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8,655,645 | 21 | 25 | 21. A computer system comprising: a database module configured to receive and store information associated with a plurality of items of digital media in a database, respective items of digital media of the plurality of items of digital media to be included in an online marketplace that makes digital media available, the information associated with the plurality of items of digital media being stored in a first language; a query module configured to receive a search request for a subset of the items of digital media, the search request being received in a second language different than the first language; a translation module configured to translate the search request from the second language into the first language; a search module configured to search the database using the translated search request to produce a set of search results responsive to the search request; and a transmission module configured to transmit the set of search results. | 21. A computer system comprising: a database module configured to receive and store information associated with a plurality of items of digital media in a database, respective items of digital media of the plurality of items of digital media to be included in an online marketplace that makes digital media available, the information associated with the plurality of items of digital media being stored in a first language; a query module configured to receive a search request for a subset of the items of digital media, the search request being received in a second language different than the first language; a translation module configured to translate the search request from the second language into the first language; a search module configured to search the database using the translated search request to produce a set of search results responsive to the search request; and a transmission module configured to transmit the set of search results. 25. The computer system of claim 21 , wherein the query module is configured to receive a search request in a third language different than the second language and different than the first language, and wherein the translation module is configured to translate the search request from the third language into the first language. | 0.756677 |
8,791,914 | 1 | 12 | 1. An input method applicable for inputting into an electronic device having an image capturing unit, a processing module, a lip-reading analyzing unit, a lip motion code database, a display module, a facial expression analyzing unit and a facial expression code database, and the input method comprising the steps of: capturing a lip motion of a person through the image capturing unit; receiving an image of the lip motion from the image capturing unit; encoding the lip motion image through the lip-reading analyzing unit to obtain a lip motion code; the processing module comparing the lip motion code with a plurality of standard lip motion codes stored in the lip motion code database, to obtain a first text result matching the lip motion code; displaying the first text result through the display module if the first text result is obtained; activating an auxiliary analyzing mode, if the first text result is not obtained, wherein the auxiliary analyzing mode is a facial expression analyzing mode; capturing a facial expression of the person through the image capturing unit; receiving an image of the facial expression from the image capturing unit; encoding the facial expression image through the facial expression analyzing unit to obtain a facial expression code; the processing module comparing the facial expression code with a plurality of standard facial expression codes stored in the facial expression code database, and comparing the lip motion code with the plurality of standard lip motion codes, to obtain a second text result matching the facial expression code and the lip motion code; and displaying the second text result through the display module if the second text result is obtained. | 1. An input method applicable for inputting into an electronic device having an image capturing unit, a processing module, a lip-reading analyzing unit, a lip motion code database, a display module, a facial expression analyzing unit and a facial expression code database, and the input method comprising the steps of: capturing a lip motion of a person through the image capturing unit; receiving an image of the lip motion from the image capturing unit; encoding the lip motion image through the lip-reading analyzing unit to obtain a lip motion code; the processing module comparing the lip motion code with a plurality of standard lip motion codes stored in the lip motion code database, to obtain a first text result matching the lip motion code; displaying the first text result through the display module if the first text result is obtained; activating an auxiliary analyzing mode, if the first text result is not obtained, wherein the auxiliary analyzing mode is a facial expression analyzing mode; capturing a facial expression of the person through the image capturing unit; receiving an image of the facial expression from the image capturing unit; encoding the facial expression image through the facial expression analyzing unit to obtain a facial expression code; the processing module comparing the facial expression code with a plurality of standard facial expression codes stored in the facial expression code database, and comparing the lip motion code with the plurality of standard lip motion codes, to obtain a second text result matching the facial expression code and the lip motion code; and displaying the second text result through the display module if the second text result is obtained. 12. The input method of claim 1 , wherein the lip motion code database is configured to store the plurality of standard lip motion codes for languages of different countries, and provides for setting one of the languages as a default language to be used on the electronic device. | 0.847874 |
9,286,404 | 1 | 5 | 1. A computer-implemented method of displaying information about a document that includes a plurality of spatial identifiers each of which identifies a corresponding location within a metric space and at least two of the locations of the spatial identifiers have a geometric relationship to each other, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; displaying a map image of a portion of the metric space; displaying a visual indicator at a position on the map image representing the location that corresponds to one of said plurality of spatial identifiers; visually indicating that the location corresponding to the visual indicator has associated data that characterizes the geometric relationship between that location and the location of another spatial identifier in the document, wherein the geometric relationship is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, the at least two corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. | 1. A computer-implemented method of displaying information about a document that includes a plurality of spatial identifiers each of which identifies a corresponding location within a metric space and at least two of the locations of the spatial identifiers have a geometric relationship to each other, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; displaying a map image of a portion of the metric space; displaying a visual indicator at a position on the map image representing the location that corresponds to one of said plurality of spatial identifiers; visually indicating that the location corresponding to the visual indicator has associated data that characterizes the geometric relationship between that location and the location of another spatial identifier in the document, wherein the geometric relationship is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, the at least two corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. 5. The computer-implemented method of claim 1 , wherein the geometric relationship is one of being a neighbor of another location. | 0.514925 |
9,275,135 | 1 | 2 | 1. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: determining which documents in a document corpus of multiple documents mention an entity of interest; clustering the documents that mention an entity of interest according to similarities across a temporal signal, a structural signal and a content signal, thereby forming multiple clusters of documents; annotating each document in the multiple clusters of documents with an annotation by marking each occurrence of the entity in each document; calculating a confidence measure for each occurrence of the entity in each document in each of the multiple clusters, wherein said confidence measure comprises the sum of (i) a measure of similarity between the given occurrence of the entity and the entity of interest, and (ii) a measure of similarity between the documents within the cluster of the given document via ∑ j x ( i , j ) sim ( i , j ) + ∑ k ∑ j ≠ N A x ( i , j ) x ( k , j ) sim ( i , k ) , wherein x(i, j) indicates mention i being assigned to entity j, sim(i, j) indicates a similarity of mention i to entity j, sim(i, k) indicates a document similarity of mention i and mention k, and NA represents a non-applicable designation; creating a graph for each of the multiple clusters, wherein each of multiple nodes of each graph represents a mention of the entity of interest, and wherein said creating comprises placing an edge between each respective pair of nodes that share a mention, wherein an edge weight attributed to each edge is equal to the similarity between the shared mention; removing said annotation from one or more documents in the multiple clusters of documents by removing said marking for each occurrence of the entity in each document that corresponds to a confidence measure below a given value; and outputting (i) each annotated document and (ii) each created graph. | 1. An article of manufacture comprising a non-transitory computer readable storage medium having computer readable instructions tangibly embodied thereon which, when implemented, cause a computer to carry out a plurality of method steps comprising: determining which documents in a document corpus of multiple documents mention an entity of interest; clustering the documents that mention an entity of interest according to similarities across a temporal signal, a structural signal and a content signal, thereby forming multiple clusters of documents; annotating each document in the multiple clusters of documents with an annotation by marking each occurrence of the entity in each document; calculating a confidence measure for each occurrence of the entity in each document in each of the multiple clusters, wherein said confidence measure comprises the sum of (i) a measure of similarity between the given occurrence of the entity and the entity of interest, and (ii) a measure of similarity between the documents within the cluster of the given document via ∑ j x ( i , j ) sim ( i , j ) + ∑ k ∑ j ≠ N A x ( i , j ) x ( k , j ) sim ( i , k ) , wherein x(i, j) indicates mention i being assigned to entity j, sim(i, j) indicates a similarity of mention i to entity j, sim(i, k) indicates a document similarity of mention i and mention k, and NA represents a non-applicable designation; creating a graph for each of the multiple clusters, wherein each of multiple nodes of each graph represents a mention of the entity of interest, and wherein said creating comprises placing an edge between each respective pair of nodes that share a mention, wherein an edge weight attributed to each edge is equal to the similarity between the shared mention; removing said annotation from one or more documents in the multiple clusters of documents by removing said marking for each occurrence of the entity in each document that corresponds to a confidence measure below a given value; and outputting (i) each annotated document and (ii) each created graph. 2. The article of manufacture of claim 1 , wherein said determining comprises using a dictionary of entities. | 0.771008 |
7,729,595 | 12 | 13 | 12. An apparatus for recording a data structure for managing reproduction of text data on a recording medium, comprising: a pickup configured to record data on the recording medium; and a controller configured to control the pickup to record at least one main audio-visual (AV) data and at least one subtitle information segment on the recording medium, each subtitle information segment being represented by each PES packet of transport packets and having a one-to-one correspondence with the PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein the at least one subtitle information segment includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment of the at least one subtitle information segment identified as the text data includes a palette identifier identifying palette information for controlling color attributes of the text data, and wherein a second subtitle information segment of the at least one subtitle information segment identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one first style information defined in the first subtitle information segment using identifier, wherein the second subtitle information segment of the at least one subtitle information segment identified as the text data includes second style information for managing reproduction of the text data by the reproducing device, and wherein a third subtitle information segment of the at least one subtitle information segment identified as the graphic data is multiplexed with the at least one main AV data into a file. | 12. An apparatus for recording a data structure for managing reproduction of text data on a recording medium, comprising: a pickup configured to record data on the recording medium; and a controller configured to control the pickup to record at least one main audio-visual (AV) data and at least one subtitle information segment on the recording medium, each subtitle information segment being represented by each PES packet of transport packets and having a one-to-one correspondence with the PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein the at least one subtitle information segment includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment of the at least one subtitle information segment identified as the text data includes a palette identifier identifying palette information for controlling color attributes of the text data, and wherein a second subtitle information segment of the at least one subtitle information segment identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one first style information defined in the first subtitle information segment using identifier, wherein the second subtitle information segment of the at least one subtitle information segment identified as the text data includes second style information for managing reproduction of the text data by the reproducing device, and wherein a third subtitle information segment of the at least one subtitle information segment identified as the graphic data is multiplexed with the at least one main AV data into a file. 13. The apparatus of claim 12 , wherein the controller is configured to control the pickup to record the second subtitle information segment identified as the text data to include more than one text subtitle region, and the subtitle information segment identified as the text data includes style information for each region. | 0.526316 |
7,930,179 | 18 | 19 | 18. A system for segmenting speech data into speaker segments by speaker, the system comprising: a processor; a first module configure to control the processor to scan input speech data with a windowed generalized likelihood ratio (GLR) function to obtain speech segments, wherein the input speech data includes a plurality of speakers; a second module configured to control the processor to cluster the speech segments into one or more clusters, wherein each cluster is associated with a single speaker; a third module configured to control the processor, if more clusters exist than speakers, to: check overlap between segments in each cluster; pool clusters that have overlap between at least one segment in each pooled cluster; and resegment and remodel the pooled clusters; a fourth module configured to control the processor to create models for each cluster; and a fifth module configured to control the processor to rescan the input speech data with the models to resegment the speech data and obtain speech segments for each speaker included in the speech data. | 18. A system for segmenting speech data into speaker segments by speaker, the system comprising: a processor; a first module configure to control the processor to scan input speech data with a windowed generalized likelihood ratio (GLR) function to obtain speech segments, wherein the input speech data includes a plurality of speakers; a second module configured to control the processor to cluster the speech segments into one or more clusters, wherein each cluster is associated with a single speaker; a third module configured to control the processor, if more clusters exist than speakers, to: check overlap between segments in each cluster; pool clusters that have overlap between at least one segment in each pooled cluster; and resegment and remodel the pooled clusters; a fourth module configured to control the processor to create models for each cluster; and a fifth module configured to control the processor to rescan the input speech data with the models to resegment the speech data and obtain speech segments for each speaker included in the speech data. 19. A system of claim 18 , wherein the first module further performs a front-end analysis on the input speech sample. | 0.504237 |
8,868,559 | 1 | 2 | 1. A method, comprising: at a computing device having one or more processors and memory: obtaining a plurality of documents, wherein a respective document in the plurality of document is associated with a query independent score; selecting a first document in the plurality of documents in accordance with a query independent score associated with the first document, wherein the first document has a fingerprint that indicates that the first document has substantially identical content to every other document in the plurality of documents; indexing, in accordance with the query independent score, the first document thereby producing an indexed first document; and with respect to the plurality of documents, including only the indexed first document in a document index. | 1. A method, comprising: at a computing device having one or more processors and memory: obtaining a plurality of documents, wherein a respective document in the plurality of document is associated with a query independent score; selecting a first document in the plurality of documents in accordance with a query independent score associated with the first document, wherein the first document has a fingerprint that indicates that the first document has substantially identical content to every other document in the plurality of documents; indexing, in accordance with the query independent score, the first document thereby producing an indexed first document; and with respect to the plurality of documents, including only the indexed first document in a document index. 2. The method of claim 1 , wherein the query independent score includes a document ranking value indicative of document importance. | 0.974394 |
8,713,433 | 11 | 12 | 11. The method of claim 1 , wherein outputting the at least one of the plurality of candidate words further comprises: outputting, by the computing device and for display at the display device, the character string; and outputting, by the computing device and for display at the display device, the at least one of the plurality of candidate words within a predefined distance above the character string. | 11. The method of claim 1 , wherein outputting the at least one of the plurality of candidate words further comprises: outputting, by the computing device and for display at the display device, the character string; and outputting, by the computing device and for display at the display device, the at least one of the plurality of candidate words within a predefined distance above the character string. 12. The method of claim 11 , wherein outputting the character string further comprises: outputting, by the computing device and for display at the display device, the character string with a format, wherein the format includes at least one of an underline, a highlight, a font size, and a font color. | 0.918033 |
8,949,773 | 1 | 8 | 1. A computer-implemented method for deriving one or more process models from natural language use case specifications, comprising: creating an in-memory model of a use case from information in natural language text describing the use case, wherein the in-memory model comprises at least an actor node and one or more action nodes comprising an action initiated at least by the actor node, wherein the action of the one or more action nodes has a type comprising at least one of input, output, create, query, update, delete, direct, initiate, and access change, the method further comprising transforming the in-memory model into a process model in predetermined modeling notation, wherein the process model comprises at least a start node, an activity node, and a sub-process node, and the method further comprising generating a selected business process model using the process model; and guiding a user to create the in-memory model, generate the selected business process model, edit the natural language text, and edit the selected business process model and edit the in-memory model; and in response to detecting an addition of a gateway in the generated business process model, the method further comprising automatically transforming the addition into creation of an exception in the natural language text of the use case of the in-memory model, wherein in response to detecting a change in at least the process model, the method further comprising triggering a consistency check among the natural language text of the use case, the in-memory model, the end-to-end business process model, and the changed process model. | 1. A computer-implemented method for deriving one or more process models from natural language use case specifications, comprising: creating an in-memory model of a use case from information in natural language text describing the use case, wherein the in-memory model comprises at least an actor node and one or more action nodes comprising an action initiated at least by the actor node, wherein the action of the one or more action nodes has a type comprising at least one of input, output, create, query, update, delete, direct, initiate, and access change, the method further comprising transforming the in-memory model into a process model in predetermined modeling notation, wherein the process model comprises at least a start node, an activity node, and a sub-process node, and the method further comprising generating a selected business process model using the process model; and guiding a user to create the in-memory model, generate the selected business process model, edit the natural language text, and edit the selected business process model and edit the in-memory model; and in response to detecting an addition of a gateway in the generated business process model, the method further comprising automatically transforming the addition into creation of an exception in the natural language text of the use case of the in-memory model, wherein in response to detecting a change in at least the process model, the method further comprising triggering a consistency check among the natural language text of the use case, the in-memory model, the end-to-end business process model, and the changed process model. 8. The method of claim 1 , wherein the predetermined modeling notation is Business Process Modeling Notation. | 0.920785 |
7,660,781 | 1 | 4 | 1. A computer implemented method executed by a processing unit for searching a database comprising a plurality of electronic documents, the method comprising: assigning each of plurality of electronic documents to at least one document category, the assigned document category based upon content of each of the plurality of electronic documents; associating metadata with each of the plurality of electronic documents, the metadata comprising a unique numeric category identifier corresponding to the at least one document category assigned to each of the plurality of electronic documents; receiving a request to search the database, the search being limited to the assigned electronic documents assigned to a specified document category associated with the request; determining if an additional search term has been received to search within the specified document category; searching the metadata associated with each of the plurality of electronic documents; returning an identity of each of the plurality of electronic documents, wherein the identity is returned as a list of document identifiers and a pointer into the list of document identifiers corresponding to a single one of the plurality of electronic documents; determining at least one application program associated with the single one of the plurality of electronic documents; providing an option to display a preview of the single one of the plurality of electronic documents, wherein the preview is operatively associated with a client-side application program that is prompted for download and installation upon selection of the option to display the preview of the single one of the plurality of electronic documents, the client-side application program being operative to display the single one of the plurality of electronic documents as it would appear when displayed in the at least one application program associated with a creation of the single one of the plurality of electronic documents, and download the single one of the plurality of electronic documents; and utilizing the pointer and the list of document identifiers to identify a second document and to retrieve the second document from the database upon selection of one of a first hyperlink and a second hyperlink, wherein the first hyperlink and the second hyperlink contain a reordered list of document identifiers according to an indicated location of the second document in the list of document identifiers without performing a second search of the metadata associated with each of the plurality of electronic documents, wherein utilizing the pointer and the list of document identifiers to identify the second document comprises: decrementing the pointer for the first hyperlink when the second document is positioned before the single one of the plurality of electronic documents in the list of document identifiers, and incrementing the pointer for the second hyperlink when the second document is positioned after the single one of the plurality of electronic documents in the list of document identifiers. | 1. A computer implemented method executed by a processing unit for searching a database comprising a plurality of electronic documents, the method comprising: assigning each of plurality of electronic documents to at least one document category, the assigned document category based upon content of each of the plurality of electronic documents; associating metadata with each of the plurality of electronic documents, the metadata comprising a unique numeric category identifier corresponding to the at least one document category assigned to each of the plurality of electronic documents; receiving a request to search the database, the search being limited to the assigned electronic documents assigned to a specified document category associated with the request; determining if an additional search term has been received to search within the specified document category; searching the metadata associated with each of the plurality of electronic documents; returning an identity of each of the plurality of electronic documents, wherein the identity is returned as a list of document identifiers and a pointer into the list of document identifiers corresponding to a single one of the plurality of electronic documents; determining at least one application program associated with the single one of the plurality of electronic documents; providing an option to display a preview of the single one of the plurality of electronic documents, wherein the preview is operatively associated with a client-side application program that is prompted for download and installation upon selection of the option to display the preview of the single one of the plurality of electronic documents, the client-side application program being operative to display the single one of the plurality of electronic documents as it would appear when displayed in the at least one application program associated with a creation of the single one of the plurality of electronic documents, and download the single one of the plurality of electronic documents; and utilizing the pointer and the list of document identifiers to identify a second document and to retrieve the second document from the database upon selection of one of a first hyperlink and a second hyperlink, wherein the first hyperlink and the second hyperlink contain a reordered list of document identifiers according to an indicated location of the second document in the list of document identifiers without performing a second search of the metadata associated with each of the plurality of electronic documents, wherein utilizing the pointer and the list of document identifiers to identify the second document comprises: decrementing the pointer for the first hyperlink when the second document is positioned before the single one of the plurality of electronic documents in the list of document identifiers, and incrementing the pointer for the second hyperlink when the second document is positioned after the single one of the plurality of electronic documents in the list of document identifiers. 4. The computer implemented method of claim 1 , further comprising determining that an additional search term has been received to search within the specified document category; and wherein returning an identity comprises returning an identity of each of the plurality of electronic documents associated with the metadata having a numeric category identifier associated with the specified document category and containing the additional search term. | 0.501111 |
9,170,782 | 1 | 2 | 1. A system comprising: a processor; a memory; and a source code editor comprising at least one module loaded into the memory causing the processor to: receive program source code to be edited; generate an editor display using the program source code; trigger execution of extension code based on an occurrence of an event at the editor display, the event associated with the extension code, the extension code being distinct from the program source code to be edited, the extension code loaded from an external source into the source code editor and executable by the processor to determine that the editor display is to be modified and to generate a changed editor display upon determining by the extension code that the editor display is to be modified; and display the changed editor display generated by the execution of the extension code. | 1. A system comprising: a processor; a memory; and a source code editor comprising at least one module loaded into the memory causing the processor to: receive program source code to be edited; generate an editor display using the program source code; trigger execution of extension code based on an occurrence of an event at the editor display, the event associated with the extension code, the extension code being distinct from the program source code to be edited, the extension code loaded from an external source into the source code editor and executable by the processor to determine that the editor display is to be modified and to generate a changed editor display upon determining by the extension code that the editor display is to be modified; and display the changed editor display generated by the execution of the extension code. 2. The system of claim 1 , further comprising at least one module loaded into the memory causing the processor to provide an application programming interface associated with the source code editor to enable the extension code to register for the event. | 0.501969 |
9,811,599 | 12 | 16 | 12. The non-transitory computer-readable medium of claim 9 , the method further comprising: transmitting the brand-driven keyword data to the user; receiving acceptance information indicating whether the user accepts or declines the brand-driven keyword data; and storing the brand-driven keyword data if the user accepts the brand-driven keyword data. | 12. The non-transitory computer-readable medium of claim 9 , the method further comprising: transmitting the brand-driven keyword data to the user; receiving acceptance information indicating whether the user accepts or declines the brand-driven keyword data; and storing the brand-driven keyword data if the user accepts the brand-driven keyword data. 16. The non-transitory computer-readable medium of claim 12 , the method further comprising: transmitting rejection information to the third party if the user declines the brand-driven keyword data. | 0.926394 |
7,958,127 | 10 | 11 | 10. The computer-readable medium of claim 9 , wherein the step of computing the tag-mediated reviewer rank for a particular reviewer comprises the steps of: obtaining implicit engagement metrics indicative of user interaction with the reviews submitted by all reviewers represented in the content quality information database; obtaining implicit engagement metrics indicative of user interaction with the reviews submitted by the particular reviewer; and normalizing the reviewer rank for the particular reviewer based on the implicit engagement metrics for the particular reviewer and the implicit engagement metrics for all reviewers represented in the content quality information database. | 10. The computer-readable medium of claim 9 , wherein the step of computing the tag-mediated reviewer rank for a particular reviewer comprises the steps of: obtaining implicit engagement metrics indicative of user interaction with the reviews submitted by all reviewers represented in the content quality information database; obtaining implicit engagement metrics indicative of user interaction with the reviews submitted by the particular reviewer; and normalizing the reviewer rank for the particular reviewer based on the implicit engagement metrics for the particular reviewer and the implicit engagement metrics for all reviewers represented in the content quality information database. 11. The computer-readable medium of claim 10 , further comprising the steps of: receiving a plurality of moderator reviews concerning the moderator reports, each moderator review expressing quality assessment information for a moderator report and one or more tags identifying subject matter addressed by the moderator review; computing a tag-mediated moderator rank for each moderator based on the moderator reviews, wherein each tag-mediated moderator rank includes tag scores for one or more tags in the associated moderator reports; storing the tag-mediated moderator ranks in the content quality information database in association with the associated tags and identifiers of the associated moderators; wherein the computation of the a tag-mediated content quality score for each electronic source document is based at least in part on the moderator ranks of one or more moderators who have submitted moderator reports concerning one or more reviews concerning the electronic source document. | 0.789129 |
6,138,086 | 20 | 21 | 20. An article of manufacture comprising a machine-readable medium, said medium having computer readable program code for handling language, country and coded graphic character set identifier requirements of a file by causing a computer to perform the steps of: (a) receiving a language code, a country code, and a coded graphic character set identifier code associated with a file; (b) mapping said language code, country code and coded graphic character set identifier code into a unique hexadecimal locale code two bytes in length; and (c) displaying said file in association with said locale code according to said language, country and coded graphic character set identifier codes. | 20. An article of manufacture comprising a machine-readable medium, said medium having computer readable program code for handling language, country and coded graphic character set identifier requirements of a file by causing a computer to perform the steps of: (a) receiving a language code, a country code, and a coded graphic character set identifier code associated with a file; (b) mapping said language code, country code and coded graphic character set identifier code into a unique hexadecimal locale code two bytes in length; and (c) displaying said file in association with said locale code according to said language, country and coded graphic character set identifier codes. 21. The article of manufacture as defined in claim 20, wherein said mapping is performed by reading from a lookup table said locale code uniquely associated with a combination of language code, country code and coded graphic character set identifier code. | 0.751462 |
10,133,715 | 8 | 9 | 8. The method of claim 7 , further comprising: generating a navigation control that includes a navigation command linked to the section, wherein the navigation command includes a label associated with the section; and displaying the navigation control overlaid on the document. | 8. The method of claim 7 , further comprising: generating a navigation control that includes a navigation command linked to the section, wherein the navigation command includes a label associated with the section; and displaying the navigation control overlaid on the document. 9. The method of claim 8 , further comprising: detecting a selection of the navigation command; and scrolling through the document to display the section. | 0.960021 |
9,466,291 | 10 | 11 | 10. A voice retrieval method comprising: setting detection criteria to detect a retrieval word, based on a characteristic of the retrieval word, such that the higher the detection accuracy of the retrieval word or the lower the pronunciation difficulty of the retrieval word or the lower the appearance probability of the retrieval word, the less number of sections to be selected, as candidate sections, from voice data including a plurality of sections obtained by dividing the voice data into a plurality of frames, the voice data being recorded using a microphone; selecting part of the plurality of sections as the candidate sections which possibly include the retrieval word by performing, by a computer processor, first voice retrieval processing on the voice data according to the detection criteria, the first voice retrieval processing including calculating a matching score using the detection criteria for each of the plurality of sections included in the voice data, the matching score indicating a possibility of the retrieval word being included in each of the plurality of sections, according to the first voice retrieval processing, and detecting sections having the matching score that satisfies the detection criteria as the candidate sections; detecting a section including the retrieval word by performing second voice retrieval processing using the detection criteria on each of the selected candidate sections, the second voice retrieval processing being different from the first voice retrieval processing; and outputting the detected section which includes the retrieval word. | 10. A voice retrieval method comprising: setting detection criteria to detect a retrieval word, based on a characteristic of the retrieval word, such that the higher the detection accuracy of the retrieval word or the lower the pronunciation difficulty of the retrieval word or the lower the appearance probability of the retrieval word, the less number of sections to be selected, as candidate sections, from voice data including a plurality of sections obtained by dividing the voice data into a plurality of frames, the voice data being recorded using a microphone; selecting part of the plurality of sections as the candidate sections which possibly include the retrieval word by performing, by a computer processor, first voice retrieval processing on the voice data according to the detection criteria, the first voice retrieval processing including calculating a matching score using the detection criteria for each of the plurality of sections included in the voice data, the matching score indicating a possibility of the retrieval word being included in each of the plurality of sections, according to the first voice retrieval processing, and detecting sections having the matching score that satisfies the detection criteria as the candidate sections; detecting a section including the retrieval word by performing second voice retrieval processing using the detection criteria on each of the selected candidate sections, the second voice retrieval processing being different from the first voice retrieval processing; and outputting the detected section which includes the retrieval word. 11. The method according to claim 10 , wherein throughput of the first voice retrieval processing is lower than that of the second voice retrieval processing. | 0.877519 |
9,418,281 | 26 | 27 | 26. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a computing device, a sequence of strokes that represent a handwritten input that was input through traces shapes of one or more handwritten characters along a handwriting input area of the computing device; determining, by the computing device, a predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area; determining, by the computing device, that (i) an end point of a first stroke of the sequence of strokes occurs in the predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area, and (ii) a beginning point of a second stroke of the sequence of strokes that immediately follows the first stroke occurs in a second sub-area of the handwriting input area that is not characterized as a character end point sub-area; based on determining that (i) the end point of the first stroke of the sequence of strokes occurs in the predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area and (ii) the beginning point of the second stroke of the sequence of strokes that immediately follows the first stroke occurs in the second sub-area of the handwriting input area that is not characterized as a character end point sub-area, designating, by the computing device, the end point of the first stroke as a candidate end point of a first handwritten character traced by the sequence of strokes; and obtaining, by the computing device, a recognized character corresponding to the first handwritten character based at least in part on the designated candidate end point of the first handwritten character. | 26. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a computing device, a sequence of strokes that represent a handwritten input that was input through traces shapes of one or more handwritten characters along a handwriting input area of the computing device; determining, by the computing device, a predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area; determining, by the computing device, that (i) an end point of a first stroke of the sequence of strokes occurs in the predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area, and (ii) a beginning point of a second stroke of the sequence of strokes that immediately follows the first stroke occurs in a second sub-area of the handwriting input area that is not characterized as a character end point sub-area; based on determining that (i) the end point of the first stroke of the sequence of strokes occurs in the predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area and (ii) the beginning point of the second stroke of the sequence of strokes that immediately follows the first stroke occurs in the second sub-area of the handwriting input area that is not characterized as a character end point sub-area, designating, by the computing device, the end point of the first stroke as a candidate end point of a first handwritten character traced by the sequence of strokes; and obtaining, by the computing device, a recognized character corresponding to the first handwritten character based at least in part on the designated candidate end point of the first handwritten character. 27. The medium of claim 26 , wherein the operations further comprise: based on determining that (i) the end point of the first stroke of the sequence of strokes occurs in the predetermined sub-area of the handwriting input area that is characterized as a character end point sub-area and (ii) the beginning point of the second stroke of the sequence of strokes that immediately follows the first stroke occurs in the second sub-area of the handwriting input area that is not characterized as a character end point sub-area, designating, by the computing device, the second stroke as being associated with a second handwritten character. | 0.500785 |
8,954,474 | 1 | 5 | 1. A method of maintaining data described in a plurality of data models, the method comprising: using an ontology to describe the data models; and managing the data models using the ontology to support semantic usage of the data in content, the managing including using a validation schema to derive and validate one or more objects governed by the ontology, the one or more objects derived from one or more data-centric components of the content, the content having a structure semantically independent of the ontology; wherein the managing is neutral relative to implementation of the content. | 1. A method of maintaining data described in a plurality of data models, the method comprising: using an ontology to describe the data models; and managing the data models using the ontology to support semantic usage of the data in content, the managing including using a validation schema to derive and validate one or more objects governed by the ontology, the one or more objects derived from one or more data-centric components of the content, the content having a structure semantically independent of the ontology; wherein the managing is neutral relative to implementation of the content. 5. The method of claim 1 , further comprising generating a report of results of the validating. | 0.893258 |
7,792,785 | 13 | 15 | 13. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive a request to identify at least one image associated with a text value; identify at least one association category from a plurality of association categories with which to perform a search; search a data structure, using the at least one association category, for an identification of the at least one image that is associated with the text value, wherein the at least one image is a visual representation of the text value; determine whether an update should be performed to one or more association categories within the plurality of association categories; responsive to an indication to perform an update of the one or more association categories, update at least one text-to-image association in the one or more association categories; responsive to identifying at least one image associated with the text value, retrieve the at least one image; and present the at least one image in a graphical user interface to a user. | 13. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive a request to identify at least one image associated with a text value; identify at least one association category from a plurality of association categories with which to perform a search; search a data structure, using the at least one association category, for an identification of the at least one image that is associated with the text value, wherein the at least one image is a visual representation of the text value; determine whether an update should be performed to one or more association categories within the plurality of association categories; responsive to an indication to perform an update of the one or more association categories, update at least one text-to-image association in the one or more association categories; responsive to identifying at least one image associated with the text value, retrieve the at least one image; and present the at least one image in a graphical user interface to a user. 15. The system of claim 13 , wherein the instructions further cause the processor to: responsive to a failure to identify the at least one image associated with the text value, present an error in a graphical user interface to a user. | 0.818885 |
8,635,521 | 1 | 6 | 1. A method of presenting a customized application page in an application, the method comprising: receiving an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; rendering an offering tile on a display by the application, the offering tile displaying a first graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus; receiving a target page identifier in response to a user selection of the offering tile; and responsive to the receiving of the user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, processing the identified markup data for the customized application page to identify at least one of the one or more resources of the application package referenced in the markup data, and rendering the customized application page defined by the identified markup data on the display to include the at least one resource. | 1. A method of presenting a customized application page in an application, the method comprising: receiving an application package from a communications network, the application package containing markup data and one or more resources defining the customized application page; rendering an offering tile on a display by the application, the offering tile displaying a first graphic image defined by an image resource in the received application package when the offering tile is in focus, and a second graphic image defined by a second image resource in the received application package when the offering tile is not in focus; receiving a target page identifier in response to a user selection of the offering tile; and responsive to the receiving of the user selection of the offering tile, identifying markup data of the application package for the customized application page according to the received target page identifier, processing the identified markup data for the customized application page to identify at least one of the one or more resources of the application package referenced in the markup data, and rendering the customized application page defined by the identified markup data on the display to include the at least one resource. 6. The method of claim 1 wherein the receiving operation comprises: periodically receiving additional application packages from a media information system server to replace the received application package, each received application package sharing a common target page identifier used by the application to reference customized application pages. | 0.559645 |
9,557,988 | 6 | 7 | 6. The method of claim 1 , further comprising: storing workflow pages in the workflow page repository, each workflow page representing steps in a workflow and comprises a reusable component defined by metadata. | 6. The method of claim 1 , further comprising: storing workflow pages in the workflow page repository, each workflow page representing steps in a workflow and comprises a reusable component defined by metadata. 7. The method of claim 6 , wherein each workflow page stored in the workflow page repository includes an ID associated with the workflow page. | 0.975627 |
7,792,831 | 1 | 6 | 1. An apparatus for extracting the structure of song lyrics using a repeated pattern of the song lyrics, comprising: a memory for storing an audio file; a lyric extractor for extracting lyric information from metadata contained in the audio file; a character string information extractor for extracting an interlude section and a repeated character string based on the extracted lyric information; a paragraph extractor for extracting a paragraph based on the repeated character string and then a set of paragraphs having a same repeated pattern among the extracted paragraphs; a lyric structure generator module for arranging interlude sections, character strings, and paragraphs related to the audio file in a tree structure; and a controller which extracts a portion of the audio file based on the tree structure and outputs the extracted portion on an audio playing device. | 1. An apparatus for extracting the structure of song lyrics using a repeated pattern of the song lyrics, comprising: a memory for storing an audio file; a lyric extractor for extracting lyric information from metadata contained in the audio file; a character string information extractor for extracting an interlude section and a repeated character string based on the extracted lyric information; a paragraph extractor for extracting a paragraph based on the repeated character string and then a set of paragraphs having a same repeated pattern among the extracted paragraphs; a lyric structure generator module for arranging interlude sections, character strings, and paragraphs related to the audio file in a tree structure; and a controller which extracts a portion of the audio file based on the tree structure and outputs the extracted portion on an audio playing device. 6. The apparatus of claim 1 , further comprising: a preprocessor for deleting supplementary information contained in the extracted lyric information. | 0.903871 |
9,665,561 | 5 | 7 | 5. A method for the clustering of related terms into separate conversation in a text-based dataset, comprising the steps of: calculating, via a lexicon engine of a data processing module, a correlation K ij between combinations of words, wherein K ij is a coefficient between a correlation parameter C ij of lemmas i with lemmas j, over F i F j , where F i is frequency of word i and F j is frequency of word j; concatenating lemmas that have a correlation K ij above a predetermined level into an artificial word via the lexicon engine; recalculating, via the lexicon engine, a correlation K ij between combinations of words in an expanded dataset comprised of said text-based dataset and artificial words obtained by concatenation; repeating the steps above for N lemmas; and using a force directed graph to visually display, via a display in communication with the data processing module, the results obtained above into separate conversations, wherein each node in the graph has N outgoing partners, and the N co-words with the highest value of K ij above a minimum value are connected together. | 5. A method for the clustering of related terms into separate conversation in a text-based dataset, comprising the steps of: calculating, via a lexicon engine of a data processing module, a correlation K ij between combinations of words, wherein K ij is a coefficient between a correlation parameter C ij of lemmas i with lemmas j, over F i F j , where F i is frequency of word i and F j is frequency of word j; concatenating lemmas that have a correlation K ij above a predetermined level into an artificial word via the lexicon engine; recalculating, via the lexicon engine, a correlation K ij between combinations of words in an expanded dataset comprised of said text-based dataset and artificial words obtained by concatenation; repeating the steps above for N lemmas; and using a force directed graph to visually display, via a display in communication with the data processing module, the results obtained above into separate conversations, wherein each node in the graph has N outgoing partners, and the N co-words with the highest value of K ij above a minimum value are connected together. 7. A method according to claim 5 , wherein said step of calculating a correlation K ij between combinations of words includes the following steps performed by the lexicon engine: replacing each word in said dataset with a lemma; correlating each lemma with every other lemma to provide a value c ij , wherein c ij is the frequency of lemma i with lemma j; calculating a correlation parameter C ij between all combinations of entries; determining a frequency of each lemma F i ; calculating said correlation K ij according to the relation K ij =C ij 2 over F i F j , wherein F i is a frequency of a word i, F j is a frequency of a word j, and F i F j is the product of frequency of word i and frequency of word j. | 0.500701 |
9,672,818 | 1 | 6 | 1. A method in a computing system of selectively updating population language models used by language recognition systems, the method comprising: receiving events for representing user changes to local language models, wherein the events are received from devices of a plurality of users; receiving information characterizing the plurality of users, wherein the information includes social-networking friend data for the users; identifying, from the received information, a user cluster based on the social-networking friend data, wherein the user cluster is for representing a subset of users sharing matching or associated instances of the social-networking friend data, and wherein the identifying is performed by a hardware processor; generating or updating a population language model for the user cluster, wherein the generating or updating of the population language model includes: identifying a subset of the events associated with the user cluster for initiating the generation or update of the population language model, and filtering the events by excluding events associated with a blacklist of vocabulary not to be added or events associated with a whitelist of vocabulary not to be deleted; aggregating the user changes and associated words corresponding to the subset of the events; and providing the population language model or updates thereof to a computing device of one or more users in the user cluster for subsequently recognizing input information provided to the computing device by the one or more users in the user cluster. | 1. A method in a computing system of selectively updating population language models used by language recognition systems, the method comprising: receiving events for representing user changes to local language models, wherein the events are received from devices of a plurality of users; receiving information characterizing the plurality of users, wherein the information includes social-networking friend data for the users; identifying, from the received information, a user cluster based on the social-networking friend data, wherein the user cluster is for representing a subset of users sharing matching or associated instances of the social-networking friend data, and wherein the identifying is performed by a hardware processor; generating or updating a population language model for the user cluster, wherein the generating or updating of the population language model includes: identifying a subset of the events associated with the user cluster for initiating the generation or update of the population language model, and filtering the events by excluding events associated with a blacklist of vocabulary not to be added or events associated with a whitelist of vocabulary not to be deleted; aggregating the user changes and associated words corresponding to the subset of the events; and providing the population language model or updates thereof to a computing device of one or more users in the user cluster for subsequently recognizing input information provided to the computing device by the one or more users in the user cluster. 6. The method of claim 1 , wherein the users in the cluster share a common interest. | 0.956067 |
9,171,272 | 9 | 10 | 9. One or more computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, wherein the computer-readable storage memory is an article of manufacture, the computer process comprising: providing a first data feed and a first plurality of applications associated with the first data feed; obtaining a second data feed; automatically without user intervention: determining applicability of the first data feed to the second data feed according to an applicability criterion; extracting expressions from the first plurality of applications associated with the first data feed based on the applicability criterion relative to the second data feed, wherein the extracted expressions satisfy the applicability criterion relative to the second data feed; and generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions, wherein the generated one or more new applications are executable at a user device allowing a user to interact with the data of the second data feed; and adjusting availability of individual ones of the generated one or more new applications to a plurality of users based on a plurality of instances of feedback received from the plurality of users who used the generated one or more of the new applications in association with the second data feed, each instance of feedback indicating which of the generated one or more new applications met one or more interests of the user in association with the second data feed. | 9. One or more computer-readable storage memory storing computer-executable instructions for executing on a computer system a computer process, wherein the computer-readable storage memory is an article of manufacture, the computer process comprising: providing a first data feed and a first plurality of applications associated with the first data feed; obtaining a second data feed; automatically without user intervention: determining applicability of the first data feed to the second data feed according to an applicability criterion; extracting expressions from the first plurality of applications associated with the first data feed based on the applicability criterion relative to the second data feed, wherein the extracted expressions satisfy the applicability criterion relative to the second data feed; and generating one or more new applications to evaluate data from the second data feed, wherein the one or more new applications include the extracted expressions, wherein the generated one or more new applications are executable at a user device allowing a user to interact with the data of the second data feed; and adjusting availability of individual ones of the generated one or more new applications to a plurality of users based on a plurality of instances of feedback received from the plurality of users who used the generated one or more of the new applications in association with the second data feed, each instance of feedback indicating which of the generated one or more new applications met one or more interests of the user in association with the second data feed. 10. The one or more computer-readable storage memory of claim 9 wherein the applicability criterion includes a similarity measure of subject matter in the first data feed and subject matter in the second data feed. | 0.615108 |
7,546,525 | 9 | 10 | 9. A method for digital ink revisions, comprising: obtaining an image of a document containing at least one handwritten annotation; sending the image to a search engine to facilitate locating an original unannotated version of the document; recognizing a handwritten annotation in the image of a the document using the original unannotated version of the document; executing a command associated with the recognized handwritten annotation, the association between the command and the recognized handwritten annotation is based at least in part upon user-preferences; undoing the executed command associated with the handwritten annotation; adding the undone command to a redo map; and selecting the undone command from the redo map to facilitate redoing the command. | 9. A method for digital ink revisions, comprising: obtaining an image of a document containing at least one handwritten annotation; sending the image to a search engine to facilitate locating an original unannotated version of the document; recognizing a handwritten annotation in the image of a the document using the original unannotated version of the document; executing a command associated with the recognized handwritten annotation, the association between the command and the recognized handwritten annotation is based at least in part upon user-preferences; undoing the executed command associated with the handwritten annotation; adding the undone command to a redo map; and selecting the undone command from the redo map to facilitate redoing the command. 10. The computer-implemented method of claim 9 , further comprising determining whether the handwritten annotation is executable. | 0.924207 |
9,432,325 | 17 | 18 | 17. The communication system as defined in claim 16 , wherein the text processing component discards a second message not determined to be a long message. | 17. The communication system as defined in claim 16 , wherein the text processing component discards a second message not determined to be a long message. 18. The communication system as defined in claim 17 , wherein negative sentiment is determined by one or more text processing techniques, wherein actionable content is determined by one or more language processing techniques. | 0.929863 |
8,332,386 | 12 | 13 | 12. The method of claim 1 , further comprising creating bonds in response to user input that expressly requests creation of bonds. | 12. The method of claim 1 , further comprising creating bonds in response to user input that expressly requests creation of bonds. 13. The method of claim 12 , further comprising receiving user input that specifies which attributes are possessed by the bonds. | 0.979721 |
8,346,577 | 10 | 11 | 10. A computerized auditing method comprising: receiving, via a processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance claim file, where each auditable item comprises a word string having one or more words; translating, using the processor, each word string for each auditable item using one or more translation steps into a translated item description; comparing, using the processor, each translated item description to a plurality of terms to generate matching information; associating, using the processor, each translated item description with an item identifier based on the matching information; using the processor, accepting or rejecting each auditable item based on the item identifier and one or more rules associated with the data file; determining at least one word of the word string is not associated with a relationship; and processing one or more non-orientation words of the word string, wherein translating the word string comprises: applying one or more combination rules to the word string, wherein each rule is associated with a logic for processing the word string; comparing the word string against a build table to generate a relationship between words of the word string, the build table comprising one or more index words, each index word being associated with index information; and generating the translated item description based on the relationship. | 10. A computerized auditing method comprising: receiving, via a processor, a data file comprising one or more auditable items, each auditable item being a line item from an insurance claim file, where each auditable item comprises a word string having one or more words; translating, using the processor, each word string for each auditable item using one or more translation steps into a translated item description; comparing, using the processor, each translated item description to a plurality of terms to generate matching information; associating, using the processor, each translated item description with an item identifier based on the matching information; using the processor, accepting or rejecting each auditable item based on the item identifier and one or more rules associated with the data file; determining at least one word of the word string is not associated with a relationship; and processing one or more non-orientation words of the word string, wherein translating the word string comprises: applying one or more combination rules to the word string, wherein each rule is associated with a logic for processing the word string; comparing the word string against a build table to generate a relationship between words of the word string, the build table comprising one or more index words, each index word being associated with index information; and generating the translated item description based on the relationship. 11. The method of claim 10 , wherein processing the one or more non-orientation words comprises: for each non-orientation word of the word string: determining whether the non-orientation word is associated with a build number; if the non-orientation word is not associated with a build number, associating the non-orientation word with a generic build number; arranging the word string based on the relationship; determining whether the word string satisfies a proper relationship criteria; and if the word string does not satisfy the proper relationship criteria, logging the word string. | 0.500847 |
6,085,160 | 14 | 24 | 14. A method of language independent speech recognition comprising: a. receiving input speech with a speech pre-processor and producing a speech-related signal representative of the input speech; b. representing in a database of acoustic hidden Markov models, subword units in each of a plurality of languages, wherein any subword unit that is common to two or more of the plurality of languages is represented by a single common acoustic hidden Markov model; c. characterizing in a language model a vocabulary of recognizable words and a set of grammar rules; and d. comparing in a speech recognizer the speech-related signal to the acoustic hidden Markov models and the language model, and recognizing the input speech as a specific word sequence of at least one word. | 14. A method of language independent speech recognition comprising: a. receiving input speech with a speech pre-processor and producing a speech-related signal representative of the input speech; b. representing in a database of acoustic hidden Markov models, subword units in each of a plurality of languages, wherein any subword unit that is common to two or more of the plurality of languages is represented by a single common acoustic hidden Markov model; c. characterizing in a language model a vocabulary of recognizable words and a set of grammar rules; and d. comparing in a speech recognizer the speech-related signal to the acoustic hidden Markov models and the language model, and recognizing the input speech as a specific word sequence of at least one word. 24. A method according to claim 14, wherein the vocabulary of recognizable words contains words in a language not present in the plurality of languages. | 0.818182 |
9,690,549 | 1 | 16 | 1. A method supporting editing of a software product, the method comprising: obtaining a graphical user interface (GUI) screen for the software product, wherein the GUI screen includes a plurality of text fields, and wherein a first resource file includes text strings for respective ones of the text fields; generating a text mapping file for the software product, wherein the text mapping file includes a module for each text string of the first resource file, wherein the module for each text string includes a text string from the resource file and a unique text string identification for the text string, and wherein the screenshot of the GUI screen for the software product includes the first text field with a first unique text string identification from the first module appended to the original first text string and the second text field with a second unique text string identification from the second module appended to the original second text string; providing a screenshot of the GUI screen for the software product for display on a display wherein the screenshot includes a first text field with an original first text string for the GUI screen from a respective first module of the text mapping file and a second text field with an original second text string for the GUI screen from a respective second module of the text mapping file; receiving user input of a new first text string for the first text field; responsive to receiving user input of the new first text string, updating the first module of the text mapping file to replace the original first text string of the first text field for the GUI screen with the new first text string of the first text field for the GUI screen; responsive to receiving user input of the new first text string, modifying the screenshot to provide a modified screenshot of the GUI screen for the software product for display on the display wherein the modified screenshot includes the first text field with the new first text string from first module of the text mapping file and the second text field with the original second text string for the GUI screen from the second module of the text mapping file, wherein the modified screenshot of the GUI screen including the first text field with the new first text string and the second text field with the original second text string for the GUI screen replaces the screenshot of the GUI screen on the display, and wherein the modified screenshot of the GUI screen for the software product includes the first text field with the first unique text string identification from the first module appended to the new first text string and the second text field with the second unique text string identification from the second module appended to the original second text string; and providing a second resource file including the new first text string for the first text field of the GUI screen; wherein the new first text string replaces the original first text string in the first text field in the modified screenshot on a first area of the display, and wherein the original second text string is maintained in the second text field in the modified screenshot on a second area of the display. | 1. A method supporting editing of a software product, the method comprising: obtaining a graphical user interface (GUI) screen for the software product, wherein the GUI screen includes a plurality of text fields, and wherein a first resource file includes text strings for respective ones of the text fields; generating a text mapping file for the software product, wherein the text mapping file includes a module for each text string of the first resource file, wherein the module for each text string includes a text string from the resource file and a unique text string identification for the text string, and wherein the screenshot of the GUI screen for the software product includes the first text field with a first unique text string identification from the first module appended to the original first text string and the second text field with a second unique text string identification from the second module appended to the original second text string; providing a screenshot of the GUI screen for the software product for display on a display wherein the screenshot includes a first text field with an original first text string for the GUI screen from a respective first module of the text mapping file and a second text field with an original second text string for the GUI screen from a respective second module of the text mapping file; receiving user input of a new first text string for the first text field; responsive to receiving user input of the new first text string, updating the first module of the text mapping file to replace the original first text string of the first text field for the GUI screen with the new first text string of the first text field for the GUI screen; responsive to receiving user input of the new first text string, modifying the screenshot to provide a modified screenshot of the GUI screen for the software product for display on the display wherein the modified screenshot includes the first text field with the new first text string from first module of the text mapping file and the second text field with the original second text string for the GUI screen from the second module of the text mapping file, wherein the modified screenshot of the GUI screen including the first text field with the new first text string and the second text field with the original second text string for the GUI screen replaces the screenshot of the GUI screen on the display, and wherein the modified screenshot of the GUI screen for the software product includes the first text field with the first unique text string identification from the first module appended to the new first text string and the second text field with the second unique text string identification from the second module appended to the original second text string; and providing a second resource file including the new first text string for the first text field of the GUI screen; wherein the new first text string replaces the original first text string in the first text field in the modified screenshot on a first area of the display, and wherein the original second text string is maintained in the second text field in the modified screenshot on a second area of the display. 16. The method of claim 1 wherein the original first text string is in a first language, and wherein the new first text string is a translation of the original first text string into a second language different than the first language. | 0.925444 |
8,782,042 | 1 | 10 | 1. A non-transitory computer readable medium storing a program which when executed by at least one processing unit identifies an entity having an entity attribute in a document, the program comprising sets of instructions for: receiving, from each process of a plurality of processes, a corresponding set of candidate identity attributes that are each for identifying a particular entity having said entity attribute specified in the document, wherein each process of the plurality of processes generates the corresponding set of candidate identity attributes based on the entity attribute specified in the document; calculating a score for each candidate identity attribute in the sets of candidate identity attributes, the calculating of a score for a particular candidate identity attribute comprising (1) identifying a set of tokens in the particular candidate identity attribute, (2) assigning a value to each token in the set of tokens based on a token count that represents a number of instances of the token across the sets of candidate identity attributes and (3) calculating the score based on the assigned values; and identifying, based on the scores calculated for the candidate identity attributes, an identity attribute from the sets of candidate identity attributes that identifies the entity having said entity attribute specified in the document, wherein a process in the plurality of processes comprises a service that identifies the set of candidate identity attributes based on a probability of a set of keywords appearing in the document. | 1. A non-transitory computer readable medium storing a program which when executed by at least one processing unit identifies an entity having an entity attribute in a document, the program comprising sets of instructions for: receiving, from each process of a plurality of processes, a corresponding set of candidate identity attributes that are each for identifying a particular entity having said entity attribute specified in the document, wherein each process of the plurality of processes generates the corresponding set of candidate identity attributes based on the entity attribute specified in the document; calculating a score for each candidate identity attribute in the sets of candidate identity attributes, the calculating of a score for a particular candidate identity attribute comprising (1) identifying a set of tokens in the particular candidate identity attribute, (2) assigning a value to each token in the set of tokens based on a token count that represents a number of instances of the token across the sets of candidate identity attributes and (3) calculating the score based on the assigned values; and identifying, based on the scores calculated for the candidate identity attributes, an identity attribute from the sets of candidate identity attributes that identifies the entity having said entity attribute specified in the document, wherein a process in the plurality of processes comprises a service that identifies the set of candidate identity attributes based on a probability of a set of keywords appearing in the document. 10. The non-transitory computer readable medium of claim 1 , wherein the set of instructions for calculating the score for the particular candidate identity attribute further comprises a set of instructions for calculating the score for the particular candidate identity attribute based on a confidence factor that represents a probability that the particular candidate identity attribute correctly identifies the entity having said entity attribute specified in the document. | 0.794296 |
8,880,548 | 10 | 11 | 10. The method of claim 6 , wherein organizing the refined search queries comprises consulting a disambiguation reference to determine that a particular first refined search query is associated with the first topic and that a particular second refined search query is associated with the second topic. | 10. The method of claim 6 , wherein organizing the refined search queries comprises consulting a disambiguation reference to determine that a particular first refined search query is associated with the first topic and that a particular second refined search query is associated with the second topic. 11. The method of claim 10 , further comprising: determining that other first refined search queries and other second refined search queries do not have readily discernable topics using the disambiguation reference; comparing first distributions of first clicked resource locators for the other first refined search queries to a corresponding first distribution of the particular first refined search query to determine that the other first refined search queries match the first topic; and comparing second distributions of second clicked resource locators for the other second refined search queries to a corresponding second distribution of the particular second refined search query to determine that the other second refined search queries match the second topic. | 0.843265 |
9,075,849 | 15 | 17 | 15. A computer-implemented method for identifying and ranking relevant documents from a corpus of citationally-related documents, said computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions: receiving a first set of identification information identifying one or more input documents from said corpus of citationally-related documents; using said first set of identification information to ascertain, from a computer-accessible index: i) a second set of identification information identifying, for each of said one or more input documents, a selected number of citationally-related output documents, and ii) for each identified pair of citationally-related input document and output document, a first numerical score having a statistical correlation to whether a direct citation exists between each said identified pair of citationally-related documents, said computer-accessible index comprising: i) identification information identifying each potential input document from said corpus of citationally-related documents, ii) identification information identifying, for each said potential input document, a selected number of citationally-related potential output documents from said corpus of citationally-related documents, and iii) said first numerical score pre-calculated for each potential pair of citationally-related potential input document and potential output document and wherein said first numerical score is calculated based at least in part on how many indirect citations exist between each said potential pair of citationally related documents and, for each indirect citation, how many citation links separate each said potential pair of citationally-related documents; calculating, for each of said citationally-related output documents, a second numerical score configured to have a statistical correlation to whether a direct citation exists between any of said one or more input documents and each of said citationally-related output documents, and wherein said second numerical score is calculated based at least in part on said first numerical score; and displaying a search query result comprising a third set of identification information identifying one or more of said citationally-related output documents and wherein said search query results are sorted in accordance with each said corresponding second numerical score. | 15. A computer-implemented method for identifying and ranking relevant documents from a corpus of citationally-related documents, said computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions: receiving a first set of identification information identifying one or more input documents from said corpus of citationally-related documents; using said first set of identification information to ascertain, from a computer-accessible index: i) a second set of identification information identifying, for each of said one or more input documents, a selected number of citationally-related output documents, and ii) for each identified pair of citationally-related input document and output document, a first numerical score having a statistical correlation to whether a direct citation exists between each said identified pair of citationally-related documents, said computer-accessible index comprising: i) identification information identifying each potential input document from said corpus of citationally-related documents, ii) identification information identifying, for each said potential input document, a selected number of citationally-related potential output documents from said corpus of citationally-related documents, and iii) said first numerical score pre-calculated for each potential pair of citationally-related potential input document and potential output document and wherein said first numerical score is calculated based at least in part on how many indirect citations exist between each said potential pair of citationally related documents and, for each indirect citation, how many citation links separate each said potential pair of citationally-related documents; calculating, for each of said citationally-related output documents, a second numerical score configured to have a statistical correlation to whether a direct citation exists between any of said one or more input documents and each of said citationally-related output documents, and wherein said second numerical score is calculated based at least in part on said first numerical score; and displaying a search query result comprising a third set of identification information identifying one or more of said citationally-related output documents and wherein said search query results are sorted in accordance with each said corresponding second numerical score. 17. The computer-implemented method of claim 15 wherein calculating said second numerical score comprises calculating, for each output document, the mathematical sum of said first numerical score for each corresponding identified pair of citationally-related input document and output document. | 0.756623 |
8,321,402 | 13 | 14 | 13. The computer system of claim 10 , further comprising: a search parameter configuration tool, wherein the search parameter configuration tool is adapted for: providing the user interface; and storing the search parameters and the result fields. | 13. The computer system of claim 10 , further comprising: a search parameter configuration tool, wherein the search parameter configuration tool is adapted for: providing the user interface; and storing the search parameters and the result fields. 14. The computer system of claim 13 , wherein the user interface is executable by a web browser. | 0.977972 |
8,412,747 | 2 | 3 | 2. The method of claim 1 , further comprising: adjusting, by the one or more processors, the probability for each of the one or more links based on one or more types of words that occur in web pages and do not occur in queries, where storing the particular information includes storing: the information identifying the probability for each of the one or more links after adjusting the probability for each of the one or more links, and the information indicating that the concept is related to the particular web page. | 2. The method of claim 1 , further comprising: adjusting, by the one or more processors, the probability for each of the one or more links based on one or more types of words that occur in web pages and do not occur in queries, where storing the particular information includes storing: the information identifying the probability for each of the one or more links after adjusting the probability for each of the one or more links, and the information indicating that the concept is related to the particular web page. 3. The method of claim 2 , where adjusting the probability for each of the one or more links based on the one or more types of words that occur in web pages and do not occur in queries includes: adjusting the probability for each of the one or more links based on a frequency of the one or more types of words that occur in web pages and do not occur in queries. | 0.868172 |
7,899,976 | 4 | 7 | 4. The integrated circuit chip according to claim 3 , wherein the programmable intelligent search memory further comprises one or more PRISM memory clusters comprising said plurality of programmable search engines, wherein said plurality of programmable search engines are organized in an array of rows and columns such that each said plurality of programmable search engines is addressable using a row address and a column address. | 4. The integrated circuit chip according to claim 3 , wherein the programmable intelligent search memory further comprises one or more PRISM memory clusters comprising said plurality of programmable search engines, wherein said plurality of programmable search engines are organized in an array of rows and columns such that each said plurality of programmable search engines is addressable using a row address and a column address. 7. The integrated circuit chip according to claim 4 , wherein the FSA extension architecture further comprises row-wise and column-wise extension architecture to couple two or more of said plurality of programmable search engines in at least one said column or at least one said row or a combination of one said row and one said column of one of said PRISM memory clusters to support a regular expression that results in a finite state automaton with a number of symbols greater than said fixed number of symbol circuits of one of said programmable search engines. | 0.883567 |
8,732,479 | 1 | 2 | 1. In a client system comprising at least one processor, at least one memory, and at least one communication interface, a computer-implemented method for backing up a user file stored in the at least one memory, the method comprising: A) generating, via the at least one processor of the client system, a plurality of file segments each corresponding to a portion of the user file; B) encrypting, via the at least one processor, each of the plurality of file segments; C) determining, via the at least one processor, mapping information and storage identifying information for each of the plurality of encrypted file segments, the mapping information comprising a location address in storage of a second system, different from the client system, where the corresponding encrypted file segment will be stored; D) updating, via the at least one processor, a backup status file associated with the user file with the plurality of mapping information and storage identifying information for each of the corresponding plurality of encrypted file segments; E) transmitting the plurality of encrypted file segments to the second system for backup, while keeping metadata of the user file at the client device in the backup status file; and F) subsequently retrieving the plurality of encrypted file segments from the second system for restoration, the encrypted file segments requested via the mapping information and storage identifying information in the backup status file, the metadata used to structurally reconstruct the client file system. | 1. In a client system comprising at least one processor, at least one memory, and at least one communication interface, a computer-implemented method for backing up a user file stored in the at least one memory, the method comprising: A) generating, via the at least one processor of the client system, a plurality of file segments each corresponding to a portion of the user file; B) encrypting, via the at least one processor, each of the plurality of file segments; C) determining, via the at least one processor, mapping information and storage identifying information for each of the plurality of encrypted file segments, the mapping information comprising a location address in storage of a second system, different from the client system, where the corresponding encrypted file segment will be stored; D) updating, via the at least one processor, a backup status file associated with the user file with the plurality of mapping information and storage identifying information for each of the corresponding plurality of encrypted file segments; E) transmitting the plurality of encrypted file segments to the second system for backup, while keeping metadata of the user file at the client device in the backup status file; and F) subsequently retrieving the plurality of encrypted file segments from the second system for restoration, the encrypted file segments requested via the mapping information and storage identifying information in the backup status file, the metadata used to structurally reconstruct the client file system. 2. The method of claim 1 , wherein the mapping information includes byte ranges for each of the plurality of file segments. | 0.87449 |
8,510,249 | 2 | 4 | 2. The information analysis apparatus according to claim 1 , further comprising: a unit-of-analysis generation unit that generates a plurality of the units of analysis from the text information, wherein the density estimation unit estimates the density for each unit of analysis generated by the unit-of-analysis generation unit. | 2. The information analysis apparatus according to claim 1 , further comprising: a unit-of-analysis generation unit that generates a plurality of the units of analysis from the text information, wherein the density estimation unit estimates the density for each unit of analysis generated by the unit-of-analysis generation unit. 4. The information analysis apparatus according to claim 2 , wherein the unit-of-analysis generation unit generates the plurality of units of analysis by, for each unit of analysis, extracting a preset number of consecutive sentences from a plurality of consecutive sentences of the text information and generating the unit of analysis from the extracted consecutive sentences. | 0.905938 |
7,831,545 | 7 | 8 | 7. A computer readable storage medium storing one or more computer programs executed by a computerized server system, the one or more computer programs comprising instructions to generate a facts database, the instructions including: instructions to access a source document from a document host; instructions to extract one or more facts from the source document, each fact including an attribute-value pair and a list of documents that include the fact; instructions to identify a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; instructions to generate a set of candidate labels from the anchor text of the linking documents; instructions to select the candidate label with a highest score as a unifying subject of the one or more facts; and instructions to, for the unifying subject, store in the facts database an object distinct from the source document, wherein the object includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and information associating the source document with at least one of the facts extracted from the source document and included in the object. | 7. A computer readable storage medium storing one or more computer programs executed by a computerized server system, the one or more computer programs comprising instructions to generate a facts database, the instructions including: instructions to access a source document from a document host; instructions to extract one or more facts from the source document, each fact including an attribute-value pair and a list of documents that include the fact; instructions to identify a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; instructions to generate a set of candidate labels from the anchor text of the linking documents; instructions to select the candidate label with a highest score as a unifying subject of the one or more facts; and instructions to, for the unifying subject, store in the facts database an object distinct from the source document, wherein the object includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and information associating the source document with at least one of the facts extracted from the source document and included in the object. 8. The computer readable storage medium of claim 7 , further comprising instructions to: select one or more second labels of the candidate labels according to second predefined criteria; and associate the selected second labels with the source document and the one or more facts extracted from the source document. | 0.784341 |
9,811,584 | 5 | 6 | 5. The information retrieval system of claim 1 , wherein the influence of each keyword is displayed linearly and the influence of each keyword changes in accordance with movement of a boundary of each linearly displayed keyword. | 5. The information retrieval system of claim 1 , wherein the influence of each keyword is displayed linearly and the influence of each keyword changes in accordance with movement of a boundary of each linearly displayed keyword. 6. The information retrieval system of claim 5 , wherein the information retrieval system further comprises a pointing device, a boundary of a keyword is displayed as a slide bar on the display device, and the influence is changed by operating the slide bar using the pointing device. | 0.900976 |
7,546,334 | 62 | 64 | 62. An information processing system 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 system comprising: an identifier of said security sensitive words, characters or data objects in said compilation of additional data; means for retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; a filter compiled from with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and an extractor, operable with said filter, for extracting, from said input data, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and, means for 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. | 62. An information processing system 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 system comprising: an identifier of said security sensitive words, characters or data objects in said compilation of additional data; means for retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; a filter compiled from with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and an extractor, operable with said filter, for extracting, from said input data, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and, means for 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. 64. An information processing system as claimed in claim 62 wherein said means for retrieving includes means for 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. | 0.700286 |
8,727,965 | 1 | 3 | 1. A method for enhancing the function of the penis of a subject in need thereof comprising: providing an engineered corpus cavernosum cell transplant, wherein said cell transplant comprises a substantially pure population of freshly isolated stromal vascular fraction (SVF) cells present in a biocompatible liquid three-dimensional matrix, and injecting the engineered corpus cavernosum cell transplant into the penis of a subject. | 1. A method for enhancing the function of the penis of a subject in need thereof comprising: providing an engineered corpus cavernosum cell transplant, wherein said cell transplant comprises a substantially pure population of freshly isolated stromal vascular fraction (SVF) cells present in a biocompatible liquid three-dimensional matrix, and injecting the engineered corpus cavernosum cell transplant into the penis of a subject. 3. The method of claim 1 , wherein the subject has been diagnosed with, or is at risk of developing erectile dysfunction. | 0.748963 |
7,802,183 | 30 | 36 | 30. An electronic medical record management system for generating an electronic medical document based on a specific context from among a plurality of contexts within which an event may be documented, the system comprising a server coupled to one or more workstations, wherein a computing device of the server or one of the one or more workstations: provides one or more headings and a selection of available subheadings corresponding to each of the one or more headings; receives input signals from one or more authors to enter content for association with one or more of the selection of available subheadings corresponding to at least one of the one or more headings; converts each of the one or more available subheadings for which an input signal to enter content has been received into a corresponding one of one or more selected subheadings to be associated with a position within a structural hierarchy; receives input signals from the one or more authors to associate one or more of a plurality of contexts with the entered content and/or selected subheadings and corresponding headings; defines outlines for presenting the content to the one or more authors in an electronic medical document; and generates the electronic medical document including the content and the associated selected subheadings and headings that are associated with a specific context from among the plurality of contexts. | 30. An electronic medical record management system for generating an electronic medical document based on a specific context from among a plurality of contexts within which an event may be documented, the system comprising a server coupled to one or more workstations, wherein a computing device of the server or one of the one or more workstations: provides one or more headings and a selection of available subheadings corresponding to each of the one or more headings; receives input signals from one or more authors to enter content for association with one or more of the selection of available subheadings corresponding to at least one of the one or more headings; converts each of the one or more available subheadings for which an input signal to enter content has been received into a corresponding one of one or more selected subheadings to be associated with a position within a structural hierarchy; receives input signals from the one or more authors to associate one or more of a plurality of contexts with the entered content and/or selected subheadings and corresponding headings; defines outlines for presenting the content to the one or more authors in an electronic medical document; and generates the electronic medical document including the content and the associated selected subheadings and headings that are associated with a specific context from among the plurality of contexts. 36. The record management system of claim 30 , wherein the computing device further displays said electronic document in a workspace having a plurality of editor window panes that have a visible and logical association with the individually numbered insertion points that are present within the document, wherein said workspace displays the content of said electronic document in an additional window pane with the dictation insertion points highlighted. | 0.560928 |
9,558,101 | 7 | 9 | 7. The system of claim 5 , wherein the one or more circuits of the heuristic module are further configured to apply at least one of a Jaro distance, Jaro-Winkler distance, Hamming distance, Levenshtein distance, Damerau-Levenshtein distance, or a phonetic matching technique to the identified preprocessor directive symbol and respective preprocessor directive symbols in the set of undefined preprocessor directive symbols. | 7. The system of claim 5 , wherein the one or more circuits of the heuristic module are further configured to apply at least one of a Jaro distance, Jaro-Winkler distance, Hamming distance, Levenshtein distance, Damerau-Levenshtein distance, or a phonetic matching technique to the identified preprocessor directive symbol and respective preprocessor directive symbols in the set of undefined preprocessor directive symbols. 9. The system of claim 7 , wherein the one or more circuits of the heuristic module are further configured to apply the Levenshtein distance technique to the identified preprocessor directive symbol and respective preprocessor directive symbols in the set of undefined preprocessor directive symbols and compare a result of applying the Levenshtein distance to a threshold distance; and the system comprising a report module including one or more circuits configured to report that it is likely that the identified preprocessor directive symbol is presented erroneously in the source code file in response to determining that the result is less than the threshold. | 0.890248 |
8,249,356 | 17 | 18 | 17. A computer system for performing physical page layout analysis via tab-stop detection, the computer system comprising: a non-transitory computer-readable storage medium storing executable computer program instructions comprising instructions for: receiving an input image; determining the physical page layout of the input image, comprising: determining connected components from the input image, wherein the connected components comprise connected groups of pixels that may be text; identifying a subset of the connected components that are candidates for being located at a tab-stop by, for each respective connected component in question: establishing a vertical gutter to a side of the connected component in question; determining if neighboring connected components are in the clutter; determining if the neighboring connected components are edge-aligned with the connected component in question; and identifying the connected component in question as a candidate connected component responsive to no neighboring connected components being in the gutter and neighboring connected components being edge-aligned with the connected component in question; forming a plurality of tab-stop lines from the candidate connected components, wherein a tab-stop line defines a position of a tab-stop for a vertical span of a respective tab-stop line; creating column partitions from the positions of the plurality of tab-stop lines; and forming chains of column partitions to identify regions of the physical page layout of the input image; determining a reading order of the identified regions of the physical page layout of the input image; and outputting metadata describing at least one selected from a group consisting of the regions and the reading order for use in optical character recognition; and a processor configured to execute the computer program instructions stored on the computer-readable storage medium. | 17. A computer system for performing physical page layout analysis via tab-stop detection, the computer system comprising: a non-transitory computer-readable storage medium storing executable computer program instructions comprising instructions for: receiving an input image; determining the physical page layout of the input image, comprising: determining connected components from the input image, wherein the connected components comprise connected groups of pixels that may be text; identifying a subset of the connected components that are candidates for being located at a tab-stop by, for each respective connected component in question: establishing a vertical gutter to a side of the connected component in question; determining if neighboring connected components are in the clutter; determining if the neighboring connected components are edge-aligned with the connected component in question; and identifying the connected component in question as a candidate connected component responsive to no neighboring connected components being in the gutter and neighboring connected components being edge-aligned with the connected component in question; forming a plurality of tab-stop lines from the candidate connected components, wherein a tab-stop line defines a position of a tab-stop for a vertical span of a respective tab-stop line; creating column partitions from the positions of the plurality of tab-stop lines; and forming chains of column partitions to identify regions of the physical page layout of the input image; determining a reading order of the identified regions of the physical page layout of the input image; and outputting metadata describing at least one selected from a group consisting of the regions and the reading order for use in optical character recognition; and a processor configured to execute the computer program instructions stored on the computer-readable storage medium. 18. The computer system of claim 17 , wherein the instructions for determining the physical page layout of the input image further comprise instructions for: forming sets of column partitions that identify regions of uniform column layout of the input image. | 0.709459 |
8,515,731 | 17 | 22 | 17. A system comprising: one or more computers programmed to perform operations comprising: receiving a term and a candidate synonym for the term, where the term is in a first language, and the candidate synonym is in a second language, and where the second language is different than the first language; generating a term group of one or more text strings and a synonym group of one or more text strings, each text string in the term group corresponding to a translation of the term into a third language, and each text string in the synonym group corresponding to a translation of the synonym into the third language, where the third language is different from the first language and the second language; and determining, from an amount of overlap between the term group of text strings and the synonym group of text strings, whether the candidate synonym is a valid synonym for the term. | 17. A system comprising: one or more computers programmed to perform operations comprising: receiving a term and a candidate synonym for the term, where the term is in a first language, and the candidate synonym is in a second language, and where the second language is different than the first language; generating a term group of one or more text strings and a synonym group of one or more text strings, each text string in the term group corresponding to a translation of the term into a third language, and each text string in the synonym group corresponding to a translation of the synonym into the third language, where the third language is different from the first language and the second language; and determining, from an amount of overlap between the term group of text strings and the synonym group of text strings, whether the candidate synonym is a valid synonym for the term. 22. The system of claim 17 , where the term is from a search query and the candidate synonym is not a valid synonym for the term, the system further programmed to perform operations comprising: determining, from an analysis of a number of terms in the search query, whether to perform one of expanding the search query to include the candidate synonym or ranking search results responsive to the search query using the candidate synonym instead of expanding the search query to include the candidate synonym. | 0.500982 |
7,552,145 | 1 | 15 | 1. A method of restating telecommunications data by a batch-driven integrated rules module that receives batched client data, comprising: selecting a set of criteria for restating data from a Graphic User Interface (GUI), the set of criteria includes attributes of a business rule to be applied for restating the data; communicating the set of criteria to the batch-driven integrated rules module wherein the batch-driven integrated rules module comprises a rules database and a script generator; mapping the attributes of the business rule in the communicated set of criteria to rules in the rules database by iteratively utilizing a collection of look-up tables and conditional logic in the rules database; automatically generating a script by the script generator of the batch-driven integrated rules module by communicating with the rules database and compiling the rules in the rules database that were mapped to the attributes of the business rule; extracting data from a data warehouse based on the generated script, the data comprises legacy client data; queuing the legacy client data into a batch; transforming the batched legacy client data based on the generated script; and loading the transformed legacy client data in the data warehouse. | 1. A method of restating telecommunications data by a batch-driven integrated rules module that receives batched client data, comprising: selecting a set of criteria for restating data from a Graphic User Interface (GUI), the set of criteria includes attributes of a business rule to be applied for restating the data; communicating the set of criteria to the batch-driven integrated rules module wherein the batch-driven integrated rules module comprises a rules database and a script generator; mapping the attributes of the business rule in the communicated set of criteria to rules in the rules database by iteratively utilizing a collection of look-up tables and conditional logic in the rules database; automatically generating a script by the script generator of the batch-driven integrated rules module by communicating with the rules database and compiling the rules in the rules database that were mapped to the attributes of the business rule; extracting data from a data warehouse based on the generated script, the data comprises legacy client data; queuing the legacy client data into a batch; transforming the batched legacy client data based on the generated script; and loading the transformed legacy client data in the data warehouse. 15. The method according to claim 1 , wherein the criteria includes default attributes of the business rule. | 0.881579 |
8,190,988 | 11 | 19 | 11. A computer-readable storage medium encoding a computer program for executing a computer process on a computer system, the computer process comprising: receiving a selection of electronic form instances to be merged into a bundled electronic form instance, each electronic form instance including at least one named form field and at least one script referencing the at least one named form field; renaming at least one named form field in at least one of the electronic form instances of the selection to be unique across the selection of electronic form instances; renaming one or more references to the named form field in the at least one script in the at least one of the electronic form instances of the selection to match the renamed form field; merging the selection of electronic form instances into the bundled electronic form instance, responsive to the renaming operations. | 11. A computer-readable storage medium encoding a computer program for executing a computer process on a computer system, the computer process comprising: receiving a selection of electronic form instances to be merged into a bundled electronic form instance, each electronic form instance including at least one named form field and at least one script referencing the at least one named form field; renaming at least one named form field in at least one of the electronic form instances of the selection to be unique across the selection of electronic form instances; renaming one or more references to the named form field in the at least one script in the at least one of the electronic form instances of the selection to match the renamed form field; merging the selection of electronic form instances into the bundled electronic form instance, responsive to the renaming operations. 19. The computer-readable storage medium of claim 11 wherein the at least one script includes a form-field-specific script. | 0.852163 |
6,016,470 | 1 | 5 | 1. A rejection grammar process for use in speech recognition of an utterance comprising the steps of: selecting a digitized sub-list of phoneme models from a digitized list of phoneme models in a language, presenting a digitized sequential representation of the utterance to the rejection grammar process, and calculating a first set of probabilities indicating how well the digitized sequential representation of the utterance matches sequential combinations, or paths, of the digitized sub-list of phoneme models. | 1. A rejection grammar process for use in speech recognition of an utterance comprising the steps of: selecting a digitized sub-list of phoneme models from a digitized list of phoneme models in a language, presenting a digitized sequential representation of the utterance to the rejection grammar process, and calculating a first set of probabilities indicating how well the digitized sequential representation of the utterance matches sequential combinations, or paths, of the digitized sub-list of phoneme models. 5. The rejection grammar process of claim 1, wherein generating the selected digitized list of phoneme models comprises the steps of: (a) compiling a complete list of all phoneme models in a language, (b) forming a test set of digitized sequential representations of utterances, with known acceptable and rejectable parts thereof, (c) running said rejection grammar process, analyzing the results found for the test set, and accumulating a false rejections list and a false acceptance list and statistics of false rejections and of false acceptances, and (d) determining if the statistics of the process is acceptable, if acceptable, using the list of phoneme models, and if not acceptable: 1. determining and counting the phoneme models found in the accumulated false rejection list, 2. forming an ordered list, starting with the highest quantity, of said phoneme models found in part (1), 3. deleting a selected number of phoneme models from the beginning of the ordered list leaving another, smaller, selected digitized list of phoneme models, and 4. repeating step (c) until the statistics of the method are acceptable. | 0.595461 |
9,311,823 | 9 | 14 | 9. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive an input question to be answered from a source; process the input question to extract one or more features of the input question; compare the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determine whether there is a matching entry in the one or more entries of the QA cache, wherein the instructions to determine whether there is a matching entry in the one or more entries of the QA cache further cause the processor to: generate, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and compare the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value the instructions further cause the processor to determine a corresponding entry to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, the instructions further cause the processor to determine that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieve, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and return the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. | 9. An apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive an input question to be answered from a source; process the input question to extract one or more features of the input question; compare the extracted one or more features to cached features stored in one or more entries of a question and answer (QA) cache of the data processing system; determine whether there is a matching entry in the one or more entries of the QA cache, wherein the instructions to determine whether there is a matching entry in the one or more entries of the QA cache further cause the processor to: generate, for each entry in the QA cache, a match value indicative of a degree of matching between the one or more extracted features of the input question to cached features of the entry in the QA cache; and compare the match value to one or more threshold values indicating one or more requisite degrees of similarity between the input question and an entry in the QA cache, wherein: in response to the match value equaling or exceeding a first threshold value the instructions further cause the processor to determine a corresponding entry to match the input question, and in response to the match value being less than the first threshold value but the match value being equal to or greater than a second threshold value, the instructions further cause the processor to determine that the corresponding entry is sufficiently similar for updating the corresponding entry with the one or more extracted features of the input question; retrieve, in response to a matching entry being present in the one or more entries of the QA cache, candidate answer information from the matching entry; and return the retrieved candidate answer information to the source of the input question as candidate answer information for answering the input question. 14. The apparatus of claim 9 , wherein, in response to determining that there is not a matching entry in the one or more entries of the QA cache, the instructions further cause the processor to: determine if there is a subset of entries in the one or more entries that is similar to the input question; and output a listing of the subset of entries to a user for user selection of an entry in the subset of entries to be retrieved and used to generate candidate answers for the input question. | 0.616044 |
7,921,390 | 1 | 2 | 1. A method of using text from a design tool to display an output to a user, said method comprising: graphically displaying said output from said text of said design tool; graphically listing design rule violations; displaying said output as part of a software layer of said design tool such that no permanent changes are made to any original design file; requesting that particular violations be saved in a subset output file; generating and annotating said subset output file for use by other users such that said subset output file contains only said particular violations said user requested to be saved; generating said subset output file in a form that allows said subset output file to be applied against the design file; generating software help functions allowing said user to gain information about design rule violations; and iterating this process using said subset output file through a rule checking process as many times as necessary to remove said particular violations. | 1. A method of using text from a design tool to display an output to a user, said method comprising: graphically displaying said output from said text of said design tool; graphically listing design rule violations; displaying said output as part of a software layer of said design tool such that no permanent changes are made to any original design file; requesting that particular violations be saved in a subset output file; generating and annotating said subset output file for use by other users such that said subset output file contains only said particular violations said user requested to be saved; generating said subset output file in a form that allows said subset output file to be applied against the design file; generating software help functions allowing said user to gain information about design rule violations; and iterating this process using said subset output file through a rule checking process as many times as necessary to remove said particular violations. 2. The method of claim 1 wherein said design tool is a design rule checking system. | 0.871118 |
7,533,335 | 18 | 21 | 18. A system for representing fields in a markup language document, said system tangibly embodied on a computing device and comprising: an application that is configured to: input an application document that has been generated by a word-processing application that uses a non-markup language file format that is specific to the application; determine properties relating to a field included in at least one section of the application document, wherein the field comprises unique properties are defined by the application determine whether the field is one of a complex field and a simple field; map the properties into at least one of a markup language element, an attribute, and a value, wherein the field is designated with a simple field markup language element when the field is determined to be a simple field; store the properties in the markup language document; and a validation engine configured to validate the markup language document. | 18. A system for representing fields in a markup language document, said system tangibly embodied on a computing device and comprising: an application that is configured to: input an application document that has been generated by a word-processing application that uses a non-markup language file format that is specific to the application; determine properties relating to a field included in at least one section of the application document, wherein the field comprises unique properties are defined by the application determine whether the field is one of a complex field and a simple field; map the properties into at least one of a markup language element, an attribute, and a value, wherein the field is designated with a simple field markup language element when the field is determined to be a simple field; store the properties in the markup language document; and a validation engine configured to validate the markup language document. 21. The system of claim 18 , wherein an instruction portion of the field excludes richly formatted content and embedded additional fields when the field is a simple field. | 0.877857 |
8,539,349 | 1 | 5 | 1. A method of splitting a Chinese character sequence into word segments, the method comprising: providing a synchronization list including a plurality of Chinese words at a system; receiving an input data string including a first Chinese character sequence at the system; identifying one of the plurality of Chinese words from the synchronization list in the first Chinese character sequence at the system, wherein the identifying includes, comparing the Chinese words in the synchronization list with characters in the first Chinese character sequence; detecting a first match between a first Chinese word in the synchronization list and a leftmost or rightmost unsegmented section of the first Chinese character sequence; continuing to compare the characters in the first Chinese character sequence against other Chinese words in the synchronization list that begin with the first Chinese word; and identifying a longest Chinese word in the synchronization list that matches the leftmost or rightmost unsegmented section of the first Chinese character sequence; defining the identified longest Chinese word as a word segment in the first Chinese character sequence at the system; identifying a first undefined character sequence in the first Chinese character sequence at the system; and segmenting the first undefined character sequence into at least one word segment at the system. | 1. A method of splitting a Chinese character sequence into word segments, the method comprising: providing a synchronization list including a plurality of Chinese words at a system; receiving an input data string including a first Chinese character sequence at the system; identifying one of the plurality of Chinese words from the synchronization list in the first Chinese character sequence at the system, wherein the identifying includes, comparing the Chinese words in the synchronization list with characters in the first Chinese character sequence; detecting a first match between a first Chinese word in the synchronization list and a leftmost or rightmost unsegmented section of the first Chinese character sequence; continuing to compare the characters in the first Chinese character sequence against other Chinese words in the synchronization list that begin with the first Chinese word; and identifying a longest Chinese word in the synchronization list that matches the leftmost or rightmost unsegmented section of the first Chinese character sequence; defining the identified longest Chinese word as a word segment in the first Chinese character sequence at the system; identifying a first undefined character sequence in the first Chinese character sequence at the system; and segmenting the first undefined character sequence into at least one word segment at the system. 5. The method of claim 1 , further comprising providing a graphical user interface for receiving user feedback associated with the segmentation of the first Chinese character sequence into word segments at the system. | 0.926491 |
6,097,888 | 46 | 52 | 46. A computer-readable medium containing instructions that cause a computer system to generate executable instructions that implement a computer program represented by a program tree, the program tree having nodes representing high-level computational constructs that form the computer program, by: for each node of the program tree, selecting a reduction function for the high-level computational construct of the node; and invoking the selected reduction function to transform a portion of the program tree relating to the node to represent the high-level computational construct using low-level computational constructs; and after invoking the selected reduction function, generating executable code from the transformed representation of the program tree to implement the computer program. | 46. A computer-readable medium containing instructions that cause a computer system to generate executable instructions that implement a computer program represented by a program tree, the program tree having nodes representing high-level computational constructs that form the computer program, by: for each node of the program tree, selecting a reduction function for the high-level computational construct of the node; and invoking the selected reduction function to transform a portion of the program tree relating to the node to represent the high-level computational construct using low-level computational constructs; and after invoking the selected reduction function, generating executable code from the transformed representation of the program tree to implement the computer program. 52. The computer-readable medium of claim 46 wherein the generating of executable code is performed by a code generator portion of an existing compiler for a programming language. | 0.892686 |
9,613,145 | 1 | 13 | 1. A method comprising: obtaining selection data identifying a term selected by a user from a document displayed to the user, the term comprising one or more adjacent words; obtaining context data comprising one or more other words in the document; determining, from the context data and the selection data, a type of contextual search presentation to request from a search engine for the selected term, comprising: determining whether or not the context data and the selection data satisfy one or more criteria for presenting any of one or more types of special case contextual search presentations, wherein each type of special case contextual search presentation includes a formatted presentation of a different type of content; in response to determining that the context data and the selection data satisfy one or more criteria for presenting a first type of special case contextual search presentation: obtaining, from the search engine, a first special case contextual search presentation for the term identified by the selection data that includes a first type of content corresponding to the first type of special case contextual presentation; in response to determining that the context data and the selection data do not satisfy the criteria for presenting any of the types of special case contextual search presentations: obtaining, from the search engine, a default contextual search presentation for the selected term that includes a second type of content corresponding to the default contextual search presentation; and providing the first special case contextual search presentation or the default contextual search presentation for presentation to the user. | 1. A method comprising: obtaining selection data identifying a term selected by a user from a document displayed to the user, the term comprising one or more adjacent words; obtaining context data comprising one or more other words in the document; determining, from the context data and the selection data, a type of contextual search presentation to request from a search engine for the selected term, comprising: determining whether or not the context data and the selection data satisfy one or more criteria for presenting any of one or more types of special case contextual search presentations, wherein each type of special case contextual search presentation includes a formatted presentation of a different type of content; in response to determining that the context data and the selection data satisfy one or more criteria for presenting a first type of special case contextual search presentation: obtaining, from the search engine, a first special case contextual search presentation for the term identified by the selection data that includes a first type of content corresponding to the first type of special case contextual presentation; in response to determining that the context data and the selection data do not satisfy the criteria for presenting any of the types of special case contextual search presentations: obtaining, from the search engine, a default contextual search presentation for the selected term that includes a second type of content corresponding to the default contextual search presentation; and providing the first special case contextual search presentation or the default contextual search presentation for presentation to the user. 13. The method of claim 1 , wherein the one or more types of special case contextual search presentations comprise a time zone type of contextual search presentation that includes a time zone answer box, wherein a time zone answer box is a formatted presentation of a time in a first time zone and a corresponding time in a second time zone. | 0.722764 |
8,005,850 | 23 | 24 | 23. The method of claim 21 wherein identifying one or more hits includes comparing the query to the user-specific metadata of the annotations. | 23. The method of claim 21 wherein identifying one or more hits includes comparing the query to the user-specific metadata of the annotations. 24. The method of claim 23 wherein identifying one or more hits further includes: extracting a search term from the query; and detecting, for each of the annotations, whether the search term is present in the user-specific metadata, wherein one of the plurality of documents belonging to the corpus is identified as a hit in the event that the search term is present in the user-specific metadata. | 0.949517 |
9,792,330 | 1 | 10 | 1. A method of ranking local search results based on reviews by experts, the method comprising: receiving a query from a user via a user device; identifying a geographic area and a category of business for the query; identifying, with one or more processors using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking, with the one or more processors, local search results responsive to the query based on reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. | 1. A method of ranking local search results based on reviews by experts, the method comprising: receiving a query from a user via a user device; identifying a geographic area and a category of business for the query; identifying, with one or more processors using reviews related to the geographic area and the category of business from a plurality of users, a plurality of experts within the plurality of users based at least on respective numbers of reviews each user submitted, including iteratively modifying the category of business to identify at least a threshold number of experts; ranking, with the one or more processors, local search results responsive to the query based on reviews of the local search results by the plurality of experts; and causing the ranked local search results to be displayed via the user device. 10. The method of claim 1 , wherein ranking local search results comprises: determining, for a respective local search result, a rating from an expert; and calculating a weighted rating of the respective local search result based on the rating and an expertise score of the expert. | 0.67552 |
9,304,987 | 8 | 12 | 8. A content creation support method, comprising the following steps, when executed by a processor, performing a speech synthesis on a first text including an original string to generate a synthesized speech of the first text; performing a speech recognition on the synthesized speech to obtain a second text including a recognized string resulting from the speech recognition; extracting feature values by performing a morphological analysis on each of the first text and the second text, the feature values each including one of pronunciations of the original string and the recognized string; obtaining a first difference string and a second difference string by extracting a difference between the first text and the second text, to compare a first feature value that indicates one of the feature values corresponding to the first difference string and a second feature value that indicates one of the feature values corresponding to the second difference string, the first difference string that is a string in the first text including a difference from the second text, the second difference string that is a string in the second text including a difference from the first text; presenting one or more correction candidates according to the second feature value; and selecting at least one of the correction candidates in accordance with an instruction from a user. | 8. A content creation support method, comprising the following steps, when executed by a processor, performing a speech synthesis on a first text including an original string to generate a synthesized speech of the first text; performing a speech recognition on the synthesized speech to obtain a second text including a recognized string resulting from the speech recognition; extracting feature values by performing a morphological analysis on each of the first text and the second text, the feature values each including one of pronunciations of the original string and the recognized string; obtaining a first difference string and a second difference string by extracting a difference between the first text and the second text, to compare a first feature value that indicates one of the feature values corresponding to the first difference string and a second feature value that indicates one of the feature values corresponding to the second difference string, the first difference string that is a string in the first text including a difference from the second text, the second difference string that is a string in the second text including a difference from the first text; presenting one or more correction candidates according to the second feature value; and selecting at least one of the correction candidates in accordance with an instruction from a user. 12. The method according to claim 8 , wherein the extracting the feature values further extracts, as each of the feature values, a surface expression of a string. | 0.782842 |
8,477,109 | 20 | 21 | 20. An electronic device as recited in claim 19 , wherein the user input is received at a particular location on the touch-sensitive display associated with a particular portion of the content item, and wherein the selected reference work entry is associated with the particular portion of the content item. | 20. An electronic device as recited in claim 19 , wherein the user input is received at a particular location on the touch-sensitive display associated with a particular portion of the content item, and wherein the selected reference work entry is associated with the particular portion of the content item. 21. An electronic device as recited in claim 20 , wherein the content item comprises an electronic book, and the particular portion of the electronic book comprises a word within the electronic book. | 0.915606 |
9,128,926 | 11 | 18 | 11. A speech translation method for translating speech, comprising: accepting, by a first-language automatic speech recognition unit, spoken sound from a first speaker in a first language and creating a plurality of partial hypotheses of the spoken sound of the first speaker in substantially real time while the first speaker is speaking; merging, by a first-language resegmentation unit that is in communication with the first-language automatic speech recognition unit, at least two of the partial hypotheses received from the first-language automatic speech recognition unit; resegmenting, by the first-language resegmentation unit, the merged partial hypotheses into a first-language translatable segment in the first language, wherein a segment boundary for the first-language translatable segment is determined based on sound from a second speaker in a second language; and outputting, by a first-language machine translation unit that is in communication with the first-language resegmentation unit and that receives the first-language translatable segment in the first-language from the first-language resegmentation unit, a translation of the spoken sound from the first speaker into the second language based on the received first-language translatable segment. | 11. A speech translation method for translating speech, comprising: accepting, by a first-language automatic speech recognition unit, spoken sound from a first speaker in a first language and creating a plurality of partial hypotheses of the spoken sound of the first speaker in substantially real time while the first speaker is speaking; merging, by a first-language resegmentation unit that is in communication with the first-language automatic speech recognition unit, at least two of the partial hypotheses received from the first-language automatic speech recognition unit; resegmenting, by the first-language resegmentation unit, the merged partial hypotheses into a first-language translatable segment in the first language, wherein a segment boundary for the first-language translatable segment is determined based on sound from a second speaker in a second language; and outputting, by a first-language machine translation unit that is in communication with the first-language resegmentation unit and that receives the first-language translatable segment in the first-language from the first-language resegmentation unit, a translation of the spoken sound from the first speaker into the second language based on the received first-language translatable segment. 18. The speech translation method of claim 11 , wherein the segment boundary for the first-language translatable segment is determined based on translated speech from the second speaker in the second language. | 0.927831 |
7,584,097 | 8 | 11 | 8. A method of noisy automatic speech recognition, for a digital signal processor, employing joint compensation of additive and convolutive distortions, comprising: estimating an additive distortion factor; using estimates of a convolutive distortion factor and said additive distortion factor to compensate acoustic models and recognize a current utterance; aligning said current utterance using recognition output; and estimating an updated convolutive distortion factor based on said current utterance using first-order differential terms but disregarding log-spectral domain variance terms. | 8. A method of noisy automatic speech recognition, for a digital signal processor, employing joint compensation of additive and convolutive distortions, comprising: estimating an additive distortion factor; using estimates of a convolutive distortion factor and said additive distortion factor to compensate acoustic models and recognize a current utterance; aligning said current utterance using recognition output; and estimating an updated convolutive distortion factor based on said current utterance using first-order differential terms but disregarding log-spectral domain variance terms. 11. The method as recited in claim 8 wherein said estimating said updated convolutive distortion factor comprises obtaining sufficient statistics for each state, mixture component and frame of said current utterance. | 0.783567 |
8,112,425 | 1 | 8 | 1. A computer-implemented method for time searching data, comprising: receiving time series data streams from an information processing environment that includes a plurality of servers; organizing the time series data stream for subsequent searching by performing actions, including: determining at least one domain that corresponds to data in the time series data streams, wherein data in the time series data streams is aggregated based on at least the one determined domain; time stamping the time series data streams to create at least one time stamped event that includes at least a portion of aggregated data from the time series data streams, wherein the time stamped event represents a statistic and a pattern of behavior; employing at least one feature of the included aggregated data to determine at least one boundary for each time stamped event; segmenting each time stamped event into a plurality of segments, wherein a segment is a substring of event text; time indexing the time stamped events to create time bucketed indices based on the time stamps and segments; and receiving a time series search request; and executing the time series search request at least in part by searching the time bucketed indices. | 1. A computer-implemented method for time searching data, comprising: receiving time series data streams from an information processing environment that includes a plurality of servers; organizing the time series data stream for subsequent searching by performing actions, including: determining at least one domain that corresponds to data in the time series data streams, wherein data in the time series data streams is aggregated based on at least the one determined domain; time stamping the time series data streams to create at least one time stamped event that includes at least a portion of aggregated data from the time series data streams, wherein the time stamped event represents a statistic and a pattern of behavior; employing at least one feature of the included aggregated data to determine at least one boundary for each time stamped event; segmenting each time stamped event into a plurality of segments, wherein a segment is a substring of event text; time indexing the time stamped events to create time bucketed indices based on the time stamps and segments; and receiving a time series search request; and executing the time series search request at least in part by searching the time bucketed indices. 8. The method of claim 1 wherein the step of time indexing the time stamped events to create time bucketed indices comprises assigning the time stamped events to time buckets according to their time stamps. | 0.758782 |
9,632,693 | 3 | 4 | 3. The storage medium of claim 1 , wherein: the instructions to translate based on the application translation profile comprise: instructions to identify a touch action of the application translation profile corresponding to at least the received touch input; and instructions to provide to the OS the local input mapped to the identified touch action in the application translation profile associated with the application in focus; and the local input includes information emulating output of at least one input device whose output is useable by the OS. | 3. The storage medium of claim 1 , wherein: the instructions to translate based on the application translation profile comprise: instructions to identify a touch action of the application translation profile corresponding to at least the received touch input; and instructions to provide to the OS the local input mapped to the identified touch action in the application translation profile associated with the application in focus; and the local input includes information emulating output of at least one input device whose output is useable by the OS. 4. The storage medium of claim 3 , wherein the local input includes information emulating a sequence of keystrokes output by a keyboard, the sequence defined to invoke a given function in the application in focus. | 0.955063 |
9,069,757 | 18 | 19 | 18. A method for converting speech into text comprising: receiving a first speech signal of a first speaker; receiving a second speech signal of a second speaker; extracting paralinguistic characteristics from said first input speech signal; converting said first speech signal to a text sequence; generating phonemes based on said second speech signal; transforming said text sequence of said first speech signal into a converted speech signal of said second speaker based on said one or more phonemes of said second speech signal; and converting said converted speech signal into an output speech signal of said second speaker by applying said extracted paralinguistic characteristics to said converted speech signal. | 18. A method for converting speech into text comprising: receiving a first speech signal of a first speaker; receiving a second speech signal of a second speaker; extracting paralinguistic characteristics from said first input speech signal; converting said first speech signal to a text sequence; generating phonemes based on said second speech signal; transforming said text sequence of said first speech signal into a converted speech signal of said second speaker based on said one or more phonemes of said second speech signal; and converting said converted speech signal into an output speech signal of said second speaker by applying said extracted paralinguistic characteristics to said converted speech signal. 19. The method of claim 18 , further comprising translating said text sequence from a first language to a second language. | 0.931151 |
8,682,671 | 1 | 6 | 1. A method for use with a speech-enabled application, the method comprising: receiving, from the speech-enabled application, input comprising a plurality of text strings; identifying a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; assigning contrastive stress to the identified first portion of the first text string, but not to the identified second portion of the first text string; generating, using at least one computer system, speech synthesis output to render the plurality of text strings as speech having the assigned contrastive stress; and providing the speech synthesis output for the speech-enabled application. | 1. A method for use with a speech-enabled application, the method comprising: receiving, from the speech-enabled application, input comprising a plurality of text strings; identifying a first portion of a first text string of the plurality of text strings as differing from a corresponding first portion of a second text string of the plurality of text strings, and a second portion of the first text string as not differing from a corresponding second portion of the second text string; assigning contrastive stress to the identified first portion of the first text string, but not to the identified second portion of the first text string; generating, using at least one computer system, speech synthesis output to render the plurality of text strings as speech having the assigned contrastive stress; and providing the speech synthesis output for the speech-enabled application. 6. The method of claim 1 , wherein the speech synthesis output comprises identification of a plurality of audio recordings to render the plurality of text strings as speech, at least one of the plurality of audio recordings being selected to render the first portion of the first text string as speech carrying contrastive stress. | 0.7 |
8,145,992 | 6 | 9 | 6. The method of claim 3 , further comprising receiving user input regarding the acceptance or rejection of the second conversion chain upon review of the validation results. | 6. The method of claim 3 , further comprising receiving user input regarding the acceptance or rejection of the second conversion chain upon review of the validation results. 9. The method of claim 6 , further comprising storing the second conversion chain upon receiving user input indicating user acceptance of the second conversion chain, and iteratively performing conversion component modification, execution of newly modified conversion chains and validation results output for user comparison. | 0.870104 |
8,468,142 | 43 | 53 | 43. A system comprising: a memory comprising instructions executable by one or more processors; and one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. | 43. A system comprising: a memory comprising instructions executable by one or more processors; and one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. 53. The system of claim 43 , wherein the one or more processors are further operable, when executing the instructions, to partition the sixth BDD into a plurality of seventh BDDs, wherein a sum of sizes of the seventh BDDs is less than a size of the sixth BDD. | 0.748062 |
8,264,502 | 10 | 11 | 10. A computer-implemented method for facilitating accurate review of a document comprising the steps of: manipulating, by the computer a scanned image of the document, indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, indicating to the reader the similarities and/or differences between the two or more documents, and re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same. | 10. A computer-implemented method for facilitating accurate review of a document comprising the steps of: manipulating, by the computer a scanned image of the document, indicating to a reader portions of the document which have been already reviewed in a previous or master document, wherein the document comprises two or more documents, indicating to the reader the similarities and/or differences between the two or more documents, and re-ordering of the two or more documents by moving documents which have a large set of same or similar changes together so as to facilitate their review consecutively allowing more text, diagrams, and photos to be marked as the same. 11. The method of claim 10 wherein the step of manipulating the image includes highlighting or de-emphasizing portions of the image. | 0.562914 |
8,108,218 | 15 | 18 | 15. An apparatus for processing a voice message, comprising: a storage device for storing one or more voice representations where each voice representation corresponds to a word or phrase and is associated with a criteria measurement value, and for storing one or more actions; an interface for receiving from a user a one of: a user-specified word and a user-specified phrase; and a processor for receiving a voice message, analyzing the voice message to determine if one or more of the stored voice representations corresponding to the received user-specified word or phrase occur in the voice message and to generate a final criteria measurement value associated with the voice message, and performing one or more of the stored actions based on the final criteria measurement value if one or more of the stored voice representations are found to occur in the voice message, the final criteria measurement value based on the value associated with each determined stored voice representation occurring in the voice message. | 15. An apparatus for processing a voice message, comprising: a storage device for storing one or more voice representations where each voice representation corresponds to a word or phrase and is associated with a criteria measurement value, and for storing one or more actions; an interface for receiving from a user a one of: a user-specified word and a user-specified phrase; and a processor for receiving a voice message, analyzing the voice message to determine if one or more of the stored voice representations corresponding to the received user-specified word or phrase occur in the voice message and to generate a final criteria measurement value associated with the voice message, and performing one or more of the stored actions based on the final criteria measurement value if one or more of the stored voice representations are found to occur in the voice message, the final criteria measurement value based on the value associated with each determined stored voice representation occurring in the voice message. 18. The apparatus of claim 15 , further comprising: a user interface for receiving user specified actions, wherein the actions are to be performed in the event one or more of the stored voice representations are found in the voice message; and wherein the storage device is further for storing the user specified actions. | 0.717926 |
7,958,448 | 34 | 35 | 34. A computer-readable medium according to claim 31 , wherein the method further includes: receiving input requesting activation of a third font for rendering a third portion of the electronic document; determining if the third font already exists in the font management vault; when the third font does not exist in the font management vault, identifying the third font in one multi-font suitcase file, separating the third font from the identified multi-font suitcase file, and saving the separated third font in the font management vault. | 34. A computer-readable medium according to claim 31 , wherein the method further includes: receiving input requesting activation of a third font for rendering a third portion of the electronic document; determining if the third font already exists in the font management vault; when the third font does not exist in the font management vault, identifying the third font in one multi-font suitcase file, separating the third font from the identified multi-font suitcase file, and saving the separated third font in the font management vault. 35. A computer-readable medium according to claim 34 , wherein the third font is identified in the first multi-font suitcase file. | 0.947707 |
6,098,033 | 21 | 23 | 21. A method in a computer system for determining the strength of a selected relationship between a pair of input words, the method comprising: (a) selecting a multiplicity of pairs of words between which the selected relationship is known to be strong; (b) for a each selected pair of words: (1) identifying the most salient semantic relation paths connecting the words of the selected pair, each identified semantic relation path comprising an ordered series of semantic relations, each semantic relation having a relation type; and (2) for each identified path: (A) extracting from the path a path pattern comprising the relation types of the relations of the path; and (B) augmenting a path pattern frequency indicating the likelihood that the selected relationship is strong between an arbitrary pair of words that are connected by a path having the extracted path pattern; (c) identifying the most salient semantic relation paths connecting the input words; and (d) averaging the path pattern frequencies for the path patterns of the identified paths to obtain a quantitative measure of the strength of the selected relationship between the input words. | 21. A method in a computer system for determining the strength of a selected relationship between a pair of input words, the method comprising: (a) selecting a multiplicity of pairs of words between which the selected relationship is known to be strong; (b) for a each selected pair of words: (1) identifying the most salient semantic relation paths connecting the words of the selected pair, each identified semantic relation path comprising an ordered series of semantic relations, each semantic relation having a relation type; and (2) for each identified path: (A) extracting from the path a path pattern comprising the relation types of the relations of the path; and (B) augmenting a path pattern frequency indicating the likelihood that the selected relationship is strong between an arbitrary pair of words that are connected by a path having the extracted path pattern; (c) identifying the most salient semantic relation paths connecting the input words; and (d) averaging the path pattern frequencies for the path patterns of the identified paths to obtain a quantitative measure of the strength of the selected relationship between the input words. 23. The method of claim 21, further comprising: (e) selecting a multiplicity of word pairs of a second type between which the selected relationship is known to not be strong; and (f) for each selected word pair of the second type: (1) identifying the most salient semantic relation paths connecting the words of the selected pair, each identified semantic relation path comprising an ordered series of semantic relations, each semantic relation having a relation type; and (2) for each identified path: (A) extracting from the path a path pattern comprising the relation types of the relations of the path; and (B) reducing a path pattern frequency indicating the likelihood that the selected relationship is strong between an arbitrary pair of words that are connected by a path having the extracted path pattern. | 0.501225 |
8,417,523 | 5 | 6 | 5. The system of claim 4 , wherein the session manger is further configured, when all special concepts are present and assigned a value, to perform or complete the service. | 5. The system of claim 4 , wherein the session manger is further configured, when all special concepts are present and assigned a value, to perform or complete the service. 6. The system of claim 5 , wherein the session manger is further configured to perform the service by storing the information included in the utterance and associated with the special concepts. | 0.924016 |
8,843,482 | 8 | 10 | 8. The method according to claim 7 , further comprising the step of recording at least a content item of said second set and a feedback from said user related to said at least a recorded content item. | 8. The method according to claim 7 , further comprising the step of recording at least a content item of said second set and a feedback from said user related to said at least a recorded content item. 10. The method according to claims 8 , comprising the step of recording said user request. | 0.970199 |
7,685,201 | 1 | 2 | 1. A method comprised of steps that are each performed by one or more computers, the steps manipulating data and information stored by the one or more computers, the steps of the method comprising: disambiguating person data located from one or more sets of search results, including extracting information about a person based on name entity extraction, and calculating similarity data, wherein the calculating similarity data comprises using a vector space model, wherein using the vector space model comprises determining a vector for a person, the vector comprising a plurality of entity features including one or more entity locations related to the person, one or more entity organizations related to the person, and one or more entities that the person has been associated with the person, wherein calculating similarity data comprises using a calculation in which each entity feature of the person vector has an entity weight and a nearness weight, and wherein the calculation comprises, for each entity feature, combining the corresponding entity weight and nearness weight with an entity weight and nearness weight of a same entity feature of another person vector and aggregating the combined weights of the entity features. | 1. A method comprised of steps that are each performed by one or more computers, the steps manipulating data and information stored by the one or more computers, the steps of the method comprising: disambiguating person data located from one or more sets of search results, including extracting information about a person based on name entity extraction, and calculating similarity data, wherein the calculating similarity data comprises using a vector space model, wherein using the vector space model comprises determining a vector for a person, the vector comprising a plurality of entity features including one or more entity locations related to the person, one or more entity organizations related to the person, and one or more entities that the person has been associated with the person, wherein calculating similarity data comprises using a calculation in which each entity feature of the person vector has an entity weight and a nearness weight, and wherein the calculation comprises, for each entity feature, combining the corresponding entity weight and nearness weight with an entity weight and nearness weight of a same entity feature of another person vector and aggregating the combined weights of the entity features. 2. The method of claim 1 wherein extracting the information about a person comprises locating at least one word that is within a word distance in the search results. | 0.815848 |
4,503,420 | 3 | 4 | 3. A circuitry arrangement according to claim 1 wherein said input means is a shift register having at least three stages and wherein said translating circuitry means is formed such that the word boundary of data words entering said input means shift register is defined by the signals in the third and second stages as viewed from the signal input side. | 3. A circuitry arrangement according to claim 1 wherein said input means is a shift register having at least three stages and wherein said translating circuitry means is formed such that the word boundary of data words entering said input means shift register is defined by the signals in the third and second stages as viewed from the signal input side. 4. A circuitry arrangement according to claim 3 wherein the output means is a four-stage shift register and the translation circuitry is formed to place a first bit signal in the first stage of said output means shift register when the third and second stages of said input means shift register are holding bit signals which indicate that a four-bit word is being encoded. | 0.864727 |
7,752,082 | 9 | 15 | 9. An apparatus comprising: a database for storing a plurality of reviews of a reviewed subject, wherein said plurality of reviews may be dominated by a subject-owner; a user interface which accepts input from said subject-owner related to one or more functions to be applied to said plurality of reviews in said database; and a processor that verifies said subject-owner is authorized to dominate said plurality of reviews, controls enablement of said one or more functions responsive to accepting input, and stores said input. | 9. An apparatus comprising: a database for storing a plurality of reviews of a reviewed subject, wherein said plurality of reviews may be dominated by a subject-owner; a user interface which accepts input from said subject-owner related to one or more functions to be applied to said plurality of reviews in said database; and a processor that verifies said subject-owner is authorized to dominate said plurality of reviews, controls enablement of said one or more functions responsive to accepting input, and stores said input. 15. The apparatus as claimed in claim 9 , wherein said processor further assigns syndication of said plurality of reviews to a channel; and formats said plurality of reviews responsive to said channel when said plurality of reviews are syndicated. | 0.850484 |
8,081,860 | 26 | 27 | 26. The apparatus of claim 24 , wherein the controller is configured to control a reproduction of the text data by applying the default style, the default style of the text subtitle region being specified by at least one of a region position, a region size, a region background color, a text position, a text flow, a text alignment, a line space, a font identification, a font style, a font size, and a font color defined in the region style information. | 26. The apparatus of claim 24 , wherein the controller is configured to control a reproduction of the text data by applying the default style, the default style of the text subtitle region being specified by at least one of a region position, a region size, a region background color, a text position, a text flow, a text alignment, a line space, a font identification, a font style, a font size, and a font color defined in the region style information. 27. The apparatus of claim 26 , wherein the controller is configured to control a reproduction of a clip information file of a corresponding text subtitle stream, the clip information file including a font identification specifying a font file associated with the default style defined in the region style information. | 0.909608 |
9,805,722 | 17 | 18 | 17. An interactive speech recognition system for interactively recognizing a spoken phrase, the system comprising: a database containing a plurality of reference terms, the reference terms being organized into categories; an input memory configured to store terms identified in a spoken phrase; an output memory configured to store a plurality of paths, wherein a path is a concatenation of matched reference terms of different categories; a list memory configured to store reference terms of a set of categories; a processing circuit configured to populate the list memory with the reference terms of the set of categories; a recognition circuit configured to determine when a reference term in the list memory matches one or more terms of the spoken phrase in the input memory; the recognition circuit or the processing circuit further including: means for determining that the spoken phrase has been recognized when one or more paths in the output memory uniquely identify a database entry; means for determining when the list memory has sufficient capacity to load the reference terms of a set of subsequent categories, each category in the set being determined by a respective path stored in the output memory; means for eliminating one or more paths from the output memory based on supplemental user input when the list memory has insufficient capacity; means for replacing, in the output memory, each given path with a set of extended paths for disambiguating the spoken phrase, each path in the set of extended paths being formed by concatenating to the given path a different reference term in the list memory that matches the given path, wherein when the given path matches no such reference terms, the set includes no extended paths and the given path is deleted from the output memory; and means for loading the list memory with the reference terms of the set of categories. | 17. An interactive speech recognition system for interactively recognizing a spoken phrase, the system comprising: a database containing a plurality of reference terms, the reference terms being organized into categories; an input memory configured to store terms identified in a spoken phrase; an output memory configured to store a plurality of paths, wherein a path is a concatenation of matched reference terms of different categories; a list memory configured to store reference terms of a set of categories; a processing circuit configured to populate the list memory with the reference terms of the set of categories; a recognition circuit configured to determine when a reference term in the list memory matches one or more terms of the spoken phrase in the input memory; the recognition circuit or the processing circuit further including: means for determining that the spoken phrase has been recognized when one or more paths in the output memory uniquely identify a database entry; means for determining when the list memory has sufficient capacity to load the reference terms of a set of subsequent categories, each category in the set being determined by a respective path stored in the output memory; means for eliminating one or more paths from the output memory based on supplemental user input when the list memory has insufficient capacity; means for replacing, in the output memory, each given path with a set of extended paths for disambiguating the spoken phrase, each path in the set of extended paths being formed by concatenating to the given path a different reference term in the list memory that matches the given path, wherein when the given path matches no such reference terms, the set includes no extended paths and the given path is deleted from the output memory; and means for loading the list memory with the reference terms of the set of categories. 18. The speech recognition system of claim 17 , where the recognition circuit or the processing circuit selects a path in the output memory having a highest likelihood of uniquely identifying an entry in the database, and loads the list memory with reference terms for the selected path, when the list memory has insufficient capacity to load the reference terms of the set of categories. | 0.797917 |
7,814,042 | 65 | 67 | 65. The machine-readable storage medium of claim 64 , wherein the one or more sequences of instructions further comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of determining to use the particular candidate identification technique to process the query at least in part by reading an indication that indicates which candidate identification technique, of two or more candidate identification techniques available to a query-processing unit, to use to process the query. | 65. The machine-readable storage medium of claim 64 , wherein the one or more sequences of instructions further comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of determining to use the particular candidate identification technique to process the query at least in part by reading an indication that indicates which candidate identification technique, of two or more candidate identification techniques available to a query-processing unit, to use to process the query. 67. The machine-readable storage medium of claim 65 , wherein the instructions that cause reading the indication comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform the step of receiving the indication from a user. | 0.953488 |
10,147,336 | 1 | 2 | 1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record. | 1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record. 2. The computer-implemented method of claim 1 , further comprising: identifying, by the computer, in a dictionary source a plurality of words having an edit distance based upon the target word, wherein the edit distance of a word is an amount of letter-insertions and letter-deletions required for the word to be the target word. | 0.715889 |
8,364,694 | 20 | 22 | 20. A server system for hosting an online media store for a plurality of digital media assets, comprising one or more processors; memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving at least one search character entered at a client device; determining a set of search hints that match the at least one search character, each search hint in the determined set of words being associated with one or more digital media assets available at the online media store and each digital media asset having an associated media type; for each respective word in the determined set of search hints: determining whether the client device supports the media type of at least one of the one or more digital media assets associated with the respective search hint in the determined set of search hints; in accordance with a determination that the client device does not support the media type associated with any of the one or more digital media assets associated with the respective word, removing the respective search hint from the determined set of search hints; obtaining sales popularity data for each of the digital media assets that match the at least one search hint in the filtered set of search hints, wherein the sales popularity data is based on purchase data for each of the digital media assets; and ordering the set of search hints using the sales popularity data, the sales popularity data being based on the frequency at which purchases of respective digital media assets occur. | 20. A server system for hosting an online media store for a plurality of digital media assets, comprising one or more processors; memory storing one or more programs to be executed by the one or more processors; the one or more programs comprising instructions for: receiving at least one search character entered at a client device; determining a set of search hints that match the at least one search character, each search hint in the determined set of words being associated with one or more digital media assets available at the online media store and each digital media asset having an associated media type; for each respective word in the determined set of search hints: determining whether the client device supports the media type of at least one of the one or more digital media assets associated with the respective search hint in the determined set of search hints; in accordance with a determination that the client device does not support the media type associated with any of the one or more digital media assets associated with the respective word, removing the respective search hint from the determined set of search hints; obtaining sales popularity data for each of the digital media assets that match the at least one search hint in the filtered set of search hints, wherein the sales popularity data is based on purchase data for each of the digital media assets; and ordering the set of search hints using the sales popularity data, the sales popularity data being based on the frequency at which purchases of respective digital media assets occur. 22. The server system of claim 20 , wherein the one or more programs further comprise instructions for: selecting a subset of the search hints having the highest media popularity indications; sending the subset of the search hints. | 0.791139 |
9,997,069 | 1 | 13 | 1. A method of providing context aware audible navigation prompts during a navigation presentation that an electronic device provides to offer guidance through a navigated route, the electronic device comprising a plurality of services utilizing audio, the electronic device audio played on a plurality of stereo speakers, the method comprising: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive a voice input; based on detecting that a first audio service is currently receiving the voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the voice input, determining that a non-verbal audio prompt is allowed; in response to determining that the non-verbal audio is allowed, suppressing verbal navigation prompts when a service in the plurality of services of the electronic device is being utilized to conduct the second audio service through the electronic device; determining that the electronic device has approached a juncture along the navigated route that requires a turn; playing a non-verbal audible prompt having a directional component that is defined for a particular direction of the next navigation turn when verbal navigation prompts are suppressed; and displaying a textual notification on the device describing the next navigation turn using textual instructions when verbal navigation prompts are suppressed. | 1. A method of providing context aware audible navigation prompts during a navigation presentation that an electronic device provides to offer guidance through a navigated route, the electronic device comprising a plurality of services utilizing audio, the electronic device audio played on a plurality of stereo speakers, the method comprising: identifying a navigation instruction to provide for a navigation maneuver; determining an allowed type of audio prompt for the electronic device to provide for the identified navigation instruction by determining whether any audio service of the device is currently being utilized to receive a voice input; based on detecting that a first audio service is currently receiving the voice input, determining that no audio prompt is allowed; based on detecting that a second audio service is currently receiving the voice input, determining that a non-verbal audio prompt is allowed; in response to determining that the non-verbal audio is allowed, suppressing verbal navigation prompts when a service in the plurality of services of the electronic device is being utilized to conduct the second audio service through the electronic device; determining that the electronic device has approached a juncture along the navigated route that requires a turn; playing a non-verbal audible prompt having a directional component that is defined for a particular direction of the next navigation turn when verbal navigation prompts are suppressed; and displaying a textual notification on the device describing the next navigation turn using textual instructions when verbal navigation prompts are suppressed. 13. The method of claim 1 , wherein the particular direction of the next navigation turn is a first direction, the non-verbal audio prompt is a first non-verbal audio prompt, the juncture is a first juncture, and the turn is a first turn, the method further comprising: determining that the electronic device has approached a second juncture along the navigated route that requires a second turn; and playing a second non-verbal prompt having a directional component that is defined for a second direction of the second navigation turn when verbal navigation prompts are suppressed. | 0.556402 |
8,032,877 | 4 | 9 | 4. A method for compiler neutral linking of C++ based code comprising: compiling a first software module with a first C++ compiler, wherein the first software module comprises a first main section and a first linkage section, said first main section including code written in a C++ programming language and said first linkage section including code written in a C programming language; compiling a second software module with a second C++ compiler, wherein the second software module comprises a second main section and a second linkage section, said main section including code written in a C++ programming language and said linkage section including code written in a C programming language, wherein the second C++ compiler is different from the first C++ compiler, and wherein the second C++ compiler uses different naming conventions for linkage symbols compared to those used by the first C++ compiler; creating a program comprising: machine code of the first software module, which was compiled using said first C++ compiler; and machine code of the second software module, which was compiled using the second C++ compiler, wherein the first main section includes a C++ call for an object implemented in the second main section, and wherein interactions between the first software module and the second software module are C based interactions established by the first linkage section and the second linkage section, said C based interactions including an interaction associated with the C++ call that operates in a manner transparent to the first main section and the second main section, wherein the first linkage section converts the C++ call to a corresponding call, which is a C linkage function wherein said C linkage function is implemented within the second linkage section, wherein the first linkage section includes a software component that receives an address for an instance of the object associated with the C++ call and also receives a mapping for said C linkage function that correspond to object implemented by the second software module, wherein the mapping and the address are used by the software component to determine the C linkage function that corresponds to the C++ call. | 4. A method for compiler neutral linking of C++ based code comprising: compiling a first software module with a first C++ compiler, wherein the first software module comprises a first main section and a first linkage section, said first main section including code written in a C++ programming language and said first linkage section including code written in a C programming language; compiling a second software module with a second C++ compiler, wherein the second software module comprises a second main section and a second linkage section, said main section including code written in a C++ programming language and said linkage section including code written in a C programming language, wherein the second C++ compiler is different from the first C++ compiler, and wherein the second C++ compiler uses different naming conventions for linkage symbols compared to those used by the first C++ compiler; creating a program comprising: machine code of the first software module, which was compiled using said first C++ compiler; and machine code of the second software module, which was compiled using the second C++ compiler, wherein the first main section includes a C++ call for an object implemented in the second main section, and wherein interactions between the first software module and the second software module are C based interactions established by the first linkage section and the second linkage section, said C based interactions including an interaction associated with the C++ call that operates in a manner transparent to the first main section and the second main section, wherein the first linkage section converts the C++ call to a corresponding call, which is a C linkage function wherein said C linkage function is implemented within the second linkage section, wherein the first linkage section includes a software component that receives an address for an instance of the object associated with the C++ call and also receives a mapping for said C linkage function that correspond to object implemented by the second software module, wherein the mapping and the address are used by the software component to determine the C linkage function that corresponds to the C++ call. 9. The method of claim 4 , wherein said steps of claim 4 are steps performed by at least one machine in accordance with at least one computer program stored within a machine readable memory, said computer program having a plurality of code sections that are executable by the at least one machine. | 0.82931 |
7,716,229 | 13 | 14 | 13. The system according to claim 12 , wherein the search engine receives a user query having a misspell. | 13. The system according to claim 12 , wherein the search engine receives a user query having a misspell. 14. The system according to claim 13 , wherein the search engine accesses the misspell graph to correct the user query. | 0.975833 |
8,510,260 | 1 | 3 | 1. A system for sorting e-mail documents, the system comprising: a processor; a memory having stored thereon instructions that, when executed by the processor, perform the functions of: identifying a most frequently used word in multiple e-mail documents; identifying a least frequently used word in the multiple e-mail documents; sorting the multiple e-mail documents according to e-mail documents, from the multiple e-mail documents, that contain both the most frequently used word and the least frequently used word identified in the multiple e-mail documents to create a first set of alphabetically sorted e-mail documents; alphabetically sorting the multiple e-mail documents according e-mail documents that contain the least frequently used word, but not the most frequently used word, to create a second set of alphabetically sorted e-mail documents; and displaying the second set of alphabetically sorted e-mail documents below the first set of alphabetically sorted e-mail documents. | 1. A system for sorting e-mail documents, the system comprising: a processor; a memory having stored thereon instructions that, when executed by the processor, perform the functions of: identifying a most frequently used word in multiple e-mail documents; identifying a least frequently used word in the multiple e-mail documents; sorting the multiple e-mail documents according to e-mail documents, from the multiple e-mail documents, that contain both the most frequently used word and the least frequently used word identified in the multiple e-mail documents to create a first set of alphabetically sorted e-mail documents; alphabetically sorting the multiple e-mail documents according e-mail documents that contain the least frequently used word, but not the most frequently used word, to create a second set of alphabetically sorted e-mail documents; and displaying the second set of alphabetically sorted e-mail documents below the first set of alphabetically sorted e-mail documents. 3. The system of claim 1 , further comprising: instructions that, when executed by the processor, perform the functions of: highlighting the most frequently used word and the least frequently used word displayed in the first set of alphabetically sorted e-mail documents and the second set of alphabetically sorted e-mail documents. | 0.67451 |
6,161,093 | 47 | 48 | 47. An information access system according to claim 46 wherein the terminal is battery operated. | 47. An information access system according to claim 46 wherein the terminal is battery operated. 48. An information access system according to claim 47 wherein the central system is connected to a further central system via a network and is further equipped with a network control means for controlling the exchange of information with the further central system. | 0.890625 |
9,436,915 | 4 | 8 | 4. The diagnosis support apparatus according to claim 1 , wherein the inference unit calculates, for each of the plural candidates of diagnosis name to which a priori probability are set, an inference probability of each of the plural candidates of diagnosis name by calculating a posteriori probability based on the plurality of pieces of medical information. | 4. The diagnosis support apparatus according to claim 1 , wherein the inference unit calculates, for each of the plural candidates of diagnosis name to which a priori probability are set, an inference probability of each of the plural candidates of diagnosis name by calculating a posteriori probability based on the plurality of pieces of medical information. 8. The diagnosis support apparatus according to claim 4 , wherein the calculation unit calculates a posteriori probability of each inference result based on the partial set, and calculates the degree of effect by using the priori probability and the posteriori probability. | 0.922311 |
8,073,869 | 1 | 7 | 1. A method for searching a structured data table T with m attributes and n records, where A={a 1 ; a 2 , : : : ; a m } denotes an attribute set, R={r 1 ; r 2 , : : : , r n } denotes the record set, and W={w 1 ; w 2 , : : : ; w p } denotes a distinct word set in T, where given two words, w i and w i , “w i ≦w j †denotes that w i is a prefix string of w j , where a query consists of a set of prefixes Q={p 1 , p 2 , . . . , p l }, where a predicted-word set is W k l ={w|w is a member of W and k l ≦w}, the method comprising for each prefix p i finding the set of prefixes from the data set that are similar to p i , by: determining the predicted-record set R Q ={r|r is a member of R, for every i; 1≦i≦·l−1, p i appears in r, and there exists a w included in W k l , w appears in r}; and for a keystroke that invokes query Q, returning the top-t records in R Q for a given value t, ranked by their relevancy to the query, treating every keyword as a partial keyword, namely given an input Q={k 1 ; k 2 ; : : : ; k l for each predicted record r, for each 1≦i≦·l, there exists at least one predicted word w i for k i in r, since k i must be a prefix of w i ,quantifying their similarity as:
sim =( k i ;w i )=| k i |/|w i | if there are multiple predicted words in r for a partial keyword k j , selecting the predicted word w i with the maximal similarity to k i and quantifying a weight of a predicted word to capture the importance of a predicted word, and taking into account the number of attributes that the l predicted words appear in, denoted as n a , to combine similarity, weight and number of attributes to generate a ranking function to score r for the query Q as follows: SCORE ⡠( r , Q ) = α * ∑ l = 1 1 ⢠⢠idf w i * sim ⡠( k i , w i ) + ( 1 - α ) * 1 n a , where α is a tuning parameter between 0 and 1. | 1. A method for searching a structured data table T with m attributes and n records, where A={a 1 ; a 2 , : : : ; a m } denotes an attribute set, R={r 1 ; r 2 , : : : , r n } denotes the record set, and W={w 1 ; w 2 , : : : ; w p } denotes a distinct word set in T, where given two words, w i and w i , “w i ≦w j †denotes that w i is a prefix string of w j , where a query consists of a set of prefixes Q={p 1 , p 2 , . . . , p l }, where a predicted-word set is W k l ={w|w is a member of W and k l ≦w}, the method comprising for each prefix p i finding the set of prefixes from the data set that are similar to p i , by: determining the predicted-record set R Q ={r|r is a member of R, for every i; 1≦i≦·l−1, p i appears in r, and there exists a w included in W k l , w appears in r}; and for a keystroke that invokes query Q, returning the top-t records in R Q for a given value t, ranked by their relevancy to the query, treating every keyword as a partial keyword, namely given an input Q={k 1 ; k 2 ; : : : ; k l for each predicted record r, for each 1≦i≦·l, there exists at least one predicted word w i for k i in r, since k i must be a prefix of w i ,quantifying their similarity as:
sim =( k i ;w i )=| k i |/|w i | if there are multiple predicted words in r for a partial keyword k j , selecting the predicted word w i with the maximal similarity to k i and quantifying a weight of a predicted word to capture the importance of a predicted word, and taking into account the number of attributes that the l predicted words appear in, denoted as n a , to combine similarity, weight and number of attributes to generate a ranking function to score r for the query Q as follows: SCORE ⡠( r , Q ) = α * ∑ l = 1 1 ⢠⢠idf w i * sim ⡠( k i , w i ) + ( 1 - α ) * 1 n a , where α is a tuning parameter between 0 and 1. 7. The method of claim 1 where returning the top-t records in R Q for a given value t, ranked by their relevancy to the query comprises maintaining a session cache for each user where each session cache keeps keywords that the user has input in the past and other information for each keyword, including its corresponding trie node and the top-t predicted records. | 0.731959 |
6,067,514 | 26 | 28 | 26. The method of claim 19, wherein the step of training the n-gram language model further comprises the step of segmenting a corresponding text corpus into paragraphs to obtain the conditional probabilities for the punctuation marks. | 26. The method of claim 19, wherein the step of training the n-gram language model further comprises the step of segmenting a corresponding text corpus into paragraphs to obtain the conditional probabilities for the punctuation marks. 28. The method of claim 26, wherein the n-gram language model is one of a bigram language model and a trigram language model. | 0.962842 |
9,904,736 | 2 | 5 | 2. The computer implemented method of claim 1 , wherein said identifying said first plurality of terms comprises identifying said first plurality of terms from a chapter of said electronic book based on a term frequency inverse document frequency (TF-IDF)-based analysis in accordance with a frequency and a specificity of each of said first plurality of terms, and wherein further said first plurality of terms are associated with a common theme. | 2. The computer implemented method of claim 1 , wherein said identifying said first plurality of terms comprises identifying said first plurality of terms from a chapter of said electronic book based on a term frequency inverse document frequency (TF-IDF)-based analysis in accordance with a frequency and a specificity of each of said first plurality of terms, and wherein further said first plurality of terms are associated with a common theme. 5. The computer implemented method of claim 2 , wherein said identifying said first plurality of terms further comprises stemming said first plurality of terms, wherein said stemming is configured to preempt duplicate hyperlinks within said chapter. | 0.951893 |
8,060,371 | 6 | 14 | 6. A communication unit, comprising: an audio input; a transceiver; and a processor coupled to the audio input and transceiver, the processor comprising: audio receiving and transmitting logic that receives audio from the audio input associated with at least one non-voice enabled form field of a web page and provides it to the transceiver for transmission to a speech recognition server; and text receiving and manipulating logic that receives text corresponding to the received audio and provides the received text to a non-voice enabled web browser to fill the at least one non-voice enabled form field. | 6. A communication unit, comprising: an audio input; a transceiver; and a processor coupled to the audio input and transceiver, the processor comprising: audio receiving and transmitting logic that receives audio from the audio input associated with at least one non-voice enabled form field of a web page and provides it to the transceiver for transmission to a speech recognition server; and text receiving and manipulating logic that receives text corresponding to the received audio and provides the received text to a non-voice enabled web browser to fill the at least one non-voice enabled form field. 14. The communication unit of claim 6 , wherein the communication unit is a wireless communication unit. | 0.87822 |
8,635,218 | 7 | 8 | 7. A method for transforming a first document into a second document, the second document configured for use at an electronic device, the method comprising: receiving user interface information about the electronic device; selecting content rules for modifying content in the first document according to the user interface information; selecting presentation rules for presenting the content from the first document according to the user interface information; and combining the content rules and presentation rules to form transformation instructions for transforming the first document into the second document; and wherein the user interface information includes at least one of screen size and keypad type. | 7. A method for transforming a first document into a second document, the second document configured for use at an electronic device, the method comprising: receiving user interface information about the electronic device; selecting content rules for modifying content in the first document according to the user interface information; selecting presentation rules for presenting the content from the first document according to the user interface information; and combining the content rules and presentation rules to form transformation instructions for transforming the first document into the second document; and wherein the user interface information includes at least one of screen size and keypad type. 8. The method of claim 7 , further comprising: generating the content rules according to the user interface information; and generating the presentation rules according to the user interface information. | 0.652397 |
9,704,483 | 18 | 19 | 18. The method of claim 16 , wherein selecting one or more terms from the set terms that is associated with the particular other user comprises selecting one or more terms, from among the set of terms that is associated with the particular other user, that are identified as being rejected by the particular other user. | 18. The method of claim 16 , wherein selecting one or more terms from the set terms that is associated with the particular other user comprises selecting one or more terms, from among the set of terms that is associated with the particular other user, that are identified as being rejected by the particular other user. 19. The method of claim 18 , wherein obtaining the biased language model comprises obtaining, based on the selected terms that are identified as being rejected by the particular other user, a biased language model that is biased away from the selected terms that are identified as being rejected by the particular other user. | 0.92657 |
7,617,199 | 1 | 2 | 1. A computer-implemented method of characterizing one or more search results as non-spam, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user, and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications, formulating a search query based on the user context, the search query being different than the user context; submitting the search query to a search engine; receiving one or more search results from the search engine; comparing data indicative of the one or more search results to data indicative of the user context to determine a spam score, the spam score based on at least one of: a character length of a longest matching substring and a word length of the longest matching substring, wherein the longest matching substring appears in the search result and the search query; characterizing the one or more search results as non-spam based upon comparing the spam score to a threshold; and displaying the one or more search results characterized as non-spam on a client device. | 1. A computer-implemented method of characterizing one or more search results as non-spam, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user, and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications, formulating a search query based on the user context, the search query being different than the user context; submitting the search query to a search engine; receiving one or more search results from the search engine; comparing data indicative of the one or more search results to data indicative of the user context to determine a spam score, the spam score based on at least one of: a character length of a longest matching substring and a word length of the longest matching substring, wherein the longest matching substring appears in the search result and the search query; characterizing the one or more search results as non-spam based upon comparing the spam score to a threshold; and displaying the one or more search results characterized as non-spam on a client device. 2. The method of claim 1 , wherein the threshold is a tunable threshold. | 0.927273 |
5,524,065 | 49 | 57 | 49. A method according to claim 48, further comprising a confidence level determining step determining step for determining confidence level of said plural candidates based on the distance values provided by the different distance functions. | 49. A method according to claim 48, further comprising a confidence level determining step determining step for determining confidence level of said plural candidates based on the distance values provided by the different distance functions. 57. A method according to claim 49, further comprising the step of providing a reject signal in a case where the confidence level is low. | 0.948881 |
9,852,731 | 15 | 20 | 15. One or more non-transitory computer-readable storage media storing computer-executable instructions for causing a computing device to: while the computing device is in a low-power state: receive audio input from a user at the computing device; and determine that the audio input comprises a wake phrase; transition the computing device from the low-power state to an active state if the audio input comprises the wake phrase; while the computing device is in the low-power state or the active state: attempt to verify the user based at least in part on a first portion of the audio input comprising the wake phrase; and while the computing device is in the active state: interpret a second portion of the audio input not comprising the wake phrase as a command to launch an application on the computing device; and launch the application at the computing device when the command is a user agnostic command or not launch the application when the command is not a user agnostic command, wherein a user agnostic command comprises a command that does not require identifying information or personal data of the user. | 15. One or more non-transitory computer-readable storage media storing computer-executable instructions for causing a computing device to: while the computing device is in a low-power state: receive audio input from a user at the computing device; and determine that the audio input comprises a wake phrase; transition the computing device from the low-power state to an active state if the audio input comprises the wake phrase; while the computing device is in the low-power state or the active state: attempt to verify the user based at least in part on a first portion of the audio input comprising the wake phrase; and while the computing device is in the active state: interpret a second portion of the audio input not comprising the wake phrase as a command to launch an application on the computing device; and launch the application at the computing device when the command is a user agnostic command or not launch the application when the command is not a user agnostic command, wherein a user agnostic command comprises a command that does not require identifying information or personal data of the user. 20. The one or more computer-readable storage media of claim 15 , further comprising computer-executable instructions for causing the computing device to: access a cloud-based service to determine information corresponding to the user agnostic command. | 0.761815 |
9,032,298 | 22 | 27 | 22. A Web-based method for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said method comprising: receiving over a network a plurality of video and music clips from a plurality of content provider users; storing the plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; indexing the database and media content storage devices that store the libraries of uploaded video and music clips; providing a plurality of producer users with interactive Web formatting screens, said Web formatting screens capable of allowing said producer users to select among said uploaded video and music clips; providing said plurality of producer users with an online mixer module, said mixer module capable of editing, mixing together, and playing said selected uploaded video and music clips, to thereby create video advertisement templates each comprising a static component and at least one placeholder, wherein said mixer module is further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is further capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file and encoding and formatting video advertisements in particular formats. | 22. A Web-based method for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said method comprising: receiving over a network a plurality of video and music clips from a plurality of content provider users; storing the plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; indexing the database and media content storage devices that store the libraries of uploaded video and music clips; providing a plurality of producer users with interactive Web formatting screens, said Web formatting screens capable of allowing said producer users to select among said uploaded video and music clips; providing said plurality of producer users with an online mixer module, said mixer module capable of editing, mixing together, and playing said selected uploaded video and music clips, to thereby create video advertisement templates each comprising a static component and at least one placeholder, wherein said mixer module is further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is further capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file and encoding and formatting video advertisements in particular formats. 27. The method of claim 22 , further comprising publishing the ad through a Web advertising service at various times and in various locations for a price which said advertiser establishes to develop a marketing campaign. | 0.856957 |
9,372,837 | 6 | 7 | 6. The method for providing the XSLT mapping tool of claim 5 , further comprising: determining, by the computer system, a structure of the XML target code using the call structure of the XSLT code. | 6. The method for providing the XSLT mapping tool of claim 5 , further comprising: determining, by the computer system, a structure of the XML target code using the call structure of the XSLT code. 7. The method for providing the XSLT mapping tool of claim 6 , wherein presenting the interface of the XSLT mapping tool that directly displays the mappings between the plurality of source nodes of the XML source code and the plurality of target nodes of the XML target code comprises presenting the determined structure of the XML target code. | 0.901714 |
8,429,528 | 8 | 11 | 8. A label data procurement and management method comprising the steps of: a step of a user being assigned a password and an authorization level for access to certain features of an internet based label management system; a step of a user logging into an internet accessible label management system, and upon logging in viewing a list of pending actions for said user including edit requests pending, proofs pending, orders pending and links to a work flow screen for each listed task, with authority to perform tasks specified by the administrative function; a step of a user uploading label graphics and label data onto a server accessible to a plurality of users' computers over a network; a step of a searcher searching for an existing label for editing of label data said searcher is authorized to work on by creation of a label copy for editing purposes; a step of said searcher inspecting a display of said label data in said label copy; a step of moving said label copy to a label setup workbench configured to allow the user to define editable fields in a graphic file of said label copy; a step of said searcher creating a proposed precision text edit of said label data, with said proposed edit being shown in a preview which is an accurate representation of the graphic view of the edited label, with a visual marking of the proposed edit showing proposed changes in the label copy; a step of said system advancing said proposed edit and said label data to a first label inspector team comprising at least one label inspector, wherein if said proposed edit is satisfactory to all of said label said first label inspector team apply said proposed edit to said label data and said method continues to the next step, wherein if said proposed edit is not satisfactory to at least one dissenting member of said first label inspector team a dissenting label inspector performs the following steps: i) a step of providing at least one reason said proposed edit is not satisfactory to an edit applier; ii) approving or rejecting said reason said proposed edit is not satisfactory; iii) a step of if said reason is rejected continuing to step iv but if said reason is accepted repeating said steps of creating a proposed precision text edit, and advancing said proposed text edit until said label data is satisfactory; iv) a step of applying said proposed edit to said label data; a step of advancing said label data to a proofing team comprising at least one member to approve or reject said proposed edit, with approved edits shown in a different visual marking; a step of if at least one of said proofing team members disapproves of said label, performing steps xi-xiii: xi) a first step of providing at least one reason said label is not satisfactory; xii) a second step of a proofing team leader approving or rejecting said reason said proposed edit is not satisfactory; xiii) a third step of if said reason is rejected continuing to step h but if said reason is accepted repeating said steps of creating a proposed precision text edit, advancing said proposed edit to a label inspector team, advancing said label data to a proofing team, and said proofing team members approving or rejecting said proposed edit until said label data is satisfactory; and a step of advancing said order to an order cart wherein said label data is saved on a medium for delivery to a printing location. | 8. A label data procurement and management method comprising the steps of: a step of a user being assigned a password and an authorization level for access to certain features of an internet based label management system; a step of a user logging into an internet accessible label management system, and upon logging in viewing a list of pending actions for said user including edit requests pending, proofs pending, orders pending and links to a work flow screen for each listed task, with authority to perform tasks specified by the administrative function; a step of a user uploading label graphics and label data onto a server accessible to a plurality of users' computers over a network; a step of a searcher searching for an existing label for editing of label data said searcher is authorized to work on by creation of a label copy for editing purposes; a step of said searcher inspecting a display of said label data in said label copy; a step of moving said label copy to a label setup workbench configured to allow the user to define editable fields in a graphic file of said label copy; a step of said searcher creating a proposed precision text edit of said label data, with said proposed edit being shown in a preview which is an accurate representation of the graphic view of the edited label, with a visual marking of the proposed edit showing proposed changes in the label copy; a step of said system advancing said proposed edit and said label data to a first label inspector team comprising at least one label inspector, wherein if said proposed edit is satisfactory to all of said label said first label inspector team apply said proposed edit to said label data and said method continues to the next step, wherein if said proposed edit is not satisfactory to at least one dissenting member of said first label inspector team a dissenting label inspector performs the following steps: i) a step of providing at least one reason said proposed edit is not satisfactory to an edit applier; ii) approving or rejecting said reason said proposed edit is not satisfactory; iii) a step of if said reason is rejected continuing to step iv but if said reason is accepted repeating said steps of creating a proposed precision text edit, and advancing said proposed text edit until said label data is satisfactory; iv) a step of applying said proposed edit to said label data; a step of advancing said label data to a proofing team comprising at least one member to approve or reject said proposed edit, with approved edits shown in a different visual marking; a step of if at least one of said proofing team members disapproves of said label, performing steps xi-xiii: xi) a first step of providing at least one reason said label is not satisfactory; xii) a second step of a proofing team leader approving or rejecting said reason said proposed edit is not satisfactory; xiii) a third step of if said reason is rejected continuing to step h but if said reason is accepted repeating said steps of creating a proposed precision text edit, advancing said proposed edit to a label inspector team, advancing said label data to a proofing team, and said proofing team members approving or rejecting said proposed edit until said label data is satisfactory; and a step of advancing said order to an order cart wherein said label data is saved on a medium for delivery to a printing location. 11. The method of claim 8 wherein a plurality of applied edits proposed to at least one label section of the same label family are consolidated into a single label edit before being advanced to said order cart. | 0.586614 |
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