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9,665,543 | 1 | 10 |
1. A method for supporting links within a document containing text, the method comprising: identifying representations embedded within a word processor document of links to sources external to the word processor document, the word processor document produced using a word processor program running on a computing system and configured to create, edit and display both text and hyperlinks within the word processor document; appending the word processor document to include initial content representations comprising all content of each external source; identifying a current validity status automatically for each identified link representation during creation of the word processor document, at an initial time of publication of the word processing document and at a later time after initial publication, the validity status comprising accuracy of the link representation, functionality of the link representation, accessibility of the external sources and content of the external sources; expressing the identified current validity status of one or more of the identified link representations using aspects of the document other than the identified link representations; and providing notification to an author and readers of the word processor document of the current validity status.
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1. A method for supporting links within a document containing text, the method comprising: identifying representations embedded within a word processor document of links to sources external to the word processor document, the word processor document produced using a word processor program running on a computing system and configured to create, edit and display both text and hyperlinks within the word processor document; appending the word processor document to include initial content representations comprising all content of each external source; identifying a current validity status automatically for each identified link representation during creation of the word processor document, at an initial time of publication of the word processing document and at a later time after initial publication, the validity status comprising accuracy of the link representation, functionality of the link representation, accessibility of the external sources and content of the external sources; expressing the identified current validity status of one or more of the identified link representations using aspects of the document other than the identified link representations; and providing notification to an author and readers of the word processor document of the current validity status. 10. The method of claim 1 , wherein the step of expressing the identified current validity status further comprises providing a visual indication within a printed copy of the word processor document or on a printer separator page that is provided when the word processor document is printed.
| 0.829426 |
9,055,509 | 21 | 22 |
21. A method according to claim 19 , wherein the situational parameters include one or more parameters characterizing an automobile driving environment.
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21. A method according to claim 19 , wherein the situational parameters include one or more parameters characterizing an automobile driving environment. 22. A method according to claim 21 , wherein the situational parameters include one or more parameters characterizing automobile speed, approaching objects, traffic, conditions, road conditions, weather conditions, and physical environment conditions.
| 0.5 |
9,350,636 | 7 | 8 |
7. Logic encoded in one or more non-transitory tangible media that includes code for execution and when executed by a processor is operable to perform operations comprising: processing a first text created by a user using an online service into a first bag of words, the first bag of words comprising a list of words that appear in the text, each of the words having associated therewith a number representing a number of times the associated word appears in the text; computing a similarity between the first bag of words and at least one second bag of words, wherein the computing comprises, for each word in the first bag of words, determining a compare count comprising a minimum number of times the word appears in each of the first bag of words and the second bag of words and adding the compare count to a sum of counts, wherein the computed similarity comprises two times the sum of counts divided by the total number of words in the first bag of words and the second bag of words; comparing the computed similarity with a threshold; and determining that the user is a spammer and preventing the user from using the online service to create additional texts if the computed similarity is greater than the threshold, wherein the first text comprises a user profile of the user in connection with the online service.
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7. Logic encoded in one or more non-transitory tangible media that includes code for execution and when executed by a processor is operable to perform operations comprising: processing a first text created by a user using an online service into a first bag of words, the first bag of words comprising a list of words that appear in the text, each of the words having associated therewith a number representing a number of times the associated word appears in the text; computing a similarity between the first bag of words and at least one second bag of words, wherein the computing comprises, for each word in the first bag of words, determining a compare count comprising a minimum number of times the word appears in each of the first bag of words and the second bag of words and adding the compare count to a sum of counts, wherein the computed similarity comprises two times the sum of counts divided by the total number of words in the first bag of words and the second bag of words; comparing the computed similarity with a threshold; and determining that the user is a spammer and preventing the user from using the online service to create additional texts if the computed similarity is greater than the threshold, wherein the first text comprises a user profile of the user in connection with the online service. 8. The logic of claim 7 , wherein the processing a first text into a first bag of words comprises processing each of a plurality of first texts into a first bag of words.
| 0.5 |
9,727,619 | 11 | 18 |
11. A method comprising: receiving, by a computing device, an input data set comprising a document; determining, by the computing device, at least one focus in the input data set, wherein the focus is at least one of a grammatical part of speech or a functional descriptor, and the focus is a portion of the input data set less than the input data set; forming, by the computing device, a term unit matrix from the input data set, the term unit matrix comprising a plurality of numeric integer values, the plurality of numeric integer values corresponding to a plurality of term units of the input data set, wherein the plurality of numeric integer values is a substantially lossless representation of the input data set; filtering, by the computing device, the plurality of term units by removing one or more term units from the plurality of term units based on the focus; forming, by the computing device, a group of combinations of term units that remain after filtering and that are based on an underlying grammatical rule of the input data set, wherein for each term unit of the group of combinations of term units, the underlying grammatical rule is numerically encoded in respective numeric integer values of the group of combinations of term units; identifying, by the computing device, at least one root term unit of the group of combinations of term units that remain after filtering, the at least one root term unit having a plurality of tail term units associated therewith; searching, by the computing device, a data repository that is different from the input data set using the at least one root term unit and the plurality of tail term units; organizing, by the computing device, search results based on the focus indicating presence of the at least one root term unit; and providing, by the computing device, the organized search results.
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11. A method comprising: receiving, by a computing device, an input data set comprising a document; determining, by the computing device, at least one focus in the input data set, wherein the focus is at least one of a grammatical part of speech or a functional descriptor, and the focus is a portion of the input data set less than the input data set; forming, by the computing device, a term unit matrix from the input data set, the term unit matrix comprising a plurality of numeric integer values, the plurality of numeric integer values corresponding to a plurality of term units of the input data set, wherein the plurality of numeric integer values is a substantially lossless representation of the input data set; filtering, by the computing device, the plurality of term units by removing one or more term units from the plurality of term units based on the focus; forming, by the computing device, a group of combinations of term units that remain after filtering and that are based on an underlying grammatical rule of the input data set, wherein for each term unit of the group of combinations of term units, the underlying grammatical rule is numerically encoded in respective numeric integer values of the group of combinations of term units; identifying, by the computing device, at least one root term unit of the group of combinations of term units that remain after filtering, the at least one root term unit having a plurality of tail term units associated therewith; searching, by the computing device, a data repository that is different from the input data set using the at least one root term unit and the plurality of tail term units; organizing, by the computing device, search results based on the focus indicating presence of the at least one root term unit; and providing, by the computing device, the organized search results. 18. The method of claim 11 , wherein providing comprises displaying organized search results to a human-machine interface.
| 0.881783 |
9,396,257 | 1 | 4 |
1. A method performed on a computing device that includes at least one processor and memory, the method comprising: matching, by the computing device, an audio rendition to an audio recording based on alignment of pitch contours of the audio rendition and a portion of the audio recording, and further based on similarities between pitch intervals and durations of notes of the aligned rendition and the aligned portion, where the pitch contours each indicate any variation in pitch of a note of the notes relative to a previous note of the notes, where the pitch intervals each indicate a frequency of the note, and where the durations each indicate a length in time of the note; and adding, by the computing device based on a weighting of the portion of the matched audio recording, the matched audio recording to a selection set.
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1. A method performed on a computing device that includes at least one processor and memory, the method comprising: matching, by the computing device, an audio rendition to an audio recording based on alignment of pitch contours of the audio rendition and a portion of the audio recording, and further based on similarities between pitch intervals and durations of notes of the aligned rendition and the aligned portion, where the pitch contours each indicate any variation in pitch of a note of the notes relative to a previous note of the notes, where the pitch intervals each indicate a frequency of the note, and where the durations each indicate a length in time of the note; and adding, by the computing device based on a weighting of the portion of the matched audio recording, the matched audio recording to a selection set. 4. The method of claim 1 further comprising returning information describing the matching audio recording.
| 0.522523 |
9,110,706 | 11 | 12 |
11. A method of claim 7 , further including the processor optimizing the execution plan at the client machine based on inferred properties.
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11. A method of claim 7 , further including the processor optimizing the execution plan at the client machine based on inferred properties. 12. A machine implemented method as recited in claim 11 , wherein the optimizing the execution plan is a static optimization performed at the client machine.
| 0.5 |
4,682,955 | 1 | 5 |
1. An educational toy comprising a body having a peripheral vertical wall, a guide plate secured on said body and having a plurality of cutouts to be passages, a connecting passage formed between said vertical wall and said guide plate for communicating with said cutouts, a spacer disposed between said guide plate and said body, a plurality of slider pieces slidably and undetachably movable along said cutouts and said connecting passage and a plurality of inwardly extending lugs formed inside the peripheral vertical wall of the body to prevent detachment of said slider pieces.
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1. An educational toy comprising a body having a peripheral vertical wall, a guide plate secured on said body and having a plurality of cutouts to be passages, a connecting passage formed between said vertical wall and said guide plate for communicating with said cutouts, a spacer disposed between said guide plate and said body, a plurality of slider pieces slidably and undetachably movable along said cutouts and said connecting passage and a plurality of inwardly extending lugs formed inside the peripheral vertical wall of the body to prevent detachment of said slider pieces. 5. An educational toy as defined in claim 1, wherein said slider pieces are the same number as the cutouts of said guide plate.
| 0.761278 |
9,836,448 | 1 | 2 |
1. A method for text editing on an electronic device having a processor and display, the method comprising: receiving user input corresponding to at least one keystroke at the electronic device during text entry in a text editing program; disambiguating ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the electronic device, wherein the first specific subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, displaying a plurality of specific subject matter lexicons to the user of the electronic device while displaying text previously entered within the text editing program; receiving a selection by the user of the electronic device of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguating the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and displaying at least one disambiguation result to the user of the electronic device.
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1. A method for text editing on an electronic device having a processor and display, the method comprising: receiving user input corresponding to at least one keystroke at the electronic device during text entry in a text editing program; disambiguating ambiguous keystrokes from the user input at least based on simultaneous use of a common language dictionary, a user dictionary, and a first specific subject matter lexicon selected by a user of the electronic device, wherein the first specific subject matter lexicon is related to a first particular professional area; then, in response to a user input indicating a lexicon swap, displaying a plurality of specific subject matter lexicons to the user of the electronic device while displaying text previously entered within the text editing program; receiving a selection by the user of the electronic device of a second specific subject matter lexicon from the plurality of specific subject matter lexicons displayed to the user, wherein the second specific subject matter lexicon is related to a second particular professional area; disambiguating the ambiguous keystrokes from the user input at least based on simultaneous use of the common language dictionary, the user dictionary, and the second specific subject matter lexicon; and displaying at least one disambiguation result to the user of the electronic device. 2. The method according to claim 1 , wherein at least the first specific subject matter lexicon or the second specific subject matter lexicon includes medical terminology.
| 0.755714 |
10,007,803 | 1 | 7 |
1. A computer implemented method executed by one or more computing devices for searching encrypted keywords in a database, the method comprising: generating a keyword; based on the generated keyword, creating, at a data owner computing device, two or more different encrypted keywords corresponding to the generated keyword; storing the two or more different encrypted keywords for the generated keyword in the database, wherein the database is stored on a data provider computing device and storing the two or more different encrypted keywords comprises sending the two or more different encrypted keywords from the data owner computing device to the data provider computing device; generating, by the data owner computing device, a first trapdoor that matches at least one of the two or more different encrypted keywords stored in the database; generating, by the data owner computing device, a second trapdoor, different from the first trapdoor, that matches at least one of the two or more different encrypted keywords stored in the database; receiving, at the data owner computing device, a first request for a trapdoor for the generated keyword from a data user computing device; responsive to the first request, sending the first trapdoor from the data owner computing device to the data user computing device for use in searching of the encrypted keywords in the database, wherein the first trapdoor causes a keyword-is-found result when the first trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device; receiving, at the data owner computing device, a second request for a trapdoor for the generated keyword from the data user computing device; and responsive to the second request, sending the second trapdoor from the data owner computing device to the data user computing device for use in searching the encrypted keywords in the database, wherein the second trapdoor causes a keyword-is-found result when the second trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device.
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1. A computer implemented method executed by one or more computing devices for searching encrypted keywords in a database, the method comprising: generating a keyword; based on the generated keyword, creating, at a data owner computing device, two or more different encrypted keywords corresponding to the generated keyword; storing the two or more different encrypted keywords for the generated keyword in the database, wherein the database is stored on a data provider computing device and storing the two or more different encrypted keywords comprises sending the two or more different encrypted keywords from the data owner computing device to the data provider computing device; generating, by the data owner computing device, a first trapdoor that matches at least one of the two or more different encrypted keywords stored in the database; generating, by the data owner computing device, a second trapdoor, different from the first trapdoor, that matches at least one of the two or more different encrypted keywords stored in the database; receiving, at the data owner computing device, a first request for a trapdoor for the generated keyword from a data user computing device; responsive to the first request, sending the first trapdoor from the data owner computing device to the data user computing device for use in searching of the encrypted keywords in the database, wherein the first trapdoor causes a keyword-is-found result when the first trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device; receiving, at the data owner computing device, a second request for a trapdoor for the generated keyword from the data user computing device; and responsive to the second request, sending the second trapdoor from the data owner computing device to the data user computing device for use in searching the encrypted keywords in the database, wherein the second trapdoor causes a keyword-is-found result when the second trapdoor is compared to the two or more encrypted keywords for the generated keyword in the database stored on the data provider computing device. 7. The method as claimed in claim 1 , wherein generating the first and second trapdoors comprises using a function T W =[L,K], where L is y·(H 1 (W)+s t ) −1 P 0 , K is y·P 0 , where y is a random number, H 1 is a hash function, W is the generated keyword, s t is a secret key, and P 0 is a generator of a group G1.
| 0.679226 |
8,035,534 | 1 | 9 |
1. A method of enabling input on a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a linguistic source stored on a memory, the input apparatus having a number of input members with at least some of the input members each having a number of linguistic elements assigned thereto, including input members having a non-diacritical version of linguistic elements assigned thereto and at least one diacritical version of those linguistic elements assigned thereto, and other non-diacritical input members having only non-diacritical versions of linguistic elements assigned thereto, the method comprising: detecting an actuation of one of the input members; based upon the detection of the actuation, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the one of the input members or (ii) a diacritical version of the linguistic element assigned to the one of the input members in response to the actuation, the determination comprising: determining whether the actuation corresponds to a first alphanumeric input for the enabled input, based upon a determination that the actuation corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the one of the input members, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus.
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1. A method of enabling input on a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a linguistic source stored on a memory, the input apparatus having a number of input members with at least some of the input members each having a number of linguistic elements assigned thereto, including input members having a non-diacritical version of linguistic elements assigned thereto and at least one diacritical version of those linguistic elements assigned thereto, and other non-diacritical input members having only non-diacritical versions of linguistic elements assigned thereto, the method comprising: detecting an actuation of one of the input members; based upon the detection of the actuation, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the one of the input members or (ii) a diacritical version of the linguistic element assigned to the one of the input members in response to the actuation, the determination comprising: determining whether the actuation corresponds to a first alphanumeric input for the enabled input, based upon a determination that the actuation corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the one of the input members, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. 9. The method according to claim 1 , wherein the determined output is identified based on a verb of a certain class.
| 0.790614 |
8,321,396 | 8 | 9 |
8. A computer program product having program codes stored on a non-transitory computer storage medium for automatically extracting by-line information in a document, wherein said document contains a single news article, comprising: a program code for removing formatting tags from said document to create a de-tagged version of said document; a program code for detecting a set of potential headlines of the document from a title meta-tag of the document, wherein each of the set of potential headlines comprises a separate line of the lines of text in the de-tagged version of the document; a program code for selecting a candidate headline from the set of potential headlines, wherein the program code for selecting the candidate headline evaluates the potential headlines from the set of potential headlines in order of lengths of the potential headlines, by: identifying a location of the selected candidate headline being evaluated in a de-tagged version of the document; verifying the selected candidate headline as comprising a complete line at the identified location in the de-tagged content; verifying the length of the selected candidate headline exceeds a minimum length in the de-tagged content; and ensuring that the selected candidate headline comprises regular text in the de-tagged version of said document; and a program code for extracting the by-line information from the detagged version of the document using the location of the selected candidate headline, wherein the selected candidate headline is the longest of the set of potential headlines, wherein the program code for detecting the set of potential headlines of the document is further configured to detect the selected candidate headline from the de-tagged version of the document, and wherein in response to the selected candidate headline's not being detected in the de-tagged version of the document, selecting the next longest remaining of the set of potential headlines as the selected candidate headline.
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8. A computer program product having program codes stored on a non-transitory computer storage medium for automatically extracting by-line information in a document, wherein said document contains a single news article, comprising: a program code for removing formatting tags from said document to create a de-tagged version of said document; a program code for detecting a set of potential headlines of the document from a title meta-tag of the document, wherein each of the set of potential headlines comprises a separate line of the lines of text in the de-tagged version of the document; a program code for selecting a candidate headline from the set of potential headlines, wherein the program code for selecting the candidate headline evaluates the potential headlines from the set of potential headlines in order of lengths of the potential headlines, by: identifying a location of the selected candidate headline being evaluated in a de-tagged version of the document; verifying the selected candidate headline as comprising a complete line at the identified location in the de-tagged content; verifying the length of the selected candidate headline exceeds a minimum length in the de-tagged content; and ensuring that the selected candidate headline comprises regular text in the de-tagged version of said document; and a program code for extracting the by-line information from the detagged version of the document using the location of the selected candidate headline, wherein the selected candidate headline is the longest of the set of potential headlines, wherein the program code for detecting the set of potential headlines of the document is further configured to detect the selected candidate headline from the de-tagged version of the document, and wherein in response to the selected candidate headline's not being detected in the de-tagged version of the document, selecting the next longest remaining of the set of potential headlines as the selected candidate headline. 9. The computer program product of claim 8 , wherein the program code for detecting the set of potential headlines constructs the set of potential headlines based on the title meta-tag.
| 0.63 |
8,090,724 | 1 | 2 |
1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection.
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1. A method comprising: receiving an ordered collection of text-based terms; analyzing groupings of consecutive text-based terms in the ordered collection to identify occurrences of different combinations of consecutive text-based terms in the ordered collection; and maintaining frequency information representing the occurrences of the different combinations of consecutive text-based terms in the collection. 2. The method as in claim 1 further comprising: based on the analyzing, creating a tree in which a first term in a given grouping of the groupings is defined as a parent node in the tree and a second term in the given grouping is defined as a child node of the parent node in the tree. both the first term and the second term in the given grouping being consecutive text-based terms present in the order collection.
| 0.793121 |
8,364,509 | 1 | 35 |
1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user.
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1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 35. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for at least one time percentage report.
| 0.806757 |
9,703,830 | 14 | 15 |
14. The system of claim 13 , wherein at least two of the plurality of nodes are connected with one another through an edge, wherein navigating the one or more graphs to traverse to the one or more reached nodes connected to the selected node comprises: identifying the one or more edges associated with the selected node in the one or more graphs; and navigating the one or more graphs to reach the one or more reached nodes connected to the selected node through the one or more associated edges.
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14. The system of claim 13 , wherein at least two of the plurality of nodes are connected with one another through an edge, wherein navigating the one or more graphs to traverse to the one or more reached nodes connected to the selected node comprises: identifying the one or more edges associated with the selected node in the one or more graphs; and navigating the one or more graphs to reach the one or more reached nodes connected to the selected node through the one or more associated edges. 15. The system of claim 14 , wherein the one or more graphs are navigated simultaneously through the one or more associated edges to reach the one or more reached nodes connected to the selected node.
| 0.774266 |
8,645,391 | 1 | 4 |
1. A computer-implemented method, comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values.
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1. A computer-implemented method, comprising: obtaining an initial attribute whitelist, the initial attribute whitelist including one or more initial attributes; processing a first collection of documents, wherein each of the documents has content to be displayed and an underlying structure that defines how the content is to be displayed, to identify a plurality of pairings of candidate attributes with candidate values in the documents, wherein each candidate attribute and each candidate value is content found in the content to be displayed; grouping the candidate attributes into a plurality of groups according to both a particular document in the first collection in which each candidate attribute was identified and the underlying structure in the particular document in the first collection in which each candidate attribute was identified; calculating a score for each unique attribute in the candidate attributes, where the score reflects a number of groups containing both the unique attribute and an attribute on the initial attribute whitelist; generating an expanded attribute whitelist, the expanded attribute whitelist including the initial attributes and each unique attribute having a respective score that satisfies a threshold; and using the expanded attribute whitelist to identify valid pairings of candidate attributes with candidate values. 4. The method of claim 1 , where the score further reflects a number of attributes on the initial attribute whitelist that are in a group with the unique attribute.
| 0.93317 |
7,974,938 | 11 | 12 |
11. A system for storing and using a set of observations of real-world events and actions, the system comprising: a cluster generator for generating clusters based on the set of observations, each cluster representing correlations between events and actions in a subset of observations in the set of observations; and a graph processor coupled to the cluster generator for processing the clusters into a first linked graph based on a set of rules to identify correlations between the events and actions, the first linked graph tagged to indicate the correlations between the events and the actions; wherein the cluster generator presupposes an event as reversible unless an observation contradicting reversibility of the event is obtained, and wherein the graph processor tags an edge associated with the irreversible event as having uncertain correlations with actions that are irreversible.
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11. A system for storing and using a set of observations of real-world events and actions, the system comprising: a cluster generator for generating clusters based on the set of observations, each cluster representing correlations between events and actions in a subset of observations in the set of observations; and a graph processor coupled to the cluster generator for processing the clusters into a first linked graph based on a set of rules to identify correlations between the events and actions, the first linked graph tagged to indicate the correlations between the events and the actions; wherein the cluster generator presupposes an event as reversible unless an observation contradicting reversibility of the event is obtained, and wherein the graph processor tags an edge associated with the irreversible event as having uncertain correlations with actions that are irreversible. 12. The system of claim 11 , further comprising: a storage device coupled between the cluster generator and the graph processor for storing the clusters generated by the cluster generator; an interface module coupled to the graph processor to provide a target event signal intended to cause a real-world event; and a controller for controlling an effector according to commands generated by the graph processor based on the first linked graph to cause the intended real-world event.
| 0.5 |
8,620,951 | 9 | 13 |
9. The system of claim 5 , wherein the computation component determines a fifth conditional probability, P(T|R), of the domain topic given the result.
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9. The system of claim 5 , wherein the computation component determines a fifth conditional probability, P(T|R), of the domain topic given the result. 13. The system of claim 9 , wherein the computation component determines P(T|R) based upon a comparison of a string between text associated with the result and at least one knowledge database.
| 0.596639 |
9,743,118 | 4 | 5 |
4. The method of claim 3 , further comprising: receiving a member dialogue video from the first community member, wherein the member dialogue video expresses at least one of a personal opinion and a personal viewpoint of the first community member about at least a portion of the thematic content event associated with the rant video; storing the member dialogue video of the first community member with a plurality of other member dialogue videos generated by other community members; and generating a conversation video that comprises: selected ones of the plurality of other member dialogue videos generated by other community members; and the member dialogue video of the first community member only if the first community member's assertion has been affirmed based on the received affirmation votes and denial of affirmation votes, wherein the conversation video emulates a conversation about the thematic content event between the community members who have had their member dialogue videos included in the generated conversation video.
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4. The method of claim 3 , further comprising: receiving a member dialogue video from the first community member, wherein the member dialogue video expresses at least one of a personal opinion and a personal viewpoint of the first community member about at least a portion of the thematic content event associated with the rant video; storing the member dialogue video of the first community member with a plurality of other member dialogue videos generated by other community members; and generating a conversation video that comprises: selected ones of the plurality of other member dialogue videos generated by other community members; and the member dialogue video of the first community member only if the first community member's assertion has been affirmed based on the received affirmation votes and denial of affirmation votes, wherein the conversation video emulates a conversation about the thematic content event between the community members who have had their member dialogue videos included in the generated conversation video. 5. The method of claim 4 , after the generation of the conversation video, the method further comprising: receiving, from a third media device, a first request for the generated conversation video from a third community member who is another member of the plurality of community members, wherein the request includes information that identifies the media content event; and communicating the conversation video to the third media device used by the requesting third community member, wherein the conversation video is presented by the third media device to the third community member.
| 0.5 |
9,632,985 | 55 | 68 |
55. A method for electronic learning comprising: retrieving, at a first electronic reading device executing a first execution environment, a digital specification in a first language that is one of a plurality of heterogeneous execution environments, wherein the first execution environment has platform-dependent capabilities and user interface elements, and pre-processed media data of at least one interactive content presentation object for the electronic reading device, wherein the at least one interactive content presentation object is presented with a look and feel of a user interface of the electronic reading device, and wherein the media data is pre-processed to adjust for the platform-dependent capabilities of the execution environment and to ensure a consistent layout within and around the at least one interactive content presentation object across heterogeneous execution environments; parsing the digital specification, and responsive to instructions contained in the digital specification, presenting in the first execution environment of the first electronic reading device one or more interactive content presentation objects and one or more interactive assessment objects by converting the instructions in the digital specification to a second language which is executed by one or more computer processors of the first electronic reading device; receiving content interaction data corresponding to user interactions with the interactive content presentation objects and sending the interaction data to an interaction server; receiving a second content interaction data corresponding to a second user's interactions with the interactive content presentation objects from the interaction server, the second user's interactions having been received at the interaction server from a second electronic reading device executing a second execution environment different from the first execution environment and within which the digital specification was presented with a consistent layout within and around the interactive content presentation objects and interactive assessment objects in comparison to the digital specification in the first execution environment of the first electronic reading device; presenting, in the first execution environment, the second content interaction data; and sending to the interaction server, assessment data corresponding to user interactions with the interactive assessment objects.
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55. A method for electronic learning comprising: retrieving, at a first electronic reading device executing a first execution environment, a digital specification in a first language that is one of a plurality of heterogeneous execution environments, wherein the first execution environment has platform-dependent capabilities and user interface elements, and pre-processed media data of at least one interactive content presentation object for the electronic reading device, wherein the at least one interactive content presentation object is presented with a look and feel of a user interface of the electronic reading device, and wherein the media data is pre-processed to adjust for the platform-dependent capabilities of the execution environment and to ensure a consistent layout within and around the at least one interactive content presentation object across heterogeneous execution environments; parsing the digital specification, and responsive to instructions contained in the digital specification, presenting in the first execution environment of the first electronic reading device one or more interactive content presentation objects and one or more interactive assessment objects by converting the instructions in the digital specification to a second language which is executed by one or more computer processors of the first electronic reading device; receiving content interaction data corresponding to user interactions with the interactive content presentation objects and sending the interaction data to an interaction server; receiving a second content interaction data corresponding to a second user's interactions with the interactive content presentation objects from the interaction server, the second user's interactions having been received at the interaction server from a second electronic reading device executing a second execution environment different from the first execution environment and within which the digital specification was presented with a consistent layout within and around the interactive content presentation objects and interactive assessment objects in comparison to the digital specification in the first execution environment of the first electronic reading device; presenting, in the first execution environment, the second content interaction data; and sending to the interaction server, assessment data corresponding to user interactions with the interactive assessment objects. 68. The method of claim 55 , wherein presenting one or more interactive assessment presentation objects and one or more interactive assessment objects includes presenting one or more multiple choice assessments.
| 0.701977 |
9,904,663 | 5 | 9 |
5. The information processing apparatus according to claim 1 , the detection unit having a determining unit for determining that a character string is a quotation in response to detection of an identical character string in a plurality of the texts.
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5. The information processing apparatus according to claim 1 , the detection unit having a determining unit for determining that a character string is a quotation in response to detection of an identical character string in a plurality of the texts. 9. The information processing apparatus according to claim 5 , the matching unit determining that quotation has been made from the same information when two or more of the detected quotations include a common portion.
| 0.624567 |
8,390,839 | 10 | 11 |
10. An information processor connected to a plurality of image formation apparatuses, said information processor comprising: a performance information storage unit configured to store, for each type of document, performance information related to processing rate of each said image formation apparatus to process a document, an input unit functioning as a pointing device, a display unit configured to display apparatus icons, each apparatus icon corresponding to an image formation apparatus from the plurality of image formation apparatuses, and a document icon corresponding to a document, a document selection unit configured to select a document, of which direct print processing by any one of said image formation apparatuses is to be requested, by selecting the document icon corresponding to the document through said input unit, a detection unit configured to detect a type of document selected by said document selection unit, a performance information acquisition unit configured to performance information related to processing rate of each image formation apparatus stored in said performance information storage unit for the type of document detected by said detection unit, a notification unit configured to provide a first notification to a user when the document icon is selected by said document selection unit to select the document, of the performance information of each image formation apparatus for the type of the selected document by changing said displayed apparatus icons in a respective manner corresponding to the performance information of each image formation apparatus for the type of the selected document.
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10. An information processor connected to a plurality of image formation apparatuses, said information processor comprising: a performance information storage unit configured to store, for each type of document, performance information related to processing rate of each said image formation apparatus to process a document, an input unit functioning as a pointing device, a display unit configured to display apparatus icons, each apparatus icon corresponding to an image formation apparatus from the plurality of image formation apparatuses, and a document icon corresponding to a document, a document selection unit configured to select a document, of which direct print processing by any one of said image formation apparatuses is to be requested, by selecting the document icon corresponding to the document through said input unit, a detection unit configured to detect a type of document selected by said document selection unit, a performance information acquisition unit configured to performance information related to processing rate of each image formation apparatus stored in said performance information storage unit for the type of document detected by said detection unit, a notification unit configured to provide a first notification to a user when the document icon is selected by said document selection unit to select the document, of the performance information of each image formation apparatus for the type of the selected document by changing said displayed apparatus icons in a respective manner corresponding to the performance information of each image formation apparatus for the type of the selected document. 11. The information processor according to claim 10 , further including an apparatus selection unit selecting an image formation apparatus to process the document selected by said document selection unit, wherein said notification unit provides a second notification to the user, when the image formation is selected to process the selected document, of the performance information of the selected image formation apparatus for the type of the selected document.
| 0.5 |
8,972,434 | 14 | 28 |
14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting.
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14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. 28. The computer-implemented method of claim 14 , further comprising presenting the second phase query results in conjunction with the first phase query results.
| 0.831942 |
10,037,319 | 7 | 8 |
7. The system of claim 6 , wherein the processor generates one or more candidates from an input sequence by converting the input sequence into a graph comprising one or more paths, wherein the one or more paths correspond to the one or more candidates.
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7. The system of claim 6 , wherein the processor generates one or more candidates from an input sequence by converting the input sequence into a graph comprising one or more paths, wherein the one or more paths correspond to the one or more candidates. 8. The system of claim 7 , wherein the graph comprises a collection of nodes and directed edges, each edge connecting one node to another, wherein in the graph each character of each set of characters is assigned a node, the incoming edge for each node corresponding to the probability for the associated character.
| 0.5 |
7,519,817 | 1 | 3 |
1. A method for automatically processing a first electronic document sent from a sender to a designated receiver, the first electronic document including a digital signature, the method comprising: receiving the first electronic document from the sender; validating the digital signature by usina a public key of the sender; checking whether the digital signature is from a person or a legal entity authorized to send the first electronic document; determining, if the person or the legal entity is authorized to send the first electronic document, whether the person or the legal entity that signed the first electronic document is authorized by an issuer named in the first electronic document to sign the first electronic document; creating an electronic protocol of the results of validating, checking, and determining; signing the protocol; archiving at least one of data selected from the group consisting of the protocol and the first electronic document; and presenting the first electronic document to the designated receiver.
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1. A method for automatically processing a first electronic document sent from a sender to a designated receiver, the first electronic document including a digital signature, the method comprising: receiving the first electronic document from the sender; validating the digital signature by usina a public key of the sender; checking whether the digital signature is from a person or a legal entity authorized to send the first electronic document; determining, if the person or the legal entity is authorized to send the first electronic document, whether the person or the legal entity that signed the first electronic document is authorized by an issuer named in the first electronic document to sign the first electronic document; creating an electronic protocol of the results of validating, checking, and determining; signing the protocol; archiving at least one of data selected from the group consisting of the protocol and the first electronic document; and presenting the first electronic document to the designated receiver. 3. The method of claim 1 , further comprising: requesting a time stamp from a trusted authority and adding the time stamp to the first electronic document before archiving.
| 0.760446 |
9,710,755 | 11 | 15 |
11. A system comprising: one or more processing modules; and one or more non-transitory memory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: training a machine learning algorithm to create a predictive model; for each record of a set of distinct records, using the predictive model to calculate a probability of the record being accessed; for each record of the set of distinct records, if the probability of the record being accessed as calculated is greater than a threshold value, then placing the record in a first database cluster H; for each record of the set of distinct records, if the probability of the record being accessed as calculated is not greater than the threshold value, then placing the record in a second database cluster L; receiving a request from a requester for at least one record of the set of distinct records; and presenting the at least one record from the set of distinct records to the requester in response to the request; wherein training the machine learning algorithm comprises: for each record in the set of distinct records, inputting a training feature vector associated with the record into the machine learning algorithm, the training feature vector associated with the record comprising a list of characteristics of the record; for each record in the set of distinct records, inputting a cost vector associated with the record into the machine learning algorithm, the cost vector associated with the record configured to train the machine learning algorithm to reduce a probability of a false negative prediction for the record; and iteratively operating the machine learning algorithm on each record in the set of distinct records to create the predictive model.
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11. A system comprising: one or more processing modules; and one or more non-transitory memory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: training a machine learning algorithm to create a predictive model; for each record of a set of distinct records, using the predictive model to calculate a probability of the record being accessed; for each record of the set of distinct records, if the probability of the record being accessed as calculated is greater than a threshold value, then placing the record in a first database cluster H; for each record of the set of distinct records, if the probability of the record being accessed as calculated is not greater than the threshold value, then placing the record in a second database cluster L; receiving a request from a requester for at least one record of the set of distinct records; and presenting the at least one record from the set of distinct records to the requester in response to the request; wherein training the machine learning algorithm comprises: for each record in the set of distinct records, inputting a training feature vector associated with the record into the machine learning algorithm, the training feature vector associated with the record comprising a list of characteristics of the record; for each record in the set of distinct records, inputting a cost vector associated with the record into the machine learning algorithm, the cost vector associated with the record configured to train the machine learning algorithm to reduce a probability of a false negative prediction for the record; and iteratively operating the machine learning algorithm on each record in the set of distinct records to create the predictive model. 15. The system of claim 11 wherein iteratively operating the machine learning algorithm to create the predictive model comprises: operating the machine learning algorithm on a periodic basis; for each record of the set of distinct records, receiving historical access data associated with the record; and for each record of the set of distinct records, comparing the probability of the record being accessed as calculated with the historical access data associated with the record.
| 0.518036 |
8,166,079 | 1 | 10 |
1. Apparatus for assembling content fragments into a container, wherein the container comprises markup identifying one or more content fragments, comprising: a hardware processor; computer memory that includes a first queue, and a second queue; the computer memory holding computer program instructions that when executed by the hardware processor perform the following method: receiving, by a host process, a request for the container, and placing the request in the second queue; removing from the second queue, by a first execution thread, the request, and processing the request to generate a data object; instantiating a software processor; generating, by the software processor, a parse tree representation of the container, the parse tree representation including an edge side include (ESI) code directive associated with at least one content fragment in the container; cloning the parse tree representation in a cache; processing, by the software processor, and from top to bottom of the parse tree representation, each ESI code directive, wherein, if an ESI code directive in the parse tree representation is an ESI include, placing a request associated with the ESI include in the first queue for handling by a second execution thread; as ESI code directives are processed, having the software processor concatenate results into the data object; after the parse tree representation is parsed from top to bottom, placing the data object on the first queue; retrieving, by the second execution thread, the data object, and building a response to the request for the container; and serving the response.
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1. Apparatus for assembling content fragments into a container, wherein the container comprises markup identifying one or more content fragments, comprising: a hardware processor; computer memory that includes a first queue, and a second queue; the computer memory holding computer program instructions that when executed by the hardware processor perform the following method: receiving, by a host process, a request for the container, and placing the request in the second queue; removing from the second queue, by a first execution thread, the request, and processing the request to generate a data object; instantiating a software processor; generating, by the software processor, a parse tree representation of the container, the parse tree representation including an edge side include (ESI) code directive associated with at least one content fragment in the container; cloning the parse tree representation in a cache; processing, by the software processor, and from top to bottom of the parse tree representation, each ESI code directive, wherein, if an ESI code directive in the parse tree representation is an ESI include, placing a request associated with the ESI include in the first queue for handling by a second execution thread; as ESI code directives are processed, having the software processor concatenate results into the data object; after the parse tree representation is parsed from top to bottom, placing the data object on the first queue; retrieving, by the second execution thread, the data object, and building a response to the request for the container; and serving the response. 10. The apparatus as described in claim 1 wherein the method further includes extinguishing the software processor after the response is served.
| 0.784431 |
4,724,285 | 38 | 39 |
38. The steno translation system of claim 4 further comprising: means for defining each stroke symbol translation, derived from the scan chart memory as a suffix, prefix or word root by applying the predetermined identifier rule set to the lexical stroke symbol.
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38. The steno translation system of claim 4 further comprising: means for defining each stroke symbol translation, derived from the scan chart memory as a suffix, prefix or word root by applying the predetermined identifier rule set to the lexical stroke symbol. 39. The steno translation system of claim 38 wherein the means for combining comprises: means for combining a stroke symbol translation defined as a suffix with the stroke symbol translation of the immediately preceding stroke symbol translation in accordance with a first predefined language rule set; and means for combining each stroke symbol translation next succeeding a lexical stroke symbol in accordance with a second predefined language rule set.
| 0.5 |
6,073,101 | 3 | 5 |
3. A method of performing text independent speaker recognition comprising: sampling overlapping frames of a speech signal; computing a feature vector for each said frame of said speech signal; comparing each said feature vector with vector parameters and variances stored in a codebook corresponding to an enrolled speaker; accumulating a number of frames for which the corresponding feature vector corresponds to vector parameters and variances in a codebook; identifying an enrolled speaker or detecting a new speaker in response to results of said accumulating step or said comparing step, respectively, recognizing a command or a plurality of commands within said input speech signal; retrieving enrolled information corresponding to said speaker identified in said identifying step; and interpreting said command in accordance with said enrolled information retrieved in said retrieving step, wherein said command is carried out by a procedure which differs between enrolled speakers, said method including the further step of: selecting a procedure to carry out said command in accordance with said enrolled information retrieved by said retrieving step.
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3. A method of performing text independent speaker recognition comprising: sampling overlapping frames of a speech signal; computing a feature vector for each said frame of said speech signal; comparing each said feature vector with vector parameters and variances stored in a codebook corresponding to an enrolled speaker; accumulating a number of frames for which the corresponding feature vector corresponds to vector parameters and variances in a codebook; identifying an enrolled speaker or detecting a new speaker in response to results of said accumulating step or said comparing step, respectively, recognizing a command or a plurality of commands within said input speech signal; retrieving enrolled information corresponding to said speaker identified in said identifying step; and interpreting said command in accordance with said enrolled information retrieved in said retrieving step, wherein said command is carried out by a procedure which differs between enrolled speakers, said method including the further step of: selecting a procedure to carry out said command in accordance with said enrolled information retrieved by said retrieving step. 5. A method as recited in claim 3, including the further step of providing feedback of a result of said interpreting step to said speaker.
| 0.75 |
9,921,072 | 1 | 4 |
1. A computer-implemented method, comprising: storing, in a computing apparatus, a route dictionary containing a plurality of route words identifying a plurality of routes previously traversed by a user, wherein each respective route word in the route dictionary includes an ordered sequence of symbols, each of the symbols identifying a predetermined vertex in the plurality of routes previously traversed by a user; storing, in the computing apparatus, term frequency data of the route words of the user based on frequencies with which the user has traversed respective routes represented by the route words; communicating, by the computing apparatus with a user device, to identify one or more vertices of a route currently being traversed by the user based on GPS data from the user device; generating, by the computing apparatus, a partial route word from a starting sequence of symbols representing the one or more vertices respectively; while the user is currently traversing the route, predicting, using a text prediction technique for predicting from a given partial word a complete word in a dictionary according to term frequency, a particular route word in the route dictionary containing the partial route word; identifying, by the computing apparatus, a remaining sequence of symbols that follows the starting sequence of symbols in the particular route word; predicting, by the computing apparatus, a remaining portion of the route that is currently being traversed by the user as being identified by a set of vertices corresponding to the remaining sequence of symbols in the particular route word; identifying, by the computing apparatus, a message based on the remaining portion of the route; and transmitting, by the computing apparatus to the user device, the message before the user completes the predicted, remaining portion of the route.
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1. A computer-implemented method, comprising: storing, in a computing apparatus, a route dictionary containing a plurality of route words identifying a plurality of routes previously traversed by a user, wherein each respective route word in the route dictionary includes an ordered sequence of symbols, each of the symbols identifying a predetermined vertex in the plurality of routes previously traversed by a user; storing, in the computing apparatus, term frequency data of the route words of the user based on frequencies with which the user has traversed respective routes represented by the route words; communicating, by the computing apparatus with a user device, to identify one or more vertices of a route currently being traversed by the user based on GPS data from the user device; generating, by the computing apparatus, a partial route word from a starting sequence of symbols representing the one or more vertices respectively; while the user is currently traversing the route, predicting, using a text prediction technique for predicting from a given partial word a complete word in a dictionary according to term frequency, a particular route word in the route dictionary containing the partial route word; identifying, by the computing apparatus, a remaining sequence of symbols that follows the starting sequence of symbols in the particular route word; predicting, by the computing apparatus, a remaining portion of the route that is currently being traversed by the user as being identified by a set of vertices corresponding to the remaining sequence of symbols in the particular route word; identifying, by the computing apparatus, a message based on the remaining portion of the route; and transmitting, by the computing apparatus to the user device, the message before the user completes the predicted, remaining portion of the route. 4. The method of claim 1 , further comprising: monitoring, by the computing apparatus, routes traversed by the user; updating, by the computing apparatus, the route dictionary to include route words corresponding to the routes being monitored and having been traversed by the user.
| 0.5 |
9,384,217 | 1 | 2 |
1. A method comprising: detecting, by a computing device, a user input for a telestration on an image being displayed on a display device; determining, by the computing device, a plurality of image portions of the image based on the telestration, wherein the plurality of image portions are determined by a boundary around each image portion based on the telestration; determining, by the computing device, a set of tags for the plurality of image portions, wherein the set of tags are determined based on image recognition of content in the plurality of image portions; determining, by the computing device, an operator based on the telestration, wherein the operator characterizes an operation to perform for the plurality of image portions; determining, by the computing device, a search query based on applying the operator to the set of tags; and causing, by the computing device, a search to be performed using the search query.
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1. A method comprising: detecting, by a computing device, a user input for a telestration on an image being displayed on a display device; determining, by the computing device, a plurality of image portions of the image based on the telestration, wherein the plurality of image portions are determined by a boundary around each image portion based on the telestration; determining, by the computing device, a set of tags for the plurality of image portions, wherein the set of tags are determined based on image recognition of content in the plurality of image portions; determining, by the computing device, an operator based on the telestration, wherein the operator characterizes an operation to perform for the plurality of image portions; determining, by the computing device, a search query based on applying the operator to the set of tags; and causing, by the computing device, a search to be performed using the search query. 2. The method of claim 1 , wherein detecting the user input comprises: detecting, by the computing device, a first user input for a first telestration for a first image portion in the plurality of image portions, wherein the first telestration is used to form a boundary around the first image portion; and detecting, by the computing device, a second user input for a second telestration for a second image portion in the plurality of image portions, wherein the second telestration is used to form a boundary around the second image portion.
| 0.5 |
8,868,589 | 15 | 19 |
15. A non-transitory computer-readable storage memory comprising instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform a method comprising: transforming data into a uniform format that is compatible with a plurality of interfaces by transforming the data into a normalized and tagged format and into a searchable and mashed format; saving the transformed data to a file by saving the data, the transformed data in the normalized and tagged format, and the transformed data in the searchable and mashed format in the file; and generating one or more grammatical phrases in an interface-specific format from the transformed data.
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15. A non-transitory computer-readable storage memory comprising instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform a method comprising: transforming data into a uniform format that is compatible with a plurality of interfaces by transforming the data into a normalized and tagged format and into a searchable and mashed format; saving the transformed data to a file by saving the data, the transformed data in the normalized and tagged format, and the transformed data in the searchable and mashed format in the file; and generating one or more grammatical phrases in an interface-specific format from the transformed data. 19. A non-transitory computer-readable storage memory of claim 15 , wherein the instructions, when executed by the one or more processors, perform a method further comprising generating a search query for searching a database using the one or more grammatical phrases.
| 0.654639 |
5,412,804 | 14 | 15 |
14. The method as claimed in claim 13, further comprising the step of converting said linked data structure into another linked data structure including a third node defining a first un-nested query for generating said third relation and a fourth node defining a second un-nested query for receiving said third relation, and wherein said step (a) of computing is performed by executing said first un-nested query and said step (b) of applying is performed by executing said second un-nested query.
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14. The method as claimed in claim 13, further comprising the step of converting said linked data structure into another linked data structure including a third node defining a first un-nested query for generating said third relation and a fourth node defining a second un-nested query for receiving said third relation, and wherein said step (a) of computing is performed by executing said first un-nested query and said step (b) of applying is performed by executing said second un-nested query. 15. The method as claimed in claim 14, wherein said another linked data structure includes a series of nodes defining a sequence of join and outer-join operations including a consecutive series of m joins, and wherein the first i joins are evaluated at a time first for i=1, then for i=2, then for i=3, . . . , and finally for i=m.
| 0.516082 |
9,570,047 | 7 | 11 |
7. A method of providing an interactive area representation on a display device with at least one computer, the method comprising simultaneously displaying on the display device: the area representation; a highlighted portion of the area representation indicating a first portion of the area representation that can be positioned on the area representation by a pointing device; outside of the area representation a magnified representation of the first portion of the area representation represented by the highlighted portion; information about one or more specific items associated with the area representation on the area representation, on the magnified representation or both; and outside of the area representation and the magnified representation additional information about at least one specific item of the one or more specific items, wherein the additional information about the at least one specific item includes user-selectable information; the method further comprising: in response to user input to the at least one computer with the pointing device to select user-selectable additional information from the additional information about the at least one specific item, positioning the highlighted portion on the area representation to indicate a second portion of the area representation corresponding to a location on the area representation related to the selected additional information, displaying a magnified representation of the second area representation portion represented by the positioned highlighted portion, and displaying with at least part of the additional information outside the area representation and the magnified representation further information about the at least one specific item; the method further comprising: in response to user input to the at least one computer to the area representation with the pointing device, positioning the highlighted portion on the area representation to indicate a third portion of the area representation, displaying a magnified representation of the third area representation portion indicated by the highlighted portion and displaying outside of the area representation and outside of the magnified representation additional information about at least one specific item indicated on the third area representation portion.
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7. A method of providing an interactive area representation on a display device with at least one computer, the method comprising simultaneously displaying on the display device: the area representation; a highlighted portion of the area representation indicating a first portion of the area representation that can be positioned on the area representation by a pointing device; outside of the area representation a magnified representation of the first portion of the area representation represented by the highlighted portion; information about one or more specific items associated with the area representation on the area representation, on the magnified representation or both; and outside of the area representation and the magnified representation additional information about at least one specific item of the one or more specific items, wherein the additional information about the at least one specific item includes user-selectable information; the method further comprising: in response to user input to the at least one computer with the pointing device to select user-selectable additional information from the additional information about the at least one specific item, positioning the highlighted portion on the area representation to indicate a second portion of the area representation corresponding to a location on the area representation related to the selected additional information, displaying a magnified representation of the second area representation portion represented by the positioned highlighted portion, and displaying with at least part of the additional information outside the area representation and the magnified representation further information about the at least one specific item; the method further comprising: in response to user input to the at least one computer to the area representation with the pointing device, positioning the highlighted portion on the area representation to indicate a third portion of the area representation, displaying a magnified representation of the third area representation portion indicated by the highlighted portion and displaying outside of the area representation and outside of the magnified representation additional information about at least one specific item indicated on the third area representation portion. 11. The method of claim 7 , wherein the pointing device can continuously move the highlighted portion on the display of the area representation.
| 0.803279 |
8,103,110 | 8 | 9 |
8. The system of claim 7 , wherein the at least one processor is further operable to calculate the third probability using Bayes rules.
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8. The system of claim 7 , wherein the at least one processor is further operable to calculate the third probability using Bayes rules. 9. The system of claim 8 , wherein the at least one processor is further operable to calculate the third probability using one or more metaprobabilities to adjust for the weight of evidence.
| 0.5 |
7,680,746 | 6 | 9 |
6. A hybrid prediction computer system for processing training data to predict click-through-rates, said hybrid prediction computer system processing training data by: creating a machine learning based model for making a base prediction, said machine learning model constructed using a first set of features in training data; creating a tree-structured statistical table from a second set of features in training data by applying Kalman-filter methods to a tree-structured Markov model to estimate parameters in said tree-structured statistical table; executing said machine learning model using said first set of features from test data; and adding an adjustment factor from said tree-structured statistical table to augment said base prediction from said machine learning based model to predict click-through-rates.
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6. A hybrid prediction computer system for processing training data to predict click-through-rates, said hybrid prediction computer system processing training data by: creating a machine learning based model for making a base prediction, said machine learning model constructed using a first set of features in training data; creating a tree-structured statistical table from a second set of features in training data by applying Kalman-filter methods to a tree-structured Markov model to estimate parameters in said tree-structured statistical table; executing said machine learning model using said first set of features from test data; and adding an adjustment factor from said tree-structured statistical table to augment said base prediction from said machine learning based model to predict click-through-rates. 9. The hybrid prediction computer system as set forth in claim 6 wherein obtaining an adjustment factor for said tree-structured statistical table comprises: making a classification decision based up on said second set of features; and indexing into said tree-structured statistical table using said classification.
| 0.5 |
9,361,714 | 13 | 14 |
13. The system according to claim 11 , further comprising a translator generating a translated version of the identified visual elements.
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13. The system according to claim 11 , further comprising a translator generating a translated version of the identified visual elements. 14. The system according to claim 13 , further comprising using a video editor to combine the translated version and the timelines.
| 0.5 |
8,380,492 | 9 | 14 |
9. A document cleaning system for cleaning an electronic document, comprising: a memory; one or more processors, configured to: identify at least one sentence in the electronic document; numerically represent features of the sentence to obtain a numeric feature representation associated with the sentence; input the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and remove sentences determined to be bad sentences from the electronic document to create a cleaned document, wherein numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence comprises: creating a part of speech feature vector representation by performing part of speech tagging on each word in the sentence and determining a unique number associated with each part-of-speech corresponding to each word in the sentence, each position in the part of speech feature vector representation indicating a frequency of occurrence of a part of speech tag; creating a rule vector feature representation by determining whether the sentence satisfies a plurality of predetermined rules, each position in the rule vector feature representation indicating whether the sentence satisfies a particular one of the plurality of predetermined rules; and obtaining the numeric feature representation by concatenating the part of speech feature vector representation and the rule vector feature representation.
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9. A document cleaning system for cleaning an electronic document, comprising: a memory; one or more processors, configured to: identify at least one sentence in the electronic document; numerically represent features of the sentence to obtain a numeric feature representation associated with the sentence; input the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, whether the sentence associated with that numeric feature representation is a bad sentence; and remove sentences determined to be bad sentences from the electronic document to create a cleaned document, wherein numerically representing features of the sentence to obtain a numeric feature representation associated with the sentence comprises: creating a part of speech feature vector representation by performing part of speech tagging on each word in the sentence and determining a unique number associated with each part-of-speech corresponding to each word in the sentence, each position in the part of speech feature vector representation indicating a frequency of occurrence of a part of speech tag; creating a rule vector feature representation by determining whether the sentence satisfies a plurality of predetermined rules, each position in the rule vector feature representation indicating whether the sentence satisfies a particular one of the plurality of predetermined rules; and obtaining the numeric feature representation by concatenating the part of speech feature vector representation and the rule vector feature representation. 14. The document cleaning system of claim 9 , wherein the one or more processors are further configured to, prior to identifying: train the machine learning classifier with training data, the training data including one or more electronic training documents and one or more sentence status labels which identify one or more bad sentences in the electronic training documents.
| 0.627976 |
10,055,602 | 14 | 15 |
14. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to: separately encrypt a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items, wherein the two or more encryption functions comprise (i) a brute force safe function and (ii) a range safe function; convert a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combine results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query.
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14. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to: separately encrypt a set of plain text data using two or more encryption functions, thereby producing an encrypted domain comprising at least two distinct groups of encrypted data items, wherein the two or more encryption functions comprise (i) a brute force safe function and (ii) a range safe function; convert a range query over plain text data items into a query over at least one of the distinct groups of encrypted data items; and combine results from the query over the distinct groups of encrypted data items, thereby generating a final encrypted result to the range query. 15. The computer program product of claim 14 , wherein the program instructions executable by a computing device further cause the computing device to: decrypt the final encrypted result, thereby generating a plain text result set.
| 0.5 |
7,797,150 | 1 | 2 |
1. A translation system comprising: an image reading unit that optically reads an image of a manuscript and generates image data; an inputting unit that inputs a translation target language; a character recognizing unit that generates an original text by performing a character recognition process on the image data generated by the image reading unit; a translation database that stores translation phrases in a plurality of languages, language identifiers that specify the language in which each individual translation phrase is written, and document identifiers that identify a content of the translation phrase regardless of the language in which the translation phrase is written; an extracting unit that extracts the document identifier which specifies the content of the original text from the original text; a searching unit that searches the translation database for a translation text associated with a document identifier identical to the document identifier extracted from the original text by the extracting unit and a language identifier identical to the language identifier which specify the translation target language input by the inputting unit; and an outputting unit that outputs the translation text searched by the searching unit wherein if the translation text associated with the document identifier is not found in the translation database, the original text is translated to generate a translation text for the original text and the language identifier, the document identifier, and the generated translation text are automatically stored in the translation database.
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1. A translation system comprising: an image reading unit that optically reads an image of a manuscript and generates image data; an inputting unit that inputs a translation target language; a character recognizing unit that generates an original text by performing a character recognition process on the image data generated by the image reading unit; a translation database that stores translation phrases in a plurality of languages, language identifiers that specify the language in which each individual translation phrase is written, and document identifiers that identify a content of the translation phrase regardless of the language in which the translation phrase is written; an extracting unit that extracts the document identifier which specifies the content of the original text from the original text; a searching unit that searches the translation database for a translation text associated with a document identifier identical to the document identifier extracted from the original text by the extracting unit and a language identifier identical to the language identifier which specify the translation target language input by the inputting unit; and an outputting unit that outputs the translation text searched by the searching unit wherein if the translation text associated with the document identifier is not found in the translation database, the original text is translated to generate a translation text for the original text and the language identifier, the document identifier, and the generated translation text are automatically stored in the translation database. 2. The translation system according to claim 1 , further comprising a notifying unit that notifies that the searching unit can find no translation phrases that satisfy the condition in the translation database, if none can be found.
| 0.590106 |
9,652,439 | 3 | 4 |
3. The system of claim 1 , wherein the software means is further operative on the processor for: determining a score for each of the permutations of candidate paths; and selecting one of the candidate paths based on the score for each of the permutations.
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3. The system of claim 1 , wherein the software means is further operative on the processor for: determining a score for each of the permutations of candidate paths; and selecting one of the candidate paths based on the score for each of the permutations. 4. The system of claim 3 , wherein determining the score for each of the candidate paths includes determining based on at least one of: the document type definition without inferring additional tags for each of the candidate paths; the document type definition with inferring tags for each of the candidate paths; and a recursive examination of each path for a predetermined extent from each node of the mapping file for each of the candidate paths.
| 0.5 |
7,696,427 | 13 | 17 |
13. A system for recommending music comprising: a genre classifier configured to: identify a granularity of a plurality of genres based on a request for music similarity; learn to differentiate between the plurality of genres based on the granularity; calculate a first profile according to the granularity, wherein the first profile comprises, for each of the plurality of genres, a likelihood that a music selection of a user is in the genre; and calculate a second profile according to the granularity, wherein the second profile comprises, for each of the plurality of genres, a likelihood that an unknown music selection is in the genre; and a similarity analyzer connected to the genre classifier configured to: obtain a first similarity score between the first profile and the second profile; and recommend the unknown music selection to the user based on the first similarity score.
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13. A system for recommending music comprising: a genre classifier configured to: identify a granularity of a plurality of genres based on a request for music similarity; learn to differentiate between the plurality of genres based on the granularity; calculate a first profile according to the granularity, wherein the first profile comprises, for each of the plurality of genres, a likelihood that a music selection of a user is in the genre; and calculate a second profile according to the granularity, wherein the second profile comprises, for each of the plurality of genres, a likelihood that an unknown music selection is in the genre; and a similarity analyzer connected to the genre classifier configured to: obtain a first similarity score between the first profile and the second profile; and recommend the unknown music selection to the user based on the first similarity score. 17. The system of claim 13 , wherein the similarity analyzer is further configured to: obtain a second similarity score between the music selection of the user and the unknown music selection; and sum the first similarity score multiplied by a first weight and the second similarity score multiplied by a second weight to obtain a total similarity score, wherein recommending the unknown music selection is further performed based on the total similarity score.
| 0.709332 |
8,583,672 | 14 | 16 |
14. A system comprising one or more computers and one or more storage devices storing first instructions that when executed by the one or more computers cause the one or more computers to perform first operations comprising: generating, for transmission to a user device, a user interface document that, when rendered, presents a user interface that includes an input field, wherein the user interface document includes second instructions that are operable to cause the user device to perform second operations comprising: detecting a first search query entered in the input field by a user; before the first search query is explicitly submitted by the user, obtaining first search results for the first search query and a plurality of spelling suggestions for a first misspelled term in the first search query, wherein the first search results are provided by a search engine as a response to the first search query, and wherein a first spelling suggestion of the plurality of spelling suggestions is an aggressive spelling suggestion having an edit distance between the first misspelled term and the first spelling suggestion that is greater than a specified threshold value; and displaying the first search results and the plurality of spelling suggestions in the user interface.
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14. A system comprising one or more computers and one or more storage devices storing first instructions that when executed by the one or more computers cause the one or more computers to perform first operations comprising: generating, for transmission to a user device, a user interface document that, when rendered, presents a user interface that includes an input field, wherein the user interface document includes second instructions that are operable to cause the user device to perform second operations comprising: detecting a first search query entered in the input field by a user; before the first search query is explicitly submitted by the user, obtaining first search results for the first search query and a plurality of spelling suggestions for a first misspelled term in the first search query, wherein the first search results are provided by a search engine as a response to the first search query, and wherein a first spelling suggestion of the plurality of spelling suggestions is an aggressive spelling suggestion having an edit distance between the first misspelled term and the first spelling suggestion that is greater than a specified threshold value; and displaying the first search results and the plurality of spelling suggestions in the user interface. 16. The system of claim 14 , wherein the specified threshold value is two operations.
| 0.903409 |
8,543,941 | 7 | 12 |
7. A computer implemented method of using an electronic book, comprising: displaying the electronic book on a display; identifying a point on the display based on a position of an object relative to the display as the object becomes proximate to the display; initiating a menu-creation animation in response to the object becoming proximate to the display, wherein the menu-creation animation comprises a circle being gradually drawn around the point on the display; determining options to be presented in a contextual menu responsive to the point on the display; and providing the contextual menu in response to the object remaining at the position until the menu-creation animation completes and turns into the contextual menu, wherein creation of the contextual menu is cancelled in response to the object ceasing to remain at the position before the menu-creation animation completes.
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7. A computer implemented method of using an electronic book, comprising: displaying the electronic book on a display; identifying a point on the display based on a position of an object relative to the display as the object becomes proximate to the display; initiating a menu-creation animation in response to the object becoming proximate to the display, wherein the menu-creation animation comprises a circle being gradually drawn around the point on the display; determining options to be presented in a contextual menu responsive to the point on the display; and providing the contextual menu in response to the object remaining at the position until the menu-creation animation completes and turns into the contextual menu, wherein creation of the contextual menu is cancelled in response to the object ceasing to remain at the position before the menu-creation animation completes. 12. The method of claim 7 , wherein the object is a finger of a user and the object becoming proximate to the display comprises the user pressing and holding the finger on the display at the point.
| 0.698777 |
8,694,491 | 27 | 33 |
27. A method, comprising: at a computer having one or more processors and memory storing one or more programs for execution by the one or more processors: sending Internet usage data for a particular individual computer user to a server computer, wherein the usage data include a plurality of search queries previously submitted by the particular individual computer user; receiving a set of search results in accordance with an automatic re-run of a particular search query of the plurality of search queries in its entirety; wherein the identified search query is a search query previously submitted by the particular individual computer user; wherein the particular search query is identified, without human intervention by the particular individual computer user, from the plurality of search queries, and meets one or more predefined query selection criteria; and wherein the automatic re-run of the particular search query is without human intervention by the particular individual computer user; and displaying at least one search result of the set of search results.
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27. A method, comprising: at a computer having one or more processors and memory storing one or more programs for execution by the one or more processors: sending Internet usage data for a particular individual computer user to a server computer, wherein the usage data include a plurality of search queries previously submitted by the particular individual computer user; receiving a set of search results in accordance with an automatic re-run of a particular search query of the plurality of search queries in its entirety; wherein the identified search query is a search query previously submitted by the particular individual computer user; wherein the particular search query is identified, without human intervention by the particular individual computer user, from the plurality of search queries, and meets one or more predefined query selection criteria; and wherein the automatic re-run of the particular search query is without human intervention by the particular individual computer user; and displaying at least one search result of the set of search results. 33. The method of claim 27 , wherein the Internet usage data for the particular individual computer user are grouped into query sessions.
| 0.911384 |
9,032,366 | 6 | 9 |
6. An apparatus for performing a configuration of an aeronautical system, comprising: a display configured to display a user interface for receiving aeronautical system setting information in compliance with an ARINC (Aeronautical Radio, Incorporated) 653 standard; and at least one processor configured to: generate an intermediate model of source code based on the setting information received via the user interface; create an XML document by performing XML conversion on the generated intermediate model; and generate a source code file in compliance with the ARINC 653 standard by converting the generated XML document.
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6. An apparatus for performing a configuration of an aeronautical system, comprising: a display configured to display a user interface for receiving aeronautical system setting information in compliance with an ARINC (Aeronautical Radio, Incorporated) 653 standard; and at least one processor configured to: generate an intermediate model of source code based on the setting information received via the user interface; create an XML document by performing XML conversion on the generated intermediate model; and generate a source code file in compliance with the ARINC 653 standard by converting the generated XML document. 9. The apparatus of claim 6 , wherein the source code file is generated in a form corresponding to a preset source code template.
| 0.758427 |
8,700,640 | 4 | 7 |
4. The method according to claim 1 , further comprising labeling a number of users among the group of users using an active learning process thereby dividing the group of users into labeled users and unlabeled users.
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4. The method according to claim 1 , further comprising labeling a number of users among the group of users using an active learning process thereby dividing the group of users into labeled users and unlabeled users. 7. The method according to claim 4 , wherein the active learning process uses an uncertainty density sampling technique for selecting the number of users from the group of users.
| 0.868538 |
9,183,194 | 5 | 7 |
5. The method of claim 1 , further comprising: analyzing the document structure instance to identify a document type; and determining structure categories for the document structure instance based on the document type.
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5. The method of claim 1 , further comprising: analyzing the document structure instance to identify a document type; and determining structure categories for the document structure instance based on the document type. 7. The method of claim 5 , further comprising: identifying a category glossary for a selected structure category from the structure categories; determining whether the document structure instance includes any permissible terms from the category glossary; and performing an analysis operation based on whether the document structure instance includes any of the permissible terms from the category glossary.
| 0.5 |
8,196,123 | 1 | 5 |
1. A computer-readable storage medium having computer-executable instructions for causing a computer to perform steps comprising: providing an object model for transactional memory, wherein transactional memory is a concurrency control for controlling access to shared memory in concurrent computing, the object model allowing transaction syntax to be separated from program flow; and allowing memory transaction objects created using the object model to live beyond an instantiating execution scope, thereby allowing additional properties about the memory transaction to be manipulated.
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1. A computer-readable storage medium having computer-executable instructions for causing a computer to perform steps comprising: providing an object model for transactional memory, wherein transactional memory is a concurrency control for controlling access to shared memory in concurrent computing, the object model allowing transaction syntax to be separated from program flow; and allowing memory transaction objects created using the object model to live beyond an instantiating execution scope, thereby allowing additional properties about the memory transaction to be manipulated. 5. The computer-readable storage medium of claim 1 , wherein the object model provides a constructor for creating a top level transaction.
| 0.661765 |
8,392,445 | 19 | 21 |
19. A computer readable storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: associating each of a plurality of parent queries with a respective group of one or more child queries for the parent query, wherein each child query was submitted during a respective session following submission of its associated parent query during the session; identifying one or more candidate sibling queries for a particular child query, wherein the particular child query is a child query for one or more first parent queries in the plurality of parent queries and each candidate sibling query for the particular child query is a child query for one or more second parent queries in the plurality of queries, each candidate sibling query having a fan-in measure that satisfies a fan-in threshold, wherein the fan-in measure is a number of parent queries associated with a particular sibling query, wherein for each candidate sibling query, the one or more second parent queries for the candidate sibling query and the one or more first parent queries have a group of shared parent queries in common and the group of shared parent queries has a size that satisfies a common-query threshold; and selecting one or more final sibling queries for the particular child query from the one or more candidate sibling queries, and associating the final sibling queries with the particular child query as query refinements for the particular child query.
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19. A computer readable storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: associating each of a plurality of parent queries with a respective group of one or more child queries for the parent query, wherein each child query was submitted during a respective session following submission of its associated parent query during the session; identifying one or more candidate sibling queries for a particular child query, wherein the particular child query is a child query for one or more first parent queries in the plurality of parent queries and each candidate sibling query for the particular child query is a child query for one or more second parent queries in the plurality of queries, each candidate sibling query having a fan-in measure that satisfies a fan-in threshold, wherein the fan-in measure is a number of parent queries associated with a particular sibling query, wherein for each candidate sibling query, the one or more second parent queries for the candidate sibling query and the one or more first parent queries have a group of shared parent queries in common and the group of shared parent queries has a size that satisfies a common-query threshold; and selecting one or more final sibling queries for the particular child query from the one or more candidate sibling queries, and associating the final sibling queries with the particular child query as query refinements for the particular child query. 21. The computer readable storage device of claim 19 , wherein each child query for each parent query is submitted within an amount of time from when the parent query is submitted that satisfies a submission threshold.
| 0.879425 |
8,953,753 | 5 | 6 |
5. The system of claim 4 in which the automatic speech recognition system utilizes the internet, as accessed by a search engine.
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5. The system of claim 4 in which the automatic speech recognition system utilizes the internet, as accessed by a search engine. 6. The system of claim 5 in which the automatic speech recognition system utilizes a search engine database.
| 0.5 |
7,580,837 | 1 | 12 |
1. A method of tuning a speech system comprising: accessing, from a database, information representing a plurality of utterances for at least one speech-enabled application, the plurality of utterances comprising at least a first type of utterance and a second type of utterance; accessing, from the database, interpretive information representing an assigned interpretation for at least a portion of the plurality of utterances; determining, by a training tool subsystem, an appropriate interpretation for the portion of the plurality of utterances; comparing, by the training tool subsystem, the assigned interpretation for the portion of the plurality of utterances to the appropriate interpretation for the portion of the plurality of utterances; determining, by the training tool subsystem, a frequency value for the second type of utterance that represents the percentage of occurrence of the second type of utterance in the plurality of utterances; determining, by the training tool subsystem, that the speech-enabled application more accurately responds to the first type of utterance; and electing, by the training tool subsystem, to apply a targeted tuning to the speech-enabled application to improve recognition of the second type of utterance when the frequency value for the second type of utterance is greater than a frequency threshold value.
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1. A method of tuning a speech system comprising: accessing, from a database, information representing a plurality of utterances for at least one speech-enabled application, the plurality of utterances comprising at least a first type of utterance and a second type of utterance; accessing, from the database, interpretive information representing an assigned interpretation for at least a portion of the plurality of utterances; determining, by a training tool subsystem, an appropriate interpretation for the portion of the plurality of utterances; comparing, by the training tool subsystem, the assigned interpretation for the portion of the plurality of utterances to the appropriate interpretation for the portion of the plurality of utterances; determining, by the training tool subsystem, a frequency value for the second type of utterance that represents the percentage of occurrence of the second type of utterance in the plurality of utterances; determining, by the training tool subsystem, that the speech-enabled application more accurately responds to the first type of utterance; and electing, by the training tool subsystem, to apply a targeted tuning to the speech-enabled application to improve recognition of the second type of utterance when the frequency value for the second type of utterance is greater than a frequency threshold value. 12. The method of claim 1 , further comprising storing information representing the plurality of utterances as discrete audio files.
| 0.861345 |
9,741,043 | 9 | 16 |
9. A non-transitory computer-readable medium comprising computer program code that, when executed by a communications system including a communications server in communication with one or more communications devices, enables the communications system to perform the following method for optimizing a message text: receiving on a communications server a message text comprising a plurality of words or word phrases that combine together as non-overlapping parts of the message text; treating the non-overlapping words or word phrases of the message text as multiple independent variables that are reduced to a message vector having each of the multiple independent variables as components of the message vector; automatically creating on the communications server a plurality of lexical variants of the message text, wherein the lexical variants are created by replacing a word or word phrase for each of the multiple independent variables with one or more alternate words or word phrases based on one or more value-changing rules being applied to the received word or word phrase in the message text, the lexical variants for each of the multiple independent variables being reduced to a lexical vector such that the message vector is made up of variable-sized lexical vectors; sending each of the plurality of created lexical variants of the message text to the one or more communications devices; measuring a response rate for each sent lexical variant of the message text; identifying one or more lexical variants having the best performing measured response rates for each of the lexical vectors; automatically creating on the communications server syntactical variants of the identified best performing lexical variants by rearranging the lexical vectors within the message vector based on one or more position-changing rules; sending a plurality of the syntactical variants of the identified best performing lexical variants to the one or more communications devices, wherein only grammatically-correct syntactical variants are sent; measuring a response rate for each of the sent syntactical variants; and identifying a message text having the highest measured response rate for the sent syntactical variants.
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9. A non-transitory computer-readable medium comprising computer program code that, when executed by a communications system including a communications server in communication with one or more communications devices, enables the communications system to perform the following method for optimizing a message text: receiving on a communications server a message text comprising a plurality of words or word phrases that combine together as non-overlapping parts of the message text; treating the non-overlapping words or word phrases of the message text as multiple independent variables that are reduced to a message vector having each of the multiple independent variables as components of the message vector; automatically creating on the communications server a plurality of lexical variants of the message text, wherein the lexical variants are created by replacing a word or word phrase for each of the multiple independent variables with one or more alternate words or word phrases based on one or more value-changing rules being applied to the received word or word phrase in the message text, the lexical variants for each of the multiple independent variables being reduced to a lexical vector such that the message vector is made up of variable-sized lexical vectors; sending each of the plurality of created lexical variants of the message text to the one or more communications devices; measuring a response rate for each sent lexical variant of the message text; identifying one or more lexical variants having the best performing measured response rates for each of the lexical vectors; automatically creating on the communications server syntactical variants of the identified best performing lexical variants by rearranging the lexical vectors within the message vector based on one or more position-changing rules; sending a plurality of the syntactical variants of the identified best performing lexical variants to the one or more communications devices, wherein only grammatically-correct syntactical variants are sent; measuring a response rate for each of the sent syntactical variants; and identifying a message text having the highest measured response rate for the sent syntactical variants. 16. The non-transitory computer-readable medium of claim 9 , wherein rules for manipulating the message vector are substantially in the form of a context-free grammar.
| 0.758671 |
7,814,102 | 1 | 2 |
1. A computer-implemented method for linking documents with multiple topics to related documents, implemented using a client/server network architecture, comprising: in advance of a user search request, searching in a seed source to identify seed documents having at least one discrete seed topic but lacking target document links, using the client/server network architecture, each seed document belonging to one of a plurality of collections of seed documents, each collection having a target source map defining a list of target sources to search to generate target document links for seed documents belonging in the collection, wherein the at least one seed topic corresponds to a topical classification assigned from a taxonomy for a specific subject area, and wherein the at least one seed topic is pre-defined in advance of a user search request; retrieving and formatting the identified seed documents, in advance of a user search request, using the client/server network architecture; extracting the at least one seed topic for each retrieved seed document, in advance of a user search request, using the client/server network architecture; for each retrieved seed document, retrieving the list of the target sources found in the target source map for the collection to which the seed document belongs, in advance of a user search request, using the client/server network architecture; and for each seed topic within each retrieved seed document, processing each target source within the list of target sources defined by the target source map for the collection to which the retrieved seed document belongs, to pre-establish a target document link for the seed topic using a natural language search constructed from the seed topic, in advance of a user search request, using the client/server network architecture.
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1. A computer-implemented method for linking documents with multiple topics to related documents, implemented using a client/server network architecture, comprising: in advance of a user search request, searching in a seed source to identify seed documents having at least one discrete seed topic but lacking target document links, using the client/server network architecture, each seed document belonging to one of a plurality of collections of seed documents, each collection having a target source map defining a list of target sources to search to generate target document links for seed documents belonging in the collection, wherein the at least one seed topic corresponds to a topical classification assigned from a taxonomy for a specific subject area, and wherein the at least one seed topic is pre-defined in advance of a user search request; retrieving and formatting the identified seed documents, in advance of a user search request, using the client/server network architecture; extracting the at least one seed topic for each retrieved seed document, in advance of a user search request, using the client/server network architecture; for each retrieved seed document, retrieving the list of the target sources found in the target source map for the collection to which the seed document belongs, in advance of a user search request, using the client/server network architecture; and for each seed topic within each retrieved seed document, processing each target source within the list of target sources defined by the target source map for the collection to which the retrieved seed document belongs, to pre-establish a target document link for the seed topic using a natural language search constructed from the seed topic, in advance of a user search request, using the client/server network architecture. 2. The method of claim 1 , further comprising the steps of: in response to retrieval of a seed document as the result of a search request from a user, selecting seed topics of the retrieved seed document that are relevant to the search request, based on terms of the search request occurring within the seed topics, whereby the selection of the seed topics is dynamic; and displaying to the user those candidate target document links pre-established for the selected seed topics, whereby the displayed target document links are relevant to the retrieved seed document and to the search request resulting in retrieval of the retrieved seed document.
| 0.5 |
9,367,235 | 4 | 5 |
4. A non-transitory computer-readable medium comprising program code for receiving a confirming gesture formed on or about a sensor panel, the program code for causing performance of a method comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element.
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4. A non-transitory computer-readable medium comprising program code for receiving a confirming gesture formed on or about a sensor panel, the program code for causing performance of a method comprising: detecting one or more images at a first time at the sensor panel; determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture; determining a centering parameter from the one or more images; associating the OK gesture with a user interface (UI) element coincident with the centering parameter, the UI element accepting a confirming input; and providing the confirming input to the UI element. 5. The computer-readable medium of claim 4 , the method further comprising determining that the one or more images at the first time are arranged in a pattern corresponding to a predetermined OK gesture by: identifying one or more palm edge and pinky features; and identifying a thumb and finger feature.
| 0.5 |
7,542,029 | 24 | 36 |
24. A text input and editing apparatus comprising: one or more input devices which detect one or more input actions of a user to generate and edit text; an output device on which generated text is presented to a user; and a processor coupled to the input device, and the output device, the processor comprising: a first component for recording the location of a text insertion position where a next generated textual object will be output; a second component for detecting a distinctive input action identify one or more of said textual objects previously output to said output device; a third component for identifying one or more of said textual objects previously output based on the detected distinctive input action; a fourth component for determining one or more alternate textual objects that correspond to said one or more detected input actions from which said identified one or more textual objects was previously determined; a fifth component for replacing said identified previously output one or more textual objects with one or more of said determined alternate textual objects; and a sixth component for restoring said text insertion position to a location recorded prior to said detecting of said distinctive input action.
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24. A text input and editing apparatus comprising: one or more input devices which detect one or more input actions of a user to generate and edit text; an output device on which generated text is presented to a user; and a processor coupled to the input device, and the output device, the processor comprising: a first component for recording the location of a text insertion position where a next generated textual object will be output; a second component for detecting a distinctive input action identify one or more of said textual objects previously output to said output device; a third component for identifying one or more of said textual objects previously output based on the detected distinctive input action; a fourth component for determining one or more alternate textual objects that correspond to said one or more detected input actions from which said identified one or more textual objects was previously determined; a fifth component for replacing said identified previously output one or more textual objects with one or more of said determined alternate textual objects; and a sixth component for restoring said text insertion position to a location recorded prior to said detecting of said distinctive input action. 36. The apparatus of claim 24 , wherein said processor further comprises: a seventh component for determining whether said location of said text insertion position recorded prior to said detecting of said distinctive input action is not located within the text that is currently visible on said output device; and an eighth component for preventing said sixth component from restoring said text insertion position to said location recorded prior to said detecting of said distinctive input action when said seventh component determines that said recorded location is not located within the text that is currently visible on said output device.
| 0.5 |
9,372,687 | 14 | 17 |
14. The non-transitory computer readable medium of claim 13 , the instructions, when executed by the computer processor, further comprising functionality for: identifying a first geographical region based on the attribute of the initial seed user, wherein the pre-determined task for the new user is performed within the first geographical region, wherein determining that the new user matches the attribute of the initial seed user comprises determining that the new user is within the first geographical region, and wherein the pre-determined task for the plurality of users is performed within the first geographical region.
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14. The non-transitory computer readable medium of claim 13 , the instructions, when executed by the computer processor, further comprising functionality for: identifying a first geographical region based on the attribute of the initial seed user, wherein the pre-determined task for the new user is performed within the first geographical region, wherein determining that the new user matches the attribute of the initial seed user comprises determining that the new user is within the first geographical region, and wherein the pre-determined task for the plurality of users is performed within the first geographical region. 17. The non-transitory computer readable medium of claim 14 , the instructions, when executed by the computer processor, further comprising functionality for: receiving, from a subsequent seed user and in response to displaying the message, a revision to the structural specification of the customizable component, wherein the revision is suggested by the subsequent seed user according to another requirement of a second geographical region; configuring, for another plurality of users, another plurality of instantiations of the online software application based on the revision of the structural specification of the customizable component; extracting, from the customizable component in each of the another plurality of instantiations, another plurality of structured contents used by the another plurality of users to further configure the another plurality of instantiations for performing the pre-determined task within the second geographical region; generating another statistical measure of the another plurality of users using the another plurality of instantiations to perform the pre-determined task; generating, in response to the another statistical measure exceeding the pre-determined threshold, another suggested structured content to represent another portion of the another plurality of structured contents that is qualified based on the another statistical measure; and configuring, based on the another suggested structured content and in response to at least determining that another new user of the online software application is within the second geographical region, another instantiation of the online software application for the another new user to perform the pre-determined task within the second geographical region.
| 0.5 |
7,751,511 | 2 | 8 |
2. The method of claim 1 , wherein selecting a subset of the modeled impairment correlation terms comprises selecting the modeled impairment correlation terms having corresponding model fitting parameters that satisfy a threshold.
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2. The method of claim 1 , wherein selecting a subset of the modeled impairment correlation terms comprises selecting the modeled impairment correlation terms having corresponding model fitting parameters that satisfy a threshold. 8. The method of claim 2 , further comprising: normalizing the modeled impairment correlation terms prior to selecting the subset; and determining the model fitting parameters based on the normalized modeled impairment correlation terms.
| 0.714458 |
9,792,897 | 25 | 26 |
25. The method of claim 19 , wherein each of the plurality of PPENNs is associated with a particular problematic phoneme.
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25. The method of claim 19 , wherein each of the plurality of PPENNs is associated with a particular problematic phoneme. 26. The method of claim 25 , wherein generating at least one of the plurality of detection indicator values includes generating a flag value indicative of a binary detection result satisfying a detection threshold associated with a particular problematic phoneme.
| 0.570261 |
9,697,256 | 4 | 5 |
4. The method of claim 1 , wherein the one or more meta-descriptions are explicitly indicated by a designer of the webpage.
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4. The method of claim 1 , wherein the one or more meta-descriptions are explicitly indicated by a designer of the webpage. 5. The method of claim 4 , where providing the search result document that includes the one of the first snippet or the second snippet includes: including the second snippet, in the search result document, based on the meta-descriptions.
| 0.5 |
9,208,236 | 7 | 8 |
7. The method of claim 1 , further comprising: receiving an indication of a second version-intent indicative of a second subject-version associated with the subject of the search query; and presenting a second plurality of search results that are ranked for presentation, at least in part, based on the second subject-version indicated by the second version-intent.
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7. The method of claim 1 , further comprising: receiving an indication of a second version-intent indicative of a second subject-version associated with the subject of the search query; and presenting a second plurality of search results that are ranked for presentation, at least in part, based on the second subject-version indicated by the second version-intent. 8. The method of claim 7 , wherein receiving the indication of the second version-intent comprises receiving the indication of the second version-intent via the user-manipulatable tool.
| 0.5 |
9,185,081 | 15 | 20 |
15. A system, comprising: a processor; and a memory hosting an application, which, when executed on the processor, performs an operation for encrypting a first application data file, the operation comprising: determining a file format of the first application data file, encrypting the first application data file, selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template, storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format; and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content, embedding, in the second application data file template, textual instructions for accessing the encrypted content, and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file.
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15. A system, comprising: a processor; and a memory hosting an application, which, when executed on the processor, performs an operation for encrypting a first application data file, the operation comprising: determining a file format of the first application data file, encrypting the first application data file, selecting a second application data file template having a file format matching the file format of the first application data file, wherein a placeholder image is embedded in the second application data file template, storing the first application data file as encrypted content in an image file container, wherein storing the first application data file as the encrypted content in the image file container comprises: generating the image file container having a first image format; and embedding the encrypted content, as image data, in the image file container; replacing the placeholder image in the second application data file template with the image file container storing the first application data file as encrypted content, embedding, in the second application data file template, textual instructions for accessing the encrypted content, and generating a second application data file from the second application data file template, wherein the textual instructions are presented to users when accessing the second application data file. 20. The system of claim 15 , wherein the second application data file template is selected from a plurality of application data file templates, each having a different application data file format.
| 0.703313 |
9,483,532 | 1 | 9 |
1. A computer system, comprising: a processor operable to receive a text content comprising a plurality of terms, each term comprising one or more words or phrases; tokenize the text content into a plurality of terms, each term comprising one or more words or phrases; identifying a first semantic attribute or a first part of speech, wherein the first semantic attribute is selected from the group of semantic attributes consisting of at least an action, a thing, a person, an agent of an action, a recipient of an action or a thing, a state of an object, a mental state of a person, a physical state of a person, a positive or negative opinion, a name of a product, a name of a service, a name of an organization, wherein the first part of speech is selected from the group of parts of speech consisting of at least a noun or a pronoun, a transitive or intransitive verb or modal verb or link verb, an adjective, an adverb, a preposition, an article, a conjunction; identify a first term in the text content, wherein the first term is associated with the first semantic attribute or the first part of speech; identify a second term in the text content, wherein the second term is not associated with the first semantic attribute or the first part of speech; associate an importance measure to the first term, based at least on the first semantic attribute or the first part of speech, to mark the first term as bearing more importance than the second term in representing a topic or an information focus in the text content; extract the first term based on the importance measure; and output the first term; when the first term is output, the function of the first term includes being a tag or a label to represent a topic or a summary of the text content, or a category node; when the first term is output and displayed, the display format includes the font type, size, color, shape, position, or orientation of the first term based on the importance measure; when the text content containing the first term is made searchable using a query or is associated with a search index to produce a search result, the search result is ranked based at least on the importance measure.
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1. A computer system, comprising: a processor operable to receive a text content comprising a plurality of terms, each term comprising one or more words or phrases; tokenize the text content into a plurality of terms, each term comprising one or more words or phrases; identifying a first semantic attribute or a first part of speech, wherein the first semantic attribute is selected from the group of semantic attributes consisting of at least an action, a thing, a person, an agent of an action, a recipient of an action or a thing, a state of an object, a mental state of a person, a physical state of a person, a positive or negative opinion, a name of a product, a name of a service, a name of an organization, wherein the first part of speech is selected from the group of parts of speech consisting of at least a noun or a pronoun, a transitive or intransitive verb or modal verb or link verb, an adjective, an adverb, a preposition, an article, a conjunction; identify a first term in the text content, wherein the first term is associated with the first semantic attribute or the first part of speech; identify a second term in the text content, wherein the second term is not associated with the first semantic attribute or the first part of speech; associate an importance measure to the first term, based at least on the first semantic attribute or the first part of speech, to mark the first term as bearing more importance than the second term in representing a topic or an information focus in the text content; extract the first term based on the importance measure; and output the first term; when the first term is output, the function of the first term includes being a tag or a label to represent a topic or a summary of the text content, or a category node; when the first term is output and displayed, the display format includes the font type, size, color, shape, position, or orientation of the first term based on the importance measure; when the text content containing the first term is made searchable using a query or is associated with a search index to produce a search result, the search result is ranked based at least on the importance measure. 9. The system of claim 1 , wherein the text content is a sub-segment text unit in a collection of sub-segment text units, wherein the sub-segment text unit includes a sentence or a paragraph when the collection is a document comprising a plurality of sentences or paragraphs, or the sub-segment text unit includes an individual document when the collection is a document collection containing a plurality of documents.
| 0.5 |
9,746,932 | 1 | 11 |
1. A computing device, comprising: a memory and a processor that are respectively configured to store and execute instructions, including instructions for causing the computing device to: track a gesture, wherein the gesture represents a user interaction with the computing device; associate the gesture with a data item; identify the gesture from amongst gestures of a set of gestures; and determine, from a lookup-up table, a global term to assign to the data item based on the gesture and a corresponding data-type, wherein the look-up table associates gestures with global terms based on a data-type corresponding to each gesture.
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1. A computing device, comprising: a memory and a processor that are respectively configured to store and execute instructions, including instructions for causing the computing device to: track a gesture, wherein the gesture represents a user interaction with the computing device; associate the gesture with a data item; identify the gesture from amongst gestures of a set of gestures; and determine, from a lookup-up table, a global term to assign to the data item based on the gesture and a corresponding data-type, wherein the look-up table associates gestures with global terms based on a data-type corresponding to each gesture. 11. The computing device of claim 1 , wherein: the instructions are also for causing the computing device to: track descriptive metadata associated with the gesture or a gesture series; and determine the global term to assign to the data item based on the descriptive metadata; and the descriptive metadata comprising at least one of a date of creation of the data item, a creator or author of the data item, a placement of the data item on a computer network, or standards used to create the data item.
| 0.5 |
10,002,191 | 16 | 17 |
16. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises: receiving audio data; causing a first audio fingerprint of the received audio data to be compared to audio fingerprints corresponding to a plurality of programs; and receiving an identity of a first program of the plurality of programs to which the first audio fingerprint corresponds based on the comparison; wherein the program that is currently being presented is identified based on the received identity of the first program.
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16. The non-transitory computer-readable medium of claim 15 , wherein the method further comprises: receiving audio data; causing a first audio fingerprint of the received audio data to be compared to audio fingerprints corresponding to a plurality of programs; and receiving an identity of a first program of the plurality of programs to which the first audio fingerprint corresponds based on the comparison; wherein the program that is currently being presented is identified based on the received identity of the first program. 17. The non-transitory computer-readable medium of claim 16 , wherein the method further comprises receiving a portion of the first program that is currently being presented based on a comparison of the first audio fingerprint to a plurality of audio fingerprints associated with the first program, wherein each of the plurality of audio fingerprints associated with the first program correspond to a particular portion of the first program.
| 0.5 |
7,483,940 | 12 | 13 |
12. A system, comprising: a plurality of agents executed in respective computers, each agent exchanging messages with at least one other agent according to a dynamically selectable agent communication language; wherein each agent is to receive a message according to an XML format from another agent that causes the receiving agent to change its agent communication language in order to successfully decode and interpret said message, wherein each agent carries plural interpreters to interpret messages according to different languages, wherein the messages are according to the XML format to describe functions and interfaces of the agents.
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12. A system, comprising: a plurality of agents executed in respective computers, each agent exchanging messages with at least one other agent according to a dynamically selectable agent communication language; wherein each agent is to receive a message according to an XML format from another agent that causes the receiving agent to change its agent communication language in order to successfully decode and interpret said message, wherein each agent carries plural interpreters to interpret messages according to different languages, wherein the messages are according to the XML format to describe functions and interfaces of the agents. 13. The system of claim 12 wherein the receiving agent generates machine executable code based on a dynamically selectable agent communication language and a message received from other agent.
| 0.721739 |
7,506,255 | 9 | 10 |
9. The method of claim 1 , further comprising: scanning the text selection to determine whether a second portion of the text selection is entered according to a second spoken language; and when a second portion of the text selection is entered in a second spoken language, determining a text reading order for the second portion of text according to the second spoken language.
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9. The method of claim 1 , further comprising: scanning the text selection to determine whether a second portion of the text selection is entered according to a second spoken language; and when a second portion of the text selection is entered in a second spoken language, determining a text reading order for the second portion of text according to the second spoken language. 10. The method of claim 9 , further comprising: rendering the second portion of the text selection in the determined text reading order for the second portion of the text such that the rendered text selection contains the first portion of the text selection rendered according to the determined reading order for the first portion and the second portion of the text selection rendered according to the determined reading order for the second portion.
| 0.5 |
9,633,116 | 1 | 2 |
1. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving, by a server comprising one or more computers, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, by the server from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, by the server, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items.
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1. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving, by a server comprising one or more computers, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, by the server from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, by the server, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items. 2. The computer storage medium of claim 1 , wherein: receiving the first endorsement information comprises receiving a profile of the first member in the member network; and profiles of members in the member network include endorsement information characterizing the members' rating of local product providers.
| 0.829295 |
9,208,153 | 1 | 11 |
1. A computer implemented method for filtering an event notification stream based on relevance to specific targets in a distributed file sharing and collaboration environment in which multiple users collaboratively view, modify and comment on a shared set of files, the method comprising the steps of: maintaining, by a computer, dynamic and static profile information concerning each one of the multiple users, wherein user profile information concerning a user describes the user and quantifies an interest level of the user in specific files, specific types of files and specific file content of the shared set, and quantifies a similarity level of the user to other specific users and to specific types of users; maintaining, by the computer, file profile information concerning each file of the shared set, wherein file profile information concerning a file describes the file and quantifies a similarity level of the file to other specific files, specific types of files and specific file content of the shared set; filtering the event notification stream of the file sharing and collaboration environment, by the computer, wherein the event notification stream comprises a plurality of notifications, each notification describing an event undertaken by a user and directed towards a file of the shared set; for each specific event notification in the filtered event notification stream, quantifying a relevance value, by the computer, for each specific one of the multiple users, based on user profile information concerning the specific user, file profile information concerning the file to which the event is directed, and user profile information concerning the user who undertook the event; and transmitting, by the computer, a notification describing the specific event only to those specific users for whom the relevance value exceeds a predetermined threshold value.
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1. A computer implemented method for filtering an event notification stream based on relevance to specific targets in a distributed file sharing and collaboration environment in which multiple users collaboratively view, modify and comment on a shared set of files, the method comprising the steps of: maintaining, by a computer, dynamic and static profile information concerning each one of the multiple users, wherein user profile information concerning a user describes the user and quantifies an interest level of the user in specific files, specific types of files and specific file content of the shared set, and quantifies a similarity level of the user to other specific users and to specific types of users; maintaining, by the computer, file profile information concerning each file of the shared set, wherein file profile information concerning a file describes the file and quantifies a similarity level of the file to other specific files, specific types of files and specific file content of the shared set; filtering the event notification stream of the file sharing and collaboration environment, by the computer, wherein the event notification stream comprises a plurality of notifications, each notification describing an event undertaken by a user and directed towards a file of the shared set; for each specific event notification in the filtered event notification stream, quantifying a relevance value, by the computer, for each specific one of the multiple users, based on user profile information concerning the specific user, file profile information concerning the file to which the event is directed, and user profile information concerning the user who undertook the event; and transmitting, by the computer, a notification describing the specific event only to those specific users for whom the relevance value exceeds a predetermined threshold value. 11. The method of claim 1 wherein quantifying a relevance value of an event notification for a specific user further comprises: adjusting a relevance value of an event notification for a target user in proportion to a quantification, in the user profile information concerning the target user, of the target user's interest level in the file to which the event is directed, in a file type of the file to which the event is directed or in content of the file to which the event is directed.
| 0.624424 |
8,340,425 | 8 | 9 |
8. The method as set forth in claim 1 , wherein the re-zoning comprises: identifying an incrementing text zone having a same location on a plurality of pages and for which at least a portion of the textual content generated by the first-pass character recognition increments from page to page; and identifying a new text zone as an instance of the incrementing text zone at the same location on a page other than the plurality of pages, the new text zone not having been identified by the zoning.
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8. The method as set forth in claim 1 , wherein the re-zoning comprises: identifying an incrementing text zone having a same location on a plurality of pages and for which at least a portion of the textual content generated by the first-pass character recognition increments from page to page; and identifying a new text zone as an instance of the incrementing text zone at the same location on a page other than the plurality of pages, the new text zone not having been identified by the zoning. 9. The method as set forth in claim 8 , wherein the identifying of an incrementing text zone comprises: identifying an incrementing page number text zone based on (1) the incrementing page number text zone having a same location in an upper or lower margin of a plurality of pages and (2) at least a portion of the textual content generated by the first-pass character recognition for the incrementing page number text zone incrementing in correspondence with pages of the plurality of pages.
| 0.5 |
9,037,956 | 7 | 8 |
7. The computer-implemented method of claim 6 , wherein the source graph comprises a social graph.
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7. The computer-implemented method of claim 6 , wherein the source graph comprises a social graph. 8. The computer-implemented method of claim 7 , wherein the social graph is maintained by a social networking service and indicates a structure of one or more relationships between a user and each of a plurality of social graph objects.
| 0.5 |
9,465,898 | 1 | 7 |
1. A method comprising: detecting, by a computing system, a presence of a combinational loop in a word-level netlist representation of a circuit design by identifying a portion of the word-level netlist having at least one characteristic associated with the combinational loop, translating the identified portion of the word-level netlist into a bit-level circuit representation, and utilizing the bit-level circuit representation to determine the identified portion of the word-level netlist includes the combinational loop; and modifying, by the computing system, the word-level netlist corresponding to the detected presence of the combinational loop.
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1. A method comprising: detecting, by a computing system, a presence of a combinational loop in a word-level netlist representation of a circuit design by identifying a portion of the word-level netlist having at least one characteristic associated with the combinational loop, translating the identified portion of the word-level netlist into a bit-level circuit representation, and utilizing the bit-level circuit representation to determine the identified portion of the word-level netlist includes the combinational loop; and modifying, by the computing system, the word-level netlist corresponding to the detected presence of the combinational loop. 7. The method of claim 1 , wherein utilizing the bit-level circuit representation to determine whether the identified portions of the word-level netlist implement the combinational loop further comprises computing a strongly connected component in the bit-level circuit representation, wherein a presence of the strongly connected component in the bit-level circuit representation indicates the identified portion of the word-level netlist implements the combinational loop.
| 0.5 |
7,577,902 | 16 | 17 |
16. The method of claim 1 , wherein the annotation is first displayed in the third layer and, subsequently, the annotation is removed from the third layer and displayed in the first layer.
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16. The method of claim 1 , wherein the annotation is first displayed in the third layer and, subsequently, the annotation is removed from the third layer and displayed in the first layer. 17. The method of claim 16 , wherein the annotation is removed from the third layer and displayed in the first layer by updating the first layer with the texture coloring annotation technique.
| 0.5 |
9,355,637 | 4 | 5 |
4. The method according to claim 1 , wherein decoding the extracted speech feature by using the identified decoding model comprises: searching for an optimal matching path for the extracted speech feature by using the identified decoding model, and obtaining a word net as the word recognition result, wherein the word net comprises a start node, an end node, and an intermediate node between the start node and the end node, and each node represents a word corresponding to a period of time.
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4. The method according to claim 1 , wherein decoding the extracted speech feature by using the identified decoding model comprises: searching for an optimal matching path for the extracted speech feature by using the identified decoding model, and obtaining a word net as the word recognition result, wherein the word net comprises a start node, an end node, and an intermediate node between the start node and the end node, and each node represents a word corresponding to a period of time. 5. The method according to claim 4 , wherein matching the keyword in the keyword dictionary and the word recognition result with each other comprises: performing a minimum error alignment operation on the word net, and generating a confusion network, wherein the confusion network performs sequencing according to time, and gives a word recognition result and a probability of the word recognition result during a period of time; and matching a keyword in the keyword dictionary and the word recognition result in the confusion network with each other, and determining a matched word recognition result as the matched keyword.
| 0.5 |
9,223,838 | 1 | 3 |
1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; identifying a node of the plurality of nodes corresponding to an advertiser; generating a plurality of structured queries that each comprise references to one or more nodes of the plurality of nodes and one or more edges of the plurality of edges, wherein at least one of the structured queries is a sponsored query comprising a reference to the identified node and one or more edges of the plurality of edges that are connected to the identified node; and sending one or more of the generated structured queries to the first user for display on a page currently accessed by the first user, wherein at least one of the sent structured queries is a sponsored query.
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1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; identifying a node of the plurality of nodes corresponding to an advertiser; generating a plurality of structured queries that each comprise references to one or more nodes of the plurality of nodes and one or more edges of the plurality of edges, wherein at least one of the structured queries is a sponsored query comprising a reference to the identified node and one or more edges of the plurality of edges that are connected to the identified node; and sending one or more of the generated structured queries to the first user for display on a page currently accessed by the first user, wherein at least one of the sent structured queries is a sponsored query. 3. The method of claim 1 , further comprising: providing a user interface to the advertiser, wherein the user interface displays one or more structured queries available for the advertiser to sponsor; and receiving a selection from the advertiser identifying one or more of the structured queries available for the advertiser to sponsor.
| 0.548257 |
8,959,110 | 6 | 7 |
6. A method for processing a query request, comprising generating a query request at an application module in an application server; retrieving metadata from a local data store, wherein the metadata is associated with the query request; analyzing the metadata to derive a query tree data structure from the metadata to identify a first sub-query to be performed to fulfill the query request, wherein the first sub-query is directed to an external database, wherein the query tree data structure identifies a second sub-query directed to a local database required to be performed to fulfill the query request, wherein the second sub-query in the query tree data structure is associated with a second data source location type indicating a local data type, and wherein the query tree data structure comprising one or more nodes representing one or more sub-queries required to be performed; determining from the query tree data structure a first data source location type indicating an external data type; initiating the first sub-query request to a query processing layer in the application module to retrieve the external data; initiating the second sub-query request to a second query processing layer in the local database; receiving local data from the local data store in response to the second sub-query; processing the external data and the local data to formulate a query results; and returning the query result in response to the query request.
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6. A method for processing a query request, comprising generating a query request at an application module in an application server; retrieving metadata from a local data store, wherein the metadata is associated with the query request; analyzing the metadata to derive a query tree data structure from the metadata to identify a first sub-query to be performed to fulfill the query request, wherein the first sub-query is directed to an external database, wherein the query tree data structure identifies a second sub-query directed to a local database required to be performed to fulfill the query request, wherein the second sub-query in the query tree data structure is associated with a second data source location type indicating a local data type, and wherein the query tree data structure comprising one or more nodes representing one or more sub-queries required to be performed; determining from the query tree data structure a first data source location type indicating an external data type; initiating the first sub-query request to a query processing layer in the application module to retrieve the external data; initiating the second sub-query request to a second query processing layer in the local database; receiving local data from the local data store in response to the second sub-query; processing the external data and the local data to formulate a query results; and returning the query result in response to the query request. 7. The method of claim 6 , wherein the query processing layer in the application module further provides the second sub-query to an external database interface module in the application module.
| 0.676174 |
7,647,212 | 1 | 3 |
1. A computer-based method for carrying out a negotiation concerning set of actions to execute a print job performed by selected ones of a plurality of participants, wherein at least one of the plurality of participants encapsulates a constraint solver in a service, comprising: defining processing instructions in a memory of the system for carrying out the negotiation using the service encapsulating the constraint solver to facilitate printing via a processor; and executing the processing instructions, via the processor, to carry out the negotiation with the service encapsulating the constraint solver; wherein said executing the processing instructions for carrying out the negotiation with the service encapsulating the constraint solver further comprises: (A) establishing encapsulation input in the memory that includes: (a) a mapping between one or more of a price, a size, and a delivery date of print-job parameters of the service and corresponding variables of the constraint solver, (b) a translation between negotiation statements on the one or more of a price, a size, and a delivery date of the print-job parameters of the service and domain constraints imposed on the corresponding variables of the constraint solver, and (c) a set of semantic constraints of the service on variables of the constraint solver; (B) constructing a graph in the memory for negotiating the set of actions to be performed, wherein each action corresponds to one or more invocation patterns, each node of the graph defining a negotiation context that has associated therewith a constraint store with at least a set of domain constraints stored therein; (C) propagating constraints defined by the set of semantic constraints and the set of domain constraints associated with nodes of the graph to other participants in the negotiation as domain constraints augment the set of semantic constraints during the negotiation utilizing a protocol defined by one or more primitives that are instantiated by the one or more invocation patterns; and (D) executing one or more actions based at least in part upon the interdependencies between the one or more invocation patterns, the one or more actions facilitate printing of at least one print job, each print job creates at least one hard copy document based at least in part upon the processing instructions.
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1. A computer-based method for carrying out a negotiation concerning set of actions to execute a print job performed by selected ones of a plurality of participants, wherein at least one of the plurality of participants encapsulates a constraint solver in a service, comprising: defining processing instructions in a memory of the system for carrying out the negotiation using the service encapsulating the constraint solver to facilitate printing via a processor; and executing the processing instructions, via the processor, to carry out the negotiation with the service encapsulating the constraint solver; wherein said executing the processing instructions for carrying out the negotiation with the service encapsulating the constraint solver further comprises: (A) establishing encapsulation input in the memory that includes: (a) a mapping between one or more of a price, a size, and a delivery date of print-job parameters of the service and corresponding variables of the constraint solver, (b) a translation between negotiation statements on the one or more of a price, a size, and a delivery date of the print-job parameters of the service and domain constraints imposed on the corresponding variables of the constraint solver, and (c) a set of semantic constraints of the service on variables of the constraint solver; (B) constructing a graph in the memory for negotiating the set of actions to be performed, wherein each action corresponds to one or more invocation patterns, each node of the graph defining a negotiation context that has associated therewith a constraint store with at least a set of domain constraints stored therein; (C) propagating constraints defined by the set of semantic constraints and the set of domain constraints associated with nodes of the graph to other participants in the negotiation as domain constraints augment the set of semantic constraints during the negotiation utilizing a protocol defined by one or more primitives that are instantiated by the one or more invocation patterns; and (D) executing one or more actions based at least in part upon the interdependencies between the one or more invocation patterns, the one or more actions facilitate printing of at least one print job, each print job creates at least one hard copy document based at least in part upon the processing instructions. 3. The method according to claim 1 , where the negotiation is defined by a negotiation problem statement.
| 0.769737 |
7,546,334 | 25 | 34 |
25. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving at least one of contextual, semiotic and taxonomic words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version.
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25. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving at least one of contextual, semiotic and taxonomic words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version. 34. A computer readable storage medium with programming instructions for filtering and securing data as claimed in claim 25 , wherein retrieving includes retrieving contextual words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects based upon predetermined statistical analysis of said additional data relative to said security sensitive words, characters or data objects.
| 0.671429 |
8,027,838 | 9 | 10 |
9. The method of claim 7 , wherein the defined Content Name comprises unique formats or unique forms of any selected word, phrase, or symbol in any natural language, or any combination of the above.
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9. The method of claim 7 , wherein the defined Content Name comprises unique formats or unique forms of any selected word, phrase, or symbol in any natural language, or any combination of the above. 10. The method of claim 9 , wherein the natural languages comprises one or more of Chinese, English, French, German, Russian, Spanish, Japanese, Korean, Thai, Vietnamese, Indian, Turkey, and Arabic.
| 0.5 |
8,117,203 | 18 | 19 |
18. The non-transitory computer-readable storage medium of claim 15 , wherein the clustering further includes: finding a most likely value of a clustering variable after all virtual-evidence have been propagated through the Bayesian belief network by means of a greedy agglomerative search process including: consider all pairs of clusters; evaluating a set of edges connecting one sample in one cluster to another sample in another cluster to choose one pair of clusters; and merging repeatedly the chosen pair of clusters to create a larger cluster until only one cluster results.
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18. The non-transitory computer-readable storage medium of claim 15 , wherein the clustering further includes: finding a most likely value of a clustering variable after all virtual-evidence have been propagated through the Bayesian belief network by means of a greedy agglomerative search process including: consider all pairs of clusters; evaluating a set of edges connecting one sample in one cluster to another sample in another cluster to choose one pair of clusters; and merging repeatedly the chosen pair of clusters to create a larger cluster until only one cluster results. 19. The non-transitory computer-readable storage medium of claim 18 , wherein the greedy agglomerative search process further includes: assigning a score to each of the pairs of clusters, the score being a product of probabilities associated with the edges and a pair of clusters with a highest score being merged when the merging is repeated.
| 0.5 |
7,801,912 | 69 | 97 |
69. A computer-accessible memory medium comprising program instructions, wherein the program instructions are configured to implement a searchable data service on a plurality of nodes, wherein the searchable data service is configured to: receive service requests from a plurality of client applications via a web services platform configured to provide a web service interface to the searchable data service, wherein the service requests comprise query requests and storage requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests and storage requests; process received storage requests on the plurality of nodes to store searchable data service objects specified in the storage requests in respective searchable indexes for a plurality of independent data stores used by the client applications, wherein the searchable indexes are on the plurality of nodes, wherein the data stores are on one or more storage devices each on a network and separate from the one or more computer devices that implement the plurality of nodes configured to participate in the searchable data service, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, and wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; process received query requests on the plurality of nodes, wherein each received query request is processed to locate a set of one or more searchable data service objects from the searchable indexes that satisfy the query request wherein the query request specifies one of the searchable indexes; and return at least the entity identifiers from the set of one or more searchable data service objects that satisfy the query request to the client applications in accordance with the web service interface.
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69. A computer-accessible memory medium comprising program instructions, wherein the program instructions are configured to implement a searchable data service on a plurality of nodes, wherein the searchable data service is configured to: receive service requests from a plurality of client applications via a web services platform configured to provide a web service interface to the searchable data service, wherein the service requests comprise query requests and storage requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests and storage requests; process received storage requests on the plurality of nodes to store searchable data service objects specified in the storage requests in respective searchable indexes for a plurality of independent data stores used by the client applications, wherein the searchable indexes are on the plurality of nodes, wherein the data stores are on one or more storage devices each on a network and separate from the one or more computer devices that implement the plurality of nodes configured to participate in the searchable data service, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, and wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; process received query requests on the plurality of nodes, wherein each received query request is processed to locate a set of one or more searchable data service objects from the searchable indexes that satisfy the query request wherein the query request specifies one of the searchable indexes; and return at least the entity identifiers from the set of one or more searchable data service objects that satisfy the query request to the client applications in accordance with the web service interface. 97. The computer-accessible memory medium as recited in claim 69 , wherein each of the plurality of nodes is configured to propagate searchable data service information to others of the plurality of nodes in accordance with a gossip protocol.
| 0.877654 |
9,507,876 | 1 | 17 |
1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes each corresponding to a plurality of objects, respectively, associated with the online social network, each object being of a particular object-type; receiving, from a client device of the first user, a first search query comprising a selection of a first query-domain, the first query-domain corresponding to a first object-type; identifying, responsive to the first search query, a first set of objects of the plurality of objects matching the first object-type, each of the identified objects corresponding to a second node within a threshold degree of separation of the first node; sending, to the client device of the first user, a first search-results page responsive to the first search query, the first search-results page comprising references to one or more of the identified objects from the first set of objects and one or more query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects; and receiving, from the client device of the first user, a second search query comprising a selection of one or more of the query-filters in response to the first user activating the corresponding query-filter elements.
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1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes each corresponding to a plurality of objects, respectively, associated with the online social network, each object being of a particular object-type; receiving, from a client device of the first user, a first search query comprising a selection of a first query-domain, the first query-domain corresponding to a first object-type; identifying, responsive to the first search query, a first set of objects of the plurality of objects matching the first object-type, each of the identified objects corresponding to a second node within a threshold degree of separation of the first node; sending, to the client device of the first user, a first search-results page responsive to the first search query, the first search-results page comprising references to one or more of the identified objects from the first set of objects and one or more query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects; and receiving, from the client device of the first user, a second search query comprising a selection of one or more of the query-filters in response to the first user activating the corresponding query-filter elements. 17. The method of claim 1 , wherein the search-results page is a user interface of a native application associated with the online social network on the client system of the first user.
| 0.829963 |
8,433,123 | 43 | 51 |
43. A method of processing documents associated with a deposit transaction of a customer, the method comprising: receiving in a document processing system a data file associated with the deposit transaction from a network, the data file including a plurality of records, each record including image data that is reproducible as a visually readable image of at least a portion of a respective document associated with the deposit transaction, a respective value, and respective identifying information; determining if one or more of the plurality of records is a suspect record based on a comparison of the respective identifying information with suspect information stored in the document processing system; determining that one of the records included in the data file associated with the deposit transaction is a suspect record; and in response to the determination of the suspect record, automatically making a suspect notice electronically available, the suspect notice including information indicative of the determination of the suspect record associated with the deposit transaction.
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43. A method of processing documents associated with a deposit transaction of a customer, the method comprising: receiving in a document processing system a data file associated with the deposit transaction from a network, the data file including a plurality of records, each record including image data that is reproducible as a visually readable image of at least a portion of a respective document associated with the deposit transaction, a respective value, and respective identifying information; determining if one or more of the plurality of records is a suspect record based on a comparison of the respective identifying information with suspect information stored in the document processing system; determining that one of the records included in the data file associated with the deposit transaction is a suspect record; and in response to the determination of the suspect record, automatically making a suspect notice electronically available, the suspect notice including information indicative of the determination of the suspect record associated with the deposit transaction. 51. The method of claim 43 , wherein the visually readable images have a resolution of at least about 200 DPI by at least about 100 DPI.
| 0.746269 |
9,355,370 | 3 | 4 |
3. The server system of claim 2 wherein the rules engine is configured to assign a reliability rating to each of the form selection rules based on the comparative evaluation of the form selection rules.
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3. The server system of claim 2 wherein the rules engine is configured to assign a reliability rating to each of the form selection rules based on the comparative evaluation of the form selection rules. 4. The server system of claim 3 wherein the set of document management instructions, if executed by the processor, are further operable to cause the server system to: display a suggested legal document form and its associated reliability rating for the legal transaction, wherein the suggested legal document form and its associated reliability rating are determined by the rules engine; and add the transaction data and the second user's form selection to the set of form usage data.
| 0.5 |
9,805,120 | 7 | 8 |
7. The method of claim 1 , further comprising, after selecting another language-region pair, formulating a new query in the language of the other language-region pair, if the language of the other language-region pair differs from the language of the original language-region pair.
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7. The method of claim 1 , further comprising, after selecting another language-region pair, formulating a new query in the language of the other language-region pair, if the language of the other language-region pair differs from the language of the original language-region pair. 8. The method of claim 7 , wherein formulating a new query in the language of the other language-region pair comprises translating the query into the other language of the other language-region pair while preserving the categorized intent of the query or projecting the query to a semantic space and finding the nearest corresponding query from the other language.
| 0.5 |
9,286,035 | 1 | 11 |
1. A method implemented at least in part by a computing device, the method comprising: (a) receiving source code to be remediated in light of a regulation set affecting logic of the source code, wherein the source code is of a programming language; (b) generating a plurality of language-independent annotations for the source code to be remediated, wherein the language-independent annotations are of a format having a grammar that forms an executable language and wherein the executable language comprises at least one change function and one or more parameters for the change function, wherein the annotations comprise: an indication of a token representing a constant or a variable name appearing in the source code; parameters comprising an indication of a change type associated with the token, an indication of a statement type associated with the token, and an indication of an impact location associated with the token; and an indication of a new value associated with the token; (c) based on the language-independent annotations, outputting a language-independent analysis tree comprising breaking down the annotations into a set of patterns and sequentially arranging the patterns for translation, wherein the analysis tree comprises nodes specifying the indication of the token and the parameters; and (d) generating a remediated version of the source code, wherein generating the remediated version comprises translating the annotations, wherein the translating comprises consuming the parameters of the analysis tree, and applying the parameters from the annotations to the change function indicated in the annotations, wherein the change function generates source code comprising the new value associated with the token complying with the regulation set in the programming language of the source code and outputting lines of remediated source code in the programming language of the source code according to the plurality of language-independent annotations, wherein the remediated version complies with the regulation set.
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1. A method implemented at least in part by a computing device, the method comprising: (a) receiving source code to be remediated in light of a regulation set affecting logic of the source code, wherein the source code is of a programming language; (b) generating a plurality of language-independent annotations for the source code to be remediated, wherein the language-independent annotations are of a format having a grammar that forms an executable language and wherein the executable language comprises at least one change function and one or more parameters for the change function, wherein the annotations comprise: an indication of a token representing a constant or a variable name appearing in the source code; parameters comprising an indication of a change type associated with the token, an indication of a statement type associated with the token, and an indication of an impact location associated with the token; and an indication of a new value associated with the token; (c) based on the language-independent annotations, outputting a language-independent analysis tree comprising breaking down the annotations into a set of patterns and sequentially arranging the patterns for translation, wherein the analysis tree comprises nodes specifying the indication of the token and the parameters; and (d) generating a remediated version of the source code, wherein generating the remediated version comprises translating the annotations, wherein the translating comprises consuming the parameters of the analysis tree, and applying the parameters from the annotations to the change function indicated in the annotations, wherein the change function generates source code comprising the new value associated with the token complying with the regulation set in the programming language of the source code and outputting lines of remediated source code in the programming language of the source code according to the plurality of language-independent annotations, wherein the remediated version complies with the regulation set. 11. The method of claim 1 further comprising: scanning the source code to be remediated, wherein the scanning identifies one or more portions to be modified based on token search patterns matching variables or constants in the source code to be remediated.
| 0.692308 |
8,775,161 | 19 | 20 |
19. The method of claim 15 wherein the story angle data of the angle set data structure further comprises, for each story angle, data representative of an importance value for that story angle.
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19. The method of claim 15 wherein the story angle data of the angle set data structure further comprises, for each story angle, data representative of an importance value for that story angle. 20. The method of claim 19 wherein the processing step further comprises the processor computing an interestingness value for the processed data based at least in part on the importance value of each story angle whose associated applicability conditions were satisfied by the processed data, and wherein the generating step comprises the processor generating the evaluation indicator based at least in part on the computed interestingness value.
| 0.624789 |
9,594,835 | 1 | 10 |
1. A method, comprising: receiving a search query via a web browser of a client; obtaining a set of search results corresponding to the search query; providing the set of search results corresponding to the search query; automatically storing information pertaining to a bookmark in user data of the web browser, wherein the bookmark identifies the search query that was received via the web browser of the client; retrieving information pertaining to a set of bookmarks including the bookmark from the user data of the web browser; and providing, by the web browser, the set of bookmarks underneath a search text box of a user interface, wherein each of the set of bookmarks is user-selectable, wherein each of the set of bookmarks identifies a corresponding search query that was previously received via the web browser of the client; wherein bookmarks provided by the web browser do not identify search queries received via other web browsers or client devices.
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1. A method, comprising: receiving a search query via a web browser of a client; obtaining a set of search results corresponding to the search query; providing the set of search results corresponding to the search query; automatically storing information pertaining to a bookmark in user data of the web browser, wherein the bookmark identifies the search query that was received via the web browser of the client; retrieving information pertaining to a set of bookmarks including the bookmark from the user data of the web browser; and providing, by the web browser, the set of bookmarks underneath a search text box of a user interface, wherein each of the set of bookmarks is user-selectable, wherein each of the set of bookmarks identifies a corresponding search query that was previously received via the web browser of the client; wherein bookmarks provided by the web browser do not identify search queries received via other web browsers or client devices. 10. The method as recited in claim 1 , further comprising: determining, for each bookmark in the set of bookmarks, a frequency with which the search query identified by the bookmark is executed via the web browser of the client; and wherein a first subset of the set of bookmarks for which search queries are executed more frequently via the web browser of the client are displayed more prominently than a second subset of the set of bookmarks for which search queries are executed less frequently via the web browser of the client.
| 0.711809 |
8,941,589 | 57 | 59 |
57. The system of claim 50 , wherein a smoothed hypothesis is generated through application of a correction factor to the average hypothesis.
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57. The system of claim 50 , wherein a smoothed hypothesis is generated through application of a correction factor to the average hypothesis. 59. The system of claim 57 , wherein the smoothed hypothesis is generated when at least one sensor of the plurality of sensors ceases detecting a tag, wherein the at least one additional sensor has previously detected the tag.
| 0.5 |
8,583,608 | 11 | 12 |
11. The computer program product of claim 8 , wherein the maximum allowable runtime for the received query is determined based on an execution time adjustment threshold which specifies a maximum amount of time for extending the execution of the received query.
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11. The computer program product of claim 8 , wherein the maximum allowable runtime for the received query is determined based on an execution time adjustment threshold which specifies a maximum amount of time for extending the execution of the received query. 12. The computer program product of claim 11 , wherein the execution time adjustment threshold comprises a maximum percentage value for increasing the estimated execution time.
| 0.5 |
9,052,812 | 21 | 30 |
21. Non-transitory computer-readable media storing instructions for executing a computer-implemented method comprising: providing a graphical design environment to a user using a processor, wherein the graphical design environment includes a drag and drop interface that allows the user to add a widget to a design; displaying a note field in a note interface in the graphical design environment that accepts a text string from the user; exporting the design from the graphical design environment and storing the design as an intermittent coded representation of the design in a markup language format, wherein a set of at least two widgets that includes the widget are exported with the design; rendering the design in a design player using the intermitted coded representation of the design in the markup language format; displaying a discussion interface in the design player that: (i) is displayed in the design player consistently with the design; (ii) displays the text string from the user as a note; (iii) has a scrollbar; and (iv) accepts a comment from a second user regarding the note; allowing the second user to use the scrollbar to scroll through a set of notes that are associated with different portions of the design while viewing a fixed portion of the design; in response to selection of an interface element that is in the discussion interface with the note by the second user, placing the design player into a state wherein each widget in the set of at least two widgets is exposed for selection by the second user as a selected widget, and wherein selection of the selected widget by the second user links the note with the widget; and displaying the comment in the graphical design environment after being accepted in the discussion interface; wherein the text string and comment are: (i) stored in a data store along with an indication of the selected widget; (ii) read from the data store and rendered by the design player from the markup language format; and (iii) read from the data store and displayed in the graphical design environment from a design environment format; and wherein the data store is accessible to the graphical design environment and the design player.
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21. Non-transitory computer-readable media storing instructions for executing a computer-implemented method comprising: providing a graphical design environment to a user using a processor, wherein the graphical design environment includes a drag and drop interface that allows the user to add a widget to a design; displaying a note field in a note interface in the graphical design environment that accepts a text string from the user; exporting the design from the graphical design environment and storing the design as an intermittent coded representation of the design in a markup language format, wherein a set of at least two widgets that includes the widget are exported with the design; rendering the design in a design player using the intermitted coded representation of the design in the markup language format; displaying a discussion interface in the design player that: (i) is displayed in the design player consistently with the design; (ii) displays the text string from the user as a note; (iii) has a scrollbar; and (iv) accepts a comment from a second user regarding the note; allowing the second user to use the scrollbar to scroll through a set of notes that are associated with different portions of the design while viewing a fixed portion of the design; in response to selection of an interface element that is in the discussion interface with the note by the second user, placing the design player into a state wherein each widget in the set of at least two widgets is exposed for selection by the second user as a selected widget, and wherein selection of the selected widget by the second user links the note with the widget; and displaying the comment in the graphical design environment after being accepted in the discussion interface; wherein the text string and comment are: (i) stored in a data store along with an indication of the selected widget; (ii) read from the data store and rendered by the design player from the markup language format; and (iii) read from the data store and displayed in the graphical design environment from a design environment format; and wherein the data store is accessible to the graphical design environment and the design player. 30. The non-transitory computer-readable media of claim 21 , wherein the method further comprises: displaying an identifier for the user with the note in the discussion interface.
| 0.842152 |
8,229,745 | 2 | 10 |
2. A method of automatically constructing a mixed-initiative grammar from a plurality of directed dialog grammars, said method comprising: presenting a graphical user interface comprising a first section that receives a user input specifying a prefix type of conjoin phrase, a second section that receives a user input specifying a directed dialog grammar that is associated with the prefix type of conjoin phrase, and a third section that receives a user input specifying a suffix type of conjoin phrase that is associated with the directed dialog grammar; receiving, within the graphical user interface, at least one user input associating conjoin phrases with directed dialog grammars thereby generating a plurality of sets, wherein each set comprises a prefix and/or a suffix type of conjoin phrase and a directed dialog grammar, wherein the conjoin phrase, when recognized within a user spoken utterance, indicates that the directed dialog grammar associated with the conjoin phrase is used when processing speech recognized text adjacent to the conjoin phrase within the user spoken utterance; prompting the user to select from among at least two grammar generation techniques, wherein the at least two grammar generation techniques are selected from a group consisting of a fixed order technique, a wide combination technique, and a narrow combination technique; receiving a user input specifying one of the at least two grammar generation techniques; and automatically generating the mixed-initiative grammar, wherein the mixed initiative grammar specifies an allowable ordering of the plurality of sets corresponding to an allowable ordering of phrases within the user spoken utterance and specifies whether duplicative phrases are allowed within the user spoken utterance according to the selected grammar generation technique.
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2. A method of automatically constructing a mixed-initiative grammar from a plurality of directed dialog grammars, said method comprising: presenting a graphical user interface comprising a first section that receives a user input specifying a prefix type of conjoin phrase, a second section that receives a user input specifying a directed dialog grammar that is associated with the prefix type of conjoin phrase, and a third section that receives a user input specifying a suffix type of conjoin phrase that is associated with the directed dialog grammar; receiving, within the graphical user interface, at least one user input associating conjoin phrases with directed dialog grammars thereby generating a plurality of sets, wherein each set comprises a prefix and/or a suffix type of conjoin phrase and a directed dialog grammar, wherein the conjoin phrase, when recognized within a user spoken utterance, indicates that the directed dialog grammar associated with the conjoin phrase is used when processing speech recognized text adjacent to the conjoin phrase within the user spoken utterance; prompting the user to select from among at least two grammar generation techniques, wherein the at least two grammar generation techniques are selected from a group consisting of a fixed order technique, a wide combination technique, and a narrow combination technique; receiving a user input specifying one of the at least two grammar generation techniques; and automatically generating the mixed-initiative grammar, wherein the mixed initiative grammar specifies an allowable ordering of the plurality of sets corresponding to an allowable ordering of phrases within the user spoken utterance and specifies whether duplicative phrases are allowed within the user spoken utterance according to the selected grammar generation technique. 10. The method of claim 2 , wherein the selected grammar generation technique dictates that the plurality of sets are used in any order when interpreting the user spoken utterance, wherein the selected grammar generation technique allows duplicative phrases.
| 0.585209 |
8,103,510 | 24 | 25 |
24. The device control method of claim 19 for controlling a navigation device mounted on a vehicle, wherein the process execution step specifies a content of a navigation process to be performed based on the specified content of the uttered speech, and performs the specified navigation process.
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24. The device control method of claim 19 for controlling a navigation device mounted on a vehicle, wherein the process execution step specifies a content of a navigation process to be performed based on the specified content of the uttered speech, and performs the specified navigation process. 25. The device control method according to claim 24 , further comprising: an information acquisition step of acquiring information via a predetermined communication device; and a speech output step of outputting a speech based on the information acquired in the information acquisition step, whereby when the navigation process specified in the process execution step is to output the information acquired in the information acquisition step, a speech is output based on the information in the speech output step.
| 0.5 |
8,589,164 | 11 | 12 |
11. A computer readable medium having stored thereon instructions that, when executed by a computing device, cause the computing device to perform functions comprising: receiving information indicative of a frequency of submission of a search query to a search engine, wherein the search query comprises a sequence of words; based on the frequency of submission of the search query exceeding a threshold, determining, for the sequence of words of the search query, groupings of one or more words of the search query based on an order in which the one or more words occur in the sequence of words of the search query; and providing information indicating the groupings to a speech recognition system to update a corpus of given sequences of words, wherein the speech recognition system is configured to convert a given spoken utterance into a given sequence of words based on the corpus of given sequences of words.
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11. A computer readable medium having stored thereon instructions that, when executed by a computing device, cause the computing device to perform functions comprising: receiving information indicative of a frequency of submission of a search query to a search engine, wherein the search query comprises a sequence of words; based on the frequency of submission of the search query exceeding a threshold, determining, for the sequence of words of the search query, groupings of one or more words of the search query based on an order in which the one or more words occur in the sequence of words of the search query; and providing information indicating the groupings to a speech recognition system to update a corpus of given sequences of words, wherein the speech recognition system is configured to convert a given spoken utterance into a given sequence of words based on the corpus of given sequences of words. 12. The computer readable medium of claim 11 , wherein the function of determining the groupings comprises generating a factor graph that includes automaton states and automaton arcs, each of the automaton arcs corresponding to a word from the sequence of words of the search query.
| 0.5 |
7,725,883 | 22 | 26 |
22. A computer system comprising: a byte-code compiler in a memory for translating source code representing functions into byte-codes representing functions; a virtual machine including an analysis unit in the memory, the analysis unit performing a first analysis of the byte codes to select a subsequence of the byte codes based on at least one property of at least one variable referenced by the subsequence of byte codes, the analysis unit further performing a second analysis of the subsequence to analyze a usage pattern of the at least one variable used by the subsequence, the second analysis examining at least one dynamic run-time property of the at least one variable used in the subsequence to determine whether the usage pattern of the at least one variable indicates that the at least one variable is suitable for processing by a compiler and shortening the subsequence based on the second analysis to exclude at least one byte-code referencing a variable identified as unsuitable for processing by the compiler; the virtual machine building a symbol table in memory of a general type and shape for each variable in the subsequence; a compiler, executed by a processor, for generating processor instructions from the byte-codes in the subsequence; and a second compiler, executed by a processor, for converting byte-codes not resident in the subsequence to alternate byte-codes.
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22. A computer system comprising: a byte-code compiler in a memory for translating source code representing functions into byte-codes representing functions; a virtual machine including an analysis unit in the memory, the analysis unit performing a first analysis of the byte codes to select a subsequence of the byte codes based on at least one property of at least one variable referenced by the subsequence of byte codes, the analysis unit further performing a second analysis of the subsequence to analyze a usage pattern of the at least one variable used by the subsequence, the second analysis examining at least one dynamic run-time property of the at least one variable used in the subsequence to determine whether the usage pattern of the at least one variable indicates that the at least one variable is suitable for processing by a compiler and shortening the subsequence based on the second analysis to exclude at least one byte-code referencing a variable identified as unsuitable for processing by the compiler; the virtual machine building a symbol table in memory of a general type and shape for each variable in the subsequence; a compiler, executed by a processor, for generating processor instructions from the byte-codes in the subsequence; and a second compiler, executed by a processor, for converting byte-codes not resident in the subsequence to alternate byte-codes. 26. The system of claim 22 , further comprising: a workspace, the workspace being a variable store associated with each function by a conventional interpreter resident in memory.
| 0.708197 |
9,489,291 | 3 | 4 |
3. The method of claim 1 , further comprising executing the business intelligence artifact in the business intelligence system to generate a business intelligence output.
|
3. The method of claim 1 , further comprising executing the business intelligence artifact in the business intelligence system to generate a business intelligence output. 4. The method of claim 3 , wherein the conditions of the at least one assertion comprise expectations pertaining to the quantity of data in the business intelligence output.
| 0.5 |
7,493,259 | 17 | 20 |
17. A method for accessing an enterprise data system via a voice communications device, comprising: enabling a communications connection to a voice access system; authenticating a login through the communications connection using a user identifier, wherein the authenticating comprises: querying a database with the user identifier, and in response to the querying, verifying the user identifier and receiving from the database an enterprise data system log-in data comprising a password for the enterprise data system; automatically logging into the enterprise data system using the enterprise data system log-in data; enabling access to a domain of the enterprise system after the logging into the enterprise data system, each of a plurality of domains corresponding to a respective object or type of data; determining a navigation context; receiving a navigation command; updating the navigation context in response to the navigation command; providing a system prompt based on the navigation context; enabling a request that a query be performed using a spoken language query corresponding to the navigation context; converting the spoken language query into a data query and executing the data query to retrieve data that corresponds to the data query in the accessed domain; providing feedback data in a verbal format via the communications connection, wherein the feedback data corresponds to data retrieved from the accessed domain and is based, at least in part, on the navigation context, and the providing the feedback data comprises: generating audio data by performing a text-to-speech conversion on retrieved data; and generating a verbalized system response by interspersing the audio data with waveform data of prompts.
|
17. A method for accessing an enterprise data system via a voice communications device, comprising: enabling a communications connection to a voice access system; authenticating a login through the communications connection using a user identifier, wherein the authenticating comprises: querying a database with the user identifier, and in response to the querying, verifying the user identifier and receiving from the database an enterprise data system log-in data comprising a password for the enterprise data system; automatically logging into the enterprise data system using the enterprise data system log-in data; enabling access to a domain of the enterprise system after the logging into the enterprise data system, each of a plurality of domains corresponding to a respective object or type of data; determining a navigation context; receiving a navigation command; updating the navigation context in response to the navigation command; providing a system prompt based on the navigation context; enabling a request that a query be performed using a spoken language query corresponding to the navigation context; converting the spoken language query into a data query and executing the data query to retrieve data that corresponds to the data query in the accessed domain; providing feedback data in a verbal format via the communications connection, wherein the feedback data corresponds to data retrieved from the accessed domain and is based, at least in part, on the navigation context, and the providing the feedback data comprises: generating audio data by performing a text-to-speech conversion on retrieved data; and generating a verbalized system response by interspersing the audio data with waveform data of prompts. 20. The method of claim 17 , further comprising: converting the spoken language query into a data request in an application-readable form; identifying one or more objects and data selection criteria corresponding to the spoken language query by processing the data request; and formulating the data query based, at least in part, on identified objects and data selection criteria.
| 0.5 |
8,943,094 | 6 | 7 |
6. The method of claim 5 , wherein the performing the primary search comprises searching the database, by the natural language processor, for concepts attributed to the natural language input phrase; and wherein the performing the secondary search comprises searching, by the natural language processor, on material concepts identified in the natural language input phrase.
|
6. The method of claim 5 , wherein the performing the primary search comprises searching the database, by the natural language processor, for concepts attributed to the natural language input phrase; and wherein the performing the secondary search comprises searching, by the natural language processor, on material concepts identified in the natural language input phrase. 7. The method of claim 6 , further comprising providing to the interface device, by the natural language processor, related responses based on the secondary search.
| 0.5 |
8,886,641 | 1 | 11 |
1. A method, implemented on at least one machine having at least one processor, storage, and a communication platform connected to a network for ranking a search result, comprising: accessing, by the at least one machine, a set of recency ranking data comprising one or more past search queries, one or more past search results, and one or more recency features, wherein the recency features comprise: a time-sensitive feature representing a particular time period that was determined based on content of at least some of the past search queries, wherein the at least some of the past search queries were sensitive to the particular time period, and a query timestamp feature representing the time at which the past search queries were received at a search engine; training, by the at least one machine, a first ranking model via machine learning based on the recency features; and determining when recency is to be utilized for ranking a search result based on the ranking model.
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1. A method, implemented on at least one machine having at least one processor, storage, and a communication platform connected to a network for ranking a search result, comprising: accessing, by the at least one machine, a set of recency ranking data comprising one or more past search queries, one or more past search results, and one or more recency features, wherein the recency features comprise: a time-sensitive feature representing a particular time period that was determined based on content of at least some of the past search queries, wherein the at least some of the past search queries were sensitive to the particular time period, and a query timestamp feature representing the time at which the past search queries were received at a search engine; training, by the at least one machine, a first ranking model via machine learning based on the recency features; and determining when recency is to be utilized for ranking a search result based on the ranking model. 11. The method of claim 1 , further comprising: accessing, by the at least one machine, a second search query received at the search engine; identifying, by the at least one machine, a plurality of second network resources for the second search query; automatically determining, by the at least one machine, whether the second search query is sensitive with respect to a second time period during which the second search query is received at the search engine; if the second search query is sensitive, then ranking, by the at least one machine, the second network resources using the first ranking model that has been trained with at least the recency features; and if the second search query is not sensitive, then ranking, by the at least one machine, the second network resources using a second ranking model that has been trained without any recency feature.
| 0.50967 |
8,457,968 | 14 | 15 |
14. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving an N-best list of speech recognition candidates; receiving a list of current partitions and a belief for each of the current partitions, wherein a partition is a group of dialog states; in an outer loop, iterating over each of the speech recognition candidates in the N-best list; in an inner loop, performing a split, update, and recombination process to generate a fixed number of partitions after each speech recognition candidate in the N-best list; and recognizing speech based on the N-best list and the fixed number of partitions.
|
14. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving an N-best list of speech recognition candidates; receiving a list of current partitions and a belief for each of the current partitions, wherein a partition is a group of dialog states; in an outer loop, iterating over each of the speech recognition candidates in the N-best list; in an inner loop, performing a split, update, and recombination process to generate a fixed number of partitions after each speech recognition candidate in the N-best list; and recognizing speech based on the N-best list and the fixed number of partitions. 15. The computer-readable storage device of claim 14 , wherein the split process performs all possible splits on all partitions.
| 0.621302 |
9,788,055 | 1 | 5 |
1. A computer-implemented method, comprising: at an electronic device that includes a processor and memory, automatically and without user interaction at the electronic device: streaming a media program to a first client device for display on the first client device; receiving a content search request associated with the media program displayed on the first client device, wherein the content search request is received from a second client device that is communicatively coupled to the first client device; obtaining an image of what is being displayed on the first client device by capturing screen display data associated with the media program displayed on the first client device; in response to the content search request: after obtaining the image of what is being displayed on the first client device: analyzing the obtained image for one or more predefined indicators of a program information overlay including information about the media program, wherein the program information overlay is distinct from the media program; in response to the analysis, determining whether the one or more predefined indicators are present in the obtained image; and in response to determining that the obtained image includes the one or more predefined indicators, extracting text displayed on the program information overlay in the obtained image, wherein the extracted text is associated with the media program; generating search terms from the extracted text; performing an Internet search based on at least some of the generated search terms to identify content associated with the media program; and transmitting the results of the Internet search to the second screen client device for concurrent display thereon when the media program is displayed on the first client device.
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1. A computer-implemented method, comprising: at an electronic device that includes a processor and memory, automatically and without user interaction at the electronic device: streaming a media program to a first client device for display on the first client device; receiving a content search request associated with the media program displayed on the first client device, wherein the content search request is received from a second client device that is communicatively coupled to the first client device; obtaining an image of what is being displayed on the first client device by capturing screen display data associated with the media program displayed on the first client device; in response to the content search request: after obtaining the image of what is being displayed on the first client device: analyzing the obtained image for one or more predefined indicators of a program information overlay including information about the media program, wherein the program information overlay is distinct from the media program; in response to the analysis, determining whether the one or more predefined indicators are present in the obtained image; and in response to determining that the obtained image includes the one or more predefined indicators, extracting text displayed on the program information overlay in the obtained image, wherein the extracted text is associated with the media program; generating search terms from the extracted text; performing an Internet search based on at least some of the generated search terms to identify content associated with the media program; and transmitting the results of the Internet search to the second screen client device for concurrent display thereon when the media program is displayed on the first client device. 5. The method of claim 1 , further comprising comparing the extracted text to electronic program guide data to confirm identification of the playing broadcast media program.
| 0.801606 |
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