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1. A computer system for processing Chinese language text comprising: a computer memory; an input apparatus for entering a plurality of Chinese phonetic language syllables into the system, each syllable having one or more characters, the input apparatus marking one or more of the accented syllables with diacritic that indicates a tone of the accented syllable; an input unit that provides a character code for each character and a tone code for each diacritic entered by the input apparatus, the input unit recognizing a syllable as a string of character codes marked by tone code; a syllable list having a plurality of syllable strings, each syllable string being associated with one or more syllable string codes, the input unit matching the string of character codes marked by the diacritic code to one of the syllable string codes and storing in the computer memory a syllable representation for the syllable string associated with the syllable string code that matches the string of character codes marked by the tone code.
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1. A computer system for processing Chinese language text comprising: a computer memory; an input apparatus for entering a plurality of Chinese phonetic language syllables into the system, each syllable having one or more characters, the input apparatus marking one or more of the accented syllables with diacritic that indicates a tone of the accented syllable; an input unit that provides a character code for each character and a tone code for each diacritic entered by the input apparatus, the input unit recognizing a syllable as a string of character codes marked by tone code; a syllable list having a plurality of syllable strings, each syllable string being associated with one or more syllable string codes, the input unit matching the string of character codes marked by the diacritic code to one of the syllable string codes and storing in the computer memory a syllable representation for the syllable string associated with the syllable string code that matches the string of character codes marked by the tone code. 10. A system, as in claim 1, where the input unit recognizes the string of character codes as a non Chinese syllable where the string of character codes is unmarked by a tone code.
| 0.763089 |
1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries.
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1. A system, comprising: a processing device; and a memory device in communication with the processing device, the memory device storing instructions that when executed by the processing device result in: receiving a geographic location indicator associated with a plurality of geographic location-based rules stored in a database; monitoring a user input interface of an interactive user display for a user input string comprising a minimum number of characters; generating a suggestion request to retrieve a data set from the plurality of geographic location-based rules stored in the database that match the geographic location indicator and the user input string based on determining that the user input string includes at least the minimum number of characters, the geographic location-based rules constraining a plurality of numeric classification codes and corresponding descriptions based on the geographic location indicator, and a same numeric classification code having a different corresponding description defined by the geographic location-based rules; receiving the data set in response to the suggestion request; formatting the data set as a list comprising one or more entries, each of the entries comprising one of the numeric classification codes and one of the corresponding descriptions based on the geographic location indicator; and outputting the list on the interactive user display as one or more user selectable instances of the one or more entries. 2. The system of claim 1 , further comprising instructions that when executed by the processing device result in: determining a requested search type; and initiating a keyword search of description data associated with the geographic location indicator in the database as the suggestion request based on determining that the requested search type is a keyword search.
| 0.559965 |
1. A computer-implemented method comprising: normalizing a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filtering the normalized plurality of keywords against one or more keyword filtration lists; producing site-specific variants of the filtered plurality of keywords; associating a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; defining a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and storing the processed plurality of keywords and dimension data in a keyword database, and selecting at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database.
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1. A computer-implemented method comprising: normalizing a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filtering the normalized plurality of keywords against one or more keyword filtration lists; producing site-specific variants of the filtered plurality of keywords; associating a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; defining a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and storing the processed plurality of keywords and dimension data in a keyword database, and selecting at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database. 2. The method as claimed in claim 1 wherein the one or more keyword filtration lists includes a blacklist.
| 0.866915 |
1. A method of identifying electronic text messages as spam, the method comprising: (a) creating a hierarchic list of spam message categories and sub-categories, wherein the hierarchic list defines properties of key terms within the spam message categories and sub-categories; (b) composing a database of the key terms and a database of sample messages in a human language for each of the spam message categories and message templates for sub-categories, wherein the key terms are identified using human language-specific variants of a combination of separate words in a particular human language; (c) defining at least one spam message category from the hierarchic list of the spam message categories for which (i) a weight factor of a morphologically transformed text message exceeds a first pre-determined threshold or (ii) a similarity score of the text message exceeds a second pre-determined threshold, wherein the weight factor value and the similarity score value are compared against the respective threshold values using a precise matching comparison; and (d) associating with the at least one spam message category the text message having (i) the weight factor value exceeding the first threshold or (ii) the similarity score value exceeding the second threshold, wherein the properties of the key terms within the spam message categories are any of: a frequency of occurrence of the key term within the message; a location of the key term within the message; and a number of separate words in the key term.
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1. A method of identifying electronic text messages as spam, the method comprising: (a) creating a hierarchic list of spam message categories and sub-categories, wherein the hierarchic list defines properties of key terms within the spam message categories and sub-categories; (b) composing a database of the key terms and a database of sample messages in a human language for each of the spam message categories and message templates for sub-categories, wherein the key terms are identified using human language-specific variants of a combination of separate words in a particular human language; (c) defining at least one spam message category from the hierarchic list of the spam message categories for which (i) a weight factor of a morphologically transformed text message exceeds a first pre-determined threshold or (ii) a similarity score of the text message exceeds a second pre-determined threshold, wherein the weight factor value and the similarity score value are compared against the respective threshold values using a precise matching comparison; and (d) associating with the at least one spam message category the text message having (i) the weight factor value exceeding the first threshold or (ii) the similarity score value exceeding the second threshold, wherein the properties of the key terms within the spam message categories are any of: a frequency of occurrence of the key term within the message; a location of the key term within the message; and a number of separate words in the key term. 4. The method of claim 1 , wherein each of the key terms comprises at least one separate word in a particular human language.
| 0.600111 |
3. The computer-implemented method of claim 1 , wherein calculating the first recency score comprises: determining a time associated with the first segment; and applying a decay function to the time to determine the first recency score.
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3. The computer-implemented method of claim 1 , wherein calculating the first recency score comprises: determining a time associated with the first segment; and applying a decay function to the time to determine the first recency score. 4. The computer-implemented method of claim 3 , further comprising: determining a quantity of temporal words within the first segment; and determining a second recency score by adjusting the first recency score based on the quantity of temporal words, wherein the ranking is further based at least on the second recency score.
| 0.922879 |
11. The system of claim 10 , wherein if the name assigned to the data does not appear in the one or more normalized labels, then the lexical name matching component compares the name to a list of synonyms generated for each of the one or more normalized labels, and if the name appears in the list of synonyms, then the one or more normalized labels corresponding with the list of synonyms is added to the list of suggested labels for the data.
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11. The system of claim 10 , wherein if the name assigned to the data does not appear in the one or more normalized labels, then the lexical name matching component compares the name to a list of synonyms generated for each of the one or more normalized labels, and if the name appears in the list of synonyms, then the one or more normalized labels corresponding with the list of synonyms is added to the list of suggested labels for the data. 12. The system of claim 11 , wherein the taxonomy component assigns the one or more normalized labels to the data which are assets of the enterprise system, and the one or more normalized labels are business terms that are organized in a controlled vocabulary and are organized into one or more hierarchies.
| 0.900124 |
17. A data processing system for managing information about a multi-step process in disparate knowledge repositories, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to collect practice requirements for the multi-step process, wherein the practice requirements comprise procedure information for performing tasks in the multi-step process, and wherein the procedure information specifies a particular execution order of the tasks in the multi-step process; and create a process metadata data structure in a metadata repository comprising process information that conforms to the practice requirements, wherein the computer usable code to create a process metadata data structure further comprises creating a template document for each task in the multi-step process; populating the template documents with the procedure information in the practice requirements; creating hierarchical and horizontal associations among the template documents based on the execution order of the tasks in the procedure information; creating a process document for each task in the multi-step process; populating the process documents with information about the tasks; and storing the task information, procedure information, and association information for each task as metadata in the process metadata structure.
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17. A data processing system for managing information about a multi-step process in disparate knowledge repositories, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to collect practice requirements for the multi-step process, wherein the practice requirements comprise procedure information for performing tasks in the multi-step process, and wherein the procedure information specifies a particular execution order of the tasks in the multi-step process; and create a process metadata data structure in a metadata repository comprising process information that conforms to the practice requirements, wherein the computer usable code to create a process metadata data structure further comprises creating a template document for each task in the multi-step process; populating the template documents with the procedure information in the practice requirements; creating hierarchical and horizontal associations among the template documents based on the execution order of the tasks in the procedure information; creating a process document for each task in the multi-step process; populating the process documents with information about the tasks; and storing the task information, procedure information, and association information for each task as metadata in the process metadata structure. 18. The data processing system of claim 17 , wherein the tasks in the multi-step process are components comprising an information technology solution.
| 0.631505 |
7. The method of claim 6 wherein the extracted features are derived from recognition, understanding and dialog data.
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7. The method of claim 6 wherein the extracted features are derived from recognition, understanding and dialog data. 8. The method of claim 7 , further comprising storing a first dialog exchange in a dialog history database, wherein the first dialog exchange includes a first automated dialog output and the user's first input communication and the further dialog conducted with the user includes a second dialog exchange which includes a second dialog output and the user's second input communication; and determining whether the probability of understanding exceeds the first threshold using the first dialog exchange and the second dialog exchange.
| 0.699776 |
11. A development system for automatically deploying objects into a networked display, comprising: a processor; and a memory, wherein said processor is operative to execute a deployment engine in said memory, said deployment engine being operative to: receive an object for deployment thereof as a client-side rendered component from at a networked portal system, said object having a name and a class, and after said receiving of said object having said name and said class: (i) automatically incorporate said name and said class in a markup language document, (ii) automatically create a view component that enables an embedding of said object in a portal iView, said object being displayable by a browser in said portal iView; and (iii) thereafter automatically transmit said object, said markup language document, and said view component to a server where the view component is registered into a portal as client-side rendered components.
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11. A development system for automatically deploying objects into a networked display, comprising: a processor; and a memory, wherein said processor is operative to execute a deployment engine in said memory, said deployment engine being operative to: receive an object for deployment thereof as a client-side rendered component from at a networked portal system, said object having a name and a class, and after said receiving of said object having said name and said class: (i) automatically incorporate said name and said class in a markup language document, (ii) automatically create a view component that enables an embedding of said object in a portal iView, said object being displayable by a browser in said portal iView; and (iii) thereafter automatically transmit said object, said markup language document, and said view component to a server where the view component is registered into a portal as client-side rendered components. 12. The development system according to claim 11 , wherein said deployment engine is operative to wrap said object prior to a transmission of said object.
| 0.534184 |
9. A method for extracting the structure of song lyrics using a repeated pattern of the song lyrics, the method comprising: extracting lyric information from metadata contained in an audio file stored in a memory; extracting an interlude section and a repeated character string based on the extracted lyric information by a character string information extractor; extracting a paragraph based on the repeated character string by a paragraph extractor; extracting a set of paragraphs having the same repeated pattern among the extracted paragraph by the paragraph extractors; arranging interlude sections, character strings, and paragraphs related to the audio file in a tree structure; extracting a portion of the audio file based on the tree structure; and outputting the extracted portion of the audio file on an audio playing device.
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9. A method for extracting the structure of song lyrics using a repeated pattern of the song lyrics, the method comprising: extracting lyric information from metadata contained in an audio file stored in a memory; extracting an interlude section and a repeated character string based on the extracted lyric information by a character string information extractor; extracting a paragraph based on the repeated character string by a paragraph extractor; extracting a set of paragraphs having the same repeated pattern among the extracted paragraph by the paragraph extractors; arranging interlude sections, character strings, and paragraphs related to the audio file in a tree structure; extracting a portion of the audio file based on the tree structure; and outputting the extracted portion of the audio file on an audio playing device. 12. The method of claim 9 , further comprising performing preprocessing by the preprocessor to delete supplementary information contained in the extracted lyric information.
| 0.737075 |
15. The computer-implemented method of claim 6 , further comprising: determining that a default value is to be associated with the data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas.
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15. The computer-implemented method of claim 6 , further comprising: determining that a default value is to be associated with the data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas. 16. The computer-implemented method of claim 15 , further comprising: in response to determining that a default value is to be associated with the data entry field of the selected data entry field type placed onto the first canvas page of the electronic canvas, adding the default value in the second record.
| 0.940997 |
9. The computer program product of claim 8 , wherein handling of the subset of the plurality of string queries when operating in the training mode further comprises: computer usable program code configured to receive a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; computer usable program code configured to select a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; computer usable program code configured to execute the selected string analysis algorithm upon the string query of the subset; computer usable program code configured to convey results of the execution of the selected string analysis algorithm to the client application; computer usable program code configured to receive selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and computer usable program code configured to, when the received selection feedback indicates an unsatisfactory selection of the string analysis algorithm, automatically modify the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy.
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9. The computer program product of claim 8 , wherein handling of the subset of the plurality of string queries when operating in the training mode further comprises: computer usable program code configured to receive a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; computer usable program code configured to select a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; computer usable program code configured to execute the selected string analysis algorithm upon the string query of the subset; computer usable program code configured to convey results of the execution of the selected string analysis algorithm to the client application; computer usable program code configured to receive selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and computer usable program code configured to, when the received selection feedback indicates an unsatisfactory selection of the string analysis algorithm, automatically modify the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy. 10. The computer program product of claim 9 , wherein selecting of the string analysis algorithm further comprises: computer usable program code configured to analyze the plurality of contextual metadata associated with the string query of the subset; computer usable program code configured to identify at least one string analysis algorithm from the plurality of string analysis algorithms applicable to at least one of the analysis of the plurality of contextual metadata and the string query of the subset; and computer usable program code configured to, when multiple string analysis algorithms are identified, order the multiple string analysis algorithms by effectiveness to address the received query request as determined by the heuristic strategy, wherein the string analysis algorithm ordered as having a highest effectiveness is considered to best address the string query of the subset.
| 0.766965 |
19. The non-transitory computer-readable medium of claim 18 , wherein the frames comprise a nested structure.
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19. The non-transitory computer-readable medium of claim 18 , wherein the frames comprise a nested structure. 20. The non-transitory computer-readable medium of claim 19 , wherein the nested structure comprises dimension values for at least two different dimensions.
| 0.955104 |
4. A method for producing an electronic literary macramé of texts from a literary work, comprising the steps of: breaking the literary work down into scene text files and reference text files; establishing a set of reference hypertext files derived from the reference text files; establishing a set of scene hypertext files by linking among scene text files of the literary work and by linking the scene hypertext files to the reference hypertext files; linking the reference hypertext files back to the scene hypertext files of the work and linking the reference hypertext files among and within themselves; constructing an augmented term link list containing the author's term, the name of the anchor to which it will link, the form of the author's term to be displayed where the link is placed, the name of the file in which the anchor resides, the area in which the reference will be displayed, and any formatting information needed for the reference display modifying the augmented term link list to eliminate unwanted references, change file names, or adjust other values and entries; executing a generating program script of the invention to create a link installation script containing file modification editing instructions for inserting hypertext links wherever text references to items in the term link list appear; applying the link installation script to each scene text file; applying the link installation script to each reference file.
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4. A method for producing an electronic literary macramé of texts from a literary work, comprising the steps of: breaking the literary work down into scene text files and reference text files; establishing a set of reference hypertext files derived from the reference text files; establishing a set of scene hypertext files by linking among scene text files of the literary work and by linking the scene hypertext files to the reference hypertext files; linking the reference hypertext files back to the scene hypertext files of the work and linking the reference hypertext files among and within themselves; constructing an augmented term link list containing the author's term, the name of the anchor to which it will link, the form of the author's term to be displayed where the link is placed, the name of the file in which the anchor resides, the area in which the reference will be displayed, and any formatting information needed for the reference display modifying the augmented term link list to eliminate unwanted references, change file names, or adjust other values and entries; executing a generating program script of the invention to create a link installation script containing file modification editing instructions for inserting hypertext links wherever text references to items in the term link list appear; applying the link installation script to each scene text file; applying the link installation script to each reference file. 5. The method of claim 4 wherein the step of applying the scene link installation script to each scene text file further comprises the steps of: scene link installation script inserting links at points within each scene text file to anchors in the files of reference materials by the use of scripts containing all author's terms for which anchors have been created in the reference files; locating in each scene text file every occurrence of every such author's term and replace the term in the scene text file with the link to that term's anchor in a reference file, leaving the appearance of the term in the scene text file intact, and producing a linked scene text file; locating in each reference file every occurrence of every such author's term and replace the term in the reference file with the link to that term's anchor in a reference file, leaving the appearance of the term in the reference file intact, and producing a linked reference file.
| 0.655338 |
1. A method of communicating between a plurality of navigation devices comprising: obtaining positional information for a first navigation device by assessing a plurality of global positioning satellite signals; generating a data signal for transmission to a plurality of other devices, the data signal including a latitude value obtained from the positional information for the first navigation device, a longitude value obtained from the positional information for the first navigation device, and an identification of the first navigation device; transmitting the data signal to a communication device through a signal cable, wherein the communication device is separate from the first navigation device; and transmitting the data signal, utilizing the communication device, to a plurality of other navigation devices such that each of the plurality of navigation devices can identify and display a geographic position of the first navigation device.
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1. A method of communicating between a plurality of navigation devices comprising: obtaining positional information for a first navigation device by assessing a plurality of global positioning satellite signals; generating a data signal for transmission to a plurality of other devices, the data signal including a latitude value obtained from the positional information for the first navigation device, a longitude value obtained from the positional information for the first navigation device, and an identification of the first navigation device; transmitting the data signal to a communication device through a signal cable, wherein the communication device is separate from the first navigation device; and transmitting the data signal, utilizing the communication device, to a plurality of other navigation devices such that each of the plurality of navigation devices can identify and display a geographic position of the first navigation device. 3. The method of claim 1 wherein the data signal further comprises: a course bearing; an altitude value; a speed value; and a waypoint name.
| 0.937222 |
13. A method for managing active fonts on a computer system, comprising: receiving, by a computing system, input requesting activation of a first font for rendering a first portion of an electronic document; receiving, by the computing system, input requesting activation of a second font for rendering a second portion of the electronic document; determining, by the computing system, that the first font and the second font do not exist in a font management vault; upon determining that the first font does not exist in the font management vault, identifying the first font in a first multi-font suitcase file of a first plurality of multi-font suitcase files, each multi-font suitcase file of the first plurality including a similarly named version of the first font, separating the first font from the first multi-font suitcase file, and saving the separated first font in the font management vault; and upon determining that the second font does not exist in the font management vault, identifying the second font in a second multi-font suitcase file, separating the second font from the second multi-font suitcase file, and saving the separated second font in the font management vault.
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13. A method for managing active fonts on a computer system, comprising: receiving, by a computing system, input requesting activation of a first font for rendering a first portion of an electronic document; receiving, by the computing system, input requesting activation of a second font for rendering a second portion of the electronic document; determining, by the computing system, that the first font and the second font do not exist in a font management vault; upon determining that the first font does not exist in the font management vault, identifying the first font in a first multi-font suitcase file of a first plurality of multi-font suitcase files, each multi-font suitcase file of the first plurality including a similarly named version of the first font, separating the first font from the first multi-font suitcase file, and saving the separated first font in the font management vault; and upon determining that the second font does not exist in the font management vault, identifying the second font in a second multi-font suitcase file, separating the second font from the second multi-font suitcase file, and saving the separated second font in the font management vault. 14. A method for managing active fonts according to claim 13 , further comprising: activating the first font and the second font from the font management vault.
| 0.663381 |
8. An apparatus for handling a query directed toward structured and unstructured data, the apparatus comprising: a processor configured to (1) execute relational engine software and (2) execute coprocessor interface software, wherein the relational engine software is configured to (1) apply a portion of a query that is directed toward structured data to a relational database to thereby identify a subset of unstructured data, and (2) invoke the coprocessor interface software upon encountering a portion of the query that is directed toward unstructured data, and wherein the coprocessor interface software is configured to invoke a coprocessor to perform a query-specified data processing operation on the identified subset of unstructured data.
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8. An apparatus for handling a query directed toward structured and unstructured data, the apparatus comprising: a processor configured to (1) execute relational engine software and (2) execute coprocessor interface software, wherein the relational engine software is configured to (1) apply a portion of a query that is directed toward structured data to a relational database to thereby identify a subset of unstructured data, and (2) invoke the coprocessor interface software upon encountering a portion of the query that is directed toward unstructured data, and wherein the coprocessor interface software is configured to invoke a coprocessor to perform a query-specified data processing operation on the identified subset of unstructured data. 9. The apparatus of claim 8 wherein the coprocessor interface software is further configured to pass data to the coprocessor to thereby enable the coprocessor to perform the query-specified data processing operation on the identified subset of unstructured data.
| 0.5 |
1. A method for displaying an electronic document, the method comprising: receiving an electronic document; displaying a current page of the electronic document on a screen of a handheld device operated by a user; and displaying an adjacent page of the electronic document on a display that is external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document.
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1. A method for displaying an electronic document, the method comprising: receiving an electronic document; displaying a current page of the electronic document on a screen of a handheld device operated by a user; and displaying an adjacent page of the electronic document on a display that is external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document. 4. The method of claim 1 , wherein the user input comprises a stroking action on the screen.
| 0.883166 |
1. A method of analyzing a context free grammar for a speech system during authoring of the context free grammar, comprising: authoring at least a portion of the context free grammar; loading the authored context free grammar into a grammar analyzer having a plurality of static analysis components each capable of identifying a different class of grammar defects, wherein at least one of the classes is related to identifying defects related to speech recognition and at least one of the classes is related to identifying defects related to something other than speech recognition; intermittently, while authoring the context free grammar, selecting one of the plurality of accessible static analysis components; running the selected static analysis component on the context free grammar to identify specific defects in the context free grammar of the class associated with the selected static analysis component wherein the selected static analysis component identifies over-generation defects in the context free grammar by selecting each text fragment allowed by the context free grammar, calculating a language model score for the selected text fragment with a language model to determine whether the selected text fragment is likely to be used by a user based on the language model score; and if not, generating an output indicative of a possibility that an unusual text fragment, allowed by the context free grammar, has been identified; and repeating the steps of selecting and running for each desired static analysis component.
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1. A method of analyzing a context free grammar for a speech system during authoring of the context free grammar, comprising: authoring at least a portion of the context free grammar; loading the authored context free grammar into a grammar analyzer having a plurality of static analysis components each capable of identifying a different class of grammar defects, wherein at least one of the classes is related to identifying defects related to speech recognition and at least one of the classes is related to identifying defects related to something other than speech recognition; intermittently, while authoring the context free grammar, selecting one of the plurality of accessible static analysis components; running the selected static analysis component on the context free grammar to identify specific defects in the context free grammar of the class associated with the selected static analysis component wherein the selected static analysis component identifies over-generation defects in the context free grammar by selecting each text fragment allowed by the context free grammar, calculating a language model score for the selected text fragment with a language model to determine whether the selected text fragment is likely to be used by a user based on the language model score; and if not, generating an output indicative of a possibility that an unusual text fragment, allowed by the context free grammar, has been identified; and repeating the steps of selecting and running for each desired static analysis component. 4. The method of claim 1 wherein the selected static analysis component identifies acoustically confusable tokens in the context free grammar.
| 0.555234 |
7. The method of claim 1 , further comprising: extracting a first candidate value of a first attribute of a first instance from a first electronic document; extracting a second candidate value of the first attribute of the first instance from a second electronic document; determining a first likelihood that the first candidate value correctly characterizes the first attribute of the first instance; determining a second likelihood that the second candidate value correctly characterizes the first attribute of the first instance; determining that the first likelihood is higher than the second likelihood; and establishing, in response to determining that the first likelihood is higher than the second likelihood, the first candidate value rather than the second candidate value as characterizing the first instance in the structured data collection.
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7. The method of claim 1 , further comprising: extracting a first candidate value of a first attribute of a first instance from a first electronic document; extracting a second candidate value of the first attribute of the first instance from a second electronic document; determining a first likelihood that the first candidate value correctly characterizes the first attribute of the first instance; determining a second likelihood that the second candidate value correctly characterizes the first attribute of the first instance; determining that the first likelihood is higher than the second likelihood; and establishing, in response to determining that the first likelihood is higher than the second likelihood, the first candidate value rather than the second candidate value as characterizing the first instance in the structured data collection. 9. The method of claim 7 , where the first likelihood and the second likelihood are determined based on quality of documents from which the respective candidate value is used to characterize the respective attribute of the respective instance.
| 0.88403 |
4. A method according to claim 1 , wherein said classifying uses said preferred classifier in conjunction with available partial information regarding correspondence between electronic document instances and the plurality of classes.
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4. A method according to claim 1 , wherein said classifying uses said preferred classifier in conjunction with available partial information regarding correspondence between electronic document instances and the plurality of classes. 5. A method according to claim 4 , wherein said partial information includes information read from an electronic document instance's machine readable zone.
| 0.930247 |
17. The method according to claim 16 , wherein said tracts and initiatives are embodied in a learning blueprint, said blueprint assisting in identifying learning effort approaches to meet said requests.
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17. The method according to claim 16 , wherein said tracts and initiatives are embodied in a learning blueprint, said blueprint assisting in identifying learning effort approaches to meet said requests. 19. The method according to claim 17 , wherein said learning blueprint is revised as necessary to reflect significant changes in said business goals, strategies, and priorities.
| 0.946707 |
19. A computer system comprising: a non-transitory computer-readable storage medium comprising instructions; one or more processors configured to execute the instructions to perform operations comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema.
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19. A computer system comprising: a non-transitory computer-readable storage medium comprising instructions; one or more processors configured to execute the instructions to perform operations comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. 24. The system of claim 19 , wherein the operations further comprise: presenting the mapping of the at least one of the first data element definitions in the first schema to the corresponding one of the second data element definitions in the second schema to a user as a suggestion which the user can at least accept or reject; and receiving user input that the user accepts the presented mapping; wherein the mapping of the at least one of the first data element definitions in the first schema to the corresponding one of the second data element definitions in the second schema is performed in response to receiving the user input.
| 0.504315 |
10. The system of claim 9 , further comprising: means for preprocessing a plurality of initial documents; and means for computing a data model representing the plurality of initial documents; and wherein the document vector for the document is compared to at least document vector for the data model to determine the similarity of the document to the documents forming the data model.
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10. The system of claim 9 , further comprising: means for preprocessing a plurality of initial documents; and means for computing a data model representing the plurality of initial documents; and wherein the document vector for the document is compared to at least document vector for the data model to determine the similarity of the document to the documents forming the data model. 11. The system of claim 10 , wherein the document vector for the document is compared to a document vector for the data model without updating the data model until a second plurality of documents have been received and processed by the computer.
| 0.863669 |
4. The method of claim 1 , wherein optimizing the persuasiveness of communications further comprises: generating a script.
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4. The method of claim 1 , wherein optimizing the persuasiveness of communications further comprises: generating a script. 5. The method of claim 4 , wherein the script is generated based on borrower behavioral information.
| 0.943918 |
1. A system comprising: a non-transitory memory storing instructions; a processor configured to execute the instructions to cause a system to: retrieve, by a social graph module, social data of a subject user, the social data including entities that have a relationship with the subject user based on one or more interactions by the subject user with a plurality of social network services; analyze, by the social graph module, the social data retrieved and generate a social graph based in part on the social data analyzed, the social graph comprising a plurality of nodes, the plurality of nodes including a focal node representing the subject user, a remainder of the plurality of nodes each representing one or more objects having the relationship with the subject user, the one or more objects corresponding to the entities that have a relationship with the subject user; learn, by a relevance module, a social routine of the subject user using the interactions by the subject user with the remainder of the plurality of nodes; calculate, by the relevance module, a relevance score for each node of the remainder of the plurality of nodes, the relevance score for a given node being an indicator of an amount or frequency of interaction between the subject user and the given node, wherein the relevance score is based at least in part on at least one of: a frequency with which the subject user accesses a social network account, a frequency with which the subject user uses a particular application, a frequency with which the subject user interacts with members of the plurality of social network services, and a frequency with which the subject user interacts with the entities that have a relationship with the subject user; determine, by the relevance module, that a particular node lacks relevance to the subject user based on the particular node being associated with a particular relevance score having a value below a predefined threshold; and eliminate, by the elimination module, the relationship of the subject user with the particular node in response to determining that the particular node lacks relevance to the subject user, based on the particular relevance score having a value below the predefined threshold, where the particular node is removed from the social graph to create a maintained social graph.
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1. A system comprising: a non-transitory memory storing instructions; a processor configured to execute the instructions to cause a system to: retrieve, by a social graph module, social data of a subject user, the social data including entities that have a relationship with the subject user based on one or more interactions by the subject user with a plurality of social network services; analyze, by the social graph module, the social data retrieved and generate a social graph based in part on the social data analyzed, the social graph comprising a plurality of nodes, the plurality of nodes including a focal node representing the subject user, a remainder of the plurality of nodes each representing one or more objects having the relationship with the subject user, the one or more objects corresponding to the entities that have a relationship with the subject user; learn, by a relevance module, a social routine of the subject user using the interactions by the subject user with the remainder of the plurality of nodes; calculate, by the relevance module, a relevance score for each node of the remainder of the plurality of nodes, the relevance score for a given node being an indicator of an amount or frequency of interaction between the subject user and the given node, wherein the relevance score is based at least in part on at least one of: a frequency with which the subject user accesses a social network account, a frequency with which the subject user uses a particular application, a frequency with which the subject user interacts with members of the plurality of social network services, and a frequency with which the subject user interacts with the entities that have a relationship with the subject user; determine, by the relevance module, that a particular node lacks relevance to the subject user based on the particular node being associated with a particular relevance score having a value below a predefined threshold; and eliminate, by the elimination module, the relationship of the subject user with the particular node in response to determining that the particular node lacks relevance to the subject user, based on the particular relevance score having a value below the predefined threshold, where the particular node is removed from the social graph to create a maintained social graph. 3. The system of claim 1 , wherein the social graph is obtained from a social network service.
| 0.619097 |
6. A method as claimed in claim 1, characterised in that only the names of sub-categories are displayed which have been determined to have a relevance with respect to the selected category that is above a predetermined threshold.
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6. A method as claimed in claim 1, characterised in that only the names of sub-categories are displayed which have been determined to have a relevance with respect to the selected category that is above a predetermined threshold. 7. A method as claimed in claim 6, characterised in that the user is offered the option of modifying the predetermined threshold in order to modify the number of displayed names of sub-categories.
| 0.929035 |
8. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: comparing a transcription of a media presentation to a list of anchor word candidates to identify a pair of anchor words separated from one another within the media presentation by a time greater than an anchor word time duration requirement; and generating captions by aligning the transcription with an automatic speech recognition output of the media presentation according to the pair of anchor words.
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8. A system comprising: a processor; and a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising: comparing a transcription of a media presentation to a list of anchor word candidates to identify a pair of anchor words separated from one another within the media presentation by a time greater than an anchor word time duration requirement; and generating captions by aligning the transcription with an automatic speech recognition output of the media presentation according to the pair of anchor words. 9. The system of claim 8 , wherein the list of anchor word candidates further comprises a stop word list of words not to be considered as the pair of anchor words.
| 0.734727 |
15. A method to classify a multimedia content, comprising: processing, by one or more processing devices, the multimedia content to provide text for an analysis of the multimedia content; analyzing, by the one or more processing devices, the multimedia content for predetermined parameters, wherein at least one of the predetermined parameters is based on image media content; generating, by the one or more processing devices, a tag that encapsulates at least one of the predetermined parameters; associating, by the one or more processing devices, the tag with the text to provide one or more tokens; and mapping, by the one or more processing devices, the one or more tokens into a vector space containing a first plurality of vectors at a first location, and a second plurality of vectors at a second location, wherein the first location comprises materials related to predefined legitimate multimedia content, the second location comprises materials related to predefined explicit multimedia content, and wherein the one or more tokens are mapped into a third location in the vector space; determining by the one or more processing devices distances between the third location and the first location, and the third location and the second location; and determining, by the one or more processing devices, whether to filter the multimedia content based on the distances.
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15. A method to classify a multimedia content, comprising: processing, by one or more processing devices, the multimedia content to provide text for an analysis of the multimedia content; analyzing, by the one or more processing devices, the multimedia content for predetermined parameters, wherein at least one of the predetermined parameters is based on image media content; generating, by the one or more processing devices, a tag that encapsulates at least one of the predetermined parameters; associating, by the one or more processing devices, the tag with the text to provide one or more tokens; and mapping, by the one or more processing devices, the one or more tokens into a vector space containing a first plurality of vectors at a first location, and a second plurality of vectors at a second location, wherein the first location comprises materials related to predefined legitimate multimedia content, the second location comprises materials related to predefined explicit multimedia content, and wherein the one or more tokens are mapped into a third location in the vector space; determining by the one or more processing devices distances between the third location and the first location, and the third location and the second location; and determining, by the one or more processing devices, whether to filter the multimedia content based on the distances. 18. The method of claim 15 , further including removing one or more stop words from the text.
| 0.595408 |
155. The method of claim 152 , further comprising: projecting a final size of the documents in each of the categories, once categorized across the whole data set.
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155. The method of claim 152 , further comprising: projecting a final size of the documents in each of the categories, once categorized across the whole data set. 156. The method of claim 155 , further comprising: assessing a possible overfitting of categorization mechanisms to a particular sample, based on the final size projection.
| 0.896044 |
1. A computer implemented method of dynamically generating cascading style sheets for a client application, comprising: providing a first style sheet containing a noncompliant function to a standard style sheet language according to W3C cascading style sheet specification; retrieving the first style sheet at a client from a server; extracting from the first style sheet the noncompliant function; executing the noncompliant function at the client to produce a function output wherein the noncompliant function transforms a noncompliant color value according to W3C cascading style sheet specification that is operating system specific into a standard style sheet language compliant color value according to W3C cascading style sheet specification; generating a second style sheet based on the first style sheet and the function output, wherein the second style sheet is compliant according to W3C cascading style sheet specification; and executing the second style sheet on a standard style sheet language compliant browser according to W3C cascading style sheet specification at the client.
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1. A computer implemented method of dynamically generating cascading style sheets for a client application, comprising: providing a first style sheet containing a noncompliant function to a standard style sheet language according to W3C cascading style sheet specification; retrieving the first style sheet at a client from a server; extracting from the first style sheet the noncompliant function; executing the noncompliant function at the client to produce a function output wherein the noncompliant function transforms a noncompliant color value according to W3C cascading style sheet specification that is operating system specific into a standard style sheet language compliant color value according to W3C cascading style sheet specification; generating a second style sheet based on the first style sheet and the function output, wherein the second style sheet is compliant according to W3C cascading style sheet specification; and executing the second style sheet on a standard style sheet language compliant browser according to W3C cascading style sheet specification at the client. 3. The method of claim 1 , wherein the noncompliant function provides a parameter of a cascading style sheet (CSS) compliant function.
| 0.82 |
1. A computer-implemented method, comprising: displaying an electronic document on a touch screen of an electronic device; defining a left region, a center region, and a right region associated with the touch screen, the center region located between the left region and the right region; associating with the left region a previous page command to display a previous page of the electronic document; associating with the right region a next page command to display a next page of the electronic document; associating with the center region a command to display or hide a control object; detecting a first touch input in the center region; displaying the control object based at least in part on the first touch input, the control object displayed with an opacity set to a last used opacity level; receiving, by the control object, a second touch input representing a swiping movement on the touch screen; and controlling, by a processor of the electronic device, a perceived visible brightness of the electronic document based at least in part on the second touch input by increasing or decreasing the opacity of the control object.
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1. A computer-implemented method, comprising: displaying an electronic document on a touch screen of an electronic device; defining a left region, a center region, and a right region associated with the touch screen, the center region located between the left region and the right region; associating with the left region a previous page command to display a previous page of the electronic document; associating with the right region a next page command to display a next page of the electronic document; associating with the center region a command to display or hide a control object; detecting a first touch input in the center region; displaying the control object based at least in part on the first touch input, the control object displayed with an opacity set to a last used opacity level; receiving, by the control object, a second touch input representing a swiping movement on the touch screen; and controlling, by a processor of the electronic device, a perceived visible brightness of the electronic document based at least in part on the second touch input by increasing or decreasing the opacity of the control object. 2. The computer-implemented method of claim 1 , wherein controlling the perceived visible brightness of the electronic document comprises: decreasing the perceived visible brightness of the electronic document by increasing the opacity of the control object.
| 0.594231 |
1. A method implemented by a computerized machine learning system, said method comprising: receiving, at the computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class.
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1. A method implemented by a computerized machine learning system, said method comprising: receiving, at the computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class. 4. The method of claim 1 , further comprising blocking examples associated with the second class from being distributed to a worker receiving only examples associated with the first class.
| 0.609636 |
1. A computer system for providing responses to requests, the system configured to deploy code to execute multiple commands and provide answers resulting from the commands, the computer system comprising: a broker; a router; a service pack store; and a service pack stored in the service pack store, the service pack including: a plurality of service worker modules, wherein at least two service worker modules are configured to process a request differently from each other; and a plurality of routes, each route associating a service worker module and a location; wherein the broker is configured to download the service pack from the service pack store, distribute the service worker modules to a plurality of locations, and store a command sequence corresponding to each route within the router; wherein the router is configured to receive a plurality of requests and distribute each request according to the command sequences; wherein the service worker modules are each configured to determine an answer based on each request; and wherein the router is configured to receive the answers for each request from the service worker modules and provide a response output for each request based on at least one of the answers.
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1. A computer system for providing responses to requests, the system configured to deploy code to execute multiple commands and provide answers resulting from the commands, the computer system comprising: a broker; a router; a service pack store; and a service pack stored in the service pack store, the service pack including: a plurality of service worker modules, wherein at least two service worker modules are configured to process a request differently from each other; and a plurality of routes, each route associating a service worker module and a location; wherein the broker is configured to download the service pack from the service pack store, distribute the service worker modules to a plurality of locations, and store a command sequence corresponding to each route within the router; wherein the router is configured to receive a plurality of requests and distribute each request according to the command sequences; wherein the service worker modules are each configured to determine an answer based on each request; and wherein the router is configured to receive the answers for each request from the service worker modules and provide a response output for each request based on at least one of the answers. 10. The computer system of claim 1 , wherein the broker includes a service monitor that manages active instance counts for all service worker modules deployed to a node.
| 0.552788 |
16. The electronic device of claim 10 wherein the input apparatus comprises a plurality of input members, and wherein the memory has stored therein a map file comprising an assignment of each character to a corresponding input member, and wherein the operations further comprise: detecting a press-and-hold actuation of a particular input member; and outputting at least a first character from the map file that is assigned to the particular input member and is in the inactive character set.
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16. The electronic device of claim 10 wherein the input apparatus comprises a plurality of input members, and wherein the memory has stored therein a map file comprising an assignment of each character to a corresponding input member, and wherein the operations further comprise: detecting a press-and-hold actuation of a particular input member; and outputting at least a first character from the map file that is assigned to the particular input member and is in the inactive character set. 18. The electronic device of claim 16 wherein the operations further comprise detecting as the input of the particular character an input of a character from the map file that is not already included in the active character set.
| 0.828986 |
10. A method of generating alternate translations for a statistical machine translation database through a game, the method comprising: providing a monolingual structure to a player; receiving a first translation attempt from the player; comparing, using a processor, the first translation attempt from the player to a reference translation; providing feedback to the player; and receiving and comparing attempts and providing feedback to iteratively converge subsequent translations from the player into a final translated structure.
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10. A method of generating alternate translations for a statistical machine translation database through a game, the method comprising: providing a monolingual structure to a player; receiving a first translation attempt from the player; comparing, using a processor, the first translation attempt from the player to a reference translation; providing feedback to the player; and receiving and comparing attempts and providing feedback to iteratively converge subsequent translations from the player into a final translated structure. 15. A method as recited in claim 10 , wherein the comparing includes determining a similarity score of a translation attempt of the player to the reference translation.
| 0.702081 |
5. The device of claim 1 , wherein the display further includes a first user-link, where selecting the link provides instructions to the display means.
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5. The device of claim 1 , wherein the display further includes a first user-link, where selecting the link provides instructions to the display means. 7. The device of claim 5 , wherein the instructions provided to the display means instruct the display means to display additional textual or graphical electronic program guide data.
| 0.940955 |
1. A method implemented in one or more data processing systems, comprising: receiving an input expression including a set of options joined using logical operators; converting the input expression into an order string; receiving at least one rule that defines relationships between variants of different option families; receiving a configuration expression, the configuration expression specifying values for some but not all variants of the option families; producing a conjunctive normal form (CNF) order expression corresponding to the order string, at least one rule, and configuration expression; and performing a partial solve of the order expression, the partial solve producing a result set that describes all possible configurations that correspond to the configuration expression.
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1. A method implemented in one or more data processing systems, comprising: receiving an input expression including a set of options joined using logical operators; converting the input expression into an order string; receiving at least one rule that defines relationships between variants of different option families; receiving a configuration expression, the configuration expression specifying values for some but not all variants of the option families; producing a conjunctive normal form (CNF) order expression corresponding to the order string, at least one rule, and configuration expression; and performing a partial solve of the order expression, the partial solve producing a result set that describes all possible configurations that correspond to the configuration expression. 4. The method of claim 1 , wherein producing the CNF order expression includes negating a Boolean expression, computing a disjunctive normal form (DNF) expression from the negated Boolean expression, and negating literals of the DNF expression to produce the CNF order expression.
| 0.558732 |
1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models.
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1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models. 29. The method according to claim 1 , wherein said step of personalizing an aspect of a service includes proposing to said user names or addresses of users with matching interests or profiles.
| 0.624555 |
15. A computer readable memory device including software that when executed by a processor is operable to: create a plurality of first models according to a second model including elements with information defining a structure and hierarchical arrangement of elements for the first models; associate elements of the second model with a presentation policy model including presentation policies, wherein the presentation policies indicate display characteristics controlling a visual appearance for presented elements; apply the presentation policies to the elements of the first models to generate a corresponding presentation model for each of the first models based on the association between the elements of the second model and the presentation policy model, wherein the corresponding presentation models provide different customized for the first models and corresponding model entities created from those first models, and wherein each presentation model associates each of one or more individual elements of a corresponding first model with one or more corresponding display characteristics controlling a visual appearance of a presented element; create a model entity according to a first model, wherein the model entity includes actual data pertaining to an entity and the first model includes elements with information defining a structure and hierarchical arrangement of elements for the model entity; read model content from said first model and read presentation data from said corresponding presentation model; and apply the read model content and presentation data to said model entity including the actual data to present elements of the model entity with a visual appearance in accordance with the associated display characteristics of corresponding individual elements of the first model, wherein at least two elements of the model entity are presented with different display characteristics within a presentation.
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15. A computer readable memory device including software that when executed by a processor is operable to: create a plurality of first models according to a second model including elements with information defining a structure and hierarchical arrangement of elements for the first models; associate elements of the second model with a presentation policy model including presentation policies, wherein the presentation policies indicate display characteristics controlling a visual appearance for presented elements; apply the presentation policies to the elements of the first models to generate a corresponding presentation model for each of the first models based on the association between the elements of the second model and the presentation policy model, wherein the corresponding presentation models provide different customized for the first models and corresponding model entities created from those first models, and wherein each presentation model associates each of one or more individual elements of a corresponding first model with one or more corresponding display characteristics controlling a visual appearance of a presented element; create a model entity according to a first model, wherein the model entity includes actual data pertaining to an entity and the first model includes elements with information defining a structure and hierarchical arrangement of elements for the model entity; read model content from said first model and read presentation data from said corresponding presentation model; and apply the read model content and presentation data to said model entity including the actual data to present elements of the model entity with a visual appearance in accordance with the associated display characteristics of corresponding individual elements of the first model, wherein at least two elements of the model entity are presented with different display characteristics within a presentation. 16. The memory device of claim 15 , wherein the software is further operable to: select a presentation policy from the presentation policy model.
| 0.585479 |
4. The method of claim 1 , further comprising: receiving feedback for at least one returned concept; and updating a weight between the identified node of each concept and the associated assertion in the assertion base based on the received feedback.
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4. The method of claim 1 , further comprising: receiving feedback for at least one returned concept; and updating a weight between the identified node of each concept and the associated assertion in the assertion base based on the received feedback. 5. The method of claim 4 , further comprising: upon determining that the weight between the at least one concept and the associated assertion falls below a predefined threshold, removing the association between the at least one concept and the associated assertion.
| 0.76036 |
16. An associative memory system according to claim 15 wherein the processing system further comprises: a task input system that is responsive to user queries and is configured to produce user-task IDs and query data therefrom; a parser that is responsive to the task input system and is configured to extract entities from the query data; and a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity query system, the document query system and the community query system.
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16. An associative memory system according to claim 15 wherein the processing system further comprises: a task input system that is responsive to user queries and is configured to produce user-task IDs and query data therefrom; a parser that is responsive to the task input system and is configured to extract entities from the query data; and a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity query system, the document query system and the community query system. 17. An associative memory system according to claim 16 wherein the processing system further comprises: a controller that is configured to control the task input system, the parser and the context generator according to a query itinerary; and a whiteboard that is configured to store intermediate results that are produced by the task input system, the parser and the context generator.
| 0.858386 |
5. A computer-implemented method, comprising: identifying a first language model configured for speech processing corresponding to multiple devices; identifying a first table representing words corresponding to the first language model; identifying a plurality of word strings associated with a first user profile; creating a second language model configured for speech processing corresponding to the plurality of word strings, the second language model including a plurality of references to a second table; generating a second table representing words of the plurality of word strings, the second table including at least: a first entry including a first word in the plurality of word strings and a first index value corresponding to a third entry in the first table, the third entry corresponding to the first word, and a second entry including a second word in the plurality of word strings and a second index value corresponding to a fourth entry in the first table, the fourth entry corresponding to the second word; generating a second language model configured for speech processing corresponding to the first user profile, the second language model including a third index value corresponding to the first entry and a fourth index value corresponding to the second entry; and storing the second table and the second language model as associated with the first user profile.
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5. A computer-implemented method, comprising: identifying a first language model configured for speech processing corresponding to multiple devices; identifying a first table representing words corresponding to the first language model; identifying a plurality of word strings associated with a first user profile; creating a second language model configured for speech processing corresponding to the plurality of word strings, the second language model including a plurality of references to a second table; generating a second table representing words of the plurality of word strings, the second table including at least: a first entry including a first word in the plurality of word strings and a first index value corresponding to a third entry in the first table, the third entry corresponding to the first word, and a second entry including a second word in the plurality of word strings and a second index value corresponding to a fourth entry in the first table, the fourth entry corresponding to the second word; generating a second language model configured for speech processing corresponding to the first user profile, the second language model including a third index value corresponding to the first entry and a fourth index value corresponding to the second entry; and storing the second table and the second language model as associated with the first user profile. 9. The computer-implemented method of claim 5 , further comprising: determining that a third word in the plurality of word strings is not represented in the first table; and performing grapheme-to-phoneme processing to determine pronunciation data representing an estimated pronunciation of the third word, wherein creating the second table further comprises creating a third entry including a reference to the pronunciation data.
| 0.682131 |
1. A computer program product, embodied in a computer-readable medium, the computer program product being operable to cause data processing apparatus to: a) receive, during a first time duration, a first electronic document being communicated between business entities, the first electronic document comprising instances of a plurality of business data elements, the first electronic document having a format corresponding to a business communication schema, wherein the business communication schema includes a set of predefined business data elements for use in electronically communicating business data from a first business entity to a second business entity; b) identify an instance of a particular business data element in the first electronic document; c) increment a counter associated with the particular business data element in response to identifying the instance of the particular business data element in the first electronic document; d) receive, during the first time duration, a second electronic document being communicated between business entities; e) identify an instance of the particular business data element in the second electronic document; f) increment the counter associated with the particular business data element in response to identifying the instance of the particular business data element in the second electronic document; g) subsequent to elapse of the first time duration, compare the counter with a threshold value; h) based on the counter being less than the threshold value, delete the particular business data element from the business communication schema; i) prior to deleting the particular business data element from the business communication schema, notify a user if the counter is less than the threshold value; j) receive an instruction from the user to remove the particular business data element from the business communication schema: k) reset the counter when the counter is at least equal to the threshold value; l) begin a second time duration upon resetting of the counter; and m) repeat operations b) through h) for a third electronic document being communicated between business entities during the second time duration.
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1. A computer program product, embodied in a computer-readable medium, the computer program product being operable to cause data processing apparatus to: a) receive, during a first time duration, a first electronic document being communicated between business entities, the first electronic document comprising instances of a plurality of business data elements, the first electronic document having a format corresponding to a business communication schema, wherein the business communication schema includes a set of predefined business data elements for use in electronically communicating business data from a first business entity to a second business entity; b) identify an instance of a particular business data element in the first electronic document; c) increment a counter associated with the particular business data element in response to identifying the instance of the particular business data element in the first electronic document; d) receive, during the first time duration, a second electronic document being communicated between business entities; e) identify an instance of the particular business data element in the second electronic document; f) increment the counter associated with the particular business data element in response to identifying the instance of the particular business data element in the second electronic document; g) subsequent to elapse of the first time duration, compare the counter with a threshold value; h) based on the counter being less than the threshold value, delete the particular business data element from the business communication schema; i) prior to deleting the particular business data element from the business communication schema, notify a user if the counter is less than the threshold value; j) receive an instruction from the user to remove the particular business data element from the business communication schema: k) reset the counter when the counter is at least equal to the threshold value; l) begin a second time duration upon resetting of the counter; and m) repeat operations b) through h) for a third electronic document being communicated between business entities during the second time duration. 11. The computer program product of claim 1 wherein the counter associated with the particular business data element is incremented only once in response to identifying more than one instance of the particular business data element.
| 0.626601 |
29. A computer program product comprising a non-transient computer-readable memory comprising computer-executable instructions for enterprise content management including integrating a plurality of applications and federating information, the instructions comprising: instructions for initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: receiving a request from a client system; and translating the request from the client system; and instructions for performing one or more high level validations; instructions for retrieving information from a mapping of a plurality of entities; and instructions for continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, wherein: at least one of the plurality of actions comprises at least one decision block, input or mapped process and where at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service.
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29. A computer program product comprising a non-transient computer-readable memory comprising computer-executable instructions for enterprise content management including integrating a plurality of applications and federating information, the instructions comprising: instructions for initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: receiving a request from a client system; and translating the request from the client system; and instructions for performing one or more high level validations; instructions for retrieving information from a mapping of a plurality of entities; and instructions for continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, wherein: at least one of the plurality of actions comprises at least one decision block, input or mapped process and where at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service. 35. The computer program product of claim 29 , wherein the plurality of attributes comprise one or more metadata models.
| 0.560338 |
10. A method for processing text comprising: converting speech to text; displaying to a user on a first text display a first sequence of text items, an active text item, and an active cursor position, wherein ones of the first sequence of text items is limited to a maximum number of text items, wherein the first active text item corresponds to one of the sequence of text items, and wherein the active cursor position is associated with either a displayed text item or a text boundary; displaying on a second text display a second sequence of text items and a second active text item, wherein the second sequence of text items includes the first sequence of text items, and wherein the second text display is synchronized with the first text display so that the first active text item and second active text item are the same; receiving input from a user control to adjust the first active text item and the active cursor position with the first sequence of text items; determining the first sequence of text items to display from the second sequence of text items based upon the active cursor position and the maximum number of text items, receiving new text from the speech recognition processor; determining if the active cursor position is an active text boundary or an active text item; if the active cursor position is an text boundary, inserting the new text between the displayed text items separated by the active text boundary; and if the active cursor position is an active text item, replacing a displayed text item with the new text, wherein the first and second text displays are text displays within an automobile passenger compartment, wherein the first text display is positioned directly in front of an automobile driver, and wherein the second text display is positioned to one side of the automobile driver.
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10. A method for processing text comprising: converting speech to text; displaying to a user on a first text display a first sequence of text items, an active text item, and an active cursor position, wherein ones of the first sequence of text items is limited to a maximum number of text items, wherein the first active text item corresponds to one of the sequence of text items, and wherein the active cursor position is associated with either a displayed text item or a text boundary; displaying on a second text display a second sequence of text items and a second active text item, wherein the second sequence of text items includes the first sequence of text items, and wherein the second text display is synchronized with the first text display so that the first active text item and second active text item are the same; receiving input from a user control to adjust the first active text item and the active cursor position with the first sequence of text items; determining the first sequence of text items to display from the second sequence of text items based upon the active cursor position and the maximum number of text items, receiving new text from the speech recognition processor; determining if the active cursor position is an active text boundary or an active text item; if the active cursor position is an text boundary, inserting the new text between the displayed text items separated by the active text boundary; and if the active cursor position is an active text item, replacing a displayed text item with the new text, wherein the first and second text displays are text displays within an automobile passenger compartment, wherein the first text display is positioned directly in front of an automobile driver, and wherein the second text display is positioned to one side of the automobile driver. 12. The method according to claim 10 , wherein the active cursor position is an active text boundary selected by a second user navigation operation changing the active cursor position after a first user navigation operation, the using navigation operations being in different directions.
| 0.64 |
26. A computer-implemented method comprising: detecting audio containing speech at a client device; encoding the detected audio as audio data; transmitting the audio data to a server system; identifying a docking context of the client device; transmitting information indicating the docking context to the server system; and receiving a transcription of at least a portion of the audio data at the client device, the server system having determined, for each of a plurality of language models, a weighting value based on the docking context, the weighting value indicating a probability that the language model will indicate a correct transcription for the encoded speech, selected at least one of the plurality of language models based on the weighting values, and generated the transcription by performing speech recognition on the audio data using the selected at least one language model, and transmitted the transcription to the client device.
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26. A computer-implemented method comprising: detecting audio containing speech at a client device; encoding the detected audio as audio data; transmitting the audio data to a server system; identifying a docking context of the client device; transmitting information indicating the docking context to the server system; and receiving a transcription of at least a portion of the audio data at the client device, the server system having determined, for each of a plurality of language models, a weighting value based on the docking context, the weighting value indicating a probability that the language model will indicate a correct transcription for the encoded speech, selected at least one of the plurality of language models based on the weighting values, and generated the transcription by performing speech recognition on the audio data using the selected at least one language model, and transmitted the transcription to the client device. 27. The computer-implemented method of claim 26 , wherein the identified docking context is the docking context of the client device at the time the audio is detected.
| 0.809345 |
8. A user device, comprising: a memory device storing processor-executable instructions; and a processor configured to execute the processor-executable instructions, wherein executing the processor-executable instructions causes the processor to: present, during an ongoing voice call in which the user device is involved, a user interface that includes a control option that allows selection of a pre-recorded word or phrase, from a plurality of pre-recorded words or phrases, that has been received from a user of the user device prior to the ongoing voice call, wherein the ongoing voice call is a voice call between the user device and at least one other party; receive, via the user interface and during the ongoing voice call, a selection of a particular pre-recorded word or phrase from the plurality of pre-recorded words or phrases; receive, via the user interface and during the ongoing voice call, another word or phrase and an indication to pre-pend or post-pend the another word or phrase to the particular pre-recorded word or phrase; and interject the selected particular pre-recorded word or phrase and, in accordance with the indication, the another word or phrase, into the ongoing voice call, the interjecting including outputting, via the ongoing voice call and to the at least one other party, the selected particular pre-recorded word or phrase and the another word or phrase, based on the indication.
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8. A user device, comprising: a memory device storing processor-executable instructions; and a processor configured to execute the processor-executable instructions, wherein executing the processor-executable instructions causes the processor to: present, during an ongoing voice call in which the user device is involved, a user interface that includes a control option that allows selection of a pre-recorded word or phrase, from a plurality of pre-recorded words or phrases, that has been received from a user of the user device prior to the ongoing voice call, wherein the ongoing voice call is a voice call between the user device and at least one other party; receive, via the user interface and during the ongoing voice call, a selection of a particular pre-recorded word or phrase from the plurality of pre-recorded words or phrases; receive, via the user interface and during the ongoing voice call, another word or phrase and an indication to pre-pend or post-pend the another word or phrase to the particular pre-recorded word or phrase; and interject the selected particular pre-recorded word or phrase and, in accordance with the indication, the another word or phrase, into the ongoing voice call, the interjecting including outputting, via the ongoing voice call and to the at least one other party, the selected particular pre-recorded word or phrase and the another word or phrase, based on the indication. 14. The user device of claim 8 , wherein executing the processor-executable instructions further causes the processor to: automatically interject one or more additional pre-recorded words or phrases based on a termination of the ongoing voice call.
| 0.563512 |
16. A non-transitory computer storage medium having computer-executable instructions stored thereon that, in response to execution by a computer system, cause the computer system to: instruct to process annotations that include a dynamic annotation received at a target system and that is associated with data to be processed by the target system, wherein the dynamic annotation changes at the target system as a code block that is associated with the dynamic annotation is executed, wherein the dynamic annotation varies as a function of at least one of an available energy, an available memory or an available storage capacity; apply the processed annotations to at least one hardware component of the target system based on a hardware customization specified in the received annotations; instruct to process the data using the hardware customization that is specified by the received annotations, wherein the specified hardware customization is based upon a specified quality of service level to process the data with a reduced energy expenditure, and wherein the quality of service level is different from the reduced energy expenditure; instruct to modify at least one annotation of the processed annotations based on one or more values obtained from sensors at the target system; apply the modified at least one annotation to the at least one hardware component of the target system at a time when the code block that is associated with the dynamic annotation is executed; and reduce energy expended to process the data while maintaining the quality of service level through use of the hardware customization specified in the received annotations and the at least one hardware component of the target system to which the modified at least one annotation was applied, wherein one or more of the annotations are based, at least in part, on a system software configuration that is associated with a data block and wherein the one or more annotations specify how to process the data block when the code block is executed.
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16. A non-transitory computer storage medium having computer-executable instructions stored thereon that, in response to execution by a computer system, cause the computer system to: instruct to process annotations that include a dynamic annotation received at a target system and that is associated with data to be processed by the target system, wherein the dynamic annotation changes at the target system as a code block that is associated with the dynamic annotation is executed, wherein the dynamic annotation varies as a function of at least one of an available energy, an available memory or an available storage capacity; apply the processed annotations to at least one hardware component of the target system based on a hardware customization specified in the received annotations; instruct to process the data using the hardware customization that is specified by the received annotations, wherein the specified hardware customization is based upon a specified quality of service level to process the data with a reduced energy expenditure, and wherein the quality of service level is different from the reduced energy expenditure; instruct to modify at least one annotation of the processed annotations based on one or more values obtained from sensors at the target system; apply the modified at least one annotation to the at least one hardware component of the target system at a time when the code block that is associated with the dynamic annotation is executed; and reduce energy expended to process the data while maintaining the quality of service level through use of the hardware customization specified in the received annotations and the at least one hardware component of the target system to which the modified at least one annotation was applied, wherein one or more of the annotations are based, at least in part, on a system software configuration that is associated with a data block and wherein the one or more annotations specify how to process the data block when the code block is executed. 19. The computer storage medium of claim 16 , wherein the annotations, which are to be processed and which were received at the target system are obtained by the target system from a peer system.
| 0.539326 |
12. A system, comprising a server computer communicatively coupled to a network and comprising at least one processor executing computer-executable instructions within a memory that, when executed, cause the system to: receive, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenize the domain name search string; identify a search string token within the domain name search string as a concept seed; execute a first database command to create a data record storing the search string token in association with a concept id; execute a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenize at least one domain name text string within the domain name search log or the at least one DNS zone file; identify, within the at least one domain name text string, at least one synonym or translation of the search string token; execute a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identify, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generate a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmit the second GUI to the client computer for display.
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12. A system, comprising a server computer communicatively coupled to a network and comprising at least one processor executing computer-executable instructions within a memory that, when executed, cause the system to: receive, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenize the domain name search string; identify a search string token within the domain name search string as a concept seed; execute a first database command to create a data record storing the search string token in association with a concept id; execute a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenize at least one domain name text string within the domain name search log or the at least one DNS zone file; identify, within the at least one domain name text string, at least one synonym or translation of the search string token; execute a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identify, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generate a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmit the second GUI to the client computer for display. 19. The system of claim 12 , wherein the server computer is further configured to: identify at least one interchangeable term; generate an interchangeable term dictionary from the at least one interchangeable term; and rank the at least one available domain name according to the interchangeable term dictionary.
| 0.587832 |
7. A system, comprising: a processor; a memory in communication with the processor; and a non-transitory storage media in communication with the processor and the memory, the non-transitory storage media having machine-readable instructions stored thereon to cause the processor to perform a method of operating a query, the method comprising: sorting a first relation and a second relation in order, wherein the first relation comprises a group of tuples and the second relation comprises a group of tuples; concatenating the second relation to the first relation such that all of the tuples of the second relation follow all of the tuples of the first relation in the concatenated relations; reading the concatenated relations in order, comprising reading all the tuples of the first relation then reading the tuples of the second relation; caching data of the first relation; checking each data point of the second relation against the cached data of the first relation; and determining a closest new point of the data of the first relation for each of the points of the second relation.
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7. A system, comprising: a processor; a memory in communication with the processor; and a non-transitory storage media in communication with the processor and the memory, the non-transitory storage media having machine-readable instructions stored thereon to cause the processor to perform a method of operating a query, the method comprising: sorting a first relation and a second relation in order, wherein the first relation comprises a group of tuples and the second relation comprises a group of tuples; concatenating the second relation to the first relation such that all of the tuples of the second relation follow all of the tuples of the first relation in the concatenated relations; reading the concatenated relations in order, comprising reading all the tuples of the first relation then reading the tuples of the second relation; caching data of the first relation; checking each data point of the second relation against the cached data of the first relation; and determining a closest new point of the data of the first relation for each of the points of the second relation. 8. The system of claim 7 , wherein the machine-readable instructions stored on the non-transitory storage media further cause the processor to check each point of the second relation data against the cached first relation data by resetting the query to run on the second relation data when the first relation data is cached.
| 0.576713 |
1. A machine-implemented method of information retrieval, comprising: receiving, at a processing device, object-oriented data from multiple data sources; receiving, at the processing device, a query from a query application that formulates the query and supplies the query to an information retrieval system, wherein the query application is not part of the information retrieval system, the query comprising an ordered set of clause definitions each comprising a clause pipeline and a time constraint, wherein the clause pipeline comprises an ordered set of clause specifications that comprises: an expansion operation and/or a filter operation, wherein a first clause specification in the clause pipeline operates on an initial set of objects of the object-oriented data, and each subsequent clause specification in the clause pipeline operates on one or more objects that is produced from a respective previous clause specification that is executed directly before the subsequent clause specification within the ordered set of clause specifications, parsing, at the processing device, the query into a graph of data nodes; processing, at the processing device, the data nodes in the graph on the object-oriented data to generate a current object set, wherein each data node is processed using a data model generated by a model builder component, the model builder component obtaining data for the data model from a given data source of the multiple data sources; and returning, at the processing device, the current object set to the query application in response to the query.
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1. A machine-implemented method of information retrieval, comprising: receiving, at a processing device, object-oriented data from multiple data sources; receiving, at the processing device, a query from a query application that formulates the query and supplies the query to an information retrieval system, wherein the query application is not part of the information retrieval system, the query comprising an ordered set of clause definitions each comprising a clause pipeline and a time constraint, wherein the clause pipeline comprises an ordered set of clause specifications that comprises: an expansion operation and/or a filter operation, wherein a first clause specification in the clause pipeline operates on an initial set of objects of the object-oriented data, and each subsequent clause specification in the clause pipeline operates on one or more objects that is produced from a respective previous clause specification that is executed directly before the subsequent clause specification within the ordered set of clause specifications, parsing, at the processing device, the query into a graph of data nodes; processing, at the processing device, the data nodes in the graph on the object-oriented data to generate a current object set, wherein each data node is processed using a data model generated by a model builder component, the model builder component obtaining data for the data model from a given data source of the multiple data sources; and returning, at the processing device, the current object set to the query application in response to the query. 7. The method as described in claim 1 wherein the query application comprises a monitoring tool for an IT infrastructure.
| 0.832418 |
1. A computer implemented method for surveying a plurality of users with a sequence of questions that is automatically tailored per user to create a corresponding individualized compensation report, comprising the steps of: creating, with a computer implemented survey engine, for each of said users a corresponding user profile containing a tailored sequence of questions and corresponding answers, said tailored sequence of questions directed towards determination of job information, career information, and potential profile matches responsive of a user profile and one or more affinity groups of said user; creating, with said computer implemented survey engine, at least periodically, said one or more affinity groups for said users responsive of each of said corresponding user profiles, each of said one or more affinity groups having at least one user profile in an affinity group, said one or more affinity groups being created independent of the order in which said tailored sequence of questions is presented to a user; associating, with said computer implemented survey engine, each user profile with at least one affinity group; presenting to each user, with a collaborative filtering engine of said computer implemented survey engine, a sequence of questions from a source containing a plurality of different questions, said sequence of questions and order of each question in said sequence of questions being independently, asynchronously, and dynamically tailored for each and every user on an individual basis responsive to both an answer received from each individual user to a question previously presented to said individual user and a particular affinity group or combination of affinity groups to which a profile of said individual user is associated; receiving answers from each user; filtering said user profile, with a collaborative filtering engine of said computer implemented survey engine, wherein said filtering further comprises the application of a rules engine that comrpares said user profile to a set of predefined criteria; modifying an answer if it is inconsistent with at least one of: said user profile; and said affinity group; storing said user profile of said each user in a storage associated with said computer implemented survey engine; wherein said affinity group comprises at least one of: profession; compensation; compensation range; experience; experience range; position; and position range; the steps repeated at least once more per user; determining, with said collaborative filtering engine of said computer implemented survey engine, when no additional questions are to be presented to said individual based upon said individual's response to said sequence of questions; capturing, with said collaborative filtering engine of said computer implemented survey engine, profile attributes comprising targeted compensation variables with regard to said individual user's profile responsive to an individual's answers to said sequence of questions; generating a personalized compensation report, which includes job information, career information, compensation, and potential profile matches for a user responding to said tailored sequence of questions responsive of a request from said user to generate said report; and creating, by the computer implemented survey engine, when applicable new affinity groups as additional users respond to respective tailored sequence of questions.
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1. A computer implemented method for surveying a plurality of users with a sequence of questions that is automatically tailored per user to create a corresponding individualized compensation report, comprising the steps of: creating, with a computer implemented survey engine, for each of said users a corresponding user profile containing a tailored sequence of questions and corresponding answers, said tailored sequence of questions directed towards determination of job information, career information, and potential profile matches responsive of a user profile and one or more affinity groups of said user; creating, with said computer implemented survey engine, at least periodically, said one or more affinity groups for said users responsive of each of said corresponding user profiles, each of said one or more affinity groups having at least one user profile in an affinity group, said one or more affinity groups being created independent of the order in which said tailored sequence of questions is presented to a user; associating, with said computer implemented survey engine, each user profile with at least one affinity group; presenting to each user, with a collaborative filtering engine of said computer implemented survey engine, a sequence of questions from a source containing a plurality of different questions, said sequence of questions and order of each question in said sequence of questions being independently, asynchronously, and dynamically tailored for each and every user on an individual basis responsive to both an answer received from each individual user to a question previously presented to said individual user and a particular affinity group or combination of affinity groups to which a profile of said individual user is associated; receiving answers from each user; filtering said user profile, with a collaborative filtering engine of said computer implemented survey engine, wherein said filtering further comprises the application of a rules engine that comrpares said user profile to a set of predefined criteria; modifying an answer if it is inconsistent with at least one of: said user profile; and said affinity group; storing said user profile of said each user in a storage associated with said computer implemented survey engine; wherein said affinity group comprises at least one of: profession; compensation; compensation range; experience; experience range; position; and position range; the steps repeated at least once more per user; determining, with said collaborative filtering engine of said computer implemented survey engine, when no additional questions are to be presented to said individual based upon said individual's response to said sequence of questions; capturing, with said collaborative filtering engine of said computer implemented survey engine, profile attributes comprising targeted compensation variables with regard to said individual user's profile responsive to an individual's answers to said sequence of questions; generating a personalized compensation report, which includes job information, career information, compensation, and potential profile matches for a user responding to said tailored sequence of questions responsive of a request from said user to generate said report; and creating, by the computer implemented survey engine, when applicable new affinity groups as additional users respond to respective tailored sequence of questions. 11. The method of claim 1 , further comprising the steps of: periodically creating a new affinity group by associating at least one user profile of said users to said new affinity group.
| 0.544496 |
11. The machine readable medium of claim 7 , further comprising applying the data tags of the first data object associated with the first data feed to a first data object associated with a third data feed, the first data object not having existing data tags.
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11. The machine readable medium of claim 7 , further comprising applying the data tags of the first data object associated with the first data feed to a first data object associated with a third data feed, the first data object not having existing data tags. 12. The machine readable medium of claim 11 , wherein a name of the first data object associated with the first data feed is identical to a name of the first data object associated with the third data feed.
| 0.947381 |
27. The apparatus of claim 26 wherein the user interface further includes means for prompting the user to accept or reject component updating for each of the components to be updated.
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27. The apparatus of claim 26 wherein the user interface further includes means for prompting the user to accept or reject component updating for each of the components to be updated. 28. The apparatus of claim 27 wherein the means for prompting includes means for prompting the user to accept or reject each updated component to include in the first and second documents.
| 0.939946 |
21. A method for improving a statistical message classifier comprising: receiving a message over a network communication interface; identifying by a processor executing instructions out of a memory a feature in the message that is associated with a junk count; testing the message with a first classifier by the processor, wherein the first classifier is a reliable junk classifier capable of making a first classification by the processor performing a calculation according to a logarithmic function including the junk count, wherein the first classifier outputs a value for the statistical message classifier for storage in the memory; in the event that the message is classifiable by the first classifier, updating the statistical message classifier stored in the memory according to the first classification by the processor performing the logarithmic calculation; in the event that the first classifier does not make the first classification, testing the message with a second classifier, wherein the second classifier is capable of making a second classification; and updating the statistical message classifier stored in the memory according to the second classification by the processor, wherein the statistical message classifier corresponds to a probability that the feature in the message is spam; identifying that the message is spam based on the probability that the feature in the message is spam; and quarantining the message.
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21. A method for improving a statistical message classifier comprising: receiving a message over a network communication interface; identifying by a processor executing instructions out of a memory a feature in the message that is associated with a junk count; testing the message with a first classifier by the processor, wherein the first classifier is a reliable junk classifier capable of making a first classification by the processor performing a calculation according to a logarithmic function including the junk count, wherein the first classifier outputs a value for the statistical message classifier for storage in the memory; in the event that the message is classifiable by the first classifier, updating the statistical message classifier stored in the memory according to the first classification by the processor performing the logarithmic calculation; in the event that the first classifier does not make the first classification, testing the message with a second classifier, wherein the second classifier is capable of making a second classification; and updating the statistical message classifier stored in the memory according to the second classification by the processor, wherein the statistical message classifier corresponds to a probability that the feature in the message is spam; identifying that the message is spam based on the probability that the feature in the message is spam; and quarantining the message. 23. The method for improving a message classifier as recited in claim 21 , wherein the second classifier is a reliable junk classifier having a probability of erroneous classification of less than one percent.
| 0.531613 |
11. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising: instructions for responding to a single search query, including: instructions for searching a message repository to identify a plurality of conversations that include at least one message relevant to the search query, wherein each of the plurality of the conversations includes one or more messages sharing a common set of characteristics that meet predefined criteria, and wherein each of the plurality of the identified conversations includes a respective conversation identifier, and instructions for sending a list of conversations representing at least a subset of the plurality of conversations, wherein at least one of the conversations in the list includes a plurality of email messages; and instructions for providing differentiating information associated with a selected conversation from the list of conversations such that one or more first messages of the selected conversation that do not include text matching the search query are differentiated from one or more second messages of the selected conversation that do include text matching the search query; wherein the instructions providing differentiating information include: instructions for providing formatting information for the first messages in a first format and providing formatting information for the second messages in a second format, wherein the first format differs from the second format in a visually distinctive manner.
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11. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising: instructions for responding to a single search query, including: instructions for searching a message repository to identify a plurality of conversations that include at least one message relevant to the search query, wherein each of the plurality of the conversations includes one or more messages sharing a common set of characteristics that meet predefined criteria, and wherein each of the plurality of the identified conversations includes a respective conversation identifier, and instructions for sending a list of conversations representing at least a subset of the plurality of conversations, wherein at least one of the conversations in the list includes a plurality of email messages; and instructions for providing differentiating information associated with a selected conversation from the list of conversations such that one or more first messages of the selected conversation that do not include text matching the search query are differentiated from one or more second messages of the selected conversation that do include text matching the search query; wherein the instructions providing differentiating information include: instructions for providing formatting information for the first messages in a first format and providing formatting information for the second messages in a second format, wherein the first format differs from the second format in a visually distinctive manner. 15. The computer readable storage medium of claim 11 , wherein such differentiating information is associated with a predefined status.
| 0.526888 |
1. A method of sharing in one or more network(s), the method comprising: storing and managing each registered user's one or more profile(s), IN and OUT permission and relational connections or dynamic relationships in a non-transitory computer readable memory of a central server; mapping or requesting sharing of one or more selected contents by one or more requestor or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; determining one or more target users by requestor(s) or sharing user(s) with the said request including share selected one or more contents from one or more network(s) with or via one or more selected communication channels or services, applications or modules, connections or relations from set of requestor(s) or sharing user(s) related subscribed communication channels or services, installed applications or modules and connected or related users; receiving, storing and processing one or more shared contents with metadata including determined target users of requestor(s) or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; matching by the central server a target user with the requestor or sharing user, wherein the matching is conducted by the central server based on one or more selections, IN and OUT preferences, profiles and connections of requestor(s) or sharing user(s); and providing or synchronizing or updating said one or more shared contents of said requestor(s) or sharing user(s) from one or more network(s) to said determined one or more target users.
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1. A method of sharing in one or more network(s), the method comprising: storing and managing each registered user's one or more profile(s), IN and OUT permission and relational connections or dynamic relationships in a non-transitory computer readable memory of a central server; mapping or requesting sharing of one or more selected contents by one or more requestor or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; determining one or more target users by requestor(s) or sharing user(s) with the said request including share selected one or more contents from one or more network(s) with or via one or more selected communication channels or services, applications or modules, connections or relations from set of requestor(s) or sharing user(s) related subscribed communication channels or services, installed applications or modules and connected or related users; receiving, storing and processing one or more shared contents with metadata including determined target users of requestor(s) or sharing user(s) from one or more network(s) in a non-transitory computer readable memory of a central server; matching by the central server a target user with the requestor or sharing user, wherein the matching is conducted by the central server based on one or more selections, IN and OUT preferences, profiles and connections of requestor(s) or sharing user(s); and providing or synchronizing or updating said one or more shared contents of said requestor(s) or sharing user(s) from one or more network(s) to said determined one or more target users. 5. The method as claimed in claim 1 , wherein said receiving sharing request or one or more shared contents from one or more sharing user(s) or requestor(s) from one or more network(s) via one or more AI agents, browser plug-ins, API and web service(s), 3 rd parties applications, devices, networks and services.
| 0.55708 |
6. A system for graphically representing tags in a networked computing environment, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and a processor coupled to the bus that when executing the instructions causes the system to: determine a frequency of use of each of a set of tags associated with content contained in at least one computer storage device of the networked computing environment, the content being received from one or more feeds together with the associated tags, which describe a subject matter of the content; identify a set of relationships between the set of tags; display each of the set of tags within a set of objects of a graphical diagram according to the frequency, wherein the set of relationships between the set of tags determines an amount of overlap of the set of objects; and format the set of tags in the graphical diagram to represent each experience option in turn enabled by a selection by a user from the following: utilizing different shapes for the set of tags to represent topics corresponding to the set of tags, utilizing different shapes for the set of tags to represent groupings of the topics corresponding to the set of tags, utilizing different colors for the set of tags to represent trends related to the set of tags, and changing an intensity of the different colors for the set of tags to represent an importance of the set of tags.
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6. A system for graphically representing tags in a networked computing environment, comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and a processor coupled to the bus that when executing the instructions causes the system to: determine a frequency of use of each of a set of tags associated with content contained in at least one computer storage device of the networked computing environment, the content being received from one or more feeds together with the associated tags, which describe a subject matter of the content; identify a set of relationships between the set of tags; display each of the set of tags within a set of objects of a graphical diagram according to the frequency, wherein the set of relationships between the set of tags determines an amount of overlap of the set of objects; and format the set of tags in the graphical diagram to represent each experience option in turn enabled by a selection by a user from the following: utilizing different shapes for the set of tags to represent topics corresponding to the set of tags, utilizing different shapes for the set of tags to represent groupings of the topics corresponding to the set of tags, utilizing different colors for the set of tags to represent trends related to the set of tags, and changing an intensity of the different colors for the set of tags to represent an importance of the set of tags. 7. The system of claim 6 , the memory medium further comprising instructions for causing the system to display each of the set of tags in a size that corresponds to the frequency of use.
| 0.527317 |
3. The non-transitory, computer readable media as recited in claim 1 , wherein, in response to the user interacting with the interactivity element displayed in the touch sensitive display, the instructions also cause a second plurality of control interface elements to be temporarily added to the content access interface together with the first plurality of control interface elements and the one or more of the plurality of media interface elements, wherein each of the second plurality of control interface elements is representative of transport operational function of the first controllable appliance and each of the second plurality of control interface elements is selectable by the user to cause the smart device to transmit a command to cause the first controllable appliance to perform a transport control function corresponding to the selected one of the second plurality of control interface elements.
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3. The non-transitory, computer readable media as recited in claim 1 , wherein, in response to the user interacting with the interactivity element displayed in the touch sensitive display, the instructions also cause a second plurality of control interface elements to be temporarily added to the content access interface together with the first plurality of control interface elements and the one or more of the plurality of media interface elements, wherein each of the second plurality of control interface elements is representative of transport operational function of the first controllable appliance and each of the second plurality of control interface elements is selectable by the user to cause the smart device to transmit a command to cause the first controllable appliance to perform a transport control function corresponding to the selected one of the second plurality of control interface elements. 10. The non-transitory, computer readable media as recited in claim 3 , wherein the first and second plurality of control interface elements are temporarily added to the content access user interface until such time as the instructions sense a subsequent user interaction with the interactivity element displayed in the touch sensitive display.
| 0.887329 |
8. The method of claim 1 wherein said adding the most probable completion alternative to the content string entry line of said display further comprises Identifying as part of said most probable completion alternative, a most probable phrase consisting of at least a first word and a second word, said first word and said second word corresponding to a phrase stored in said personalized and learning database; displaying the most probable phrase in said content string entry line of said display; receiving a third input accepting said most probable phrase; and adding the most probable phrase to the content string entry line of said display in response to receiving said third input.
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8. The method of claim 1 wherein said adding the most probable completion alternative to the content string entry line of said display further comprises Identifying as part of said most probable completion alternative, a most probable phrase consisting of at least a first word and a second word, said first word and said second word corresponding to a phrase stored in said personalized and learning database; displaying the most probable phrase in said content string entry line of said display; receiving a third input accepting said most probable phrase; and adding the most probable phrase to the content string entry line of said display in response to receiving said third input. 10. The method of operating an electronic device as defined in claim 8 wherein the user accepts the entire most probable phrase.
| 0.899491 |
8. A computer-implemented search method of a semantic-based search system, the method comprising: (a) generating, using a processor, a user log storing information searched by a user by reflecting user preference; (b) generating, using a processor, a common log storing knowledge corresponding to general knowledge when the user inputs a keyword; (c) analyzing, using a processor, vector characteristics corresponding to an instance among interpretation alternatives according to the keyword input; (d) calculating, using a processor, weighted values of confidence values and cosine similarity values of interpretation alternatives including the vector characteristics of the instance with respect to at least any one of the common log and the user log; and (e) aligning, using a processor, rankings of the interpretation alternatives according to the keyword input on the basis of the calculated weighted values of the confidence values and the cosine similarity values.
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8. A computer-implemented search method of a semantic-based search system, the method comprising: (a) generating, using a processor, a user log storing information searched by a user by reflecting user preference; (b) generating, using a processor, a common log storing knowledge corresponding to general knowledge when the user inputs a keyword; (c) analyzing, using a processor, vector characteristics corresponding to an instance among interpretation alternatives according to the keyword input; (d) calculating, using a processor, weighted values of confidence values and cosine similarity values of interpretation alternatives including the vector characteristics of the instance with respect to at least any one of the common log and the user log; and (e) aligning, using a processor, rankings of the interpretation alternatives according to the keyword input on the basis of the calculated weighted values of the confidence values and the cosine similarity values. 9. The search method of claim 8 , wherein the confidence values include confidence values between the common log and the interpretation alternatives and confidence values between the user log and the interpretation alternatives.
| 0.556031 |
3. An information processing apparatus for presenting information on an item selected in accordance with a user's preference, the information including a comment on the item, the apparatus comprising: a processor, wherein the processor is configured to: store comment data on the item, wherein the comment data includes comment information in the form of sentences describing the item; select a keyword from words in the comment data; store content data on the item, wherein the content data includes content information representing the item; extract a feature quantity of the content data; verbalize the feature quantity in the form of a word corresponding to the feature quantity, based on a dictionary that shows a relationship between the feature quantity and the word; match the keyword and the word corresponding to the feature quantity with user preference information; and control presentation of information on the item selected in accordance with the user's preference by displaying the word corresponding to the feature quantity in a format different from other words out of words constituting the comment, the word contributing to the selection of the item.
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3. An information processing apparatus for presenting information on an item selected in accordance with a user's preference, the information including a comment on the item, the apparatus comprising: a processor, wherein the processor is configured to: store comment data on the item, wherein the comment data includes comment information in the form of sentences describing the item; select a keyword from words in the comment data; store content data on the item, wherein the content data includes content information representing the item; extract a feature quantity of the content data; verbalize the feature quantity in the form of a word corresponding to the feature quantity, based on a dictionary that shows a relationship between the feature quantity and the word; match the keyword and the word corresponding to the feature quantity with user preference information; and control presentation of information on the item selected in accordance with the user's preference by displaying the word corresponding to the feature quantity in a format different from other words out of words constituting the comment, the word contributing to the selection of the item. 7. The apparatus according to claim 3 , wherein a word having served for the selection of the item is the same word as the word included in preference information representing the user's preference, or the word corresponding to the word included in the preference information out of words included in meta-data of the item referenced at the time of selecting the item.
| 0.592656 |
14. The system of claim 1 , wherein: the rich media file includes a first dialogue box structured to appear responsive to the viewing limits of the rich media file, the first dialogue box to communicate to the user an invitation to access another rich media file; and the second computer is configured to send the another rich media file to the user responsive to the first dialogue box.
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14. The system of claim 1 , wherein: the rich media file includes a first dialogue box structured to appear responsive to the viewing limits of the rich media file, the first dialogue box to communicate to the user an invitation to access another rich media file; and the second computer is configured to send the another rich media file to the user responsive to the first dialogue box. 15. The system of claim 14 , wherein: the rich media file includes a second dialogue box structured to appear responsive to an update offer, the second dialogue box for prompting the user of the rich media file to check for a newer version of the rich media file; and the second computer is configured to send the newer version of the rich media file to the user responsive to the second dialogue box.
| 0.700431 |
3. The computer implemented method of claim 1 , further including identifying a second element corresponding to the first element by searching at least one of the textual component or the graphical component based on the first element.
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3. The computer implemented method of claim 1 , further including identifying a second element corresponding to the first element by searching at least one of the textual component or the graphical component based on the first element. 5. The computer implemented method of claim 3 , further including linking the second element with the first element by receiving a linking designation.
| 0.925563 |
1. A method performed on a computing device, the method comprising: generating, by the computing device, a graph representing switches between various windows, the graph comprising nodes, edges, and weights, where each node in the graph represents one of the various windows, and where each edge of the graph represents a switch between two of the various windows, and where the each edge is weighted based on a number of switches between the two of the various windows; discarding directionality of the edges of the generated graph; eliminating the edges of the generated graph that are weighted less than a particular threshold; grouping, based on the generated graph subsequent to the discarding and the eliminating, some of the various windows.
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1. A method performed on a computing device, the method comprising: generating, by the computing device, a graph representing switches between various windows, the graph comprising nodes, edges, and weights, where each node in the graph represents one of the various windows, and where each edge of the graph represents a switch between two of the various windows, and where the each edge is weighted based on a number of switches between the two of the various windows; discarding directionality of the edges of the generated graph; eliminating the edges of the generated graph that are weighted less than a particular threshold; grouping, based on the generated graph subsequent to the discarding and the eliminating, some of the various windows. 7. The method of claim 1 where the grouping is based on a temporal clustering model.
| 0.635815 |
1. A method of extracting individual posts from a weblog, comprising: accessing a home page of the weblog; identifying at least one feed associated with the weblog; determining whether the at least one feed contains sufficient content for feed-guided segmentation; if the at least one feed contains sufficient content for feed-guided segmentation, determining whether the at least one feed contains full content or partial content of the weblog; if the at least one feed contains full content of the weblog, mapping data found in the at least one feed into a representation for weblog posts; and if the at least one feed contains partial content of the weblog, screen scraping the weblog into a representation for weblog posts using the data.
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1. A method of extracting individual posts from a weblog, comprising: accessing a home page of the weblog; identifying at least one feed associated with the weblog; determining whether the at least one feed contains sufficient content for feed-guided segmentation; if the at least one feed contains sufficient content for feed-guided segmentation, determining whether the at least one feed contains full content or partial content of the weblog; if the at least one feed contains full content of the weblog, mapping data found in the at least one feed into a representation for weblog posts; and if the at least one feed contains partial content of the weblog, screen scraping the weblog into a representation for weblog posts using the data. 8. The method of claim 1 , wherein in determining whether the at least one feed contains sufficient content for feed-guided segmentation, an item in the at least one feed is deemed to contain sufficient content if it contains a date-posted field and either a content field or a description field.
| 0.66916 |
1. A method of operating on-line search services, the method comprising: receiving, from a user, a search word for searching communities; conducting a search using the search word, thereby locating a plurality of communities, wherein the search is conducted using a computing device comprising a processor and a memory; determining a reliability value for each of a plurality of located communities using at least one reliability factor selected from the group consisting of a community user reliability index and a community activity index, the reliability value being indicative of how reliable information from each community is, wherein the community user reliability index for a first one of the plurality of located communities is determined based on reliability indices of users registered with the first community, wherein the community activity index for the first community is determined based on activities of users registered with the first community; formulating a search result page such that at least part of the plurality of located communities are arranged based on the reliability values thereof on the search result page; and providing the user with the formulated search result page.
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1. A method of operating on-line search services, the method comprising: receiving, from a user, a search word for searching communities; conducting a search using the search word, thereby locating a plurality of communities, wherein the search is conducted using a computing device comprising a processor and a memory; determining a reliability value for each of a plurality of located communities using at least one reliability factor selected from the group consisting of a community user reliability index and a community activity index, the reliability value being indicative of how reliable information from each community is, wherein the community user reliability index for a first one of the plurality of located communities is determined based on reliability indices of users registered with the first community, wherein the community activity index for the first community is determined based on activities of users registered with the first community; formulating a search result page such that at least part of the plurality of located communities are arranged based on the reliability values thereof on the search result page; and providing the user with the formulated search result page. 4. The method of claim 1 , wherein the community user reliability index indicates a sum of reliability indices of users registered with the first community, wherein each reliability index of a user indicates reliability of the information provided by the user.
| 0.637865 |
5. A computer-implemented method for reconstituting a document in a repository in a content management system, the method comprising the steps of: during initial reconstitution of the document, performing the steps of: (A) retrieving from the repository objects corresponding to original links in the document; (B) storing values from the retrieved objects in corresponding fallback elements in the document; (C) generating a list with the original links in the document and corresponding voidable links; and (D) replacing any original link in the document that is not voidable with a corresponding voidable link defined in the list, during each subsequent reconstitution of the document that follows the initial reconstitution of the document in steps (A) through (D), performing the steps of: (E) determining the original links in the list for the document; (F) querying the repository to determine which of the objects corresponding to the original links in the list have not changed since the last reconstitution of the document; and (G) for each object that has not changed since the last reconstitution of the document, invalidating a corresponding voidable link.
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5. A computer-implemented method for reconstituting a document in a repository in a content management system, the method comprising the steps of: during initial reconstitution of the document, performing the steps of: (A) retrieving from the repository objects corresponding to original links in the document; (B) storing values from the retrieved objects in corresponding fallback elements in the document; (C) generating a list with the original links in the document and corresponding voidable links; and (D) replacing any original link in the document that is not voidable with a corresponding voidable link defined in the list, during each subsequent reconstitution of the document that follows the initial reconstitution of the document in steps (A) through (D), performing the steps of: (E) determining the original links in the list for the document; (F) querying the repository to determine which of the objects corresponding to the original links in the list have not changed since the last reconstitution of the document; and (G) for each object that has not changed since the last reconstitution of the document, invalidating a corresponding voidable link. 8. The method of claim 5 wherein, if a voidable link in the document is valid, performing the step of accessing the corresponding object in the repository using the voidable link.
| 0.703261 |
9. A system comprising: one or more devices, including at least one memory and at least one processor, to: receive a document; select terms from the received document to form a plurality of term groups for the received document, each term group, of the plurality of term groups, being associated with an indication that a first term, of the term group, occurs before a second term, of the term group, within the received document; identify, from an inverted index of term groups, one or more clusters of a plurality of clusters, each cluster, of the one or more identified clusters, comprising a set of term groups for a respective other document, each respective term group, of the set of term groups, being associated with an indication that a first term, of the respective term group, occurs before a second term, of the respective term group, within the respective other document; determine measures of similarity between the plurality of term groups for the received document and the set of term groups for each of the one or more identified clusters; and determine, based on the determined measures of similarity, that the received document is similar to the respective other document.
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9. A system comprising: one or more devices, including at least one memory and at least one processor, to: receive a document; select terms from the received document to form a plurality of term groups for the received document, each term group, of the plurality of term groups, being associated with an indication that a first term, of the term group, occurs before a second term, of the term group, within the received document; identify, from an inverted index of term groups, one or more clusters of a plurality of clusters, each cluster, of the one or more identified clusters, comprising a set of term groups for a respective other document, each respective term group, of the set of term groups, being associated with an indication that a first term, of the respective term group, occurs before a second term, of the respective term group, within the respective other document; determine measures of similarity between the plurality of term groups for the received document and the set of term groups for each of the one or more identified clusters; and determine, based on the determined measures of similarity, that the received document is similar to the respective other document. 13. The system of claim 9 , where the one or more devices are further to: store the inverted index, the inverted index including: information regarding the cluster associated with the respective other document, and a list of the plurality of clusters that include a particular term group of the plurality of term groups.
| 0.715715 |
1. A non-transitory computer-readable storage medium containing instructions to configure a processor to perform operations comprising: receiving a first query; generating, based on a model including metadata representing a data structure, a second query specific to the data structure stored in a database, the second query being a single direct query to the database and defining all nodes and associations, including a root node, nodes dependent on the root node, and associations between all nodes, needed to traverse at least one business object and nodes stored in the database to generate a result set without buffering of intermediate results; and sending the second query to the database; and executing the second query page by page basis at runtime based on a page being displayed on a user interface used for executing the second query and using data transported from the database and associated only with the page being displayed on the user interface, the data associated with the displayed page is searched in and obtained from data stored in the database, and by searching an unrestricted amount of data at the database at constant seek time as a prerequisite of paging.
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1. A non-transitory computer-readable storage medium containing instructions to configure a processor to perform operations comprising: receiving a first query; generating, based on a model including metadata representing a data structure, a second query specific to the data structure stored in a database, the second query being a single direct query to the database and defining all nodes and associations, including a root node, nodes dependent on the root node, and associations between all nodes, needed to traverse at least one business object and nodes stored in the database to generate a result set without buffering of intermediate results; and sending the second query to the database; and executing the second query page by page basis at runtime based on a page being displayed on a user interface used for executing the second query and using data transported from the database and associated only with the page being displayed on the user interface, the data associated with the displayed page is searched in and obtained from data stored in the database, and by searching an unrestricted amount of data at the database at constant seek time as a prerequisite of paging. 5. The non-transitory computer-readable medium of claim 1 , wherein the generating further comprises: generating the second query in accordance with SQL.
| 0.688976 |
1. A method performed using one or more processors of a processor-based system, the method comprising: determining, by at least one of the one or more processors, that a developer performs an operation with regard to development of designated code; filtering, by at least one of the one or more processors, a plurality of social updates that are associated with a plurality of users in a social networking environment in a social data graph to determine a subset of the plurality of social updates that relates to development of software applications; determining, by at least one of the one or more processors, information that is contextually related to the designated code based on the subset of the plurality of social updates in response to a determination that the developer performs the operation with regard to the development of the designated code, the information being associated with the plurality of users; and recommending, by at least one of the one or more processors, at least a portion of the information for use with regard to the designated code based on at least the portion of the information being associated with at least one user of the plurality of users who is included in a social network of the developer in the social data graph.
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1. A method performed using one or more processors of a processor-based system, the method comprising: determining, by at least one of the one or more processors, that a developer performs an operation with regard to development of designated code; filtering, by at least one of the one or more processors, a plurality of social updates that are associated with a plurality of users in a social networking environment in a social data graph to determine a subset of the plurality of social updates that relates to development of software applications; determining, by at least one of the one or more processors, information that is contextually related to the designated code based on the subset of the plurality of social updates in response to a determination that the developer performs the operation with regard to the development of the designated code, the information being associated with the plurality of users; and recommending, by at least one of the one or more processors, at least a portion of the information for use with regard to the designated code based on at least the portion of the information being associated with at least one user of the plurality of users who is included in a social network of the developer in the social data graph. 6. The method of claim 1 , comprising: recommending, by at least one of the one or more processors, at least one code snippet to the developer based on at least one of a preference or one or more demographic characteristics of the developer.
| 0.704429 |
1. A method comprising: determining that a title of a current web page does not fit in a title display area of a display; removing at least one word from the title of the current page until the title of the current page fits in the title display area wherein removing the at least one word comprises: determining, by a processor, that the title of the current web page starts with at least one same word as a title of a previous page; and removing at least one word from a beginning portion of the title of the current page that is in common with the title of the previous page; and determining that there is at least one common word in between an end portion of the current title and an end portion of the previous title and removing the at least one common word.
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1. A method comprising: determining that a title of a current web page does not fit in a title display area of a display; removing at least one word from the title of the current page until the title of the current page fits in the title display area wherein removing the at least one word comprises: determining, by a processor, that the title of the current web page starts with at least one same word as a title of a previous page; and removing at least one word from a beginning portion of the title of the current page that is in common with the title of the previous page; and determining that there is at least one common word in between an end portion of the current title and an end portion of the previous title and removing the at least one common word. 3. The method of claim 1 further comprising inserting a predetermined indicator to indicate the removed at least one common word.
| 0.695407 |
2. The method of claim 1 , wherein the intermediary data structure defines elements or attributes of a mandatory data type in the context of a specific service operation.
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2. The method of claim 1 , wherein the intermediary data structure defines elements or attributes of a mandatory data type in the context of a specific service operation. 3. The method of claim 2 , wherein the intermediary data structure uses an XML query language for constraints and enforces context specific constraints on data types in the XML schema.
| 0.926808 |
15. A system, comprising: one or more processors; and a computer-readable storage medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations to compare a first structured data document to a second structured data document, the operations comprising: receiving the first and second structured data documents as first and second encrypted documents, respectively, the first and second encrypted documents being transmitted from a remote computing device over a network, structure and content of each of the first and second encrypted documents being encrypted using encrypted integer labels (EBOL), wherein encrypting the first and second structured data documents comprises, for each node of each of the first and second structured data documents: assigning an integer pair comprising a unique identifier and a depth of the node, encrypting the integer pair to provide an encrypted integer pair, and encrypting structure encoding information of the node, comparing nodes of the first encrypted document to nodes of the second encrypted document, a content and a location of each of the nodes remaining confidential during the comparing; generating matched pairs of nodes based on the comparing, and storing the matched pairs in computer memory, each matched pair comprising a node of the first encrypted document and a corresponding node of the second encrypted document; determining one or more edit operations based on the matched pairs; and generating an edit script comprising the one or more edit operations, the edit script being executable by one or more processors to transform the first encrypted document to provide a transformed encrypted document that is isomorphic to the second encrypted document.
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15. A system, comprising: one or more processors; and a computer-readable storage medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations to compare a first structured data document to a second structured data document, the operations comprising: receiving the first and second structured data documents as first and second encrypted documents, respectively, the first and second encrypted documents being transmitted from a remote computing device over a network, structure and content of each of the first and second encrypted documents being encrypted using encrypted integer labels (EBOL), wherein encrypting the first and second structured data documents comprises, for each node of each of the first and second structured data documents: assigning an integer pair comprising a unique identifier and a depth of the node, encrypting the integer pair to provide an encrypted integer pair, and encrypting structure encoding information of the node, comparing nodes of the first encrypted document to nodes of the second encrypted document, a content and a location of each of the nodes remaining confidential during the comparing; generating matched pairs of nodes based on the comparing, and storing the matched pairs in computer memory, each matched pair comprising a node of the first encrypted document and a corresponding node of the second encrypted document; determining one or more edit operations based on the matched pairs; and generating an edit script comprising the one or more edit operations, the edit script being executable by one or more processors to transform the first encrypted document to provide a transformed encrypted document that is isomorphic to the second encrypted document. 19. The system of claim 15 , wherein determining one or more edit operations comprises: determining that a sibling node of a first node of a matched pair and a sibling node of a second node of the matched pair are different; generating a move operation to move the first node such that a sibling node of the first node is the same as the sibling node of the second node; and adding the move operation to the edit script.
| 0.542647 |
33. The system of claim 1 , wherein the processor further implements the first processing node and the second processing node for allowing the relevant network access and activity further by: detecting the at least one user has met the required threshold level of the verification criteria; communicating this success at the first and the second processing nodes to at least one of a user, device, session, network transmission, or provisioning system; and allowing the user access to or utilization of the network responsive to the detection.
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33. The system of claim 1 , wherein the processor further implements the first processing node and the second processing node for allowing the relevant network access and activity further by: detecting the at least one user has met the required threshold level of the verification criteria; communicating this success at the first and the second processing nodes to at least one of a user, device, session, network transmission, or provisioning system; and allowing the user access to or utilization of the network responsive to the detection. 34. The system of claim 33 , wherein the processor implements the first processing node and the second processing node for allowing the relevant network access and activity by continuously monitoring and verifying for a dynamic time period after allowing the relevant network access or activity, to ensure continued user identity and activity fidelity.
| 0.886007 |
1. An apparatus that is configured to identify a moving object in spatial data, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive, from a spatial data source, a data structure that comprises spatial-temporal data, wherein spatial-temporal data comprises a combination of time series data and spatial data; convert the spatial-temporal data to a sequence of spatial data frames, where the sequence of spatial data frames represents the spatial data as a sequence of image-like objects; determine a location of one or more clusters in the sequence of spatial data frames at two or more of a plurality of time values, the sequence of spatial data frames defining one or more locations of the one or more clusters at the plurality of time values; determine that a first cluster of the one or more clusters in a first of the two or more time values corresponds to a second cluster of the one or more clusters in a second of the two or more time values; wherein, to determine that the first cluster corresponds to the second cluster, the processor is further configured to: determine a location of each cluster at the first of the two or more time values; determine a location of each cluster at the second of the two or more time values; compute a cluster similarity score for one or more of the clusters at the first time value with one or more of the clusters at the second time value; and associate the first cluster with the second cluster based on the similarity score; determine at least one motion vector between the first cluster and the second cluster; and determine a moving object based on information comprising the at least one motion vector, wherein the processor is further configured to generate an output text using a natural language generation system, the output text linguistically describing the moving object.
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1. An apparatus that is configured to identify a moving object in spatial data, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive, from a spatial data source, a data structure that comprises spatial-temporal data, wherein spatial-temporal data comprises a combination of time series data and spatial data; convert the spatial-temporal data to a sequence of spatial data frames, where the sequence of spatial data frames represents the spatial data as a sequence of image-like objects; determine a location of one or more clusters in the sequence of spatial data frames at two or more of a plurality of time values, the sequence of spatial data frames defining one or more locations of the one or more clusters at the plurality of time values; determine that a first cluster of the one or more clusters in a first of the two or more time values corresponds to a second cluster of the one or more clusters in a second of the two or more time values; wherein, to determine that the first cluster corresponds to the second cluster, the processor is further configured to: determine a location of each cluster at the first of the two or more time values; determine a location of each cluster at the second of the two or more time values; compute a cluster similarity score for one or more of the clusters at the first time value with one or more of the clusters at the second time value; and associate the first cluster with the second cluster based on the similarity score; determine at least one motion vector between the first cluster and the second cluster; and determine a moving object based on information comprising the at least one motion vector, wherein the processor is further configured to generate an output text using a natural language generation system, the output text linguistically describing the moving object. 17. The apparatus of claim 1 , wherein the first cluster is associated with the second cluster based on the association maximizing the cluster similarity score for the first cluster.
| 0.52975 |
2. The method of claim 1 , wherein the at least one item of supplemental content relates to an article, a person, or a concept, and the at least one item of supplemental content comprises at least one of: text, audio, video, a multimedia presentation, a photograph, an image, a uniform resource locator, a computer application, data, commentary, advertising copy, a keyword, a tag, an element that encourages interactive participation by the viewer, variable data, raw data, stylized information, or a placeholder.
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2. The method of claim 1 , wherein the at least one item of supplemental content relates to an article, a person, or a concept, and the at least one item of supplemental content comprises at least one of: text, audio, video, a multimedia presentation, a photograph, an image, a uniform resource locator, a computer application, data, commentary, advertising copy, a keyword, a tag, an element that encourages interactive participation by the viewer, variable data, raw data, stylized information, or a placeholder. 3. The method of claim 2 , wherein the article, person or concept is depicted in or suggested by the media stream.
| 0.903332 |
35. A touch system comprising: a touch panel having a touch surface; a device for generating an image that is presented on said touch surface; and computing structure executing at least one program and being coupled to said touch panel and said device, said computing structure being responsive to output generated by said touch panel in response to proximity of a pointing device to said touch surface and updating image data conveyed to said device so that images presented on said touch surface reflect the activity of said pointing device, said computing structure executing a routine to detect when a stationary pointing device contact on said touch surface that exceeds a first non-zero threshold duration occurs and in response updating the image data to signify visually the start of a potential input gesture entry, to determine when a gesture is made via interaction of said pointing device with said touch surface following said updating, in response to said gesture, to convert handwritten input drawn on said touch surface into a form suitable for said at least one program, to display the result of the conversion together with a clear result option, to enter the handwritten input into said at least one program substantially at a position indicated by said gesture upon selection of the conversion result and to clear the conversion result upon selection of said clear result option.
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35. A touch system comprising: a touch panel having a touch surface; a device for generating an image that is presented on said touch surface; and computing structure executing at least one program and being coupled to said touch panel and said device, said computing structure being responsive to output generated by said touch panel in response to proximity of a pointing device to said touch surface and updating image data conveyed to said device so that images presented on said touch surface reflect the activity of said pointing device, said computing structure executing a routine to detect when a stationary pointing device contact on said touch surface that exceeds a first non-zero threshold duration occurs and in response updating the image data to signify visually the start of a potential input gesture entry, to determine when a gesture is made via interaction of said pointing device with said touch surface following said updating, in response to said gesture, to convert handwritten input drawn on said touch surface into a form suitable for said at least one program, to display the result of the conversion together with a clear result option, to enter the handwritten input into said at least one program substantially at a position indicated by said gesture upon selection of the conversion result and to clear the conversion result upon selection of said clear result option. 36. A touch system according to claim 35 wherein the conversion result comprises one or more possible text representations of the handwritten input, and wherein the converted handwritten input corresponding to a selected text representation is entered into said at least one program.
| 0.5 |
1. A computer-implemented method comprising: receiving a first character of a query associated with a user of a social networking system in response to the user entering the first character into a text area displayed in a client device; obtaining a first result set comprising a plurality of objects from an object store of the social networking system that match the first character of the query; ordering at least a plurality of the objects of the first result set based at least in part on measures of affinities of the user for the objects, the measures of affinities of the user for the objects based at least in part on information about the user stored by the social networking system; providing at least a portion of the first result set to the client device; receiving a second character of the query in response to the user entering an the second character into the text area; obtaining a second result set of objects from the object store that match the first and second characters of the query; and providing at least a portion of the second result set to the client device.
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1. A computer-implemented method comprising: receiving a first character of a query associated with a user of a social networking system in response to the user entering the first character into a text area displayed in a client device; obtaining a first result set comprising a plurality of objects from an object store of the social networking system that match the first character of the query; ordering at least a plurality of the objects of the first result set based at least in part on measures of affinities of the user for the objects, the measures of affinities of the user for the objects based at least in part on information about the user stored by the social networking system; providing at least a portion of the first result set to the client device; receiving a second character of the query in response to the user entering an the second character into the text area; obtaining a second result set of objects from the object store that match the first and second characters of the query; and providing at least a portion of the second result set to the client device. 3. The computer-implemented method of claim 1 , further comprising obtaining a second result set of objects from the object store that match a concatenation of the first and second characters of the query.
| 0.826599 |
1. A computer-implemented process for identifying conceptually related terms in results of a search, comprising: using at least one computer to perform the following process actions: inputting a search query from a user; initiating the performance of a search of one or more databases using the search query as input from the user to produce search results; accessing the search results produced from the completed search performed using the search query as input from the user; identifying terms corresponding to the search query employed in the completed search; identifying word tokens in the search query terms; identifying potential phrases that can be made from the identified word tokens in the search query terms; identifying conceptually related words and phrases in the search results corresponding to the identified word tokens and potential phrases; and specifying the locations of the conceptually related words and phrases within the search results.
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1. A computer-implemented process for identifying conceptually related terms in results of a search, comprising: using at least one computer to perform the following process actions: inputting a search query from a user; initiating the performance of a search of one or more databases using the search query as input from the user to produce search results; accessing the search results produced from the completed search performed using the search query as input from the user; identifying terms corresponding to the search query employed in the completed search; identifying word tokens in the search query terms; identifying potential phrases that can be made from the identified word tokens in the search query terms; identifying conceptually related words and phrases in the search results corresponding to the identified word tokens and potential phrases; and specifying the locations of the conceptually related words and phrases within the search results. 14. The process of claim 1 , wherein the process action of identifying potential phrases that can be made from the identified words in the search query terms, comprises identifying all the phrases that can be constructed from the identified word tokens, up to a prescribed n-gram limit.
| 0.638681 |
8. A computer system comprising: a processor; a storage device coupled to the processor and storing instructions, that when executed by the processor, cause the processor to perform operations comprising: receiving a first query at a central information provider from a first client device over a network, identifying whether the first query includes one or more media-related terms, and in response to determining that the first query does not include one or more media-related terms, providing search results responsive to the first query in a format that includes a list of one or more uniform resource locator links; receiving a second query over the network; identifying one or more media-related terms in the second query that indicate the second query relates to one or more media-related objects; identifying one or more time-based terms in the second query; responding to the identification of the one or more media-related terms by: translating the time-based terms from a general time description to a time range; and receiving from a search engine media-specific results that are responsive to the second query; formatting the received media-specific results for display, wherein the format of the media-specific results provided in response to the second query is different than the format of the search results provided in response to the first query, and the media-specific results comprise: (a) a list of one or more program episodes that are responsive to the second query and that occur during the time range, the one or more program episodes in the list being grouped according to a program title and one or more broadcast date and time; and (b) a schedule grid that displays a plurality of programs on a plurality of different channels for a time period including at least the time range, and wherein the plurality of programs include one or more of the program episodes responsive to the second query, wherein the schedule grid is defined by a time axis and a channel axis and includes one or more indicators near particular ones of the plurality of programs that are provided in both the list and the schedule grid, the one or more indicators being used to signify that the particular ones of the plurality of programs match search criteria used to generate the list, and wherein the list and the schedule grid are to be displayed simultaneously next to each other; and generating code for the display of the formatted results.
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8. A computer system comprising: a processor; a storage device coupled to the processor and storing instructions, that when executed by the processor, cause the processor to perform operations comprising: receiving a first query at a central information provider from a first client device over a network, identifying whether the first query includes one or more media-related terms, and in response to determining that the first query does not include one or more media-related terms, providing search results responsive to the first query in a format that includes a list of one or more uniform resource locator links; receiving a second query over the network; identifying one or more media-related terms in the second query that indicate the second query relates to one or more media-related objects; identifying one or more time-based terms in the second query; responding to the identification of the one or more media-related terms by: translating the time-based terms from a general time description to a time range; and receiving from a search engine media-specific results that are responsive to the second query; formatting the received media-specific results for display, wherein the format of the media-specific results provided in response to the second query is different than the format of the search results provided in response to the first query, and the media-specific results comprise: (a) a list of one or more program episodes that are responsive to the second query and that occur during the time range, the one or more program episodes in the list being grouped according to a program title and one or more broadcast date and time; and (b) a schedule grid that displays a plurality of programs on a plurality of different channels for a time period including at least the time range, and wherein the plurality of programs include one or more of the program episodes responsive to the second query, wherein the schedule grid is defined by a time axis and a channel axis and includes one or more indicators near particular ones of the plurality of programs that are provided in both the list and the schedule grid, the one or more indicators being used to signify that the particular ones of the plurality of programs match search criteria used to generate the list, and wherein the list and the schedule grid are to be displayed simultaneously next to each other; and generating code for the display of the formatted results. 12. The system of claim 8 , wherein the list includes a plurality of groupings of the program episodes, and wherein the program episodes are grouped by programs of the program episodes.
| 0.569075 |
21. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for performing an exact search for specified data using the one or more indexes, said method steps comprising: associating specified data to a data cluster based on clustering information, said data cluster being a partition of an original data input set; reducing a dimensionality of the specified data, based on dimensionality reduction information for a reduced dimensionality version of the cluster; recursively applying said associating and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; and searching, using low dimensional indexes to said lowest level and a reduced dimensionality specified data, for cluster elements of the reduced dimensionality version of the cluster matching the specified data.
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21. A program storage device readable by a machine which includes one or more reduced dimensionality indexes to multidimensional data, the program storage device tangibly embodying a program of instructions executable by the machine to perform method steps for performing an exact search for specified data using the one or more indexes, said method steps comprising: associating specified data to a data cluster based on clustering information, said data cluster being a partition of an original data input set; reducing a dimensionality of the specified data, based on dimensionality reduction information for a reduced dimensionality version of the cluster; recursively applying said associating and reducing steps until a corresponding lowest level of a hierarchy of reduced dimensionality clusters has been reached; and searching, using low dimensional indexes to said lowest level and a reduced dimensionality specified data, for cluster elements of the reduced dimensionality version of the cluster matching the specified data. 22. The program storage device of claim 21, wherein the clustering information comprises an identifier of a centroid of the cluster associated with a unique label.
| 0.721349 |
1. A multi-data analysis based proactive defect detection and resolution system comprising: a data analyzer, executed by at least one hardware processor, to analyze operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, in response to a determination that the functionality related to the application is below the predetermined threshold associated with the functionality related to the application, generate an indication to perform defect analysis related to the functionality related to the application, perform, in response to the generated indication, a sentiment analysis on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis, in response to a determination that the sentiment is a negative sentiment, on the consumer data related to the application to determine a function associated with the negative sentiment; a defect detector, executed by the at least one hardware processor, to analyze, in response to the determination that the sentiment is the negative sentiment, application code and process data related to the application to determine a defect associated with the application by comparing a new user interaction pattern with the application to a previous user interaction pattern with the application, and in response to a determination that the new user interaction pattern with the application is different from the previous user interaction pattern with the application, identifying the defect associated with the application; and a defect resolver, executed by the at least one hardware processor, to modify a code of the application to correct the defect associated with the application.
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1. A multi-data analysis based proactive defect detection and resolution system comprising: a data analyzer, executed by at least one hardware processor, to analyze operational data for an application to determine whether a functionality related to the application is below a predetermined threshold associated with the functionality related to the application, in response to a determination that the functionality related to the application is below the predetermined threshold associated with the functionality related to the application, generate an indication to perform defect analysis related to the functionality related to the application, perform, in response to the generated indication, a sentiment analysis on consumer data related to the application to determine a sentiment of the consumer data related to the application, and a natural language processing (NLP) analysis, in response to a determination that the sentiment is a negative sentiment, on the consumer data related to the application to determine a function associated with the negative sentiment; a defect detector, executed by the at least one hardware processor, to analyze, in response to the determination that the sentiment is the negative sentiment, application code and process data related to the application to determine a defect associated with the application by comparing a new user interaction pattern with the application to a previous user interaction pattern with the application, and in response to a determination that the new user interaction pattern with the application is different from the previous user interaction pattern with the application, identifying the defect associated with the application; and a defect resolver, executed by the at least one hardware processor, to modify a code of the application to correct the defect associated with the application. 7. The multi-data analysis based proactive defect detection and resolution system according to claim 1 , wherein the data analyzer is to perform, in response to the generated indication, the NLP analysis, in response to the determination that the sentiment is the negative sentiment, on the consumer data related to the application to determine the function associated with the negative sentiment by comparing a text of the consumer data related to the application to a catalog of known functions related to the application, and based on a match of the text of the consumer data related to the application to a plurality of catalog functions from the catalog of known functions related to the application, identifying a catalog function from the plurality of catalog functions that includes a highest number of matches as the function associated with the negative sentiment.
| 0.532158 |
1. A method of suggesting a query for identifying documents in a litigation hold, comprising: receiving a training set of documents, wherein each document in the training set of documents is given a relevance indicator; identifying, by one or more processing devices, properties shared among documents having a similar relevance indicator, and an initial query with one or more initial keywords; determining a spatial proximity between one of the initial keywords and a set of keywords in the training set of documents; generating one or more neighboring queries from the initial query based on the spatial proximity, the neighboring queries including one or more additional queries; receiving a quality score of the neighboring queries, including an indication of a highest ranked neighboring query; repeating the generating one or more neighboring queries and receiving a quality score of the neighboring queries, wherein the highest ranked neighboring query is provided as the initial query, until an indication is received that a quality score of the highest ranked neighboring query is less than a quality score of the initial query, wherein a previously highest ranked neighboring query with a quality score greater than or equal to the quality score of the initial query is a resultant query; and generating a suggested litigation hold query based on the resultant query, wherein the suggested litigation hold query returns documents subject to the litigation hold.
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1. A method of suggesting a query for identifying documents in a litigation hold, comprising: receiving a training set of documents, wherein each document in the training set of documents is given a relevance indicator; identifying, by one or more processing devices, properties shared among documents having a similar relevance indicator, and an initial query with one or more initial keywords; determining a spatial proximity between one of the initial keywords and a set of keywords in the training set of documents; generating one or more neighboring queries from the initial query based on the spatial proximity, the neighboring queries including one or more additional queries; receiving a quality score of the neighboring queries, including an indication of a highest ranked neighboring query; repeating the generating one or more neighboring queries and receiving a quality score of the neighboring queries, wherein the highest ranked neighboring query is provided as the initial query, until an indication is received that a quality score of the highest ranked neighboring query is less than a quality score of the initial query, wherein a previously highest ranked neighboring query with a quality score greater than or equal to the quality score of the initial query is a resultant query; and generating a suggested litigation hold query based on the resultant query, wherein the suggested litigation hold query returns documents subject to the litigation hold. 3. The method of claim 1 , wherein the relevance indicator is given to the documents based on the result of a query.
| 0.603187 |
8. The method of claim 1 , wherein the transmitting step comprises transmitting the XML representation or the binary representation through the network based upon a choice of which representation to transmit.
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8. The method of claim 1 , wherein the transmitting step comprises transmitting the XML representation or the binary representation through the network based upon a choice of which representation to transmit. 9. The method of claim 8 , wherein the accessing and parsing steps need not be performed if the XML representation is chosen for transmission.
| 0.958479 |
11. A speech recognition method with cepstral noise subtraction, comprising: obtaining a plurality of first feature vectors according to a voice signal; obtaining a first feature vector of a preset voice frame and first feature vectors of a plurality of voice frames before the preset voice frame, so as to calculate a feature mean vector; calculating a second feature vector of a preset voice frame according to the first feature vector, the feature mean vector, a first scalar coefficient, and a second scalar coefficient of the preset voice frame; converting the second feature vector of the preset voice frame into a cepstral feature vector; calculating a model parameter according to the cepstral feature vector; and calculating a recognized voice signal according to the cepstral feature vector and the model parameter.
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11. A speech recognition method with cepstral noise subtraction, comprising: obtaining a plurality of first feature vectors according to a voice signal; obtaining a first feature vector of a preset voice frame and first feature vectors of a plurality of voice frames before the preset voice frame, so as to calculate a feature mean vector; calculating a second feature vector of a preset voice frame according to the first feature vector, the feature mean vector, a first scalar coefficient, and a second scalar coefficient of the preset voice frame; converting the second feature vector of the preset voice frame into a cepstral feature vector; calculating a model parameter according to the cepstral feature vector; and calculating a recognized voice signal according to the cepstral feature vector and the model parameter. 17. The speech recognition method according to claim 11 , wherein the first feature vectors are log Mel filterbank energy feature vectors.
| 0.793457 |
11. An article of manufacture having computer-readable program portions embodied thereon for review and adoption of a clinical content structure, the article comprising computer-readable instructions for: providing a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; receiving a default clinical content structure; selecting the default clinical content structure based on user input data from at least one of one or more users of the first authoring environment and one or more users of the second authoring environment; duplicating the default clinical content structure in the first authoring environment and the second authoring environment; displaying the duplicated clinical content structure for review by the one or more users of the first authoring environment and the one or more users of the second authoring environment; receiving first modification data based on a review of the duplicated clinical content structure by the one or more users of the first authoring environment and second modification data based on a review of the duplicated clinical content structure by the one or more users of the second authoring environment; customizing the duplicated clinical content structure based on the first modification data from the one or more users of the first authoring environment and the second modification data from the one or more users of the second authoring environment to create a customized clinical content structure; storing a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; storing a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; automatically translating the customized clinical content structure into a first standard structure using the first plurality of data translation rules; automatically translating the customized clinical content structure into a second standard structure using the second plurality of data translation rules; converting the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; converting the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and transmitting the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers.
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11. An article of manufacture having computer-readable program portions embodied thereon for review and adoption of a clinical content structure, the article comprising computer-readable instructions for: providing a first authoring environment that operates on a first set of one or more programmed computers associated with a first protocol and a second authoring environment that operates on a second set of one or more programmed computers associated with a second protocol, wherein the first set of one or more programmed computers and the second set of one or more programmed computers are communicatively coupled to a server via a network, the first protocol and the second protocol are different, and the clinical content structure comprises a set of one or more evidence-based options that are selectable by a clinician during patient care; receiving a default clinical content structure; selecting the default clinical content structure based on user input data from at least one of one or more users of the first authoring environment and one or more users of the second authoring environment; duplicating the default clinical content structure in the first authoring environment and the second authoring environment; displaying the duplicated clinical content structure for review by the one or more users of the first authoring environment and the one or more users of the second authoring environment; receiving first modification data based on a review of the duplicated clinical content structure by the one or more users of the first authoring environment and second modification data based on a review of the duplicated clinical content structure by the one or more users of the second authoring environment; customizing the duplicated clinical content structure based on the first modification data from the one or more users of the first authoring environment and the second modification data from the one or more users of the second authoring environment to create a customized clinical content structure; storing a first plurality of data translation rules associated with the first authoring environment, wherein each data translation rule of the first plurality of data translation rules maps at least one term associated with the first authoring environment to one or more terms of one or more standard term libraries; storing a second plurality of data translation rules associated with the second authoring environment, wherein each data translation rule of the second plurality of data translation rules maps at least one term associated with the second authoring environment to one or more terms of the one or more standard term libraries; automatically translating the customized clinical content structure into a first standard structure using the first plurality of data translation rules; automatically translating the customized clinical content structure into a second standard structure using the second plurality of data translation rules; converting the first standard structure into a first export structure that is executable by the first protocol of the first set of one or more programmed computers; converting the second standard structure into a second export structure that is executable by the second protocol of the second set of one or more programmed computers; and transmitting the first export structure to the first set of one or more programmed computers and the second export structure to the second set of one or more programmed computers. 13. The article of manufacture of claim 11 wherein the computer-readable instructions are web-based.
| 0.856164 |
9. The method of claim 1 , further comprising a step of using real-time feedback to modify the statistical information provided to one or more learning nodes of the set of learning nodes.
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9. The method of claim 1 , further comprising a step of using real-time feedback to modify the statistical information provided to one or more learning nodes of the set of learning nodes. 10. The method of claim 9 , wherein the real-time feedback comprises a response of a human agent to the relevance of the text to associated categories based upon the set of match scores.
| 0.929167 |
3. A system for allocating the execution of a database query between a database server and a storage system coupled to the database server via a communication network, comprising a load balancing module communicatively coupled to the database server, the load balancing module configured to: establish a ranking scheme comprising a plurality of rank values; assign a first rank from the plurality of rank values to the database query; determine whether the database query comprises at least an outer table query and an inner table query; if the database query comprises at least an outer table query and an inner table query, assign the first rank to an outer table query of the database query and assign a second rank to the inner table query of the database query; determine a threshold rank from the plurality of rank values; compare the first rank to the threshold rank; and if the first rank is greater than the threshold rank, communicate the database query to the database server for execution; and if the first rank is not greater than the threshold rank, communicate the database query to the storage system for execution.
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3. A system for allocating the execution of a database query between a database server and a storage system coupled to the database server via a communication network, comprising a load balancing module communicatively coupled to the database server, the load balancing module configured to: establish a ranking scheme comprising a plurality of rank values; assign a first rank from the plurality of rank values to the database query; determine whether the database query comprises at least an outer table query and an inner table query; if the database query comprises at least an outer table query and an inner table query, assign the first rank to an outer table query of the database query and assign a second rank to the inner table query of the database query; determine a threshold rank from the plurality of rank values; compare the first rank to the threshold rank; and if the first rank is greater than the threshold rank, communicate the database query to the database server for execution; and if the first rank is not greater than the threshold rank, communicate the database query to the storage system for execution. 4. The system of claim 3 , wherein the load balancing module is further configured to: determine whether the inner table query uses an index scan; and if the inner query uses an index scan, assign the highest value in the ranking scheme to be the value of the second rank; and if the inner query does not use an index scan, assign the second rank from a second plurality of rank values, wherein the second plurality of rank values are based at least on the number of rows resulting from the outer query of the database query.
| 0.5 |
1. A method for automated language analysis based on word-selection, comprising the steps: a) preparing a computer system ( 1 . 30 ) by aa) storing a plurality of reference language files ( 1 . 10 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ) in order to form a reference sample ( 1 . 40 ), wherein each reference language file ( 1 . 10 ) comprises a minimum number of 100 words, and each reference language file ( 1 . 10 ) originates from a different person having known characteristics, the characteristics including personality traits, ab) storing a dictionary file ( 2 . 20 ) containing a multiplicity of different categories ( 2 . 10 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein all the words in the dictionary file ( 2 . 20 ) are classified in at least one of the categories ( 2 . 10 ), ac) making an individual comparison of each reference language file ( 1 . 10 ) in the reference sample ( 1 . 40 ) with the dictionary file ( 2 . 20 ) by calculating the percentage frequency ( 3 . 40 ) of occurrence of the words in each reference language file ( 1 . 10 ) that are contained in each category ( 2 . 10 ) of the dictionary file ( 2 . 20 ), and ad) storing a set of rules ( 5 . 40 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein the set of rules uses statistical and/or algorithmic methods to calculate associations at least between the percentage frequencies ( 3 . 40 ) calculated in step ac) in one or more categories ( 2 . 10 ) and at least one known characteristic ( 4 . 20 ) of the people from whom the reference language files ( 1 . 10 ) originate, b) following preparation of the computer system in accordance with steps aa)-ad), recording and storing a language file ( 6 . 10 ), in addition to the reference language files ( 1 . 10 ) of the reference sample ( 1 . 40 ), in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein each language file ( 6 . 10 ) and each reference language file is one of a text file or an audio file that is converted into a text file by a transcription, c) analyzing the language file ( 6 . 10 ) additionally recorded and stored in step b), by ca) making an individual comparison of the language file ( 6 . 10 ) with the dictionary file ( 2 . 20 ) by calculating the percentage frequency ( 7 . 30 ) of the words in the language file ( 6 . 10 ) that are contained in each category ( 2 . 10 ) of the dictionary file ( 2 . 20 ), and cb) using the set of rules ( 5 . 40 ) to process the percentage frequencies ( 7 . 30 ) calculated in step ca), wherein the set of rules uses statistical and/or algorithmic methods to examine the percentage frequencies ( 7 . 30 ) calculated in step ca) for similarities with the percentage frequencies ( 3 . 40 ) calculated in step ac), and classifies the language file ( 6 . 10 ) according to the established similarities, and associates said file with at least one known characteristic belonging to the people from whom the reference language files ( 1 . 10 ) originate, d) creating an output file ( 8 . 20 ), which contains characteristics ( 4 . 20 ) associated with the language file ( 6 . 10 ) in step cb), and e) outputting the output file ( 8 . 20 ) by displaying the output file on a screen, outputting the output file using a speaker, transmitting the output file via a network, or printing the output file using a printer, f) fa) expanding the reference sample ( 1 . 40 ) in step aa) by adding as reference language files ( 1 . 10 ), each language file ( 6 . 10 ) recorded in step b), fb) providing a feedback through an input, which allows an evaluation of the correctness of the analysis of step c), and fc) updating and re-saving the set of rules ( 5 . 40 ) taking into account the enlarged database from step ad).
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1. A method for automated language analysis based on word-selection, comprising the steps: a) preparing a computer system ( 1 . 30 ) by aa) storing a plurality of reference language files ( 1 . 10 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ) in order to form a reference sample ( 1 . 40 ), wherein each reference language file ( 1 . 10 ) comprises a minimum number of 100 words, and each reference language file ( 1 . 10 ) originates from a different person having known characteristics, the characteristics including personality traits, ab) storing a dictionary file ( 2 . 20 ) containing a multiplicity of different categories ( 2 . 10 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein all the words in the dictionary file ( 2 . 20 ) are classified in at least one of the categories ( 2 . 10 ), ac) making an individual comparison of each reference language file ( 1 . 10 ) in the reference sample ( 1 . 40 ) with the dictionary file ( 2 . 20 ) by calculating the percentage frequency ( 3 . 40 ) of occurrence of the words in each reference language file ( 1 . 10 ) that are contained in each category ( 2 . 10 ) of the dictionary file ( 2 . 20 ), and ad) storing a set of rules ( 5 . 40 ) in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein the set of rules uses statistical and/or algorithmic methods to calculate associations at least between the percentage frequencies ( 3 . 40 ) calculated in step ac) in one or more categories ( 2 . 10 ) and at least one known characteristic ( 4 . 20 ) of the people from whom the reference language files ( 1 . 10 ) originate, b) following preparation of the computer system in accordance with steps aa)-ad), recording and storing a language file ( 6 . 10 ), in addition to the reference language files ( 1 . 10 ) of the reference sample ( 1 . 40 ), in a memory unit ( 1 . 20 ) of the computer system ( 1 . 30 ), wherein each language file ( 6 . 10 ) and each reference language file is one of a text file or an audio file that is converted into a text file by a transcription, c) analyzing the language file ( 6 . 10 ) additionally recorded and stored in step b), by ca) making an individual comparison of the language file ( 6 . 10 ) with the dictionary file ( 2 . 20 ) by calculating the percentage frequency ( 7 . 30 ) of the words in the language file ( 6 . 10 ) that are contained in each category ( 2 . 10 ) of the dictionary file ( 2 . 20 ), and cb) using the set of rules ( 5 . 40 ) to process the percentage frequencies ( 7 . 30 ) calculated in step ca), wherein the set of rules uses statistical and/or algorithmic methods to examine the percentage frequencies ( 7 . 30 ) calculated in step ca) for similarities with the percentage frequencies ( 3 . 40 ) calculated in step ac), and classifies the language file ( 6 . 10 ) according to the established similarities, and associates said file with at least one known characteristic belonging to the people from whom the reference language files ( 1 . 10 ) originate, d) creating an output file ( 8 . 20 ), which contains characteristics ( 4 . 20 ) associated with the language file ( 6 . 10 ) in step cb), and e) outputting the output file ( 8 . 20 ) by displaying the output file on a screen, outputting the output file using a speaker, transmitting the output file via a network, or printing the output file using a printer, f) fa) expanding the reference sample ( 1 . 40 ) in step aa) by adding as reference language files ( 1 . 10 ), each language file ( 6 . 10 ) recorded in step b), fb) providing a feedback through an input, which allows an evaluation of the correctness of the analysis of step c), and fc) updating and re-saving the set of rules ( 5 . 40 ) taking into account the enlarged database from step ad). 5. The method as claimed in claim 1 , wherein different dictionary files ( 2 . 20 ) are stored on the computer system ( 1 . 30 ) according to the intended use of the method.
| 0.665625 |
1. A method of storing descriptive metatag-value pairs for parametized information regarding first and second items having differing classifications, comprising: providing a first electronic interface through which a first human user identifies the first item in a first document to a computer system; prompting the first user to select a first classification for the first item, wherein the first user selects the first classification for the first item; providing the first user with a first set of metatag choices determined at least in part by the first user's selection of the first classification; presenting the first user with: (a) the first set of metatag choices for possible association with the first item, and (b) candidate values for at least one of the metatag choices that allows the first user to define a first metatag-value pair; providing a second electronic interface through which the first user creates a new metatag for the first set of metatag choices which based on an analysis of a second document that includes the second item, is subsequently displayed in the first set of metatag choices to a second human user for the second user to utilize in entering a second metatag-value pair for possible association with the second item in the second document; and storing an association of the first item and the new metatag in a data structure.
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1. A method of storing descriptive metatag-value pairs for parametized information regarding first and second items having differing classifications, comprising: providing a first electronic interface through which a first human user identifies the first item in a first document to a computer system; prompting the first user to select a first classification for the first item, wherein the first user selects the first classification for the first item; providing the first user with a first set of metatag choices determined at least in part by the first user's selection of the first classification; presenting the first user with: (a) the first set of metatag choices for possible association with the first item, and (b) candidate values for at least one of the metatag choices that allows the first user to define a first metatag-value pair; providing a second electronic interface through which the first user creates a new metatag for the first set of metatag choices which based on an analysis of a second document that includes the second item, is subsequently displayed in the first set of metatag choices to a second human user for the second user to utilize in entering a second metatag-value pair for possible association with the second item in the second document; and storing an association of the first item and the new metatag in a data structure. 6. The method of claim 1 , wherein the step of identifying the first item to the system comprises identifying a transportation device as the item.
| 0.507212 |
1. A method for creating a virtual personal assistant (“VPA”) computer application for a domain of interest, the method comprising, with a computing system: determining the domain of interest; accessing a computerized ontology defining a structure for representing knowledge relating to a plurality of domains including the domain of interest, each domain referring to a category of information and/or activities in relation to which the VPA computer application may conduct a conversational natural language dialog with a computing device user, the ontology having linked thereto a plurality of re-usable VPA components, each of the re-usable VPA components being accessible by an executable VPA engine to, during operation of the VPA, determine a likely intended goal of the computing device user based on a determined meaning of explicit and implicit conversational natural language input of the computing device user, execute a task on behalf of the computing device user, and/or generate a likely appropriate system output in response to the conversational natural language input; determining a data relationship between the domain of interest and at least a portion of the ontology; and suggesting a re-usable VPA component to use to create the VPA computer application for the domain of interest based on the data relationship between the domain of interest and the ontology.
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1. A method for creating a virtual personal assistant (“VPA”) computer application for a domain of interest, the method comprising, with a computing system: determining the domain of interest; accessing a computerized ontology defining a structure for representing knowledge relating to a plurality of domains including the domain of interest, each domain referring to a category of information and/or activities in relation to which the VPA computer application may conduct a conversational natural language dialog with a computing device user, the ontology having linked thereto a plurality of re-usable VPA components, each of the re-usable VPA components being accessible by an executable VPA engine to, during operation of the VPA, determine a likely intended goal of the computing device user based on a determined meaning of explicit and implicit conversational natural language input of the computing device user, execute a task on behalf of the computing device user, and/or generate a likely appropriate system output in response to the conversational natural language input; determining a data relationship between the domain of interest and at least a portion of the ontology; and suggesting a re-usable VPA component to use to create the VPA computer application for the domain of interest based on the data relationship between the domain of interest and the ontology. 3. The method of claim 1 , comprising creating a customized version of the suggested re-usable VPA component for the domain of interest.
| 0.654595 |
15. A manufacture comprising: non-transitory computer readable media comprising executable instructions, the executable instructions being executable by one or more processors to perform operations comprising: obtaining a translation of a message in a first language to a second language wherein the translation was submitted by a user; generating a part-of-speech (POS) n-gram representation of the translation comprising a plurality of POS n-grams of two or more different lengths; determining a respective probability for each POS n-gram as a ratio of a count of occurrences of the POS n-grams in a corpus for the second language to a count of all POS n-grams in the corpus having a same length as the POS n-gram and determining an accuracy of the translation based on a combination of the probabilities.
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15. A manufacture comprising: non-transitory computer readable media comprising executable instructions, the executable instructions being executable by one or more processors to perform operations comprising: obtaining a translation of a message in a first language to a second language wherein the translation was submitted by a user; generating a part-of-speech (POS) n-gram representation of the translation comprising a plurality of POS n-grams of two or more different lengths; determining a respective probability for each POS n-gram as a ratio of a count of occurrences of the POS n-grams in a corpus for the second language to a count of all POS n-grams in the corpus having a same length as the POS n-gram and determining an accuracy of the translation based on a combination of the probabilities. 20. The manufacture of claim 15 wherein generating the POS n-gram representation of the translation comprises: generating a first POS n-gram from the translation of a first length; calculating a probability of the first POS n-gram; and determining that the probability of the first POS n-gram does not exceed a threshold and, based thereon, breaking the first POS n-gram into two or more second POS n-grams having lengths that are less than the first length.
| 0.5 |
9. A computing system comprising: one or more processors; one or more hardware storage device storing computer executable instructions that when executed by the one or more processors cause the computing system to be configured with an architecture that improves a search engine's ability to output results for a given query by generating an enhanced token stream used to index a document stored at a knowledge base, and wherein the architecture comprises: a knowledge discovery module that receives a document; a preprocessing component that preprocesses the received document by removing article tags and other extraneous document data to format the received document in a plain text format whenever the received document is not already in a plain text format when received at the discovery module; an analyzer module that processes the received document once it is in a plain text format, and generates an enhanced token stream for the received document, by performing the following: at a tokenizer, converting the plain text into smaller atomic units that represent tokens corresponding to words or phrases and wherein the tokens form a token stream; enhancing the token stream by applying a plurality of filters to the token stream, wherein the plurality of filters comprise: (i) one or more canonicalization filters that perform at least one of the following: expand one or more camel-case words into corresponding constituent words added to the token stream; identify for one or more tokens a value type which is added to the token stream; and generate and add to the token stream a lower case version of an identified token; (ii) a truncation filter that removes from the token stream one or more frequently occurring common words represented by one or more tokens; (iii) an expansion filter that performs the following: identification of words in the token stream that are related to each other and are identified as at least two distinct tokens in the token stream, wherein identifying words in the token stream that are related to each other comprises: determining if a token in the token stream exists as an entity in a named entity list; determining if a next token in the token stream exists as a connected entity in the named entity list when the token is determined to exist in the named entity list; repeating the steps until the next token does not exist as a connected entity in the named entity list; and combining the at least two distinct tokens into a single token in the token stream; (iv) a normalization filter that returns corresponding words for one or more tokens to a base form; indexing the document with the enhanced token stream in a knowledge database; and using the indexed document to provide a response to a given query.
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9. A computing system comprising: one or more processors; one or more hardware storage device storing computer executable instructions that when executed by the one or more processors cause the computing system to be configured with an architecture that improves a search engine's ability to output results for a given query by generating an enhanced token stream used to index a document stored at a knowledge base, and wherein the architecture comprises: a knowledge discovery module that receives a document; a preprocessing component that preprocesses the received document by removing article tags and other extraneous document data to format the received document in a plain text format whenever the received document is not already in a plain text format when received at the discovery module; an analyzer module that processes the received document once it is in a plain text format, and generates an enhanced token stream for the received document, by performing the following: at a tokenizer, converting the plain text into smaller atomic units that represent tokens corresponding to words or phrases and wherein the tokens form a token stream; enhancing the token stream by applying a plurality of filters to the token stream, wherein the plurality of filters comprise: (i) one or more canonicalization filters that perform at least one of the following: expand one or more camel-case words into corresponding constituent words added to the token stream; identify for one or more tokens a value type which is added to the token stream; and generate and add to the token stream a lower case version of an identified token; (ii) a truncation filter that removes from the token stream one or more frequently occurring common words represented by one or more tokens; (iii) an expansion filter that performs the following: identification of words in the token stream that are related to each other and are identified as at least two distinct tokens in the token stream, wherein identifying words in the token stream that are related to each other comprises: determining if a token in the token stream exists as an entity in a named entity list; determining if a next token in the token stream exists as a connected entity in the named entity list when the token is determined to exist in the named entity list; repeating the steps until the next token does not exist as a connected entity in the named entity list; and combining the at least two distinct tokens into a single token in the token stream; (iv) a normalization filter that returns corresponding words for one or more tokens to a base form; indexing the document with the enhanced token stream in a knowledge database; and using the indexed document to provide a response to a given query. 10. The computing system of claim 9 wherein the value type filter identifies as values numerical values and Boolean values.
| 0.575407 |
1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon.
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1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. 7. The game apparatus as claimed in claim 1, wherein said topics comprise food, money, music, number, school, science, sports, and travel.
| 0.550189 |
1. A method of generating animation data for at least one rendered image of a computer graphics scene, the method comprising: receiving animation data defining at least a portion of a first pose of an object at a first shot time; identifying a previously defined first hold animation structure including the first shot time, wherein the first hold animation structure defines at least a second pose of the object from a second shot time prior to the first shot time up to a third shot time following the first shot time; replacing the first hold animation structure with a second hold animation structure defined as beginning at the second shot time and ending before the first shot time and a third hold animation structure defined from after the second hold animation structure up to the third shot time; associating the second pose of the object with the second hold animation structure, such that the object is posed according to at least the second pose during at least a portion of the second hold animation structure; associating the first pose of the object with the third hold animation structure, such that the object is posed according to at least the first pose during at least a portion of the third hold animation structure; and rendering at least one image of the computer graphics scene including at least a portion of the object in the first pose during the third hold animation structure.
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1. A method of generating animation data for at least one rendered image of a computer graphics scene, the method comprising: receiving animation data defining at least a portion of a first pose of an object at a first shot time; identifying a previously defined first hold animation structure including the first shot time, wherein the first hold animation structure defines at least a second pose of the object from a second shot time prior to the first shot time up to a third shot time following the first shot time; replacing the first hold animation structure with a second hold animation structure defined as beginning at the second shot time and ending before the first shot time and a third hold animation structure defined from after the second hold animation structure up to the third shot time; associating the second pose of the object with the second hold animation structure, such that the object is posed according to at least the second pose during at least a portion of the second hold animation structure; associating the first pose of the object with the third hold animation structure, such that the object is posed according to at least the first pose during at least a portion of the third hold animation structure; and rendering at least one image of the computer graphics scene including at least a portion of the object in the first pose during the third hold animation structure. 11. The method of claim 1 , wherein the animation data is selected from a group consisting of: user-provided animation data; application-provided animation data; forward kinematics animation data; inverse kinematics animation data; procedurally-generated animation data; simulation data; and motion capture data.
| 0.619592 |
16. A method comprising: receiving, at a first communication device, provisioning information indicating types of alerts to be applied for contact entries stored by the first communication device; detecting, by the first communication device, an auto-correction in a corrected text message of a target word of a group of words, the target word having a type; detecting, at the first communication device, an input command requesting a transmission of the corrected text message to a second communication device; and responsive to the detecting of the input command, presenting a correction alert at the first communication device indicating the target word that has been auto-corrected, wherein a type of the correction alert corresponds to the type of the target word.
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16. A method comprising: receiving, at a first communication device, provisioning information indicating types of alerts to be applied for contact entries stored by the first communication device; detecting, by the first communication device, an auto-correction in a corrected text message of a target word of a group of words, the target word having a type; detecting, at the first communication device, an input command requesting a transmission of the corrected text message to a second communication device; and responsive to the detecting of the input command, presenting a correction alert at the first communication device indicating the target word that has been auto-corrected, wherein a type of the correction alert corresponds to the type of the target word. 19. The method of claim 16 , comprising providing a recipient alert with the transmission of the corrected text message to the second communication device, wherein the recipient alert is configured for presentation at the second communication device to indicate the target word that has been auto-corrected, and wherein the recipient alert enables the second communication device to access an unmodified version of the target word.
| 0.795589 |
6. A method of selecting a microphone from two or more microphones for a multi-microphone speech processing system operating in a noisy environment, each of the microphones being associated with a respective channel and being suitable for picking up a noisy sound signal having a useful speech component from a main sound signal source (s(t)) mixed with a diffuse noise component, the method comprising the following steps: digitizing the sound signals picked up simultaneously by the two microphones (N, M); transforming the signals (x n (t), x m (t)) picked up on the two channels in such a manner as to produce a succession of frames in a series of frequency bands; applying an algorithm for calculating a speech-presence index of each channel; selecting one of the two microphones by applying a decision rule to the successive frames of each of the channels, which rule is a function both of a channel selection criterion and of said speech-presence index, and eliminating, from the successive frames, frequency bands that are situated beneath a second given threshold; and implementing speech processing on the basis of the sound signal picked up by the one selected microphone; which method is characterized in that: said transformation of the signals (x n (t), x m (t)) picked up on the two channels is a short-term Fourier transform; said speech-presence index is a confidence index calculated for each frequency band of each frame; and said selection criterion is calculated in frequency bands on only those frequency bands for which the confidence index is greater than a first given threshold, wherein: said multi-microphone speech processor system is a system having spaced-apart directional or non-directional microphones; and said channel selection criterion is an energy criterion based on comparing respective signal-to-noise ratio values of the signals picked up simultaneously on the two channels, the microphone for selection being the microphone for which the signal-to-noise ratio is greater than the other.
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6. A method of selecting a microphone from two or more microphones for a multi-microphone speech processing system operating in a noisy environment, each of the microphones being associated with a respective channel and being suitable for picking up a noisy sound signal having a useful speech component from a main sound signal source (s(t)) mixed with a diffuse noise component, the method comprising the following steps: digitizing the sound signals picked up simultaneously by the two microphones (N, M); transforming the signals (x n (t), x m (t)) picked up on the two channels in such a manner as to produce a succession of frames in a series of frequency bands; applying an algorithm for calculating a speech-presence index of each channel; selecting one of the two microphones by applying a decision rule to the successive frames of each of the channels, which rule is a function both of a channel selection criterion and of said speech-presence index, and eliminating, from the successive frames, frequency bands that are situated beneath a second given threshold; and implementing speech processing on the basis of the sound signal picked up by the one selected microphone; which method is characterized in that: said transformation of the signals (x n (t), x m (t)) picked up on the two channels is a short-term Fourier transform; said speech-presence index is a confidence index calculated for each frequency band of each frame; and said selection criterion is calculated in frequency bands on only those frequency bands for which the confidence index is greater than a first given threshold, wherein: said multi-microphone speech processor system is a system having spaced-apart directional or non-directional microphones; and said channel selection criterion is an energy criterion based on comparing respective signal-to-noise ratio values of the signals picked up simultaneously on the two channels, the microphone for selection being the microphone for which the signal-to-noise ratio is greater than the other. 10. The method of claim 6 , wherein, if it is decided to select one of the microphones, said selection is performed progressively over a given transition time lapse by applying increasing gain to the channel of the microphone that is to be selected and decreasing gain to the channel of the microphone that is to be deselected.
| 0.5 |
1. A method for proposing candidate solutions for updating a knowledge base, comprising: for each of a set of knowledge base solutions, each knowledge base solution comprising a sequence of main steps, expressed in a natural language, to be performed on a class of device, processing the knowledge base solution to generate a first action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; receiving a recorded solution, expressed in a natural language, comprising actions performed on a device in the device class; processing the recorded solution to generate a second action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; with a processor, comparing the second action sequence with each of the first action sequences to determine whether the recorded solution corresponds to one of the knowledge base solutions; and based on the comparison, providing for proposing an update to the knowledge base, based on the recorded solution.
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1. A method for proposing candidate solutions for updating a knowledge base, comprising: for each of a set of knowledge base solutions, each knowledge base solution comprising a sequence of main steps, expressed in a natural language, to be performed on a class of device, processing the knowledge base solution to generate a first action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; receiving a recorded solution, expressed in a natural language, comprising actions performed on a device in the device class; processing the recorded solution to generate a second action sequence of atomic steps, each of the atomic steps including a verb and an object, the object comprising a noun which is in a syntactic dependency with the verb; with a processor, comparing the second action sequence with each of the first action sequences to determine whether the recorded solution corresponds to one of the knowledge base solutions; and based on the comparison, providing for proposing an update to the knowledge base, based on the recorded solution. 16. The method of claim 1 , wherein the recorded solution is made by a person who records the solution based on actions performed on the device during a repair of the device or by an agent who instructs a person to perform actions on the device during a repair of the device.
| 0.561969 |
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