in a second format, wherein the first format is an image-based format and the second format is in a structured data format, and wherein the structured data format is in a non-image text data organized by fields and respective values; determining a schema, the schema including a plurality of categories determined based on an expected structural content in the first set of medical documents or second set of medical documents; determining indices from the plurality of categories to be used for tagging the first set of medical documents and the second set of medical documents when converted into the image-based format based on a review of an organizing principle to which a common set of descriptors can be identified to tag and organize images of the first set of medical documents and the second set of medical documents; converting the non-image text data of the second set of medical documents into images in the image-based format based on the determined indices, wherein the second format is removed in the conversion and content included in each image is determined based on the determined indices applying to the fields and respective values; indexing images of the first medical documents and the images of the second medical documents in the image-based format by associating the determined indices based on the schema with content determined from the first and second medical documents; and storing the images of the first set of medical documents and the images of the second set of medical documents in the image-based format with the indices to allow searching of both the first set of medical documents and the second set of medical documents together based on a search query. | 1. A method comprising: receiving a plurality of medical documents, the plurality of medical documents including a first set of medical documents in a first format and a second set of medical documents in a second format, wherein the first format is an image-based format and the second format is in a structured data format, and wherein the structured data format is in a non-image text data organized by fields and respective values; determining a schema, the schema including a plurality of categories determined based on an expected structural content in the first set of medical documents or second set of medical documents; determining indices from the plurality of categories to be used for tagging the first set of medical documents and the second set of medical documents when converted into the image-based format based on a review of an organizing principle to which a common set of descriptors can be identified to tag and organize images of the first set of medical documents and the second set of medical documents; converting the non-image text data of the second set of medical documents into images in the image-based format based on the determined indices, wherein the second format is removed in the conversion and content included in each image is determined based on the determined indices applying to the fields and respective values; indexing images of the first medical documents and the images of the second medical documents in the image-based format by associating the determined indices based on the schema with content determined from the first and second medical documents; and storing the images of the first set of medical documents and the images of the second set of medical documents in the image-based format with the indices to allow searching of both the first set of medical documents and the second set of medical documents together based on a search query. 7. The method of claim 1 , wherein the plurality of medical documents are received from different medical providers. | 0.601299 |
1. A method for titling a recording comprising: receiving a stimulus to commence a title acquisition mode; receiving an utterance representing a title during the title acquisition mode; converting the utterance into a series of textual characters using a speech to text converter, wherein the textual characters represent a lingual translation of the utterance; storing the series of textual characters representing the title in memory; automatically commencing a recording mode a predetermined time after the title acquisition mode is commenced; receiving a body of a recording during the recording mode; storing the body of the recording in memory; and automatically linking the series of textual characters representing the title with the body of the recording in memory to title the body of the recording. | 1. A method for titling a recording comprising: receiving a stimulus to commence a title acquisition mode; receiving an utterance representing a title during the title acquisition mode; converting the utterance into a series of textual characters using a speech to text converter, wherein the textual characters represent a lingual translation of the utterance; storing the series of textual characters representing the title in memory; automatically commencing a recording mode a predetermined time after the title acquisition mode is commenced; receiving a body of a recording during the recording mode; storing the body of the recording in memory; and automatically linking the series of textual characters representing the title with the body of the recording in memory to title the body of the recording. 9. The method of claim 1 , further comprising: displaying, prior to accepting the confirmation from the user, the series of textual characters representing the title. | 0.64722 |
1. A sports skill evaluation system, comprising: an inputting section for inputting, while course selection items displayed on a screen are selected, required data for each of the items regarding a user; a basic database for storing personal basic data of the user including a level, a match experience, an age and a sex inputted through said inputting section; a coefficient table in which application coefficients including level-based coefficients, age-based coefficients and sex-based coefficients are stored in advance; application coefficient calculation means for referring to said coefficient table based on the level, age and sex inputted through said inputting section to determine respective individual application coefficients; skill item point calculation means for calculating, from a score according to a result of a match of the user inputted through said inputting section and the individual application coefficients determined by said application coefficient calculation section, a skill item point for each of skills required for the match; skill diagnosis graph production means for producing diagnosis graphs for the individual skills from the skill item points for the individual skills calculated by said skill item point calculation means; comment pattern designation value calculation means for converting the level, match experience, age and sex inputted through said inputting section into numerical values and calculating comment pattern designation values for the individual skill items based on the numerical values in accordance with a predetermined calculation expression; a comment table in which a plurality of comments to be presented each as a comment to a user are stored such that the comments are classified for the individual skill items and are numbered for the individual comments; and comment extraction means for extracting a comment of a number corresponding to each of the comment pattern designation values calculated by said comment pattern designation value calculation means for each of the skill items from said comment table. | 1. A sports skill evaluation system, comprising: an inputting section for inputting, while course selection items displayed on a screen are selected, required data for each of the items regarding a user; a basic database for storing personal basic data of the user including a level, a match experience, an age and a sex inputted through said inputting section; a coefficient table in which application coefficients including level-based coefficients, age-based coefficients and sex-based coefficients are stored in advance; application coefficient calculation means for referring to said coefficient table based on the level, age and sex inputted through said inputting section to determine respective individual application coefficients; skill item point calculation means for calculating, from a score according to a result of a match of the user inputted through said inputting section and the individual application coefficients determined by said application coefficient calculation section, a skill item point for each of skills required for the match; skill diagnosis graph production means for producing diagnosis graphs for the individual skills from the skill item points for the individual skills calculated by said skill item point calculation means; comment pattern designation value calculation means for converting the level, match experience, age and sex inputted through said inputting section into numerical values and calculating comment pattern designation values for the individual skill items based on the numerical values in accordance with a predetermined calculation expression; a comment table in which a plurality of comments to be presented each as a comment to a user are stored such that the comments are classified for the individual skill items and are numbered for the individual comments; and comment extraction means for extracting a comment of a number corresponding to each of the comment pattern designation values calculated by said comment pattern designation value calculation means for each of the skill items from said comment table. 7. A sports skill evaluation system according to claim 1 , wherein said basic database stores a health diagnosis result of the user, and said skill item point calculation means refers to the health diagnosis result and basic data arithmetically operated based on the health diagnosis result to calculate points of skill items relating to the health of the user. | 0.577478 |
2. The method of claim 1 wherein at least some of the plurality of data objects are of an object type selected from the list: image, video, flash, text node, anchor, area. | 2. The method of claim 1 wherein at least some of the plurality of data objects are of an object type selected from the list: image, video, flash, text node, anchor, area. 5. The method of claim 2 wherein at least one of the plurality of data objects is of the object type image, and the metadata collected from the HTML code includes an alt, a title and a src associated with the at least one of the plurality of data objects. | 0.947216 |
26. The system of claim 20 , wherein the media object is a book, and the content comprises body text. | 26. The system of claim 20 , wherein the media object is a book, and the content comprises body text. 28. The system of claim 26 , wherein the new metadata includes at least one of: a genre; a target demograph; a proportion of users that complete the book after starting it; an average amount of time taken to complete the book; an average amount of time users spend reading the book in a single sitting; and an average number of sittings it takes for a user to complete the book. | 0.707865 |
22. The system of claim 21 , wherein in case a record exhibits a visual similarity above a predefined threshold with at least one record in a specified group, it is not filtered out. | 22. The system of claim 21 , wherein in case a record exhibits a visual similarity above a predefined threshold with at least one record in a specified group, it is not filtered out. 23. The system of claim 22 , wherein the records in the specified group are obtained by querying the representative texts or querying by the image data in at least one public image databases. | 0.953897 |
1. A social media content access processor-implemented method, comprising: identifying a request to access user 3 rd party social media content; obtaining user authorization credentials to access 3 rd party user social media content; sending an access request with the obtained user authorization credentials to a device disjunct social media platform; receiving social media content data from the device disjunct social media platform; determining a type of the received media content data; tagging the received media content data based on the type according to a progressive taxonomy mechanism, wherein the progressive taxonomy mechanism comprises a set of pre-determined key terms; receiving a social media analytics request for an item; querying the tagged media content data based on key terms related to the item; performing text analytics on the social media content data; and determining impression heuristics for the item based on query results. | 1. A social media content access processor-implemented method, comprising: identifying a request to access user 3 rd party social media content; obtaining user authorization credentials to access 3 rd party user social media content; sending an access request with the obtained user authorization credentials to a device disjunct social media platform; receiving social media content data from the device disjunct social media platform; determining a type of the received media content data; tagging the received media content data based on the type according to a progressive taxonomy mechanism, wherein the progressive taxonomy mechanism comprises a set of pre-determined key terms; receiving a social media analytics request for an item; querying the tagged media content data based on key terms related to the item; performing text analytics on the social media content data; and determining impression heuristics for the item based on query results. 10. The method of claim 1 , wherein the receiving social media content data from the social media platform is performed on demand. | 0.541506 |
20. The method of claim 18 , wherein the user selectable SMSC is dedicated to translating content from the first language to the second language only. | 20. The method of claim 18 , wherein the user selectable SMSC is dedicated to translating content from the first language to the second language only. 21. The method of claim 20 , further comprising offering multiple user selectable SMSCs to subscribers, each one of said multiple user selectable SMSCs respectively being operable to translate between different pairs of languages. | 0.860441 |
17. The system of claim 14 , wherein the processing system is further configured to: identify one or more tags in the electronic resource; parse content text associated with each of the identified tags to determine whether the content text matches a normalized data entry; and mark an identified tag of the electronic resource with a navigation filter heading annotation in response to a determination that the content text associated with the identified tag matches one or more of the normalized data entries. | 17. The system of claim 14 , wherein the processing system is further configured to: identify one or more tags in the electronic resource; parse content text associated with each of the identified tags to determine whether the content text matches a normalized data entry; and mark an identified tag of the electronic resource with a navigation filter heading annotation in response to a determination that the content text associated with the identified tag matches one or more of the normalized data entries. 19. The system of claim 17 , wherein the processing system is configured to, for each of the identified tags: determine whether the tag is a child node of a hyperlink; and remove the tag from consideration as a potential navigation filter heading in response to a determination that the tag is a child node of a hyperlink. | 0.908963 |
8. An apparatus, comprising: a housing comprising a front face and a back side; a primary display; a secondary display comprising a prism arranged to create an illusion that a text title is floating in a middle of the prism and the prism is rounded toward the front face of the housing to enable a user to read a side display screen when the apparatus is lying flat on the back side, the primary and secondary displays comprising separate displays; and processing circuitry coupled with the primary display and the secondary display, the processing circuitry to: receive a communication message, determine whether the communication message is a voice message, an e-mail message or a text message, use one or more words from the voice message as text for the text title when the communication message is a voice message, use one or more words from the e-mail message as text for the text title when the communication message is an e-mail message, use one or more words from the text message as text for the text title when the communication message is a text message, and display the text title associated with the communication message on the secondary display. | 8. An apparatus, comprising: a housing comprising a front face and a back side; a primary display; a secondary display comprising a prism arranged to create an illusion that a text title is floating in a middle of the prism and the prism is rounded toward the front face of the housing to enable a user to read a side display screen when the apparatus is lying flat on the back side, the primary and secondary displays comprising separate displays; and processing circuitry coupled with the primary display and the secondary display, the processing circuitry to: receive a communication message, determine whether the communication message is a voice message, an e-mail message or a text message, use one or more words from the voice message as text for the text title when the communication message is a voice message, use one or more words from the e-mail message as text for the text title when the communication message is an e-mail message, use one or more words from the text message as text for the text title when the communication message is a text message, and display the text title associated with the communication message on the secondary display. 11. The apparatus of claim 8 , the processing circuitry to use one or more words from the e-mail message to create text for the text title via one or more of a summary program, a word frequency count program and a semantic reasoning program when the communication message is an e-mail message. | 0.598394 |
9. The method as recited in claim 1 , further comprising training the boosting chain using face images, non-face images, and weak classifiers. | 9. The method as recited in claim 1 , further comprising training the boosting chain using face images, non-face images, and weak classifiers. 10. The method as recited in claim 9 , wherein the boosting chain includes the plurality of boosting nodes arranged in an order within the boosting chain. | 0.928772 |
9. The computer-readable memory device of claim 8 , where the programming instructions further comprise: one or more instructions to monitor a portion of the particular search result document to detect one or more changes in the portion of the particular search result document; and one or more instructions to determine that content of the particular search result document changed, upon detecting the one or more changes in the portion of the particular search result document. | 9. The computer-readable memory device of claim 8 , where the programming instructions further comprise: one or more instructions to monitor a portion of the particular search result document to detect one or more changes in the portion of the particular search result document; and one or more instructions to determine that content of the particular search result document changed, upon detecting the one or more changes in the portion of the particular search result document. 10. The computer-readable memory device of claim 9 , where the portion of the particular search result document corresponds to a set of terms that appear most frequently in the particular search result document, relative to other terms in the particular search result document. | 0.838956 |
1. A document acceptor for authenticating and storing documents, the document acceptor comprising: a document validator configured to authenticate received documents; a document cassette configured to store the documents received by the document validator; and a displacement actuator including a housing, a lever, and a cam operatively coupled to the lever, wherein rotation of the lever causes the cam to transition between a first cam position and a second cam position, wherein the cam is configured to interface with the document cassette when moving to the second cam position to change a position of the document cassette from a first position to a second position to mate the document cassette with the document validator, wherein the housing is adapted to removably secure the displacement actuator to a document acceptor, and wherein the housing is held in a fixed position relative to the document validator while the position of the document cassette is changed. | 1. A document acceptor for authenticating and storing documents, the document acceptor comprising: a document validator configured to authenticate received documents; a document cassette configured to store the documents received by the document validator; and a displacement actuator including a housing, a lever, and a cam operatively coupled to the lever, wherein rotation of the lever causes the cam to transition between a first cam position and a second cam position, wherein the cam is configured to interface with the document cassette when moving to the second cam position to change a position of the document cassette from a first position to a second position to mate the document cassette with the document validator, wherein the housing is adapted to removably secure the displacement actuator to a document acceptor, and wherein the housing is held in a fixed position relative to the document validator while the position of the document cassette is changed. 7. The document acceptor of claim 1 , further comprising a chassis coupling the document validator and the displacement actuator, the displacement actuator including a housing being removably secured to the chassis. | 0.601109 |
20. The routing method according to claim 18 , further comprising: finding whether the Lth and (L+1)th words of the routing string are the repetitive words; if the Lth and (L+1)th words of the routing string are the repetitive words, cloning the packet and the routing string to generate cloned packets and cloned routing strings; modifying target addresses of the cloned packets and the cloned routing strings; and transmitting each of the cloned packets to the other connected core according to the 2nd through (L+1)th words of the corresponding cloned routing string. | 20. The routing method according to claim 18 , further comprising: finding whether the Lth and (L+1)th words of the routing string are the repetitive words; if the Lth and (L+1)th words of the routing string are the repetitive words, cloning the packet and the routing string to generate cloned packets and cloned routing strings; modifying target addresses of the cloned packets and the cloned routing strings; and transmitting each of the cloned packets to the other connected core according to the 2nd through (L+1)th words of the corresponding cloned routing string. 21. The routing method according to claim 20 , wherein a differential value between the length of the routing string and the addressing string length is obtained, and whether the (L−j)th and (L−j+1)th words of the target address are the same words is checked to determine whether the Lth and (L+1)th words of the routing string are the repetitive words. | 0.724175 |
5. The method according to claim 1 , comprising applying learned balancing factors to each of: the relevance score with respect to a post in a discussion thread, the penalty or reward regulizer, and the at least one of: a subjectivity score of the thread and an objectivity score of the thread. | 5. The method according to claim 1 , comprising applying learned balancing factors to each of: the relevance score with respect to a post in a discussion thread, the penalty or reward regulizer, and the at least one of: a subjectivity score of the thread and an objectivity score of the thread. 6. The method according to claim 5 , wherein the penalty or reward regulizer comprises a calculation of graph cover with respect to the chosen number of posts for calculating a relevance score of a thread. | 0.916829 |
1. A method for routing a facsimile, comprising: receiving text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text of the facsimile for at least one of a meaning and a context of the text; routing the facsimile or text thereof to one or more destinations based on the analysis; initiating a business process based on the analysis; detecting a problem with the business process; generating a notification of the problem; and notifying one or more entities of the problem, wherein the routing utilizes an outgoing communication device. | 1. A method for routing a facsimile, comprising: receiving text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text of the facsimile for at least one of a meaning and a context of the text; routing the facsimile or text thereof to one or more destinations based on the analysis; initiating a business process based on the analysis; detecting a problem with the business process; generating a notification of the problem; and notifying one or more entities of the problem, wherein the routing utilizes an outgoing communication device. 8. The method as recited in claim 1 , wherein at least one of the destinations corresponds to an intended recipient of the facsimile. | 0.622967 |
13. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including: accessing an electronic structure file that corresponds to an assessment and includes structure-file data, the structure-file data including a region of interest where a response to a question on the assessment is to be provided rendering an image of the structure-file data or processed version of the structure-file data, the rendered image representing the region of interest; detecting a first input provided during a presentation of the rendered image corresponding to specification of a position of the region of interest; detecting a second input identifying a target data element corresponding to the question; defining a segment-position specification indicative of the position of the region of interest; generating an electronic template that associates an identifier of the question with the segment-position specification; detecting a content object for processing that includes content-object data; determining that the content object for processing corresponds to the electronic template; extracting, using the segment-position specification of the template, a portion of the content-object data that corresponds to the region of interest, the portion of the content-object data including a response to the question on the assessment; evaluating the portion of the content-object data to identify the response to the question included in portion of the content-object data; determining an evaluation quality metric reflecting a confidence in the identification of the response; and determining whether a quality criterion is satisfied based on the evaluation quality metric; and when it is determined that the quality criterion is not satisfied: facilitating a presentation that includes the portion of the content-object data; and receiving a third input corresponding to an identification of a score corresponding to the response. | 13. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including: accessing an electronic structure file that corresponds to an assessment and includes structure-file data, the structure-file data including a region of interest where a response to a question on the assessment is to be provided rendering an image of the structure-file data or processed version of the structure-file data, the rendered image representing the region of interest; detecting a first input provided during a presentation of the rendered image corresponding to specification of a position of the region of interest; detecting a second input identifying a target data element corresponding to the question; defining a segment-position specification indicative of the position of the region of interest; generating an electronic template that associates an identifier of the question with the segment-position specification; detecting a content object for processing that includes content-object data; determining that the content object for processing corresponds to the electronic template; extracting, using the segment-position specification of the template, a portion of the content-object data that corresponds to the region of interest, the portion of the content-object data including a response to the question on the assessment; evaluating the portion of the content-object data to identify the response to the question included in portion of the content-object data; determining an evaluation quality metric reflecting a confidence in the identification of the response; and determining whether a quality criterion is satisfied based on the evaluation quality metric; and when it is determined that the quality criterion is not satisfied: facilitating a presentation that includes the portion of the content-object data; and receiving a third input corresponding to an identification of a score corresponding to the response. 14. The computer-program product as recited in claim 13 , wherein the actions further include: the content-object data so as to change a file type, coordinate system, zoom, alignment or skew of, wherein the portion of the content-object data is extracted from the processed content-object data. | 0.831818 |
9. A computer-implemented method performed by a first terminal for managing media resources, comprising: receiving a selection of a media resource to be transmitted to a second terminal; accessing a stored first relationship model associated with the user of the first terminal and describing hierarchically the content of the media resource, the first relationship model including: first topic nodes corresponding to first keywords describing the content of the media resource, a first resource node identifying the media resource, and first links connecting the first topic nodes and the first resource node; accessing a stored second relationship model associated with a user of the second terminal and describing hierarchically the content of the media resource, the second relationship model including: second topic nodes corresponding to second keywords describing the content of the media resource, a second resource node identifying the media resource, and second links connecting the second topic nodes and the second resource node; determining whether the first relationship model contains a topic node that is different from the second relationship model, based on whether a keyword of the first keywords is different from the second keywords; and when it is determined that the first relationship model contains the different topic node: updating the second relationship model to include the different topic node; and transmitting to the second terminal the selected media resource and the updated second relationship model. | 9. A computer-implemented method performed by a first terminal for managing media resources, comprising: receiving a selection of a media resource to be transmitted to a second terminal; accessing a stored first relationship model associated with the user of the first terminal and describing hierarchically the content of the media resource, the first relationship model including: first topic nodes corresponding to first keywords describing the content of the media resource, a first resource node identifying the media resource, and first links connecting the first topic nodes and the first resource node; accessing a stored second relationship model associated with a user of the second terminal and describing hierarchically the content of the media resource, the second relationship model including: second topic nodes corresponding to second keywords describing the content of the media resource, a second resource node identifying the media resource, and second links connecting the second topic nodes and the second resource node; determining whether the first relationship model contains a topic node that is different from the second relationship model, based on whether a keyword of the first keywords is different from the second keywords; and when it is determined that the first relationship model contains the different topic node: updating the second relationship model to include the different topic node; and transmitting to the second terminal the selected media resource and the updated second relationship model. 11. The method of claim 9 , wherein the first and second relationship models further include respective weightings assigned to the first and second links, the weightings respectively indicating the values of the first and second topic nodes connected by the first and second links in leading the users of the first and second terminals to access the media resource. | 0.536916 |
14. A non-transitory computer-readable medium storing instructions, which, when executed by one or more processors, cause the one or more processors to perform: identifying first data representing an object-oriented data model, which comprises a plurality of object-oriented data model constructs for modeling object-oriented classes; wherein identifying the first data comprises identifying the first data amongst data representing an object-oriented data model; translating the first data to second data, which represents one or more YANG data model statements, but which is not extensible markup language data and which does not comprise constructs for modeling the object-oriented classes; wherein the one or more YANG data model statements capture relationships between the object-oriented data model constructs; wherein each YANG statement of the one or more YANG data model statements represented by the second data comprises a YANG keyword, which is followed by zero or more arguments, which is followed by either a semicolon or a block of YANG sub-statements enclosed within braces; and storing the second data in one or more non-transitory computer-readable media; wherein storing the second data comprises storing the second data as part of data representing a YANG data model. | 14. A non-transitory computer-readable medium storing instructions, which, when executed by one or more processors, cause the one or more processors to perform: identifying first data representing an object-oriented data model, which comprises a plurality of object-oriented data model constructs for modeling object-oriented classes; wherein identifying the first data comprises identifying the first data amongst data representing an object-oriented data model; translating the first data to second data, which represents one or more YANG data model statements, but which is not extensible markup language data and which does not comprise constructs for modeling the object-oriented classes; wherein the one or more YANG data model statements capture relationships between the object-oriented data model constructs; wherein each YANG statement of the one or more YANG data model statements represented by the second data comprises a YANG keyword, which is followed by zero or more arguments, which is followed by either a semicolon or a block of YANG sub-statements enclosed within braces; and storing the second data in one or more non-transitory computer-readable media; wherein storing the second data comprises storing the second data as part of data representing a YANG data model. 24. The non-transitory computer-readable medium of claim 14 , wherein an object-oriented data model construct, from the plurality of object-oriented data model constructs, is a particular declaration of a complex type object-oriented class instance variable of a particular object-oriented class; wherein the one or more YANG data model statements includes a particular YANG list statement declared as a YANG sub-statement of a particular YANG grouping statement, the particular YANG grouping statement having been generated for the particular object-oriented class; wherein translating the first data to the second data comprises translating the particular declaration of the complex type object-oriented class instance variable of the particular object-oriented class to the particular YANG list statement. | 0.502424 |
1. A method comprising: receiving, by a computing device, an indication of user-inputted text; storing, by the computing device, a lexicon that includes a set of in-lexicon candidate strings and does not include a set of out-of-lexicon candidate strings, wherein each of the in-lexicon candidate strings and each of the out-of-lexicon candidate strings is a respective word in a particular language; for each respective in-lexicon candidate string of the set of in-lexicon candidate strings, determining, by the computing device, a respective score for the respective in-lexicon candidate string, wherein: the respective score is based at least in part on a probability of the respective in-lexicon candidate string as a whole being entered, and the probability of the respective in-lexicon candidate string being entered is affected by a word-level context of the respective in-lexicon candidate string that includes one or more character strings that precede the respective in-lexicon candidate string in the user-inputted text; for each respective out-of-lexicon candidate string of the set of out-of-lexicon candidate strings, determining, by the computing device, a respective score for the respective out-of-lexicon candidate string, wherein the respective score for the respective out-of-lexicon candidate string is based at least in part on respective probabilities of individual characters in the respective out-of-lexicon candidate string being entered and is not based on word-level probabilities; determining, by the computing device and based at least in part on the scores for the in-lexicon candidate strings and the scores for the out-of-lexicon candidate strings, a combined set of candidate strings from the set of in-lexicon candidate strings and the set of out-of-lexicon candidate strings, the combined set of candidate strings including at least one in-lexicon candidate string from the set of in-lexicon candidate strings and at least one out-of-lexicon candidate string from the set of out-of-lexicon candidate strings; outputting, by the computing device, at least a portion of the combined set of candidate strings for display; and responsive to an indication of a selection of a candidate string from the combined set of candidate strings, outputting, by the computing device, for display in place of the user-inputted text, the selected candidate string. | 1. A method comprising: receiving, by a computing device, an indication of user-inputted text; storing, by the computing device, a lexicon that includes a set of in-lexicon candidate strings and does not include a set of out-of-lexicon candidate strings, wherein each of the in-lexicon candidate strings and each of the out-of-lexicon candidate strings is a respective word in a particular language; for each respective in-lexicon candidate string of the set of in-lexicon candidate strings, determining, by the computing device, a respective score for the respective in-lexicon candidate string, wherein: the respective score is based at least in part on a probability of the respective in-lexicon candidate string as a whole being entered, and the probability of the respective in-lexicon candidate string being entered is affected by a word-level context of the respective in-lexicon candidate string that includes one or more character strings that precede the respective in-lexicon candidate string in the user-inputted text; for each respective out-of-lexicon candidate string of the set of out-of-lexicon candidate strings, determining, by the computing device, a respective score for the respective out-of-lexicon candidate string, wherein the respective score for the respective out-of-lexicon candidate string is based at least in part on respective probabilities of individual characters in the respective out-of-lexicon candidate string being entered and is not based on word-level probabilities; determining, by the computing device and based at least in part on the scores for the in-lexicon candidate strings and the scores for the out-of-lexicon candidate strings, a combined set of candidate strings from the set of in-lexicon candidate strings and the set of out-of-lexicon candidate strings, the combined set of candidate strings including at least one in-lexicon candidate string from the set of in-lexicon candidate strings and at least one out-of-lexicon candidate string from the set of out-of-lexicon candidate strings; outputting, by the computing device, at least a portion of the combined set of candidate strings for display; and responsive to an indication of a selection of a candidate string from the combined set of candidate strings, outputting, by the computing device, for display in place of the user-inputted text, the selected candidate string. 15. The method of claim 1 , wherein: a finite state transducer (FST) includes arcs that correspond to characters; and determining the scores for the out-of-lexicon candidate strings comprises determining, by the computing device and based at least in part on scores associated with followed arcs in the FST, a score for a particular out-of-lexicon candidate string in the set of out-of-lexicon candidate strings, wherein the followed arcs of the FST are arcs of the FST that correspond to characters of the particular out-of-lexicon candidate string, wherein for each respective one of the followed arcs, the score that corresponds to the respective followed arc is based at least in part on a probability of the character that corresponds to the respective followed arc. | 0.569972 |
14. The method according to claim 1 , wherein one or more learning parameters used for the step of learning operations are incorporated into at least one received message. | 14. The method according to claim 1 , wherein one or more learning parameters used for the step of learning operations are incorporated into at least one received message. 15. The method according to claim 14 , wherein the one or more learning parameters include at least one decay constant. | 0.930769 |
8. A system for filtering content based on acquiring data associated with language identification, comprising: a computing device having a processor and a memory including instructions, which when executed by the processor, provides: a language preference model for acquiring data associated with language identification from a plurality of sources associated with the content of an interactive program guide, performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of an interactive program guide has a highest priority, and in response to performing the analysis, processing the acquired data to utilize the source with the highest priority to identify a preferred language of the interactive program guide based on the analysis of the acquired data associated with language identification; and a recommendation engine, in response to performing the analysis, receiving the identified preferred language from the language preference model and filtering content presented in the interactive program guide based on the identified preferred language, wherein filtering content presented in the interactive program guide based on a preferred language identified comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device. | 8. A system for filtering content based on acquiring data associated with language identification, comprising: a computing device having a processor and a memory including instructions, which when executed by the processor, provides: a language preference model for acquiring data associated with language identification from a plurality of sources associated with the content of an interactive program guide, performing an analysis of the acquired data associated with language identification to determine which source of the plurality of sources associated with the content of an interactive program guide has a highest priority, and in response to performing the analysis, processing the acquired data to utilize the source with the highest priority to identify a preferred language of the interactive program guide based on the analysis of the acquired data associated with language identification; and a recommendation engine, in response to performing the analysis, receiving the identified preferred language from the language preference model and filtering content presented in the interactive program guide based on the identified preferred language, wherein filtering content presented in the interactive program guide based on a preferred language identified comprises the computing device filtering data based on a parameter associated with and obtained from a user device or based on the user's use of the user device. 9. The system of claim 8 , wherein the plurality of sources comprise two or more of a device management interface, a closed captioning language selection, a subtitle language selection, a language associated with a keyboard, a language associated with programs most watched by a user, manual settings of a user and data from identity management (IdM). | 0.5 |
12. A computer system for automatically generating a meeting digest of a set of meetings, the computer system comprising: a bus system; a storage device connected to bus system, wherein the storage device stores computer readable program code; and a processor connected to the bus system, wherein the processor executes the computer readable program code to detect a set of topics of interest to parties to the set of meetings utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings; receive recorded meeting data corresponding to the set of meetings from a conferencing server that recorded contents of the set of meetings; extract topic-related content associated with the set of topics of interest to the parties from the recorded meeting data corresponding to the set of meetings received from the conferencing server; and generate the meeting digest of the set of meetings using the topic-related content associated with the set of topics of interest to the parties extracted from the recorded meeting data corresponding to the set of meetings. | 12. A computer system for automatically generating a meeting digest of a set of meetings, the computer system comprising: a bus system; a storage device connected to bus system, wherein the storage device stores computer readable program code; and a processor connected to the bus system, wherein the processor executes the computer readable program code to detect a set of topics of interest to parties to the set of meetings utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings; receive recorded meeting data corresponding to the set of meetings from a conferencing server that recorded contents of the set of meetings; extract topic-related content associated with the set of topics of interest to the parties from the recorded meeting data corresponding to the set of meetings received from the conferencing server; and generate the meeting digest of the set of meetings using the topic-related content associated with the set of topics of interest to the parties extracted from the recorded meeting data corresponding to the set of meetings. 13. The computer system of claim 12 , wherein the processor further executes the computer readable program code to generate an email that includes the meeting digest of the set of meetings; and send the email that includes the meeting digest of the set of meetings via a network. | 0.768493 |
10. The method of claim 9 wherein if the digital text file is flagged as misidentified, proofing the digital text file further comprises: (A) substituting a next-best alternative character for the suspect character having the highest probability of an error to produce the digital text file; (B) encoding the digital text file using the encoding algorithm to produce the encoded text; (C) comparing the encoded text to the digital information; and uploading or transmitting the digital text file if the encoded text matches the digital information, or flagging the digital text file as misidentified if the encoded text does not match the digital information, and returning to (A) until all identified alternative characters have been substituted for the suspect character having the highest probability of an error. | 10. The method of claim 9 wherein if the digital text file is flagged as misidentified, proofing the digital text file further comprises: (A) substituting a next-best alternative character for the suspect character having the highest probability of an error to produce the digital text file; (B) encoding the digital text file using the encoding algorithm to produce the encoded text; (C) comparing the encoded text to the digital information; and uploading or transmitting the digital text file if the encoded text matches the digital information, or flagging the digital text file as misidentified if the encoded text does not match the digital information, and returning to (A) until all identified alternative characters have been substituted for the suspect character having the highest probability of an error. 11. The method of claim 10 wherein if the digital text file is flagged as misidentified after all identified alternative characters have been substituted for the suspect character, proofing the digital text file further comprises: substituting the best alternative character for the suspect character having a next-highest probability of an error to produce the digital text file; encoding the digital text file using the encoding algorithm to produce the encoded text; comparing the encoded text to the digital information; and uploading or transmitting the digital text file if the encoded text matches the digital information, or flagging the digital text file as misidentified if the encoded text does not match the digital information. | 0.643018 |
1. A method, in a data processing system comprising a processor and a memory, for validating a candidate answer to an input question, the method comprising: generating, by the data processing system, a candidate answer to an input question using a natural language processing of the input question and a corpus of information from which the candidate answer is identified; selecting, by the data processing system, a validator to apply to the candidate answer based on a characteristic of a correct answer for the input question; applying, by the data processing system, the validator to the candidate answer to evaluate whether or not one or more criteria of the validator are satisfied by the candidate answer; generating, by the data processing system, validation information based the evaluation of whether or not criteria of the validator are met by the candidate answer; and storing, by the data processing system, the validation information in a validation status object associated with the input question, wherein the validator is one of a plurality of validators registered with a pluggable validator framework, and wherein registration of the validator with the pluggable validator framework comprises specifying for which answer type or answer extension type in an answer key data structure the validator corresponds to. | 1. A method, in a data processing system comprising a processor and a memory, for validating a candidate answer to an input question, the method comprising: generating, by the data processing system, a candidate answer to an input question using a natural language processing of the input question and a corpus of information from which the candidate answer is identified; selecting, by the data processing system, a validator to apply to the candidate answer based on a characteristic of a correct answer for the input question; applying, by the data processing system, the validator to the candidate answer to evaluate whether or not one or more criteria of the validator are satisfied by the candidate answer; generating, by the data processing system, validation information based the evaluation of whether or not criteria of the validator are met by the candidate answer; and storing, by the data processing system, the validation information in a validation status object associated with the input question, wherein the validator is one of a plurality of validators registered with a pluggable validator framework, and wherein registration of the validator with the pluggable validator framework comprises specifying for which answer type or answer extension type in an answer key data structure the validator corresponds to. 2. The method of claim 1 , wherein selecting a validator to apply to the candidate answer based on a characteristic of the correct answer for the input question comprises: performing a lookup operation in an answer key data structure for an entry corresponding to a question type of the input question, wherein the entry comprises at least one of an answer type or an answer extension type, and wherein the answer type is either a literal answer type or a regular expression answer type and the answer extension type is an extended answer type other than a literal answer type or regular expression answer type; and selecting the validator based on a correspondence between the validator and at least one of the answer type or the answer extension type. | 0.503601 |
8. The method of claim 6 , further comprising pre-allocating a temporary memory space for use during search activity by the user. | 8. The method of claim 6 , further comprising pre-allocating a temporary memory space for use during search activity by the user. 9. The method of claim 8 , wherein the temporary memory space is an APP container space. | 0.974816 |
8. A system, comprising: one or more processors, implemented at least partially by hardware; and memory storing instructions that when executed by the at least one or more processors effectuate operations comprising: retrieving an electronic resource including text, identifying, within the electronic resource, a geotoken referring to a geographic location, determining a location where the geotoken is contained within the electronic resource, scoring relevance of the electronic resource to the geographic location as a function of the determined location of the geotoken within the electronic resource, to generate a relevance score, including: determining that the geotoken is one of N different geotokens, each referencing a different respective geographic location, located in a title part of the electronic resource, and assigning a weight to the geotoken inversely proportional to N, and designating the electronic resource as relevant to the geographic location in memory, in accordance with the generated relevance score. | 8. A system, comprising: one or more processors, implemented at least partially by hardware; and memory storing instructions that when executed by the at least one or more processors effectuate operations comprising: retrieving an electronic resource including text, identifying, within the electronic resource, a geotoken referring to a geographic location, determining a location where the geotoken is contained within the electronic resource, scoring relevance of the electronic resource to the geographic location as a function of the determined location of the geotoken within the electronic resource, to generate a relevance score, including: determining that the geotoken is one of N different geotokens, each referencing a different respective geographic location, located in a title part of the electronic resource, and assigning a weight to the geotoken inversely proportional to N, and designating the electronic resource as relevant to the geographic location in memory, in accordance with the generated relevance score. 13. The system of claim 8 , the operations further comprising: determining that the geotoken is included in a boilerplate included in a plurality of electronic resources independently of content to which the corresponding electronic resource relates, and in response to determining that the geotoken is included in the boilerplate, lowering the relevance score of the geotoken. | 0.721239 |
1. A method comprising: crawling, via an entity extraction computer, a corpus of a plurality of electronic documents; extracting, via the entity extraction computer, a plurality of features from each of the crawled electronic documents in the corpus; aggregating, via a knowledge base aggregator computer, instances of co-occurrence of two or more of the plurality of features across the crawled electronic documents to determine a count of the instances of co-occurrence across the plurality of electronic documents, wherein the count of the instances of co-occurrence of two or more features are determined by adding up number of co-occurrences of the two or more features co-occurred in each of the plurality of electronic documents, wherein the knowledge base aggregator computer includes a main memory hosting a feature co-occurrence in-memory database, wherein the entity extraction computer is distinct from the knowledge base aggregator computer, wherein the feature co-occurrence in-memory database comprises one or more entries of the plurality of features, wherein each entry of the one or more entries contains semantically-related features of the plurality of features, and wherein the co-occurrence is an instance of a feature of the plurality of features identified by an entry of the one or more entries in the corpus of the electronic documents in the co-occurrence database, and wherein the co-occurrence corresponds to determination of related entities upon the occurrence of the two or more of the plurality of features that are related to each other across the crawled electronic documents in no defined order; and adding, via the knowledge base aggregator computer, the instances of the co-occurrence of the two or more features to the feature co-occurrence database based on the count of the instances of co-occurrence across the plurality of electronic documents exceeding a predetermined threshold. | 1. A method comprising: crawling, via an entity extraction computer, a corpus of a plurality of electronic documents; extracting, via the entity extraction computer, a plurality of features from each of the crawled electronic documents in the corpus; aggregating, via a knowledge base aggregator computer, instances of co-occurrence of two or more of the plurality of features across the crawled electronic documents to determine a count of the instances of co-occurrence across the plurality of electronic documents, wherein the count of the instances of co-occurrence of two or more features are determined by adding up number of co-occurrences of the two or more features co-occurred in each of the plurality of electronic documents, wherein the knowledge base aggregator computer includes a main memory hosting a feature co-occurrence in-memory database, wherein the entity extraction computer is distinct from the knowledge base aggregator computer, wherein the feature co-occurrence in-memory database comprises one or more entries of the plurality of features, wherein each entry of the one or more entries contains semantically-related features of the plurality of features, and wherein the co-occurrence is an instance of a feature of the plurality of features identified by an entry of the one or more entries in the corpus of the electronic documents in the co-occurrence database, and wherein the co-occurrence corresponds to determination of related entities upon the occurrence of the two or more of the plurality of features that are related to each other across the crawled electronic documents in no defined order; and adding, via the knowledge base aggregator computer, the instances of the co-occurrence of the two or more features to the feature co-occurrence database based on the count of the instances of co-occurrence across the plurality of electronic documents exceeding a predetermined threshold. 2. The method of claim 1 wherein each of the plurality of features is selected from the group consisting of a person, a location, an organization name, a topic, an event, and a fact. | 0.535208 |
69. The server apparatus of claim 65 , wherein the computerized logic is further configured to select advertising that is contextually related to an attribute or type of the organization or entity for display on a remotely disposed electronic display device. | 69. The server apparatus of claim 65 , wherein the computerized logic is further configured to select advertising that is contextually related to an attribute or type of the organization or entity for display on a remotely disposed electronic display device. 70. The server apparatus of claim 69 , wherein the advertising is selected based at least in part on the available presentation times before the location is encountered during a journey thereto. | 0.920842 |
4. A system, comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to: identify, by one or more computing devices, a plurality of content component identifiers for an application running on a user computing device, each of the plurality of content component identifiers identifying a respective one of a plurality of separate content components presented by the application, wherein the plurality of separate content components include at least two different types of content including portions of text, media, images, or chat interfaces that are simultaneously presented within the application; receive, by the one or more computing devices and through a first user interface of the application, an indication that a user recommended the application that is running on the user computing device and that presents the plurality of separate content components simultaneously; in response to receiving the indication that the user recommended the application: generate, by the one or more computing devices and in response to receiving the indication, a recommendation intent query in a second user interface, wherein the generated recommendation intent query: presents a list of the plurality of content component identifiers of the plurality of separate content components that were simultaneously presented by the application when the user recommended the application; and enables the user to choose, from the list of the plurality of content component identifiers, a given content component identifier that identifies a given content component that contributed to the user recommendation of the application; and transmit the recommendation intent query for presentation at the user computing device; receive, in response to presentation of the recommendation intent query and from the user computing device that presents the second user interface, an indication of user selection of at least one of the plurality of content component identifiers from the list of the plurality of content component identifiers that were presented by the recommendation intent query; generate, by the one or more computing devices and based on the user recommendation of the application by the user and the user selection of the at least one of the plurality of content component identifiers, a social annotation that communicates the recommendation of the application and any of the plurality of separate content components of the application that the user selected, from the list of the plurality of content component identifiers, as having contributed to the user recommendation of the application; and serve, by the one or more computing devices and via a network, the at least one social annotation to a second user computing device in a format suitable for presentation on the second user computing device. | 4. A system, comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, cause the at least one processor to: identify, by one or more computing devices, a plurality of content component identifiers for an application running on a user computing device, each of the plurality of content component identifiers identifying a respective one of a plurality of separate content components presented by the application, wherein the plurality of separate content components include at least two different types of content including portions of text, media, images, or chat interfaces that are simultaneously presented within the application; receive, by the one or more computing devices and through a first user interface of the application, an indication that a user recommended the application that is running on the user computing device and that presents the plurality of separate content components simultaneously; in response to receiving the indication that the user recommended the application: generate, by the one or more computing devices and in response to receiving the indication, a recommendation intent query in a second user interface, wherein the generated recommendation intent query: presents a list of the plurality of content component identifiers of the plurality of separate content components that were simultaneously presented by the application when the user recommended the application; and enables the user to choose, from the list of the plurality of content component identifiers, a given content component identifier that identifies a given content component that contributed to the user recommendation of the application; and transmit the recommendation intent query for presentation at the user computing device; receive, in response to presentation of the recommendation intent query and from the user computing device that presents the second user interface, an indication of user selection of at least one of the plurality of content component identifiers from the list of the plurality of content component identifiers that were presented by the recommendation intent query; generate, by the one or more computing devices and based on the user recommendation of the application by the user and the user selection of the at least one of the plurality of content component identifiers, a social annotation that communicates the recommendation of the application and any of the plurality of separate content components of the application that the user selected, from the list of the plurality of content component identifiers, as having contributed to the user recommendation of the application; and serve, by the one or more computing devices and via a network, the at least one social annotation to a second user computing device in a format suitable for presentation on the second user computing device. 6. The system of claim 4 , wherein the at least one processor is further caused to: generate, by the one or more computing devices, at least one component reference table based on the plurality of content component identifiers, the at least one component reference table including, for each of the plurality of content component identifiers, which of the plurality of separate content components of the application is identified by the content component identifier; store, by the one or more computing devices, the at least one component reference table for the application; and map, by the one or more computing devices, each of the plurality of separate content components to a respective one of the plurality of content component identifiers included in the at least one component reference table to the application. | 0.513652 |
11. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for role-based personalization of a collaborative space embodied therein, the computer usable code when executed on a computer hardware system causes the computer hardware system to perform the operations of: obtaining role-based information for an interacting user that has been defined by an underlying business process model in a workflow; and generating the collaborative space utilizing the role-based information, including: parsing the workflow to extract a role model; generating a collaborative space domain model from the role model; selecting a plurality of user interface components based upon the role model, wherein mapping rules are defined to transform role information aggregated in the role model to user interface components for incorporation in the collaborative space domain model, and wherein the mapping rules include user-specified mapping rules between a group of workflow tasks and existing user interface components where existing user interface components exist when the collaborative space is created, and suggested mapping rules obtained by segmenting the workflow based upon role-assignment or a control-flow structure where user interface components do not exist when the collaborative space is created; organizing the selected user interface components in the collaborative space; and rendering the collaborative space. | 11. A computer program product comprising a computer usable storage medium having stored therein computer usable program code for role-based personalization of a collaborative space embodied therein, the computer usable code when executed on a computer hardware system causes the computer hardware system to perform the operations of: obtaining role-based information for an interacting user that has been defined by an underlying business process model in a workflow; and generating the collaborative space utilizing the role-based information, including: parsing the workflow to extract a role model; generating a collaborative space domain model from the role model; selecting a plurality of user interface components based upon the role model, wherein mapping rules are defined to transform role information aggregated in the role model to user interface components for incorporation in the collaborative space domain model, and wherein the mapping rules include user-specified mapping rules between a group of workflow tasks and existing user interface components where existing user interface components exist when the collaborative space is created, and suggested mapping rules obtained by segmenting the workflow based upon role-assignment or a control-flow structure where user interface components do not exist when the collaborative space is created; organizing the selected user interface components in the collaborative space; and rendering the collaborative space. 13. The computer program product of claim 11 , wherein segmenting the workflow based upon role-assignment is carried out by decomposing the workflow into segments at a connector connecting tasks for different roles. | 0.538395 |
10. A method for scrolling a computer generated image including a plurality of note areas, where adjacent note areas have an immediately preceding note area and an immediately subsequent note area and are separated by divider indicia in the form of a header bar, the header bar containing information corresponding to the immediately subsequent note area, at least one of the note areas has a length greater than the height of a computer screen on which one or more of the note areas and the respective header bars are displayed, said method comprising: detecting a scrolling command; and scrolling through said adjacent note areas in a scroll direction indicated by said scrolling command using discrete jumps, said scrolling including scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a remaining undisplayed area of a displayed one of the note areas as well as at least a portion of an adjacent note area when the remaining undisplayed area of the displayed one of the note areas in the scroll direction has an undisplayed length that is greater than zero but less than the height of the computer screen, scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a next successive portion of a remaining undisplayed area of a displayed one of the note areas as well as to not display any portion of an adjacent note area when the remaining undisplayed area of the displayed one of the note areas in the scroll direction has an undisplayed length that is greater than the height of the computer screen, and scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a least a portion of an adjacent note area with the header bar associated therewith displayed at the top of the computer screen when the displayed one of the note areas and a portion of the adjacent note area are displayed and the displayed one of the note areas does not have any remaining undisplayed area in the scroll direction. | 10. A method for scrolling a computer generated image including a plurality of note areas, where adjacent note areas have an immediately preceding note area and an immediately subsequent note area and are separated by divider indicia in the form of a header bar, the header bar containing information corresponding to the immediately subsequent note area, at least one of the note areas has a length greater than the height of a computer screen on which one or more of the note areas and the respective header bars are displayed, said method comprising: detecting a scrolling command; and scrolling through said adjacent note areas in a scroll direction indicated by said scrolling command using discrete jumps, said scrolling including scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a remaining undisplayed area of a displayed one of the note areas as well as at least a portion of an adjacent note area when the remaining undisplayed area of the displayed one of the note areas in the scroll direction has an undisplayed length that is greater than zero but less than the height of the computer screen, scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a next successive portion of a remaining undisplayed area of a displayed one of the note areas as well as to not display any portion of an adjacent note area when the remaining undisplayed area of the displayed one of the note areas in the scroll direction has an undisplayed length that is greater than the height of the computer screen, and scrolling, in response to said scrolling command, in a discrete jump in the scroll direction to display a least a portion of an adjacent note area with the header bar associated therewith displayed at the top of the computer screen when the displayed one of the note areas and a portion of the adjacent note area are displayed and the displayed one of the note areas does not have any remaining undisplayed area in the scroll direction. 11. A method as recited in claim 10 wherein said detecting step detects an up-scroll command, and wherein said step of scrolling comprises: decrementing a current note number counter when an end of one of said note areas is reached; and drawing a new note corresponding to said decremented current note number counter such that the new note's header bar is displayed at the top of the computer screen. | 0.500216 |
10. A method comprising: receiving, from an optical receiver and by a device, a word, of a block of words within traffic, on which to perform forward error correction, the word including encoded bits and sets of reliability bits for identifying a respective level of reliability of each of the encoded bits; updating, by the device, a first segment of the word and a second segment of the word based on first extrinsic information, the first segment including a first subset of the encoded bits, the second segment including a second subset of the encoded bits, and the first extrinsic information modifying reliability bits associated with the first subset and the second subset; identifying, by the device, first least reliable positions (LRPs) within the updated first segment and second LRPs within the updated second segment, the first LRPs corresponding to first bits within the first subset with a lowest level of reliability, the second LRPs corresponding to second bits within the second subset with another lowest level of reliability; identifying, by the device, LRPs, within the word, based on a subset of a combination of the first bits and the second bits associated with one or more lowest levels of reliability; generating, by the device, candidate words based on different combinations of inverted encoded bits, within the word, that corresponds to the identified LRPs; identifying, by the device, errors within the word or the candidate words; updating, by the device and based on the first extrinsic information, a first encoded bit, within the first segment, in which an error is identified; determining, by the device, first partial distances between the updated first segment and first segments of the candidate words and second partial distances between the second segment and second segments of the candidate words; generating, by the device, second extrinsic information based on two or more best words of the candidate words, the two or more best words corresponding to two or more shortest first partial distances and two or more shortest second partial distances; and processing, by the device, a next word, of the block of words, using the second extrinsic information. | 10. A method comprising: receiving, from an optical receiver and by a device, a word, of a block of words within traffic, on which to perform forward error correction, the word including encoded bits and sets of reliability bits for identifying a respective level of reliability of each of the encoded bits; updating, by the device, a first segment of the word and a second segment of the word based on first extrinsic information, the first segment including a first subset of the encoded bits, the second segment including a second subset of the encoded bits, and the first extrinsic information modifying reliability bits associated with the first subset and the second subset; identifying, by the device, first least reliable positions (LRPs) within the updated first segment and second LRPs within the updated second segment, the first LRPs corresponding to first bits within the first subset with a lowest level of reliability, the second LRPs corresponding to second bits within the second subset with another lowest level of reliability; identifying, by the device, LRPs, within the word, based on a subset of a combination of the first bits and the second bits associated with one or more lowest levels of reliability; generating, by the device, candidate words based on different combinations of inverted encoded bits, within the word, that corresponds to the identified LRPs; identifying, by the device, errors within the word or the candidate words; updating, by the device and based on the first extrinsic information, a first encoded bit, within the first segment, in which an error is identified; determining, by the device, first partial distances between the updated first segment and first segments of the candidate words and second partial distances between the second segment and second segments of the candidate words; generating, by the device, second extrinsic information based on two or more best words of the candidate words, the two or more best words corresponding to two or more shortest first partial distances and two or more shortest second partial distances; and processing, by the device, a next word, of the block of words, using the second extrinsic information. 13. The method of claim 10 , further comprising: identifying one of the first partial distances based on one of: identifying a quantity of bits, associated with a first segment of a first candidate word, that do not match encoded bits associated with the updated first segment; or identifying a difference between a first sum of reliability values that correspond to encoded bits associated with the first segment of the first candidate word and a second sum of reliability values that correspond to encoded bits associated with the first updated segment; and selecting the first segment of the first candidate word on which to base one of the two or more best words when the one of the first partial distances is less than other ones of the first partial distances. | 0.526965 |
1. A computer-implemented method of indexing documents in websites, the method comprising: on a server system having one or more processors and memory storing programs to be executed by the one or more processors: for each website of a multiplicity of websites, each website having a corresponding current crawl rate limit: crawling the respective website, in accordance with the current crawl rate limit corresponding to the respective website, to download documents from the respective website for inclusion in a database; storing crawl data associated with the crawling of the respective website; providing, for display, a crawl rate control mechanism to a respective owner of the respective website, including providing for display to the respective owner at least a portion of the crawl data, and enabling selection of a new crawl rate limit corresponding to the respective website by the respective owner; comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and in response to a request to increase a current crawl rate for crawling the respective website, increasing the current crawl rate limit only when the current crawl rate limit is a limiting factor in crawling the respective website. | 1. A computer-implemented method of indexing documents in websites, the method comprising: on a server system having one or more processors and memory storing programs to be executed by the one or more processors: for each website of a multiplicity of websites, each website having a corresponding current crawl rate limit: crawling the respective website, in accordance with the current crawl rate limit corresponding to the respective website, to download documents from the respective website for inclusion in a database; storing crawl data associated with the crawling of the respective website; providing, for display, a crawl rate control mechanism to a respective owner of the respective website, including providing for display to the respective owner at least a portion of the crawl data, and enabling selection of a new crawl rate limit corresponding to the respective website by the respective owner; comparing a maximum crawl rate for the respective website over a defined period of time with the current crawl rate limit for crawling the respective website to determine if the current crawl rate limit is a limiting factor in crawling the respective website; and in response to a request to increase a current crawl rate for crawling the respective website, increasing the current crawl rate limit only when the current crawl rate limit is a limiting factor in crawling the respective website. 7. The computer-implemented method of claim 1 , wherein storing crawl data further comprises determining a number documents of the respective website that are accessed during one or more crawl sessions. | 0.610465 |
1. A method for providing target point candidates that form a candidate set for selecting a target point from the candidate set by means of a geodetic measuring device, wherein the measuring device has a targeting unit defining a targeting direction and a camera aligned substantially in the targeting direction, the method comprising: coarsely aligning the measuring device with the target point; detecting an image in the targeting direction; searching for specific target object candidates in the detected image is effected by means of image processing, wherein: the search process is effected on the basis of predefined models; the target object candidates are respectively assigned at least one point representing the respective target object candidate as target point candidate; the target point candidates are assigned to the candidate set; a respective weight value is derived and assigned to the target point candidates; and the target point candidates of the candidate set are respectively provided together with an information item representing the weight value assigned to the respective target point candidate. | 1. A method for providing target point candidates that form a candidate set for selecting a target point from the candidate set by means of a geodetic measuring device, wherein the measuring device has a targeting unit defining a targeting direction and a camera aligned substantially in the targeting direction, the method comprising: coarsely aligning the measuring device with the target point; detecting an image in the targeting direction; searching for specific target object candidates in the detected image is effected by means of image processing, wherein: the search process is effected on the basis of predefined models; the target object candidates are respectively assigned at least one point representing the respective target object candidate as target point candidate; the target point candidates are assigned to the candidate set; a respective weight value is derived and assigned to the target point candidates; and the target point candidates of the candidate set are respectively provided together with an information item representing the weight value assigned to the respective target point candidate. 23. A tangible non-transitory computer program product comprising program code stored on a tangible non-transitory machine readable carrier, for carrying out the method for providing target point candidates for selecting a target point as claimed in claim 1 . | 0.635848 |
1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. | 1. A system comprising: one or more processors; and a computer-readable storage device storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. 6. The system of claim 1 , wherein the score for a subterm that is not in the dictionary is a default score. | 0.674208 |
13. The method of claim 11 , wherein the displaying the plurality of domains on the screen includes displaying a domain classified into a layer according to a speech recognition level. | 13. The method of claim 11 , wherein the displaying the plurality of domains on the screen includes displaying a domain classified into a layer according to a speech recognition level. 17. The method of claim 13 , wherein the displaying the plurality of domains on the screen includes displaying at least one exemplified recognition data for exemplifying a speech recognition level designated according to the selection of the at least one domain by the user. | 0.916005 |
1. A computer-implemented method for word recommendation, comprising: constructing a geographic-related language database of a geographic-related language by counting utilization frequencies of words in the geographic-related language, and collecting one or more geographic-related language words having a utilization frequency greater than a predetermined value; receiving, from a user device, a coded character string; collecting geographic information associated with the user device; determining a geographic-related language corresponding to the geographic information; and obtaining a geographic-related language candidate word corresponding to the coded character string based on the geographic-related language database of the geographic-related language. | 1. A computer-implemented method for word recommendation, comprising: constructing a geographic-related language database of a geographic-related language by counting utilization frequencies of words in the geographic-related language, and collecting one or more geographic-related language words having a utilization frequency greater than a predetermined value; receiving, from a user device, a coded character string; collecting geographic information associated with the user device; determining a geographic-related language corresponding to the geographic information; and obtaining a geographic-related language candidate word corresponding to the coded character string based on the geographic-related language database of the geographic-related language. 3. The computer-implemented method of claim 1 , further comprising: storing the one or more geographic-related language words and one or more coded character strings corresponding to the one or more geographic-related language words. | 0.817746 |
1. A method of assessing fraud in a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one of the information fields of the document, comparing handwriting in the information field to at least one handwriting profile representation from at least two information fields of at least one other document, wherein at least one handwriting profile representation has been stored in a computer system; assessing fraud in the document using at least one comparison, wherein evidence of fraud comprises a failure of at least a portion of the handwriting in at least one of the information fields of the document to approximately match at least one handwriting profile representation. | 1. A method of assessing fraud in a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one of the information fields of the document, comparing handwriting in the information field to at least one handwriting profile representation from at least two information fields of at least one other document, wherein at least one handwriting profile representation has been stored in a computer system; assessing fraud in the document using at least one comparison, wherein evidence of fraud comprises a failure of at least a portion of the handwriting in at least one of the information fields of the document to approximately match at least one handwriting profile representation. 13. The method of claim 1 , wherein the handwriting from at least one information field comprises an image. | 0.923186 |
1. An apparatus for retrieving a structured document comprising: a processor that is programmed to retrieve the structured document, wherein the processor causes: a first specifying unit to specify a plurality of object documents from a plurality of structured documents being accessible via a network, the object document being the structured document according to retrieval condition, a first extracting unit to extract a text included in the object document, a second extracting unit to extract a metadata appended to the object document, the metadata being first data indicating the text of the object document and second data indicating a link relation between the object document and related documents, each of the related documents being the structured document associated with the object document, a second specifying unit to specify whether a description supporting the object document is included in the text of the each related document, an analyzing unit to analyze whether author information of a related document is included in a metadata appended to the related document based on the metadata appended to the object document, and a first calculating unit to calculate higher importance for the object document related to the related document having the author information thereof included in the metadata compared with important of the object document related to the related document not having the author information thereof included in the metadata; and further to calculate higher importance for the object document corresponding to the related document including the description supporting the object document compared with importance of the object document corresponding to the related document not including a description supporting the object document. | 1. An apparatus for retrieving a structured document comprising: a processor that is programmed to retrieve the structured document, wherein the processor causes: a first specifying unit to specify a plurality of object documents from a plurality of structured documents being accessible via a network, the object document being the structured document according to retrieval condition, a first extracting unit to extract a text included in the object document, a second extracting unit to extract a metadata appended to the object document, the metadata being first data indicating the text of the object document and second data indicating a link relation between the object document and related documents, each of the related documents being the structured document associated with the object document, a second specifying unit to specify whether a description supporting the object document is included in the text of the each related document, an analyzing unit to analyze whether author information of a related document is included in a metadata appended to the related document based on the metadata appended to the object document, and a first calculating unit to calculate higher importance for the object document related to the related document having the author information thereof included in the metadata compared with important of the object document related to the related document not having the author information thereof included in the metadata; and further to calculate higher importance for the object document corresponding to the related document including the description supporting the object document compared with importance of the object document corresponding to the related document not including a description supporting the object document. 19. The apparatus according to claim 1 , wherein the first calculating unit calculates higher importance for a second object document compared with importance of a first object document when, in the metadata of the first object document among the object documents, a plurality of structured documents including the second object document among the object documents are associated with the first object document, a plurality of structured documents are associated with the second object document in the metadata of the second object document, and the number of the structure documents associated with the second object document is large compared with the number of the structured documents associated with the first object document. | 0.593178 |
13. A system for knowledge processing comprising: means for enabling a user to select one or more data repositories from a plurality of possible data repositories; means for gathering information from the selected one or more user data repositories, wherein gathering the one or more documents comprises generating meta-document representations of the one or more documents; means for categorizing the meta-document representations into one or more topical categories; means for determining an affinity for a user and at least one of the one or more topical categories, wherein the affinity for the user and the at least one of the one or more topical categories represents a strength of a relationship between the user and the at least one of the one or more topical categories; and means for notifying the user of any of the meta-document representations that are categorized in the at least one of the one or more topical categories for which the affinity with the user has been determined. | 13. A system for knowledge processing comprising: means for enabling a user to select one or more data repositories from a plurality of possible data repositories; means for gathering information from the selected one or more user data repositories, wherein gathering the one or more documents comprises generating meta-document representations of the one or more documents; means for categorizing the meta-document representations into one or more topical categories; means for determining an affinity for a user and at least one of the one or more topical categories, wherein the affinity for the user and the at least one of the one or more topical categories represents a strength of a relationship between the user and the at least one of the one or more topical categories; and means for notifying the user of any of the meta-document representations that are categorized in the at least one of the one or more topical categories for which the affinity with the user has been determined. 16. A system of claim 13 , wherein the selected one or more data repositories are non-web based data repositories. | 0.64132 |
12. A computer-implemented method as recited in claim 11 wherein extracting the user password from the string of characters includes: identifying a plurality of characters associated with the terminator; and identifying a plurality of user password characters adjacent to the plurality of characters associated with the terminator. | 12. A computer-implemented method as recited in claim 11 wherein extracting the user password from the string of characters includes: identifying a plurality of characters associated with the terminator; and identifying a plurality of user password characters adjacent to the plurality of characters associated with the terminator. 13. A computer-implemented method as recited in claim 12 wherein extracting the user password from the string of characters further includes aggregating the plurality of user password characters to create the user password. | 0.914634 |
15. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to: associate keywords of previous searches with a topic; identify a candidate phrase from the previous searches that contains a first keyword and at least one second keyword associated with the topic; determine a first count of the first keyword, a second count of the at least one second keyword, and a mutual count of the first keyword and the second keyword appearing simultaneously in the previous searches; weight each individual count of the first count, the second count, and the mutual count based at least in part on age of a respective individual count with respect to the previous searches, wherein each age is a difference between a time when the respective individual count appeared in the previous searches and a current time; determine pointwise mutual information score for the candidate phrase using the weighted first count of the first keyword, the weighted second count of the second keyword, and the weighted mutual count of the first keyword and the second keyword; based at least in part on the determined pointwise mutual score being greater than a threshold pointwise mutual score, select the candidate phrase as a fixed phrase; determine a relevance score for the fixed phrase with respect to the topic; based at least in part on the relevance score being above a threshold score for the topic, associate the fixed phrase with the topic; in response to receiving a search query, provide at least one search result for presentation, the at least one search result at least referencing content selected from a search index based at least in part on relevance scores of a plurality of keywords and a plurality of fixed phrases for the topic; detect interaction with a search result of the provided at least one search result from a user; and update the keywords associated with the search result. | 15. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to: associate keywords of previous searches with a topic; identify a candidate phrase from the previous searches that contains a first keyword and at least one second keyword associated with the topic; determine a first count of the first keyword, a second count of the at least one second keyword, and a mutual count of the first keyword and the second keyword appearing simultaneously in the previous searches; weight each individual count of the first count, the second count, and the mutual count based at least in part on age of a respective individual count with respect to the previous searches, wherein each age is a difference between a time when the respective individual count appeared in the previous searches and a current time; determine pointwise mutual information score for the candidate phrase using the weighted first count of the first keyword, the weighted second count of the second keyword, and the weighted mutual count of the first keyword and the second keyword; based at least in part on the determined pointwise mutual score being greater than a threshold pointwise mutual score, select the candidate phrase as a fixed phrase; determine a relevance score for the fixed phrase with respect to the topic; based at least in part on the relevance score being above a threshold score for the topic, associate the fixed phrase with the topic; in response to receiving a search query, provide at least one search result for presentation, the at least one search result at least referencing content selected from a search index based at least in part on relevance scores of a plurality of keywords and a plurality of fixed phrases for the topic; detect interaction with a search result of the provided at least one search result from a user; and update the keywords associated with the search result. 17. The non-transitory computer-readable storage medium of claim 15 , wherein the relevance scores are based at least in part on detected interaction with one or more search results previously presented that correspond to the at least one fixed phrase. | 0.519057 |
14. The system of claim 13 , wherein the training component learns a first weight matrix corresponding to the plurality of hidden units of the first module and the plurality of hidden units of the first module through utilization of convex optimization. | 14. The system of claim 13 , wherein the training component learns a first weight matrix corresponding to the plurality of hidden units of the first module and the plurality of hidden units of the first module through utilization of convex optimization. 16. The system of claim 14 , wherein the training data is image data. | 0.862471 |
14. A detector as in claim 11 where the control circuitry comprises a programmed processor. | 14. A detector as in claim 11 where the control circuitry comprises a programmed processor. 15. A detector as in claim 14 which includes executable instructions for implementing at least two different speech specified detector functions. | 0.962429 |
7. A non-transitory computer-readable medium having computer-executable instructions for performing a method, said method comprising: receiving via a user interface, a selection of an item in a hierarchy of a business application data model; receiving a new attribute of said item; associating a new attribute identifier of said new attribute with said item; incorporating into said business application data model a user provided name of the new attribute in association with the new attribute identifier such that said new attribute is included within a searchable ontology of said hierarchy, wherein the user provided name is received in response to a prompt to provide said name; wherein the user provided name is received in response to a prompt to provide said name; associating a user provided meta attribute with the new attribute identifier, wherein the user provided meta attribute is received in response to another prompt to provide said meta attribute; determining whether a data value received as input for the new attribute of the item is valid, at least by validating the data value in accordance with an inherited meta attribute and by validating the data value in accordance with the user provided meta attribute; wherein the inherited meta attribute for the new attribute identifier is determined automatically from a mandatory meta attribute of a progenitor of said item in said hierarchy; storing the data value in the business application data model when the value is determined to be valid. | 7. A non-transitory computer-readable medium having computer-executable instructions for performing a method, said method comprising: receiving via a user interface, a selection of an item in a hierarchy of a business application data model; receiving a new attribute of said item; associating a new attribute identifier of said new attribute with said item; incorporating into said business application data model a user provided name of the new attribute in association with the new attribute identifier such that said new attribute is included within a searchable ontology of said hierarchy, wherein the user provided name is received in response to a prompt to provide said name; wherein the user provided name is received in response to a prompt to provide said name; associating a user provided meta attribute with the new attribute identifier, wherein the user provided meta attribute is received in response to another prompt to provide said meta attribute; determining whether a data value received as input for the new attribute of the item is valid, at least by validating the data value in accordance with an inherited meta attribute and by validating the data value in accordance with the user provided meta attribute; wherein the inherited meta attribute for the new attribute identifier is determined automatically from a mandatory meta attribute of a progenitor of said item in said hierarchy; storing the data value in the business application data model when the value is determined to be valid. 9. The computer readable medium as recited in claim 7 , wherein said method further comprises: determining that a present attribute of said item at an initial location in said hierarchy is common with said new attribute to be associated with said item at a destination location in said hierarchy; moving the present attribute to said destination location; and adding a non-common destination attribute to said item after said present attribute is moved to said destination location. | 0.540796 |
11. The method of claim 10 , wherein features of the received and expanded queries comprise one or more of unigrams, phrases, and semantic classes, and wherein the plurality of queries are expanded additionally based on click log sessions. | 11. The method of claim 10 , wherein features of the received and expanded queries comprise one or more of unigrams, phrases, and semantic classes, and wherein the plurality of queries are expanded additionally based on click log sessions. 12. The method of claim 11 , further comprising: normalizing, under an I 2 norm, the vectors of the received and expanded queries to a length of 1 (unity) within each feature type. | 0.946984 |
9. A computer program product for information extraction via semantic abstraction, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: receive natural language dependency parse trees as input; process, using the processor, the dependency parse trees by using an action application program interface (API) that creates a mapping from nodes of the dependency parse trees into actions, roles and contextual predicates, eliminates auxiliary verbs, detects negation from adverbs, classifies verbs, and outputs a collection of annotation query language (AQL) views, wherein mappings other than a default mapping use a configuration file that provides for defining new roles through navigation in the dependency parse trees; and using the mapping for extracting information, wherein: the actions are placed in a data format that comprises columns including said verbs along with columns for said verb attributes that comprise action identification, verb base, verb classification, verb tense, verb voice and verb sentiment, wherein verb sentiment is independent of an action; the roles comprise arguments for said verbs; and the contextual predicates include modifiers for said verbs. | 9. A computer program product for information extraction via semantic abstraction, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: receive natural language dependency parse trees as input; process, using the processor, the dependency parse trees by using an action application program interface (API) that creates a mapping from nodes of the dependency parse trees into actions, roles and contextual predicates, eliminates auxiliary verbs, detects negation from adverbs, classifies verbs, and outputs a collection of annotation query language (AQL) views, wherein mappings other than a default mapping use a configuration file that provides for defining new roles through navigation in the dependency parse trees; and using the mapping for extracting information, wherein: the actions are placed in a data format that comprises columns including said verbs along with columns for said verb attributes that comprise action identification, verb base, verb classification, verb tense, verb voice and verb sentiment, wherein verb sentiment is independent of an action; the roles comprise arguments for said verbs; and the contextual predicates include modifiers for said verbs. 16. The computer program product of claim 9 , wherein adverbs and explicit negation language are uniformly exposed as negative and semi-negative voice, and the contextual predicates are classified into types. | 0.538966 |
16. The computer-readable storage medium of claim 10 , wherein the third module further comprises a transport object, the transport object coupled to the work queue for receiving work items from the work queue, the transport object coupled to a corresponding delivery mechanism for sending the document, the transport object receiving a work item, converting the result data into a document suited to the delivery mechanism and transmitting the document over the delivery mechanism. | 16. The computer-readable storage medium of claim 10 , wherein the third module further comprises a transport object, the transport object coupled to the work queue for receiving work items from the work queue, the transport object coupled to a corresponding delivery mechanism for sending the document, the transport object receiving a work item, converting the result data into a document suited to the delivery mechanism and transmitting the document over the delivery mechanism. 17. The computer-readable storage medium of claim 16 , further comprising: a routing table having information for resource allocation, resource availability, local or remote processing, and time of processing, the routing table coupled to the third module; and wherein the transport objects of the third module use the routing table to determine a time to use and type of delivery mechanism for transmitting the document. | 0.715657 |
4. The method of claim 1 , wherein generating a single query against the compound document further comprises generating a single query that requests a value of one or more attributes found in both the primary XML document and the first nested document. | 4. The method of claim 1 , wherein generating a single query against the compound document further comprises generating a single query that requests a value of one or more attributes found in both the primary XML document and the first nested document. 5. The method of claim 4 , further comprising: collecting rowsets from the primary document and the first nested document and producing a composite rowset. | 0.924387 |
2. The method of claim 1 , wherein the type of task action includes a motion constraint, the method further comprising: encapsulating a tool behavior constraint in the information kernel, the tool behavior constraint providing a motion constraint associated with the tool type; and receiving user input via the one or more UIs to perform the task action, wherein controlling the at least one functionality of the robot includes enforcing the motion constraint to constrain one or more motions of the robot in performing the task action. | 2. The method of claim 1 , wherein the type of task action includes a motion constraint, the method further comprising: encapsulating a tool behavior constraint in the information kernel, the tool behavior constraint providing a motion constraint associated with the tool type; and receiving user input via the one or more UIs to perform the task action, wherein controlling the at least one functionality of the robot includes enforcing the motion constraint to constrain one or more motions of the robot in performing the task action. 3. The method of claim 2 , wherein receiving user input further comprises: receiving user manipulation of the robot via an admittance control UI of the one or more UIs. | 0.843974 |
1. A relational database management system of the type wherein a table function returns a set of result rows which are represented in an SQL statement by a container for the table function, the relational database management system executing on a processor that has access to a storage device and the relational database management system having the improvement comprising: a rewrite method in the storage device, the rewrite method being associated with the table function returning an SQL string which does not include the table function and which when executed will return a set of result rows which is equivalent to the set of result rows returned by the table function, the relational database system executing the rewrite method prior to executing the container to obtain the SQL string and thereupon rewriting the SQL statement such that the container for the table function is replaced by the returned SQL string. | 1. A relational database management system of the type wherein a table function returns a set of result rows which are represented in an SQL statement by a container for the table function, the relational database management system executing on a processor that has access to a storage device and the relational database management system having the improvement comprising: a rewrite method in the storage device, the rewrite method being associated with the table function returning an SQL string which does not include the table function and which when executed will return a set of result rows which is equivalent to the set of result rows returned by the table function, the relational database system executing the rewrite method prior to executing the container to obtain the SQL string and thereupon rewriting the SQL statement such that the container for the table function is replaced by the returned SQL string. 2. The relational database management system set forth in claim 1 wherein: the table function has a parameter; and the rewrite method uses the parameter in producing the returned SQL string. | 0.568689 |
1. A computer-implemented method comprising: accessing listing titles of one or more item listings on a marketplace website, the item listings being associated with a particular product category in a product category structure of the marketplace website; converting words in each of the listing titles to semantic tokens in a token symbol space, based on a tokenization process; performing n-gram modeling on the tokens corresponding to each of the listing titles of the item listings in the particular product category; and identifying, by a machine having a memory and at least one processor, one or more dominant n-gram models associated with the listing titles of the item listings in the particular product category, each dominant n-gram model identifying a sequence of one or more semantic tokens that appear in a statistically significant portion of the listing titles of the item listings in the particular product category. | 1. A computer-implemented method comprising: accessing listing titles of one or more item listings on a marketplace website, the item listings being associated with a particular product category in a product category structure of the marketplace website; converting words in each of the listing titles to semantic tokens in a token symbol space, based on a tokenization process; performing n-gram modeling on the tokens corresponding to each of the listing titles of the item listings in the particular product category; and identifying, by a machine having a memory and at least one processor, one or more dominant n-gram models associated with the listing titles of the item listings in the particular product category, each dominant n-gram model identifying a sequence of one or more semantic tokens that appear in a statistically significant portion of the listing titles of the item listings in the particular product category. 2. The method of claim 1 , wherein the tokens include a product token, an accessory token, a for token, a with token, and an unknown token. | 0.627376 |
50. The method of claim 49 wherein the query is accompanied by one or more restrictions on the gaps. | 50. The method of claim 49 wherein the query is accompanied by one or more restrictions on the gaps. 51. The method of claim 50 wherein the one or more gaps comprise one or more triplets with gap entities. | 0.973565 |
4. A method for comparing first and second documents, the first and second documents containing corresponding first and second pluralities of graphic elements, the method comprising: assigning a plurality of unique identifiers to the graphic elements of the first and second pluralities of graphic elements wherein, upon determining that a first graphic element of the first plurality of graphic elements is sufficiently similar to a second graphic element of the second plurality of graphic elements, the method comprises associating the same one of the unique identifiers with both the first and second graphic elements; organizing the unique identifiers into a first list and a second list, entries of the first list corresponding to a display order of the graphic elements from the first document, and entries of the second list corresponding to a display order of the graphic elements from the second document; and further comprising: deriving edit data from the first and second lists wherein the edit data can be used to change the first list into the second list; and creating at least one target document based on the first and second documents, the first and second lists, and the edit data. | 4. A method for comparing first and second documents, the first and second documents containing corresponding first and second pluralities of graphic elements, the method comprising: assigning a plurality of unique identifiers to the graphic elements of the first and second pluralities of graphic elements wherein, upon determining that a first graphic element of the first plurality of graphic elements is sufficiently similar to a second graphic element of the second plurality of graphic elements, the method comprises associating the same one of the unique identifiers with both the first and second graphic elements; organizing the unique identifiers into a first list and a second list, entries of the first list corresponding to a display order of the graphic elements from the first document, and entries of the second list corresponding to a display order of the graphic elements from the second document; and further comprising: deriving edit data from the first and second lists wherein the edit data can be used to change the first list into the second list; and creating at least one target document based on the first and second documents, the first and second lists, and the edit data. 6. A method according to claim 4 wherein the first and second plurality of graphic elements are chosen for comparison based on a selection criterion wherein the selection criterion is based on graphic element attributes and information associated with the first and second documents; and wherein zero or more unselected graphic elements from the first document and the second document are excluded by the selection criterion. | 0.601743 |
16. An apparatus, comprising: a keyboard, the keyboard including a plurality of selectable polysemous symbols; a memory configured to store an interactive dictionary database, the interactive dictionary database including a plurality of symbol sequences, each of the plurality of symbol sequences including at least one of the selectable polysemous symbols and each of the plurality of symbol sequences being stored in association with at least one word, sentence, phoneme, message, letter, number, morpheme, command and/or phrase; and an integrated input and display device configured to display at least portions of the interactive dictionary database to a user upon receipt of user input, including information useable to assign at least a subset of the plurality of symbol sequences at least one of an active and an inactive status, the interactive dictionary database further including a plurality of rationales, each respectively relating a respective one of the plurality of symbol sequences to a respective associated at least one of words, sentences, phonemes, messages, letters, numbers, morphemes, commands and phrases, wherein when an inactive status is assigned to one of the plurality of polysemous symbol sequences, a corresponding sequence of previously selectable symbols of the keyboard is rendered unselectable by the user. | 16. An apparatus, comprising: a keyboard, the keyboard including a plurality of selectable polysemous symbols; a memory configured to store an interactive dictionary database, the interactive dictionary database including a plurality of symbol sequences, each of the plurality of symbol sequences including at least one of the selectable polysemous symbols and each of the plurality of symbol sequences being stored in association with at least one word, sentence, phoneme, message, letter, number, morpheme, command and/or phrase; and an integrated input and display device configured to display at least portions of the interactive dictionary database to a user upon receipt of user input, including information useable to assign at least a subset of the plurality of symbol sequences at least one of an active and an inactive status, the interactive dictionary database further including a plurality of rationales, each respectively relating a respective one of the plurality of symbol sequences to a respective associated at least one of words, sentences, phonemes, messages, letters, numbers, morphemes, commands and phrases, wherein when an inactive status is assigned to one of the plurality of polysemous symbol sequences, a corresponding sequence of previously selectable symbols of the keyboard is rendered unselectable by the user. 21. The apparatus of claim 16 , wherein the interactive dictionary database includes a plurality of symbol sequences stored in association with a common at least one word, sentence, phoneme, message, letter, number, morpheme, command and/or phrase. | 0.689566 |
4. The method of claim 1 wherein transforming a state of the numerical seller rating from a state that is inconsistent with the words in the feedback to a state that is reconciled with the words in the feedback is done by weighting the numerical seller rating. | 4. The method of claim 1 wherein transforming a state of the numerical seller rating from a state that is inconsistent with the words in the feedback to a state that is reconciled with the words in the feedback is done by weighting the numerical seller rating. 6. The method of claim 4 wherein weighting the numerical seller rating is based on one of geography, product listing category or average selling price. | 0.931159 |
9. The method of claim 1 , further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. | 9. The method of claim 1 , further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. 10. The method of claim 9 , wherein generating the one or more attribute suggestions comprises: identifying one or more associated attributes for each of the selected entities; and selecting the associated attributes that maximally refine the selected entities as being attribute suggestions. | 0.916142 |
1. A method for use in organizing source content, the method comprising: accessing a plurality of media content files of a subject, at least one of the media content files having parameter data associated with the at least one of the media content files, the plurality of media content files having been recorded over a period of time and associated with the subject when recorded; identifying the subject at the end of the period of time; initiating the organization of the accessed plurality of recorded multimedia content: identifying a first organizational style of a plurality of different organizational styles, where each of the plurality of organizational styles define one or more parameters that when utilized dictate how media content files are to be organized; identifying a first parameter data item as defined in the first organizational style; observing the first parameter data item, as defined in the first organizational style, within the parameter data associated with the at least one of the media content files; organizing the at least one of the media content files relative to a remainder of the plurality of media content files as a function of the first parameter data item within the parameter data associated with the at least one of the media content files, thereby organizing the plurality of media content files as a function of the first organizational style; and generating an output content incorporating the plurality of media content files as organized as a function of the first organizational style. | 1. A method for use in organizing source content, the method comprising: accessing a plurality of media content files of a subject, at least one of the media content files having parameter data associated with the at least one of the media content files, the plurality of media content files having been recorded over a period of time and associated with the subject when recorded; identifying the subject at the end of the period of time; initiating the organization of the accessed plurality of recorded multimedia content: identifying a first organizational style of a plurality of different organizational styles, where each of the plurality of organizational styles define one or more parameters that when utilized dictate how media content files are to be organized; identifying a first parameter data item as defined in the first organizational style; observing the first parameter data item, as defined in the first organizational style, within the parameter data associated with the at least one of the media content files; organizing the at least one of the media content files relative to a remainder of the plurality of media content files as a function of the first parameter data item within the parameter data associated with the at least one of the media content files, thereby organizing the plurality of media content files as a function of the first organizational style; and generating an output content incorporating the plurality of media content files as organized as a function of the first organizational style. 2. The method of claim 1 , wherein the first parameter data item is a location parameter data item, and the organizing comprises organizing the at least one of the media content files relative to a remainder of the plurality of media content files as each media content file relates in location to the remainder of the plurality of media content files. | 0.665408 |
1. A method of synchronizing robot motion with a social interaction, comprising: composing by the robot a robot dialogue comprising words, wherein the robot dialogue is composed based on a context of an on-going social interaction with a human being; parsing the robot dialogue by the robot to determine a syntax of the robot dialogue; analyzing the syntax of the dialogue by the robot; automatically generating, by the robot, a robot motion script synchronized with the robot dialogue based on the syntax of the dialogue and based on a physical cadence, wherein the robot motion script comprises a sequence of separate robot motions, and wherein generating the robot motion script based on the physical cadence comprises incorporating at least one of an eye blink robot motion, a weight shift robot motion, and a head nod robot motion into the robot motion script; playing aloud the robot dialogue by the robot; and performing the robot motion script by the robot in synchronization with the playing aloud of the robot dialogue. | 1. A method of synchronizing robot motion with a social interaction, comprising: composing by the robot a robot dialogue comprising words, wherein the robot dialogue is composed based on a context of an on-going social interaction with a human being; parsing the robot dialogue by the robot to determine a syntax of the robot dialogue; analyzing the syntax of the dialogue by the robot; automatically generating, by the robot, a robot motion script synchronized with the robot dialogue based on the syntax of the dialogue and based on a physical cadence, wherein the robot motion script comprises a sequence of separate robot motions, and wherein generating the robot motion script based on the physical cadence comprises incorporating at least one of an eye blink robot motion, a weight shift robot motion, and a head nod robot motion into the robot motion script; playing aloud the robot dialogue by the robot; and performing the robot motion script by the robot in synchronization with the playing aloud of the robot dialogue. 2. The method of claim 1 , further comprising analyzing a communication of a human being, wherein the robot motion script is further generated based on analyzing the communication of the human being. | 0.588957 |
11. A non-transitory, computer-readable storage medium comprising instructions for selecting a representative image for a recipe from among a plurality of recipe images, the instructions when executed by a processor cause the processor to: receive a recipe comprising classified recipe text and a plurality of candidate images; generate image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determine image probabilities of the plurality of candidate images depicting a finished food product described by the recipe after preparation is complete, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; rank the plurality of candidate images according to the determined image probabilities; select a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and store the selected representative image in association with the retrieved recipe. | 11. A non-transitory, computer-readable storage medium comprising instructions for selecting a representative image for a recipe from among a plurality of recipe images, the instructions when executed by a processor cause the processor to: receive a recipe comprising classified recipe text and a plurality of candidate images; generate image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determine image probabilities of the plurality of candidate images depicting a finished food product described by the recipe after preparation is complete, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; rank the plurality of candidate images according to the determined image probabilities; select a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and store the selected representative image in association with the retrieved recipe. 16. The non-transitory, computer-readable storage medium of claim 11 , wherein the classified recipe text comprises a recipe title of the received recipe, and the generated features of the candidate image include a feature representative of a match between the recipe title and image metadata of the candidate image. | 0.8457 |
9. A system for identifying an author of a social media interaction, the system comprising: a customer information database storing contact center profiles for each customer registered in a contact center environment; and a processor configured to: receive a social media profile for a user interacting in a social media interaction in a social media environment, wherein the social media profile includes one or more identification parameters defining personal information registered to the user in the social media environment and one or more content parameters defining content of a social media interaction provided by the user, for each of a plurality of customers registered in the contact center environment, receive the contact center profile for the customer including one or more identification parameters defining personal information registered to the customer in the contact center environment and one or more content parameters defining content of the customer's past contact center interactions, and compare the user's social media profile with the customer's contact center profile using an equivalence relationship that compares said respective identification parameters and content parameters of the profiles to determine a final equivalence of whether the social media user and contact center customer have the same identity, wherein a predetermined threshold is set to define a range for the equivalence relationship within which the social media user and contact center customer are determined to have the same identity, wherein the predetermined threshold is set in a testing phase to balance maximizing the accuracy and minimizing missed instances of determining users and customers to be identical that are previously known to be identical, wherein each of the user's and customer's profile is represented by a vector with each of the identification and content parameters thereof having values in a respective dimension and wherein the processor compares the profiles by calculating the vector difference between their representative vectors to measure a similarity between the social media profile and the contact center profile and wherein the content parameters comprise one or more content parameters selected from the group consisting of: linguistic richness, sentiment, tone, opinion, style, vocabulary, average length of sentences, slang and emoticons; and after determining the final equivalence that the social media user and contact center customer are determined to have the same identity, monitor that user's social media interactions by the contact center for the associated customer. | 9. A system for identifying an author of a social media interaction, the system comprising: a customer information database storing contact center profiles for each customer registered in a contact center environment; and a processor configured to: receive a social media profile for a user interacting in a social media interaction in a social media environment, wherein the social media profile includes one or more identification parameters defining personal information registered to the user in the social media environment and one or more content parameters defining content of a social media interaction provided by the user, for each of a plurality of customers registered in the contact center environment, receive the contact center profile for the customer including one or more identification parameters defining personal information registered to the customer in the contact center environment and one or more content parameters defining content of the customer's past contact center interactions, and compare the user's social media profile with the customer's contact center profile using an equivalence relationship that compares said respective identification parameters and content parameters of the profiles to determine a final equivalence of whether the social media user and contact center customer have the same identity, wherein a predetermined threshold is set to define a range for the equivalence relationship within which the social media user and contact center customer are determined to have the same identity, wherein the predetermined threshold is set in a testing phase to balance maximizing the accuracy and minimizing missed instances of determining users and customers to be identical that are previously known to be identical, wherein each of the user's and customer's profile is represented by a vector with each of the identification and content parameters thereof having values in a respective dimension and wherein the processor compares the profiles by calculating the vector difference between their representative vectors to measure a similarity between the social media profile and the contact center profile and wherein the content parameters comprise one or more content parameters selected from the group consisting of: linguistic richness, sentiment, tone, opinion, style, vocabulary, average length of sentences, slang and emoticons; and after determining the final equivalence that the social media user and contact center customer are determined to have the same identity, monitor that user's social media interactions by the contact center for the associated customer. 11. The system of claim 9 , wherein the customer information database is a customer relationship management (CRM) database. | 0.556098 |
11. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive collection of user feedback regarding word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI) on an output display; determining whether a user selected an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to determining that the user selected the of-interest word or phrase of the first sentence, highlighting the of-interest word or phrase via the UI; determining whether the user selected a linked word or phrase of a second sentence of the bilingual sentence pair; in response to determining that the user selected the linked word or phrase of the second sentence, highlighting the linked word or phrase via the UI; receiving feedback from the user regarding a quality of the word-alignments between the bilingual sentence pair; rating the feedback based at least in part on an amount of time between highlighting the linked word or phrase via the UI and receiving the feedback; and storing the feedback; wherein the storing comprises storing at least a user identifier field that identifies the user who made the selections of the determining operations. | 11. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive collection of user feedback regarding word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI) on an output display; determining whether a user selected an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to determining that the user selected the of-interest word or phrase of the first sentence, highlighting the of-interest word or phrase via the UI; determining whether the user selected a linked word or phrase of a second sentence of the bilingual sentence pair; in response to determining that the user selected the linked word or phrase of the second sentence, highlighting the linked word or phrase via the UI; receiving feedback from the user regarding a quality of the word-alignments between the bilingual sentence pair; rating the feedback based at least in part on an amount of time between highlighting the linked word or phrase via the UI and receiving the feedback; and storing the feedback; wherein the storing comprises storing at least a user identifier field that identifies the user who made the selections of the determining operations. 16. One or more computer-readable storage devices as recited in claim 11 , wherein rating the feedback comprises determining a user confidence rating for the user providing the received feedback based at least on part on previous feedback received from the user. | 0.572254 |
1. A method for adaptive fuzzing testing for web pages of a web site, the method comprising: executing a breadth first search on a web site to identify a page of the web site to test for a vulnerability; performing minimal fuzzing testing on the page of the web site that has been identified during a breadth first search; gathering at least one heuristic for the page of the web site on which minimal fuzzing testing is performed; generating a vulnerability score for the page of the web site utilizing the at least one heuristic gathered for the page; utilizing the vulnerability score for the page of the web site to identify the page of the web site as having a potential for a vulnerability; performing expanded fuzzing testing on the page of the web site that is identified as having the potential vulnerability based upon the vulnerability score that is at least equal to a predetermined vulnerability threshold value; and executing a depth first search on the web site to identify at least one additional page of the web site to test for a vulnerability subsequent to identifying the page on the web site that has the potential vulnerability, wherein the depth first search begins with a page of the web site that is identified as having a potential vulnerability. | 1. A method for adaptive fuzzing testing for web pages of a web site, the method comprising: executing a breadth first search on a web site to identify a page of the web site to test for a vulnerability; performing minimal fuzzing testing on the page of the web site that has been identified during a breadth first search; gathering at least one heuristic for the page of the web site on which minimal fuzzing testing is performed; generating a vulnerability score for the page of the web site utilizing the at least one heuristic gathered for the page; utilizing the vulnerability score for the page of the web site to identify the page of the web site as having a potential for a vulnerability; performing expanded fuzzing testing on the page of the web site that is identified as having the potential vulnerability based upon the vulnerability score that is at least equal to a predetermined vulnerability threshold value; and executing a depth first search on the web site to identify at least one additional page of the web site to test for a vulnerability subsequent to identifying the page on the web site that has the potential vulnerability, wherein the depth first search begins with a page of the web site that is identified as having a potential vulnerability. 5. The method for adaptive fuzzing testing for web pages of a web site of claim 1 , wherein the generating a vulnerability score for the page of the web site utilizing at least one heuristic gathered for the page comprises employing an exponential evaluation function that utilizes at least a value for one heuristic gathered for the page of the web site to calculate a vulnerability score for the page of the web site. | 0.669083 |
1. A method for managing a website, comprising: obtaining a plurality of data items from a plurality of websites, wherein each of the plurality of data items comprises a conversion rate corresponding to a percentage of transactions completed by a plurality of website visitors accessing the data item; receiving, by the processor and from a user, a website text item of the website; identifying a business type of the website and a website element category of the website text item; searching, by the processor and using the business type and the website element category, the plurality of data items to identify a subset of the plurality of data items; identifying, by the processor and from the subset, a comparable text item to the website text item; identifying, by the processor and from the subset, a modified text item, wherein a conversion rate of the modified text item exceeds a conversion rate of the comparable text item; generating, using the processor, a conversion improved website comprising the modified text item, wherein the modified text item replaces the website text item; receiving, from the user, an approval of the conversion improved website; obtaining a localized traffic rate of the comparable text item; identifying a modified localized traffic text item comprising a modified localized traffic rate that exceeds the localized traffic rate; generating a localized traffic improved web site comprising the modified localized traffic text item, wherein the modified localized traffic text item is text; receiving, from the user, a fourth approval of the localized traffic improved website; and generating, based on the fourth approval, the website comprising the modified localized traffic text item based on the localized traffic improved website, wherein the localized traffic improved website receives more traffic originating from a country than the website comprising the website text item. | 1. A method for managing a website, comprising: obtaining a plurality of data items from a plurality of websites, wherein each of the plurality of data items comprises a conversion rate corresponding to a percentage of transactions completed by a plurality of website visitors accessing the data item; receiving, by the processor and from a user, a website text item of the website; identifying a business type of the website and a website element category of the website text item; searching, by the processor and using the business type and the website element category, the plurality of data items to identify a subset of the plurality of data items; identifying, by the processor and from the subset, a comparable text item to the website text item; identifying, by the processor and from the subset, a modified text item, wherein a conversion rate of the modified text item exceeds a conversion rate of the comparable text item; generating, using the processor, a conversion improved website comprising the modified text item, wherein the modified text item replaces the website text item; receiving, from the user, an approval of the conversion improved website; obtaining a localized traffic rate of the comparable text item; identifying a modified localized traffic text item comprising a modified localized traffic rate that exceeds the localized traffic rate; generating a localized traffic improved web site comprising the modified localized traffic text item, wherein the modified localized traffic text item is text; receiving, from the user, a fourth approval of the localized traffic improved website; and generating, based on the fourth approval, the website comprising the modified localized traffic text item based on the localized traffic improved website, wherein the localized traffic improved website receives more traffic originating from a country than the website comprising the website text item. 3. The method of claim 1 , further comprising: receiving, from the user, a rejection of the conversion improved website; and generating the website comprising the website text item. | 0.610246 |
9. The system as recited in claim 8 , wherein the test grammar includes a set of attributes. | 9. The system as recited in claim 8 , wherein the test grammar includes a set of attributes. 10. The system as recited in claim 9 , wherein the test case generation component generates the second set of test cases based on processing the attributes in the test grammar. | 0.94729 |
2. The method of claim 1 wherein versioning information of a vNode comprises at least one of a start date corresponding to a check-in date of a version of the structured document in which the vNode is first detected, and an end date corresponding to a check-in date of another version of the structured document in which the vNode no longer exists in the structured document. | 2. The method of claim 1 wherein versioning information of a vNode comprises at least one of a start date corresponding to a check-in date of a version of the structured document in which the vNode is first detected, and an end date corresponding to a check-in date of another version of the structured document in which the vNode no longer exists in the structured document. 4. The method of claim 2 wherein the versioned function is a “document-at-date-range” function and the at least one argument of the versioned function is a “range-start-date” argument that specifies a first date and a “range-end-date” argument that specifies a second date, and wherein the identified version of the structured document is a version that at least one of exists on the first date and is checked-in on a date between the first date and the second date, and that includes an object represented by a vNode satisfying the query. | 0.783811 |
15. A method of saving digital content classified by person-based clustering, comprising: generating, on a non-transitory computer readable medium, a data structure composed of a plurality of nodes using a schema of a database that stores a plurality of digital content; extracting, on the non-transitory computer readable medium, a face descriptor of new digital content to be saved in the database; classifying, on the non-transitory computer readable medium, the new digital content and the plurality of digital content by the person-based clustering using the extracted face descriptor; and updating, on the non-transitory computer readable medium, the data structure according to the classification. | 15. A method of saving digital content classified by person-based clustering, comprising: generating, on a non-transitory computer readable medium, a data structure composed of a plurality of nodes using a schema of a database that stores a plurality of digital content; extracting, on the non-transitory computer readable medium, a face descriptor of new digital content to be saved in the database; classifying, on the non-transitory computer readable medium, the new digital content and the plurality of digital content by the person-based clustering using the extracted face descriptor; and updating, on the non-transitory computer readable medium, the data structure according to the classification. 16. The method of claim 15 , wherein the schema comprises a content information table, a person information table, and a face information table. | 0.677347 |
1. Apparatus for binding program code to portions of an XML-compliant document having a plurality of elements being arranged in a nested relationship to construct an object for accessing at least one element of the XML-compliant document, the apparatus comprising: at least one computer storage medium storing information comprising: stored information associated with the XML-compliant document, the information associated with the XML-compliant document comprising a reference to a schema document and, for each element, data and attributes representing a part of the XML-compliant document; the schema document referenced by the XML-compliant document, the schema document containing a registry which maps a tag identifying an element of the plurality of elements to program code useful for accessing data and attributes of the element; a mechanism that uses the program code to construct an object that has methods that access the data or attributes or the data and the attributes for the element and provides an interface pointer to the object to at least one process seeking to access the element of the XML-compliant document; and a storage manager configured to: receive a request for accessing a part of the XML-compliant document from an application, identify from information in the registry and at least one element of the part a program ID code associated with program code for accessing the part, make a method call on the mechanism using the program ID code for constructing the object containing the program code for accessing the part, and return to the application the interface pointer provided by the mechanism. | 1. Apparatus for binding program code to portions of an XML-compliant document having a plurality of elements being arranged in a nested relationship to construct an object for accessing at least one element of the XML-compliant document, the apparatus comprising: at least one computer storage medium storing information comprising: stored information associated with the XML-compliant document, the information associated with the XML-compliant document comprising a reference to a schema document and, for each element, data and attributes representing a part of the XML-compliant document; the schema document referenced by the XML-compliant document, the schema document containing a registry which maps a tag identifying an element of the plurality of elements to program code useful for accessing data and attributes of the element; a mechanism that uses the program code to construct an object that has methods that access the data or attributes or the data and the attributes for the element and provides an interface pointer to the object to at least one process seeking to access the element of the XML-compliant document; and a storage manager configured to: receive a request for accessing a part of the XML-compliant document from an application, identify from information in the registry and at least one element of the part a program ID code associated with program code for accessing the part, make a method call on the mechanism using the program ID code for constructing the object containing the program code for accessing the part, and return to the application the interface pointer provided by the mechanism. 2. The apparatus of claim 1 , wherein the mechanism is a Common Object Model (COM) object manager and the program code is identified in the registry by a ProgID code. | 0.616901 |
3. The method of claim 1 wherein adapting operation of the software includes: making a determination that a particular place is associated with an activity; determining one or more play types that are associated with the activity; comparing the one or more play types to the play personality of the user to determine whether the one or more play types are play types that satisfy the user's need for play; and responsive to determining that the one or more play types are play types that satisfy the user's need for play, adapting operation of the software based, at least in part, on the determination that the particular place is associated with an activity that is likely to satisfy the user's need for play; wherein the particular place is one of: a real-world store, a real-world building, a real-world venue, a virtual store, or a virtual venue. | 3. The method of claim 1 wherein adapting operation of the software includes: making a determination that a particular place is associated with an activity; determining one or more play types that are associated with the activity; comparing the one or more play types to the play personality of the user to determine whether the one or more play types are play types that satisfy the user's need for play; and responsive to determining that the one or more play types are play types that satisfy the user's need for play, adapting operation of the software based, at least in part, on the determination that the particular place is associated with an activity that is likely to satisfy the user's need for play; wherein the particular place is one of: a real-world store, a real-world building, a real-world venue, a virtual store, or a virtual venue. 21. The method of claim 3 wherein: the method further comprises receiving, at the computing device, a request to geo-locate play opportunities for the user; and the steps of making a determination that a particular place is associated with an activity; determining one or more play types that are associated with the activity; comparing the one or more play types to the play personality of the user to determine whether the one or more play types are play types that satisfy the user's need for play; and responsive to determining that the one or more play types are play types that satisfy the user's need for play, adapting operation of the software based, at least in part, on the determination that the particular place is associated with an activity that is likely to satisfy the user's need for play; are performed in response to the request to geo-locate play opportunities for the user. | 0.530435 |
3. The method of claim 1 , wherein revising the caption curve comprises: changing a portion of the caption curve from a first value indicating the caption segment is displayed to a second value indication the caption segment is not displayed. | 3. The method of claim 1 , wherein revising the caption curve comprises: changing a portion of the caption curve from a first value indicating the caption segment is displayed to a second value indication the caption segment is not displayed. 4. The method of claim 3 , wherein the change of the portion is at an end of the caption segment. | 0.930651 |
32. A machine-readable medium encoded with instructions, that when executed by one or more processors, cause the processor to carry out a process for generating attribute models for use in a navigation system in a vehicle, the process comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road attribute-of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road attribute in a conditional variant model associated with the condition, wherein storing the values of the road attribute in a conditional variant model associated with the condition comprises: partitioning values of the road attribute into separate data buckets by explicit conditions; and forming a conditional variant model for each respective explicit condition based on the values of the road attribute in that bucket. | 32. A machine-readable medium encoded with instructions, that when executed by one or more processors, cause the processor to carry out a process for generating attribute models for use in a navigation system in a vehicle, the process comprising: for each of a plurality of driving sessions, during which the user travelled over a plurality of road segments in the vehicle: collecting sensor data of the vehicle for each of the plurality road segments travelled during a driving session; and associating the sensor data with at least one of a plurality of conditions, each condition descriptive of the driving session at the time the user travelled on the road segment; for each of the plurality of road segments, determining a value of a road attribute-of the road segment based upon the sensor data collected for that road segment, and associated with at least one of the conditions; and for each of the plurality of conditions, storing the values of the road attribute in a conditional variant model associated with the condition, wherein storing the values of the road attribute in a conditional variant model associated with the condition comprises: partitioning values of the road attribute into separate data buckets by explicit conditions; and forming a conditional variant model for each respective explicit condition based on the values of the road attribute in that bucket. 40. The machine-readable medium of claim 32 , wherein the road attribute is disfavored roads. | 0.5 |
1. A non-transitory computer-readable storage medium comprising instructions stored thereon for propagating changes to copied text that, when executed by at least one processor, are configured to cause a computing system to at least: monitor changes to text copied into multiple documents, the copied text having been copied from a previous document; determine that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompt the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. | 1. A non-transitory computer-readable storage medium comprising instructions stored thereon for propagating changes to copied text that, when executed by at least one processor, are configured to cause a computing system to at least: monitor changes to text copied into multiple documents, the copied text having been copied from a previous document; determine that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompt the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. 2. The non-transitory computer-readable storage medium of claim 1 , wherein: the instructions are further configured to cause the computing system to increment a change counter each time the same deletion is made to an instance of the copied text in a different document; and the determining that the same deletion has been made to the copied text in at least the threshold number of documents includes comparing the change counter to the threshold number. | 0.5 |
48. A computer-implemented method of processing data, comprising: facilitating a user to define an index to increase searching performance; accessing, by a computing device, at least one first database of information representative of patents having said user-defined index; accessing, by the computing device, at least one second database of non-patent information; accessing at least one group formed according to non-patent criteria of interest to a user, said at least one group comprising one or more patents represented in said at least one first database that map to said non-patent criteria; and automatically processing, by the computing device and by searching said user-defined index, at least one patent in said at least one group with further consideration of at least one of patent information or non-patent information. | 48. A computer-implemented method of processing data, comprising: facilitating a user to define an index to increase searching performance; accessing, by a computing device, at least one first database of information representative of patents having said user-defined index; accessing, by the computing device, at least one second database of non-patent information; accessing at least one group formed according to non-patent criteria of interest to a user, said at least one group comprising one or more patents represented in said at least one first database that map to said non-patent criteria; and automatically processing, by the computing device and by searching said user-defined index, at least one patent in said at least one group with further consideration of at least one of patent information or non-patent information. 49. The method of claim 48 , wherein said non-patent information comprises information related to intellectual property (IP) related transactions. | 0.841989 |
9. The method of claim 8 , wherein at least 3 different controlled relevant documents are produced from the selected document using a given relevancy algorithm with search terms placed in 3 different positions in the three different controlled relevant documents with each controlled relevant document compared with the selected document with an absence of search terms in the selected document to generate three controlled relevant vectors. | 9. The method of claim 8 , wherein at least 3 different controlled relevant documents are produced from the selected document using a given relevancy algorithm with search terms placed in 3 different positions in the three different controlled relevant documents with each controlled relevant document compared with the selected document with an absence of search terms in the selected document to generate three controlled relevant vectors. 10. The method of claim 9 including using a relevancy vector chart made up of the three controlled relevant vectors to obtain a relative ranking of a plurality of search engines. | 0.878975 |
1. A method comprising: receiving, by a computing device, a media file; parsing the media file to determine a grammatical structure of language contained in the media file; and adding the language contained in the media file to an index. | 1. A method comprising: receiving, by a computing device, a media file; parsing the media file to determine a grammatical structure of language contained in the media file; and adding the language contained in the media file to an index. 2. The method of claim 1 , comprising: dividing the language contained in the media file into sentences. | 0.808065 |
34. The system of claim 31 wherein the captioned device is further programmed to perform the step of, upon receiving the indication that a captioning service should be invoked, initiating a connection over the second communication link. | 34. The system of claim 31 wherein the captioned device is further programmed to perform the step of, upon receiving the indication that a captioning service should be invoked, initiating a connection over the second communication link. 35. The system of claim 34 wherein the activator includes a switch. | 0.966602 |
6. The method of claim 5 , wherein the formatting characteristics comprise at least one tag type selected from the group of tag types comprising a distinguishing font, a distinguishing color, a hypertext link, a title, a coding tag, and a meta tag. | 6. The method of claim 5 , wherein the formatting characteristics comprise at least one tag type selected from the group of tag types comprising a distinguishing font, a distinguishing color, a hypertext link, a title, a coding tag, and a meta tag. 7. The method of claim 6 , wherein automatically computing the specificity value for each instance of each identified term is performed in association, at least in part, with a specificity weight factor of a tag type associated with the identified term. | 0.935281 |
2. The computer system of claim 1 , the instructions further including: creating an initial morphological description of the natural language having word inflection rules for groups of words in the natural language; wherein the new entry is at least in part based on the initial morphological description of the natural language. | 2. The computer system of claim 1 , the instructions further including: creating an initial morphological description of the natural language having word inflection rules for groups of words in the natural language; wherein the new entry is at least in part based on the initial morphological description of the natural language. 4. The computer system of claim 2 , wherein the morphological description of the natural language comprises one or more word formation rules. | 0.890054 |
1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding. | 1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding. 9. The computational method of claim 1 , wherein the mapping includes: enumerating a set of onset-delimited, N-part, partitionings of the speech encoding based on groupings of adjacent ones of the segments, wherein N corresponds to the number of sub-phrase portions of the phrase template; for each of the partitionings, constructing a corresponding mapping of the speech encoding segment groupings to sub-phrase portions, the mappings providing plural of the phrase candidates. | 0.520016 |
1. A computer-implemented method comprising: receiving first query terms from a user; automatically selecting, based at least in part on the first query terms, and from among a set of documents, first documents; automatically generating second query terms based at least in part on anchor text that is contained within links that occur within the first documents; automatically selecting, based at least in part on the second query terms, and from among the set of documents, second documents; wherein the first documents differ from the second documents; automatically generating third query terms based at least in part on anchor text that is contained within links that occur within the second documents, and not based on any input from said user; and automatically selecting, based at least in part on the third query terms, and from among the set of documents, third documents; wherein the third documents differ from the first documents and the second documents; determining a first number that is a number of documents in an intersection of (a) a set consisting of the first documents and (b) a set consisting of the second documents; determining a second number that is the first number divided by a number of documents in the set consisting of the second documents; determining whether the second number is at least as great as a specified percentage; and in response to determining that the second number is not at least as great as the specified percentage, automatically generating the third query terms based at least in part on anchor text that is contained within links that occur within the second documents; wherein the step of generating the third query terms is performed by one or more computing devices; and wherein said first and second documents are not displayed to said user. | 1. A computer-implemented method comprising: receiving first query terms from a user; automatically selecting, based at least in part on the first query terms, and from among a set of documents, first documents; automatically generating second query terms based at least in part on anchor text that is contained within links that occur within the first documents; automatically selecting, based at least in part on the second query terms, and from among the set of documents, second documents; wherein the first documents differ from the second documents; automatically generating third query terms based at least in part on anchor text that is contained within links that occur within the second documents, and not based on any input from said user; and automatically selecting, based at least in part on the third query terms, and from among the set of documents, third documents; wherein the third documents differ from the first documents and the second documents; determining a first number that is a number of documents in an intersection of (a) a set consisting of the first documents and (b) a set consisting of the second documents; determining a second number that is the first number divided by a number of documents in the set consisting of the second documents; determining whether the second number is at least as great as a specified percentage; and in response to determining that the second number is not at least as great as the specified percentage, automatically generating the third query terms based at least in part on anchor text that is contained within links that occur within the second documents; wherein the step of generating the third query terms is performed by one or more computing devices; and wherein said first and second documents are not displayed to said user. 10. The method of claim 1 , further comprising: associating, with each particular link in the links that occur within the first documents, a weight that is based on a number of times that text of that particular link occurs within the links that occur within the first documents. | 0.709544 |
1. One or more hardware storage devices having stored thereon computer executable instructions that, when executed by one or more processors of a computer system, implement a method for annotating a graphical element, the method comprising: displaying one or more graphical elements at a user interface, the one or more graphical elements representing one or more anatomical structures; simultaneous to display of the one or more graphical elements, displaying a user-selectable annotation button that, when selected, enables specification one or more points of the one or more graphical elements for annotation; receiving user input selecting the annotation button; subsequent to receiving the user input selecting the annotation button, receiving user input specifying a particular point of the one or more graphical elements for entry of an annotation; subsequent to receiving the user input specifying the particular point of the one or more graphical elements for entry of an annotation, displaying an annotation dialogue that provides selection of a plurality of annotation options for annotating the specified particular point, the annotation dialogue being visually associated with the specified particular point of the one or more graphical elements, the annotation dialogue including: one or more highlighting options for visually emphasizing the specified particular point, including one or more of shapes or colors; and one or more comment input options for providing information relevant to the specified particular point, including one or more of text or audio input; receiving user input selecting one or more of the highlighting options and one or more of the comment input options; receiving user comment input that provides at least one comment corresponding to the user comment input; and displaying the one or more graphical elements along with the selected annotation, including the selected highlighting options and the inputted at least one comment. | 1. One or more hardware storage devices having stored thereon computer executable instructions that, when executed by one or more processors of a computer system, implement a method for annotating a graphical element, the method comprising: displaying one or more graphical elements at a user interface, the one or more graphical elements representing one or more anatomical structures; simultaneous to display of the one or more graphical elements, displaying a user-selectable annotation button that, when selected, enables specification one or more points of the one or more graphical elements for annotation; receiving user input selecting the annotation button; subsequent to receiving the user input selecting the annotation button, receiving user input specifying a particular point of the one or more graphical elements for entry of an annotation; subsequent to receiving the user input specifying the particular point of the one or more graphical elements for entry of an annotation, displaying an annotation dialogue that provides selection of a plurality of annotation options for annotating the specified particular point, the annotation dialogue being visually associated with the specified particular point of the one or more graphical elements, the annotation dialogue including: one or more highlighting options for visually emphasizing the specified particular point, including one or more of shapes or colors; and one or more comment input options for providing information relevant to the specified particular point, including one or more of text or audio input; receiving user input selecting one or more of the highlighting options and one or more of the comment input options; receiving user comment input that provides at least one comment corresponding to the user comment input; and displaying the one or more graphical elements along with the selected annotation, including the selected highlighting options and the inputted at least one comment. 4. The one or more hardware storage devices of claim 1 , wherein the user interface further includes one or more user-selectable graphical element manipulation options, including one or more of a color control option, a cropping option, a rotation option, or a drawing option. | 0.5 |
14. A non-transitory computer readable medium comprising a plurality of computer-executable instructions stored thereon that, when executed, cause a computing system to perform processing for extracting one or more descriptors of a specified term in text data from the text data, the processing comprising: receiving, from a user: an address for at least one information source, the address being a uniform resource locator (URL) address or a location of a text file within a storage device, the term being at least one word or other text token; and the specified term; creating a tagged information file by associating part of speech tags to text data obtained from the at least one information source, including to any descriptors present in the text data, wherein a descriptor comprises one or more words of the text data that succeed or precede the specified term; identifying a location of the specified term in the tagged information file using an approximate text matching technique, wherein the approximate text matching technique: detects the specified term grouped together with the descriptors of the specified term in the text data using the tagged information file, the specified term grouped together with the descriptors of the specified term forming a variable region or variable window that is context sensitive and not of a fixed size; and identifies, through a finite state machine, a grammatical context shift in the context sensitive region pertaining to the specified term in the text data by analyzing the part of speech tags of the tagged information file, wherein the grammatical context shift is indicated by an autonomous transition of the finite state machine from a first state associated with a first part of speech tag of the tagged information file to a second state associated with a second part of speech tag of the tagged information file for parts of speech associated with words before and after the specified term; determining based on the determined grammatical context shift the one or more descriptors of the specified term; extracting the one or more descriptors of the specified term from the text data; and providing a report comprising the extracted one or more descriptors of the specified term. | 14. A non-transitory computer readable medium comprising a plurality of computer-executable instructions stored thereon that, when executed, cause a computing system to perform processing for extracting one or more descriptors of a specified term in text data from the text data, the processing comprising: receiving, from a user: an address for at least one information source, the address being a uniform resource locator (URL) address or a location of a text file within a storage device, the term being at least one word or other text token; and the specified term; creating a tagged information file by associating part of speech tags to text data obtained from the at least one information source, including to any descriptors present in the text data, wherein a descriptor comprises one or more words of the text data that succeed or precede the specified term; identifying a location of the specified term in the tagged information file using an approximate text matching technique, wherein the approximate text matching technique: detects the specified term grouped together with the descriptors of the specified term in the text data using the tagged information file, the specified term grouped together with the descriptors of the specified term forming a variable region or variable window that is context sensitive and not of a fixed size; and identifies, through a finite state machine, a grammatical context shift in the context sensitive region pertaining to the specified term in the text data by analyzing the part of speech tags of the tagged information file, wherein the grammatical context shift is indicated by an autonomous transition of the finite state machine from a first state associated with a first part of speech tag of the tagged information file to a second state associated with a second part of speech tag of the tagged information file for parts of speech associated with words before and after the specified term; determining based on the determined grammatical context shift the one or more descriptors of the specified term; extracting the one or more descriptors of the specified term from the text data; and providing a report comprising the extracted one or more descriptors of the specified term. 17. The non-transitory computer readable medium of claim 14 , wherein the at least one information source is a URL. | 0.581035 |
1. A system comprising: a non-transitory storage medium comprising: a model generation module that generates a candidate model based on a discrepancy and a model template; and a model evaluation module that selectively updates a system model based on the candidate model. | 1. A system comprising: a non-transitory storage medium comprising: a model generation module that generates a candidate model based on a discrepancy and a model template; and a model evaluation module that selectively updates a system model based on the candidate model. 2. The system of claim 1 further comprising a monitoring module that evaluates log data and that determines at least one discrepancy between the log data and the system model. | 0.732865 |
1. A method comprising: receiving one or more seed sites that present information relating to a category of products or services, an individual seed site including a plurality of labeled text nodes identifying attributes targeted in association with data extraction for the category of products or services; extracting features from the plurality of labeled text nodes; learning, by a processor, category knowledge for the category of products or services based at least in part on the features extracted from the plurality of labeled text nodes, the category knowledge characterizing attribute-specific semantics of the plurality of labeled text nodes; receiving a new web site that presents information relating to the category of products or services; identifying, based on the category knowledge, one or more attributes on the new web site; and extracting one or more values from the one or more attributes identified. | 1. A method comprising: receiving one or more seed sites that present information relating to a category of products or services, an individual seed site including a plurality of labeled text nodes identifying attributes targeted in association with data extraction for the category of products or services; extracting features from the plurality of labeled text nodes; learning, by a processor, category knowledge for the category of products or services based at least in part on the features extracted from the plurality of labeled text nodes, the category knowledge characterizing attribute-specific semantics of the plurality of labeled text nodes; receiving a new web site that presents information relating to the category of products or services; identifying, based on the category knowledge, one or more attributes on the new web site; and extracting one or more values from the one or more attributes identified. 3. The method as recited in claim 1 , wherein the features extracted from the plurality of labeled text nodes include layout features comprising at least one of a Domain Object Model (DOM) path, a visual size, or a visual position. | 0.694234 |
18. The method according to claim 17 , wherein a plurality of the data field definitions of the data component is shared between the at least one message component and the at least one data component as represented by the mapping. | 18. The method according to claim 17 , wherein a plurality of the data field definitions of the data component is shared between the at least one message component and the at least one data component as represented by the mapping. 19. The method according to claim 18 further comprising the step of linking the plurality of data field definitions to corresponding ones of the message fields as represented by the unique identifier. | 0.895407 |
1. A speech processing apparatus, comprising: a segmenting unit configured to divide a fundamental frequency signal of a speech signal corresponding to an input text into a plurality of pitch segments, based on an alignment between samples of at least one given linguistic level included in the input text and the speech signal, wherein character strings of the input text are divided into the samples based on each linguistic level; a parameterizing unit configured to generate a parametric representation of the pitch segments by means of a predetermined invertible operator such as a linear transform, and generate a group of first parameters in correspondence with each linguistic level; a descriptor generating unit configured to generate, for each linguistic level, a descriptor that includes a set of features describing each sample in the input text; a model learning unit configured to classify the first parameters of each linguistic level of all speech signals in a memory into clusters based on the descriptor corresponding to the linguistic level, and learn, for each of the clusters, a pitch segment model for the linguistic level; and a storage unit configured to store the pitch segment models for each linguistic level together with mapping rules between the descriptors describing the features of the sample, for the linguistic level and the pitch segment models. | 1. A speech processing apparatus, comprising: a segmenting unit configured to divide a fundamental frequency signal of a speech signal corresponding to an input text into a plurality of pitch segments, based on an alignment between samples of at least one given linguistic level included in the input text and the speech signal, wherein character strings of the input text are divided into the samples based on each linguistic level; a parameterizing unit configured to generate a parametric representation of the pitch segments by means of a predetermined invertible operator such as a linear transform, and generate a group of first parameters in correspondence with each linguistic level; a descriptor generating unit configured to generate, for each linguistic level, a descriptor that includes a set of features describing each sample in the input text; a model learning unit configured to classify the first parameters of each linguistic level of all speech signals in a memory into clusters based on the descriptor corresponding to the linguistic level, and learn, for each of the clusters, a pitch segment model for the linguistic level; and a storage unit configured to store the pitch segment models for each linguistic level together with mapping rules between the descriptors describing the features of the sample, for the linguistic level and the pitch segment models. 2. The apparatus according to claim 1 , wherein the segmenting unit further comprises: a re-sampling unit configured to extract, from the fundamental frequency, a plurality of pitch frequencies that match a predetermined condition, an interpolating unit configured to perform an interpolation of the pitch frequencies extracted by the re-sampling unit and smooth the fundamental frequency to obtain an interpolated pitch contour, wherein the segmenting unit divides the interpolated pitch contour into the pitch segments that correspond to the linguistic level. | 0.585796 |
1. A method in a computing system for facilitating providing augmented information, comprising: receiving one or more previously generated query templates, each previously generated query template including a relationship query specification that specifies a relationship query that includes an input specification and an output presentation specification as part of the relationship query; storing the received one or more query templates in a data repository; in response to receiving an indication of an entity, an entity type, or a link that triggers a match of one or more query templates, retrieving one or more of the matching query templates from the data repository; and for each of the retrieved one or more matching query templates, causing a user interface to be presented to obtain user input based upon the input specification of the relationship query specified by the relationship query specification and supplying the obtained user input to the matching query template; for each of the retrieved one or more matching query templates, automatically invoking the retrieved query template to cause the relationship query specified by the relationship query specification of the retrieved query template to be executed using the obtained user input according to the relationship query specification, and presenting search results according to the output presentation specification of the relationship query specified by the relationship query specification of the retrieved query template to provide information that augments the indicated entity in a manner specified by the query template. | 1. A method in a computing system for facilitating providing augmented information, comprising: receiving one or more previously generated query templates, each previously generated query template including a relationship query specification that specifies a relationship query that includes an input specification and an output presentation specification as part of the relationship query; storing the received one or more query templates in a data repository; in response to receiving an indication of an entity, an entity type, or a link that triggers a match of one or more query templates, retrieving one or more of the matching query templates from the data repository; and for each of the retrieved one or more matching query templates, causing a user interface to be presented to obtain user input based upon the input specification of the relationship query specified by the relationship query specification and supplying the obtained user input to the matching query template; for each of the retrieved one or more matching query templates, automatically invoking the retrieved query template to cause the relationship query specified by the relationship query specification of the retrieved query template to be executed using the obtained user input according to the relationship query specification, and presenting search results according to the output presentation specification of the relationship query specified by the relationship query specification of the retrieved query template to provide information that augments the indicated entity in a manner specified by the query template. 17. The method of claim 1 wherein at least some of the previously generated query templates include a description attribute that is presented to the user as part of the user interface. | 0.569862 |
6. The method according to claim 5, wherein said examining step comprises: checking, for each node in the document tree, whether descendants of the node are extendable into a legal sequence of descendants. | 6. The method according to claim 5, wherein said examining step comprises: checking, for each node in the document tree, whether descendants of the node are extendable into a legal sequence of descendants. 7. The method according to claim 6, wherein each node is checked to determine whether the node matches a corresponding gap grammar. | 0.866516 |
14. The apparatus of claim 13 , further comprising a means for displaying the summary result and the another summary result in the SCCB format wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters. | 14. The apparatus of claim 13 , further comprising a means for displaying the summary result and the another summary result in the SCCB format wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters. 16. The apparatus of claim 14 , further comprising a means for delimiting the one or more category words or phrase with at least one field separator. | 0.878019 |
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