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7,779,355 | 31 | 36 | 31. A computer program product stored on a computer-readable medium for creating a composite electronic representation, the computer program product comprising: code for scanning a paper document having text to generate an electronic representation of the document, the document including presentation material; code for applying an optical character recognition (OCR) algorithm to the text from the electronic representation of the document to generate OCR determined text, the OCR determined text corresponding to at least a portion of the presentation material; code for accessing recorded information including of audio and visual information recorded during a presentation of the presentation material, and comparing the OCR determined text to the recorded information to determine a portion of the audio of the recorded information that matches the OCR determined text, and determining matching information for each matching portion of the audio of the recorded information and the OCR determined text using a matching algorithm configured to map the OCR determined text to a portion of any of a plurality of recorded information having audio that matches the OCR determined text; code for generating a user selectable object providing a user with access to the portion of the recorded information determined to match the OCR determined text, and inserting the user selectable object and metadata including the matching information into the electronic representation of the document when the computer system locates a portion of the audio of the recorded information corresponding to the OCR determined text, the computer system thus creating a composite electronic representation of the document including the user selectable object, the user selectable object being placed in a position associated with the OCR determined text and allowing the user to access the portion of the recorded information in an application displaying the composite electronic representation or a separate application by selecting the user selectable object, the user-selectable object being able to access the portion of the recorded information using an embedded video link in the user selectable object; and code for storing the composite electronic representation as a PDF, HyperText Transfer Language (HTML), Flash or Word formatted document for access by the user or another user accessing the composite electronic document. | 31. A computer program product stored on a computer-readable medium for creating a composite electronic representation, the computer program product comprising: code for scanning a paper document having text to generate an electronic representation of the document, the document including presentation material; code for applying an optical character recognition (OCR) algorithm to the text from the electronic representation of the document to generate OCR determined text, the OCR determined text corresponding to at least a portion of the presentation material; code for accessing recorded information including of audio and visual information recorded during a presentation of the presentation material, and comparing the OCR determined text to the recorded information to determine a portion of the audio of the recorded information that matches the OCR determined text, and determining matching information for each matching portion of the audio of the recorded information and the OCR determined text using a matching algorithm configured to map the OCR determined text to a portion of any of a plurality of recorded information having audio that matches the OCR determined text; code for generating a user selectable object providing a user with access to the portion of the recorded information determined to match the OCR determined text, and inserting the user selectable object and metadata including the matching information into the electronic representation of the document when the computer system locates a portion of the audio of the recorded information corresponding to the OCR determined text, the computer system thus creating a composite electronic representation of the document including the user selectable object, the user selectable object being placed in a position associated with the OCR determined text and allowing the user to access the portion of the recorded information in an application displaying the composite electronic representation or a separate application by selecting the user selectable object, the user-selectable object being able to access the portion of the recorded information using an embedded video link in the user selectable object; and code for storing the composite electronic representation as a PDF, HyperText Transfer Language (HTML), Flash or Word formatted document for access by the user or another user accessing the composite electronic document. 36. The computer program product of claim 31 , further comprising: code for performing at least one of emailing, printing, storing, displaying, playing, and copying the created composite electronic representation. | 0.546809 |
9,465,517 | 1 | 10 | 1. A character input device that carries out inputting and editing of character strings, said character input device comprising: a memory to store information including phonetic information of a plurality of character strings; and a controller: to receive an initial character string as an input; to acquire predicted character string candidates having phonetic information that includes phonetic information associated with the initial character string; to output the predicted character string candidates to a display; to control editing of input character strings or character strings selected from predicted character string candidates to generate edited character strings based on commands from a key input; and to output said edited character strings to the display, wherein said controller executes, based on operation of a key of said key input, the two following character string editing control functions: when said key is operated before one of said predicted character string candidates is selected according to a command from said key input, deleting a character string displayed on said display, and when said key is operated after one of said predicted character string candidates is selected, changing a character string displayed on said display to a character string representing phonetic information of said character string selected from said predicted character string candidates. | 1. A character input device that carries out inputting and editing of character strings, said character input device comprising: a memory to store information including phonetic information of a plurality of character strings; and a controller: to receive an initial character string as an input; to acquire predicted character string candidates having phonetic information that includes phonetic information associated with the initial character string; to output the predicted character string candidates to a display; to control editing of input character strings or character strings selected from predicted character string candidates to generate edited character strings based on commands from a key input; and to output said edited character strings to the display, wherein said controller executes, based on operation of a key of said key input, the two following character string editing control functions: when said key is operated before one of said predicted character string candidates is selected according to a command from said key input, deleting a character string displayed on said display, and when said key is operated after one of said predicted character string candidates is selected, changing a character string displayed on said display to a character string representing phonetic information of said character string selected from said predicted character string candidates. 10. A car navigation device comprising a character input device according to claim 1 . | 0.939522 |
8,635,059 | 5 | 6 | 5. The method of claim 1 , wherein receiving a translation further comprises receiving alignment data from the machine translation system that identifies portions of the source text that correspond to each of the plurality of possible segmentations. | 5. The method of claim 1 , wherein receiving a translation further comprises receiving alignment data from the machine translation system that identifies portions of the source text that correspond to each of the plurality of possible segmentations. 6. The method of claim 5 , the operations further comprising: in response to a user action identifying a portion of the source text, highlighting a corresponding segment of the translated text. | 0.5 |
7,552,098 | 1 | 2 | 1. A method for applying a model for an interactive voice response system comprising: a) receiving a training data set at a first computing unit; b) sorting classes of the training data set by frequency distribution at the first computing unit; c) distributing the sorted classes as a plurality of S groups across a plurality of S processors using a round robin partition, wherein each group includes classes different from classes in each other group, and each group is distributed to a different processor of the plurality of S processors, each of the S processors being located within a different computing unit; d) for each processor, processing the distributed group of sorted classes to produce learning data; e) for each processor, distributing the learning data to each of the other processors; f) merging results of the processing into a model at a second computing unit; and g) outputting the model to cache operatively connected to the second computing unit; and h) applying the model to an interactive voice response system. | 1. A method for applying a model for an interactive voice response system comprising: a) receiving a training data set at a first computing unit; b) sorting classes of the training data set by frequency distribution at the first computing unit; c) distributing the sorted classes as a plurality of S groups across a plurality of S processors using a round robin partition, wherein each group includes classes different from classes in each other group, and each group is distributed to a different processor of the plurality of S processors, each of the S processors being located within a different computing unit; d) for each processor, processing the distributed group of sorted classes to produce learning data; e) for each processor, distributing the learning data to each of the other processors; f) merging results of the processing into a model at a second computing unit; and g) outputting the model to cache operatively connected to the second computing unit; and h) applying the model to an interactive voice response system. 2. The method of claim 1 , wherein prior to b), the method further comprises determining if at least two training data in the training data set are identical, and merging identical data. | 0.52551 |
9,262,403 | 1 | 4 | 1. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for translating content, the method comprising: extracting auto-suggest dictionary data including a plurality of sentence sub-segment pairs, each pair comprising a source sentence sub-segment extracted from a source sentence in a source language and a target sentence sub-segment extracted from a translation of the source sentence in a target language, the source and target sentences stored in translation data; generating a package including translation content and the extracted auto-suggest dictionary data; transmitting the package from a server to a remote device configured to: display a plurality of target sentence sub-segments as predictive translations based on correspondence between data input to the remote device by a human translator and at least a portion of the target sentence sub-segments, highlight a suggested best predictive translation in the plurality of predictive translations, receive a selection of one of the plurality of predictive translations from the human translator, and provide the received selection to the server; and updating the extracted auto-suggest dictionary data based on the received selection. | 1. A non-transitory computer readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for translating content, the method comprising: extracting auto-suggest dictionary data including a plurality of sentence sub-segment pairs, each pair comprising a source sentence sub-segment extracted from a source sentence in a source language and a target sentence sub-segment extracted from a translation of the source sentence in a target language, the source and target sentences stored in translation data; generating a package including translation content and the extracted auto-suggest dictionary data; transmitting the package from a server to a remote device configured to: display a plurality of target sentence sub-segments as predictive translations based on correspondence between data input to the remote device by a human translator and at least a portion of the target sentence sub-segments, highlight a suggested best predictive translation in the plurality of predictive translations, receive a selection of one of the plurality of predictive translations from the human translator, and provide the received selection to the server; and updating the extracted auto-suggest dictionary data based on the received selection. 4. The non-transitory computer readable storage medium of claim 1 , the method further comprising providing the updated auto-suggest dictionary data to a second remote device. | 0.827416 |
7,522,760 | 9 | 10 | 9. A method, comprising: determining that a first overall confidence level of a first digital image of a document associated with a document type is less than a threshold value associated with the document type; receiving a second digital image of the document, the digital image including a plurality of black and white pixels arranged in rows; locating at least two predefined portions of the second digital image; calculating an area confidence level for each of the predefined portions of the second digital image as a function of a total number of black pixels located in the predefined portion relative to an expected number of black pixels for the predefined portion; calculating a text confidence level as a function of a total number of pixel groups relative to a total number of characters, wherein each pixel group comprises a set of touching black pixels and each character comprises one or more pixel groups, wherein calculating the text confidence level comprises: subtracting the total number of characters from the total number of pixel groups to produce a first quantity, dividing the first quantity by the total number characters to produce a second quantity, and subtracting the second quantity from 1 to produce a text confidence level, and if the text confidence level is negative, setting the text confidence level equal to 0; calculating an image profile confidence level as a function of a black pixel distribution and a black pixel density; calculating a second overall image confidence level as a function of the area confidence level, the text confidence level, and the image profile confidence level; and storing the second digital image as a result of determining that the second overall image confidence level is greater than or equal to the threshold value. | 9. A method, comprising: determining that a first overall confidence level of a first digital image of a document associated with a document type is less than a threshold value associated with the document type; receiving a second digital image of the document, the digital image including a plurality of black and white pixels arranged in rows; locating at least two predefined portions of the second digital image; calculating an area confidence level for each of the predefined portions of the second digital image as a function of a total number of black pixels located in the predefined portion relative to an expected number of black pixels for the predefined portion; calculating a text confidence level as a function of a total number of pixel groups relative to a total number of characters, wherein each pixel group comprises a set of touching black pixels and each character comprises one or more pixel groups, wherein calculating the text confidence level comprises: subtracting the total number of characters from the total number of pixel groups to produce a first quantity, dividing the first quantity by the total number characters to produce a second quantity, and subtracting the second quantity from 1 to produce a text confidence level, and if the text confidence level is negative, setting the text confidence level equal to 0; calculating an image profile confidence level as a function of a black pixel distribution and a black pixel density; calculating a second overall image confidence level as a function of the area confidence level, the text confidence level, and the image profile confidence level; and storing the second digital image as a result of determining that the second overall image confidence level is greater than or equal to the threshold value. 10. The method of claim 9 , wherein the second digital image is a result of one or more of (i) a modification of the document prior to receiving the second digital image, (ii) a modification of the scanning equipment, or (iii) a modification to a scanned image prior to receiving. | 0.705882 |
7,596,756 | 11 | 12 | 11. The method of claim 10 , wherein the browser control engine accesses operating system controls of the controlling website specified by the script during the processing of the script. | 11. The method of claim 10 , wherein the browser control engine accesses operating system controls of the controlling website specified by the script during the processing of the script. 12. The method of claim 11 , wherein the browser control engine accesses window handle information. | 0.5 |
9,292,495 | 13 | 19 | 13. A computer program product for updating an existing document using natural language processing (NLP), the computer program product comprising: one or more computer-readable storage devices; program instructions, stored on at least one of the one or more storage devices, to receive information about a subject-matter domain; program instructions, stored on at least one of the one or more storage devices, to identify a portion of the existing document, wherein the portion corresponds to the subject-matter domain by including at least a threshold number of references to a category identified in the subject matter domain; program instructions, stored on at least one of the one or more storage devices, to lemmatize a group of words from the portion to use in a search query, wherein the search query returns a result set, the result set including current information corresponding to the subject-matter domain, the current information being recent as compared to an age of the portion; program instructions, stored on at least one of the one or more storage devices, to form natural language (NL) update content by processing the current information through an NLP application; program instructions, stored on at least one of the one or more storage devices, to associate with the NL update content a confidence rating, the confidence rating being indicative of a provenance of a data source that supplied the current information; and program instructions, stored on at least one of the one or more storage devices, to update, by changing the portion of the existing document in a document repository, the existing document using the NL update content and the confidence rating. | 13. A computer program product for updating an existing document using natural language processing (NLP), the computer program product comprising: one or more computer-readable storage devices; program instructions, stored on at least one of the one or more storage devices, to receive information about a subject-matter domain; program instructions, stored on at least one of the one or more storage devices, to identify a portion of the existing document, wherein the portion corresponds to the subject-matter domain by including at least a threshold number of references to a category identified in the subject matter domain; program instructions, stored on at least one of the one or more storage devices, to lemmatize a group of words from the portion to use in a search query, wherein the search query returns a result set, the result set including current information corresponding to the subject-matter domain, the current information being recent as compared to an age of the portion; program instructions, stored on at least one of the one or more storage devices, to form natural language (NL) update content by processing the current information through an NLP application; program instructions, stored on at least one of the one or more storage devices, to associate with the NL update content a confidence rating, the confidence rating being indicative of a provenance of a data source that supplied the current information; and program instructions, stored on at least one of the one or more storage devices, to update, by changing the portion of the existing document in a document repository, the existing document using the NL update content and the confidence rating. 19. The computer program product of claim 13 , further comprising: program instructions, stored on at least one of the one or more storage devices, to select from the result set the current information, wherein the selecting determines that the current information corresponds to the subject-matter domain by including at least a threshold amount of content from the information about the subject-matter domain. | 0.52867 |
7,698,138 | 1 | 17 | 1. A broadcast receiving method comprising: a receiving step of receiving, simultaneously with broadcast contents, additional information containing keyword information for specifying an object that appears in the broadcast contents, and a scene code indicating a scene of the broadcast contents, the additional information and the scene code being broadcasted; a language model specifying step of specifying, out of language models retained in advance, the language model corresponding to the received scene code when the scene code is received; a speech recognition step of performing speech recognition of a voice uttered by a viewing person, by using the specified language model; a specifying step of specifying the keyword information based on the speech recognition result; and a displaying step of displaying the additional information containing the specified keyword information. | 1. A broadcast receiving method comprising: a receiving step of receiving, simultaneously with broadcast contents, additional information containing keyword information for specifying an object that appears in the broadcast contents, and a scene code indicating a scene of the broadcast contents, the additional information and the scene code being broadcasted; a language model specifying step of specifying, out of language models retained in advance, the language model corresponding to the received scene code when the scene code is received; a speech recognition step of performing speech recognition of a voice uttered by a viewing person, by using the specified language model; a specifying step of specifying the keyword information based on the speech recognition result; and a displaying step of displaying the additional information containing the specified keyword information. 17. The broadcast receiving method according to claim 1 , wherein the scene code is broadcasted every time the scene has changed, the receiving step receives the scene code broadcasted every time the scene has changed, the language model specifying step specifies the language model every time the scene code has received, and the speech recognition step performs the speech recognition by using the language model specified every time the scene code is received. | 0.688005 |
8,380,507 | 37 | 44 | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. 44. The computer readable media of claim 37 , further comprising instructions for: determining that the artist text string language is not speakable in the title text string language; determining that speech content generated using the title text string language for the artist text string does not generate an audible output; and generating the speech content using an arbitrary language. | 0.501282 |
8,799,885 | 1 | 5 | 1. A method for resolving exceptions thrown by a class loader in a virtual machine environment, the method comprising: augmenting by a policy class loader of a virtual machine environment an exception message being thrown concurrently by the policy class loader for an unloadable missing class when the policy class loader attempts to load the missing class during a class loading process, wherein the policy class loader comprises one of a plurality of policy class loaders, wherein each policy class loader of the plurality of policy class loaders replaces an original class loader in the class loading process and comprises metadata describing interrelationships between the policy class loader and at least one other policy class loader of the plurality of policy class loaders based on a class loader tree of the original class loaders, wherein the class loading process uses the policy class loaders and metadata instead of the original class loaders and wherein augmenting the exception message comprises adding to the exception message the information obtained from the metadata describing interrelationships between the policy class loader and the at least one other policy class loader; identifying by an exception analyzer of the virtual machine environment a name of the missing class that is unloadable in response to and concurrent with the exception message being thrown by the policy class loader for said unloadable missing class; determining by the exception analyzer and concurrent with the exception message being thrown a sequence of policy class loaders involved in trying to return said missing class based on the name of the identified missing class; determining by a query engine of the virtual machine environment and concurrent with the exception message being thrown if said missing class is loadable from any remaining policy class loader, wherein said remaining policy class loader is not in said determined sequence of policy class loaders, and wherein determining whether the missing class is loadable is based on accessing the metadata from any policy class loader not originally in the sequence of policy class loaders; and recommending by a solution generator of the virtual machine environment and concurrent with the exception message being thrown a configuration change based on said determining if said missing class is loadable from any remaining policy class loader supporting said virtual machine environment. | 1. A method for resolving exceptions thrown by a class loader in a virtual machine environment, the method comprising: augmenting by a policy class loader of a virtual machine environment an exception message being thrown concurrently by the policy class loader for an unloadable missing class when the policy class loader attempts to load the missing class during a class loading process, wherein the policy class loader comprises one of a plurality of policy class loaders, wherein each policy class loader of the plurality of policy class loaders replaces an original class loader in the class loading process and comprises metadata describing interrelationships between the policy class loader and at least one other policy class loader of the plurality of policy class loaders based on a class loader tree of the original class loaders, wherein the class loading process uses the policy class loaders and metadata instead of the original class loaders and wherein augmenting the exception message comprises adding to the exception message the information obtained from the metadata describing interrelationships between the policy class loader and the at least one other policy class loader; identifying by an exception analyzer of the virtual machine environment a name of the missing class that is unloadable in response to and concurrent with the exception message being thrown by the policy class loader for said unloadable missing class; determining by the exception analyzer and concurrent with the exception message being thrown a sequence of policy class loaders involved in trying to return said missing class based on the name of the identified missing class; determining by a query engine of the virtual machine environment and concurrent with the exception message being thrown if said missing class is loadable from any remaining policy class loader, wherein said remaining policy class loader is not in said determined sequence of policy class loaders, and wherein determining whether the missing class is loadable is based on accessing the metadata from any policy class loader not originally in the sequence of policy class loaders; and recommending by a solution generator of the virtual machine environment and concurrent with the exception message being thrown a configuration change based on said determining if said missing class is loadable from any remaining policy class loader supporting said virtual machine environment. 5. The method of claim 1 , wherein said determining if said missing class is loadable from any remaining policy class loader further comprises: automatically accessing a global class loader list to determine which policy class loaders are not in a chain of policy class loaders, wherein said global class loader list comprises policy class loaders in a policy class loader tree defined by the metadata; and automatically accessing metadata from policy class loaders not in said chain of policy class loaders to determine if said missing class is loadable by any of said policy class loaders in said policy class loader tree. | 0.5 |
9,060,065 | 7 | 11 | 7. A device, comprising: a processor; and a memory having instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising: identifying a message class to which a voice message belongs; selecting an abbreviation library associated with the message class; producing a text representation of the voice message; and compacting the text representation using the abbreviation selected library to produce a compact text representation, wherein the compact text representation includes an abbreviation from the abbreviation library selected, and an extent to which the voice message is compacted is based on network capacity and a subscriber profile. | 7. A device, comprising: a processor; and a memory having instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising: identifying a message class to which a voice message belongs; selecting an abbreviation library associated with the message class; producing a text representation of the voice message; and compacting the text representation using the abbreviation selected library to produce a compact text representation, wherein the compact text representation includes an abbreviation from the abbreviation library selected, and an extent to which the voice message is compacted is based on network capacity and a subscriber profile. 11. The device of claim 7 , wherein the abbreviation library includes text abbreviations. | 0.716561 |
7,734,065 | 1 | 11 | 1. A computer-implemented method for text data recognition, comprising obtaining an image file from scanning device or from other source, preliminarily assigning at least a part of a list of applied supplementary data types and an order of application of the supplementary data types in the list, said list comprising, in order of application: a line-to-graphemes parsing information, a graphical element (grapheme) recognition quality, a whole words dictionary, a dictionary of permissible word fragments, rules, prescribed by applied standard data patterns or regular expressions, rules, prescribed by word disposition within the line or the paragraph, rules, prescribed by the document language peculiarities, rules, prescribed by the document type peculiarities, and supplementary rules for rare occasions, preliminarily assigning of an accuracy estimation for each type of supplementary data, performing one or more line-to-fragments parsing versions by reliably recognized spaces, said fragments presumably comprising single word images, building of line partition graph (hereinafter LPG) for each line fragment, said graph describing fragment-to-graphemes parsing versions, said graphemes presumably comprising character images, performing single graphemes recognition, using two or more classifiers of different types, assigning each said grapheme recognition version accuracy estimation, interpretation of grapheme recognition version as a character version, performing at least the following steps: the first step: for each LPG chain connecting initial node and final node, building a set of chains using all obtained recognized grapheme-to-character versions, calculating a total recognition accuracy level for each said chain, sorting obtained results in a total recognition accuracy descending order, the second step: analyzing all obtained character group versions using supplemental information about capital-small characters disposition, in a case of more than one grapheme-to-character recognition version being available, analyzing each said obtained recognition version with the application the supplemental data types in connection with the preliminarily assigned order to gain a prescribed recognition accuracy, assigning to each obtained version an accuracy estimation, discarding character versions having said accuracy estimation lower, than the preliminarily assigned level, sorting the remain versions in a descending order using pair wise comparison; the third step: performing a supplementary space recognition correction with respect to a previously mistakenly recognized spaces comprising: joining of previously mistakenly separated elements, separation of previously mistakenly combined elements. | 1. A computer-implemented method for text data recognition, comprising obtaining an image file from scanning device or from other source, preliminarily assigning at least a part of a list of applied supplementary data types and an order of application of the supplementary data types in the list, said list comprising, in order of application: a line-to-graphemes parsing information, a graphical element (grapheme) recognition quality, a whole words dictionary, a dictionary of permissible word fragments, rules, prescribed by applied standard data patterns or regular expressions, rules, prescribed by word disposition within the line or the paragraph, rules, prescribed by the document language peculiarities, rules, prescribed by the document type peculiarities, and supplementary rules for rare occasions, preliminarily assigning of an accuracy estimation for each type of supplementary data, performing one or more line-to-fragments parsing versions by reliably recognized spaces, said fragments presumably comprising single word images, building of line partition graph (hereinafter LPG) for each line fragment, said graph describing fragment-to-graphemes parsing versions, said graphemes presumably comprising character images, performing single graphemes recognition, using two or more classifiers of different types, assigning each said grapheme recognition version accuracy estimation, interpretation of grapheme recognition version as a character version, performing at least the following steps: the first step: for each LPG chain connecting initial node and final node, building a set of chains using all obtained recognized grapheme-to-character versions, calculating a total recognition accuracy level for each said chain, sorting obtained results in a total recognition accuracy descending order, the second step: analyzing all obtained character group versions using supplemental information about capital-small characters disposition, in a case of more than one grapheme-to-character recognition version being available, analyzing each said obtained recognition version with the application the supplemental data types in connection with the preliminarily assigned order to gain a prescribed recognition accuracy, assigning to each obtained version an accuracy estimation, discarding character versions having said accuracy estimation lower, than the preliminarily assigned level, sorting the remain versions in a descending order using pair wise comparison; the third step: performing a supplementary space recognition correction with respect to a previously mistakenly recognized spaces comprising: joining of previously mistakenly separated elements, separation of previously mistakenly combined elements. 11. The method of claim 1 , wherein the supplemental data is applied jointly. | 0.917382 |
7,757,163 | 1 | 2 | 1. A computer-implemented method for selecting types from a common annotation type system to identify a subject annotation type system, the computer performing the steps of: providing a reference set of document annotators, said reference set using the common annotation type system; providing a document corpus comprising a plurality of documents stored on a machine-readable medium; annotating one or more of said plurality of documents using at least one of said reference set of document annotators to generate a pre-annotated reference document set; annotating said one or more of said plurality of documents using the subject annotator to generate an evaluation annotated document set, each document in said evaluation annotated document set corresponding to a document in said one or more of said plurality of documents; comparing, using one or more processors, at least one of said documents in said evaluation annotated document set to its corresponding documents in said pre-annotated reference document set, to generate a matching data representing matches in location, within said compared documents, between instances of annotations using the subject annotation type system and instances of annotations using the common annotation type system; selecting, using said one or more processors, based on said matching data, a reference document annotation type system, comprised of one or more types from said common annotation type system, that meets a pre-determined correlation criterion with respect to said subject annotation type system; and identifying a taxonomy category for at least one annotation type in said reference annotation type system from among a set of known industry taxonomies. | 1. A computer-implemented method for selecting types from a common annotation type system to identify a subject annotation type system, the computer performing the steps of: providing a reference set of document annotators, said reference set using the common annotation type system; providing a document corpus comprising a plurality of documents stored on a machine-readable medium; annotating one or more of said plurality of documents using at least one of said reference set of document annotators to generate a pre-annotated reference document set; annotating said one or more of said plurality of documents using the subject annotator to generate an evaluation annotated document set, each document in said evaluation annotated document set corresponding to a document in said one or more of said plurality of documents; comparing, using one or more processors, at least one of said documents in said evaluation annotated document set to its corresponding documents in said pre-annotated reference document set, to generate a matching data representing matches in location, within said compared documents, between instances of annotations using the subject annotation type system and instances of annotations using the common annotation type system; selecting, using said one or more processors, based on said matching data, a reference document annotation type system, comprised of one or more types from said common annotation type system, that meets a pre-determined correlation criterion with respect to said subject annotation type system; and identifying a taxonomy category for at least one annotation type in said reference annotation type system from among a set of known industry taxonomies. 2. The method of claim 1 , wherein said identifying step further comprises: providing at least one reference taxonomy associated with at least one annotation type in said common annotation type system; and generating a taxonomy for said subject annotator based, at least in part, on said selecting a reference annotation type system and said reference taxonomy. | 0.586009 |
8,452,668 | 1 | 14 | 1. A system comprising: a) a processor; and b) a computer memory in communication with the processor, the memory containing one or more models utilized to process a customer interaction by software that is executed by the processor, said customer interaction comprising: i) one or more statements made by a customer; ii) one or more prompts played for said customer; c) a computer-readable storage medium storing a set of computer executable instructions and coupled to the processor, wherein the processor is configured to execute instructions to: i) coordinate processing of said customer interaction; ii) maintain a set of context information related to said customer interaction; iii) create a data record comprising the set of context information related to said customer interaction; iv) store the set of context information from said data record in said computer memory; v) utilize the set of context information stored in said computer memory to automatically create one or more model updates without human intervention; and vi) automatically update one or more of said models using one or more of said model updates. | 1. A system comprising: a) a processor; and b) a computer memory in communication with the processor, the memory containing one or more models utilized to process a customer interaction by software that is executed by the processor, said customer interaction comprising: i) one or more statements made by a customer; ii) one or more prompts played for said customer; c) a computer-readable storage medium storing a set of computer executable instructions and coupled to the processor, wherein the processor is configured to execute instructions to: i) coordinate processing of said customer interaction; ii) maintain a set of context information related to said customer interaction; iii) create a data record comprising the set of context information related to said customer interaction; iv) store the set of context information from said data record in said computer memory; v) utilize the set of context information stored in said computer memory to automatically create one or more model updates without human intervention; and vi) automatically update one or more of said models using one or more of said model updates. 14. The system of claim 1 wherein said computer memory further contains: a) a set of potential call dispositions, wherein each disposition correlates to a potential outcome of said customer interaction; b) for each potential call disposition from the set of potential call dispositions, an indication of the potential call disposition's desirability; c) a record of a disposition of said customer interaction; and d) wherein said processor is further configured to execute instructions to make at least one recommendation regarding processing said customer interaction based at least in part on the indication of the potential call disposition's desirability. | 0.644552 |
9,368,109 | 10 | 12 | 10. An apparatus according to claim 9 , wherein the plurality of vector representations of the speech utterances are a plurality of i-vectors corresponding to the speech utterances. | 10. An apparatus according to claim 9 , wherein the plurality of vector representations of the speech utterances are a plurality of i-vectors corresponding to the speech utterances. 12. An apparatus according to claim 10 , wherein in evaluating the clustering confidence score the processor and the memory, with the computer code instructions, are configured to further cause the apparatus to: evaluate the silhouette width criterion values for the plurality of i-vectors; and calculate an average of the silhouette width criterion values. | 0.5 |
7,685,141 | 1 | 10 | 1. A method comprising: establishing a first entity and a second entity in an entity relationship graph, wherein the entity relationship graph comprises a set of entities interconnected through a plurality of edge relationships and wherein the first entity and the second entity are included in the set of entities; assigning an initial activation value to the first entity; creating an activation value distribution in the entity relationship graph by spreading the initial activation value assigned to the first entity to other entities in the entity relationship graph; determining an activation value at the second entity in the activation value distribution; determining a plurality of candidate path relationships between the first entity and the second entity, wherein each of the plurality of candidate path relationships terminates at both the first entity and the second entity and comprises one or more edge relationships in the plurality of edge relationships; for each candidate path relationship in the plurality of candidate path relationships: determining a path type that is associated with a candidate path relationship; and generating a score value for the candidate path relationship based in part on the path type that is associated with the candidate path relationship; wherein the score value represents a likelihood that the candidate path relationship is of interest to a user; and selecting, in the plurality of candidate path relationships, one candidate path relationship having a score value that satisfies one or more first criteria; wherein the plurality of candidate path relationships is identified as one or more path relationships whose contributions to the activation value at the second entity satisfy one or more second criteria; wherein the method is performed by one or more computing devices. | 1. A method comprising: establishing a first entity and a second entity in an entity relationship graph, wherein the entity relationship graph comprises a set of entities interconnected through a plurality of edge relationships and wherein the first entity and the second entity are included in the set of entities; assigning an initial activation value to the first entity; creating an activation value distribution in the entity relationship graph by spreading the initial activation value assigned to the first entity to other entities in the entity relationship graph; determining an activation value at the second entity in the activation value distribution; determining a plurality of candidate path relationships between the first entity and the second entity, wherein each of the plurality of candidate path relationships terminates at both the first entity and the second entity and comprises one or more edge relationships in the plurality of edge relationships; for each candidate path relationship in the plurality of candidate path relationships: determining a path type that is associated with a candidate path relationship; and generating a score value for the candidate path relationship based in part on the path type that is associated with the candidate path relationship; wherein the score value represents a likelihood that the candidate path relationship is of interest to a user; and selecting, in the plurality of candidate path relationships, one candidate path relationship having a score value that satisfies one or more first criteria; wherein the plurality of candidate path relationships is identified as one or more path relationships whose contributions to the activation value at the second entity satisfy one or more second criteria; wherein the method is performed by one or more computing devices. 10. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1 . | 0.752941 |
7,747,619 | 8 | 12 | 8. A client computer system directly accessed by a user, the system comprising: a display; a gateway operable to connect the client computer system to a server; a local database, located on the client computer system and comprising at least preferences information of the user; and a processing module, located on the client computer system and operable to: i. obtain at least preferences information of the user by monitoring online activities of the user, wherein the preferences information of the user is based on a history of the online activities of the user; ii. store the obtained preferences information of the user in the database; iii. process information received from the server after the user submits a query; iv. determine likely preferences of the user based on contents of the database and the information received from the server; v. provide to the server decision information based, at least in part, on the determined likely preferences of the user and, in response, receive from the server targeted information based on the provided decision information; and vi. display the targeted information to the user on the display wherein the preferences information of the user is not accessible to any other entity except for the client computer system; wherein the server comprises a search engine, wherein the query is a search engine query and wherein the information received from the server comprises search results responsive to the query submitted by the user and a plurality of advertisements related to the search results, wherein the processing module is further operable to select at least one of the plurality of advertisements for displaying to the user based on the determined likely preferences of the user, wherein the selection is performed on the client computer system. | 8. A client computer system directly accessed by a user, the system comprising: a display; a gateway operable to connect the client computer system to a server; a local database, located on the client computer system and comprising at least preferences information of the user; and a processing module, located on the client computer system and operable to: i. obtain at least preferences information of the user by monitoring online activities of the user, wherein the preferences information of the user is based on a history of the online activities of the user; ii. store the obtained preferences information of the user in the database; iii. process information received from the server after the user submits a query; iv. determine likely preferences of the user based on contents of the database and the information received from the server; v. provide to the server decision information based, at least in part, on the determined likely preferences of the user and, in response, receive from the server targeted information based on the provided decision information; and vi. display the targeted information to the user on the display wherein the preferences information of the user is not accessible to any other entity except for the client computer system; wherein the server comprises a search engine, wherein the query is a search engine query and wherein the information received from the server comprises search results responsive to the query submitted by the user and a plurality of advertisements related to the search results, wherein the processing module is further operable to select at least one of the plurality of advertisements for displaying to the user based on the determined likely preferences of the user, wherein the selection is performed on the client computer system. 12. The client computer system of claim 8 , wherein displaying the targeted information to the user comprises displaying the at least one advertisement and the search results to the user. | 0.847967 |
7,836,028 | 19 | 21 | 19. The versioned relational database system set forth in claim 7 wherein: an operation that operates on a workspace that belongs to a multi-parent graph or on a version in such a workspace and that may result in a constraint violation uses the multi-parent graph to determine whether the operation will violate the constraint. | 19. The versioned relational database system set forth in claim 7 wherein: an operation that operates on a workspace that belongs to a multi-parent graph or on a version in such a workspace and that may result in a constraint violation uses the multi-parent graph to determine whether the operation will violate the constraint. 21. The versioned relational database system set forth in claim 19 wherein: the constraint is a unique key constraint, the unique key constraint being violated when the operation results in a logical split of a record in current versions in the workspaces belonging to the multi-parent graph. | 0.726592 |
8,370,391 | 15 | 16 | 15. A computer-readable storage medium tangibly embodying computer-executable instructions configured to, in response to execution by at least one computing device, cause operations comprising: receiving an indication of an XML file or an XML stream to update in an input tree, and an update combinator, the update combinator including a function to apply to nodes matching the update combinator; optimizing a query to search for nodes matching the update combinator at least partly by skipping a search of a subtree associated with the input tree based on an XML schema associated with the input tree; searching for at least one node in the input tree matching the update combinator using the optimized search; cloning one or more portions of the input tree that include a matching node corresponding to the update combinator; streaming portions of the input tree respectively corresponding to a matched node, wherein only a portion of the input tree is streamed into memory at any given time; updating a cloned portion of the at least one node in the input tree by applying the function indicated by the update combinator; determining an amount of memory to be used based on a size of the input tree and an expected number of updates; and outputting an output tree comprising updated nodes. | 15. A computer-readable storage medium tangibly embodying computer-executable instructions configured to, in response to execution by at least one computing device, cause operations comprising: receiving an indication of an XML file or an XML stream to update in an input tree, and an update combinator, the update combinator including a function to apply to nodes matching the update combinator; optimizing a query to search for nodes matching the update combinator at least partly by skipping a search of a subtree associated with the input tree based on an XML schema associated with the input tree; searching for at least one node in the input tree matching the update combinator using the optimized search; cloning one or more portions of the input tree that include a matching node corresponding to the update combinator; streaming portions of the input tree respectively corresponding to a matched node, wherein only a portion of the input tree is streamed into memory at any given time; updating a cloned portion of the at least one node in the input tree by applying the function indicated by the update combinator; determining an amount of memory to be used based on a size of the input tree and an expected number of updates; and outputting an output tree comprising updated nodes. 16. The computer-readable storage medium of claim 15 , the operations further comprising: reconstructing the input tree while descending into the input tree; and performing recursion into an incoming element while searching for a matching node. | 0.601307 |
8,136,025 | 1 | 9 | 1. A computer-implemented method of assigning a document identification tag to a new document, the new document to be added to a collection of documents, the method comprising: subdividing a predetermined set of monotonically ordered document identification tags into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about the new document, the information including the query-independent document importance metric; selecting, based at least on the query-independent information, one of the tiers; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in the collection of documents; and storing an assignment of the document identification tag from the respective subset of document identification tags associated with the selected tier to the new document in a computer-readable medium. | 1. A computer-implemented method of assigning a document identification tag to a new document, the new document to be added to a collection of documents, the method comprising: subdividing a predetermined set of monotonically ordered document identification tags into a plurality of tiers, wherein each tier is associated with a respective subset of the set of document identification tags, and wherein the plurality of tiers are monotonically ordered with respect to a query-independent document importance metric; receiving query-independent information about the new document, the information including the query-independent document importance metric; selecting, based at least on the query-independent information, one of the tiers; assigning to the new document a document identification tag from the respective subset of document identification tags associated with the selected tier, the assigned document identification tag not previously assigned to any of the documents in the collection of documents; and storing an assignment of the document identification tag from the respective subset of document identification tags associated with the selected tier to the new document in a computer-readable medium. 9. The method of claim 1 , further comprising; when a flush condition is satisfied, performing a flush operation, including building a sorted map, the sorted map relating globally unique identifiers to document identification tags assigned to documents since a prior flush operation. | 0.768033 |
9,176,639 | 16 | 17 | 16. An electronic device for enabling content discovery, comprising: a non-transitory computer readable storage medium storing executable computer program instructions comprising instructions for: providing, on the electronic device, a user interface (UI), the UI comprising: a concept bar presenting a user of the electronic device with a plurality of user-interactive concept tabs, the concept tabs associated with concepts currently relevant to a collaborative communication session involving the user and at least a second user using a second electronic device, each concept identified based on audio data corresponding to the collaborative communication session, wherein the concept tabs are arranged in an order indicating a relative importance of the concepts associated with the concept tabs to the user; and a content window separate from the concept bar and presenting the user of the electronic device with content relevant to the collaborative communication session selected responsive to the concept tabs presented by the concept bar, wherein the content presented by the content window is modified responsive to the user curating the content in the content window by interacting with the concept tabs, and wherein the presented content is selected from a set of content candidates associated with concept tabs presented by the concept bar such that a subset of highest ranked content candidates are selected for presentation; and a processor for executing the computer program instructions. | 16. An electronic device for enabling content discovery, comprising: a non-transitory computer readable storage medium storing executable computer program instructions comprising instructions for: providing, on the electronic device, a user interface (UI), the UI comprising: a concept bar presenting a user of the electronic device with a plurality of user-interactive concept tabs, the concept tabs associated with concepts currently relevant to a collaborative communication session involving the user and at least a second user using a second electronic device, each concept identified based on audio data corresponding to the collaborative communication session, wherein the concept tabs are arranged in an order indicating a relative importance of the concepts associated with the concept tabs to the user; and a content window separate from the concept bar and presenting the user of the electronic device with content relevant to the collaborative communication session selected responsive to the concept tabs presented by the concept bar, wherein the content presented by the content window is modified responsive to the user curating the content in the content window by interacting with the concept tabs, and wherein the presented content is selected from a set of content candidates associated with concept tabs presented by the concept bar such that a subset of highest ranked content candidates are selected for presentation; and a processor for executing the computer program instructions. 17. The electronic device of claim 16 , wherein the provided UI enables the user to reorder the arrangement of the concept tabs presented by the concept bar, and wherein the content presented by the content window is modified responsive to the reordering. | 0.622781 |
9,766,786 | 11 | 14 | 11. A method comprising: presenting a visual experience capable of telling a story via a display device associated with a mobile device, the story including an authored series of events and visual context, the authored series of events representing a storyline of the story, the visual context providing context for the storyline, the visual experience including story views each having at least a portion of a respective event of the authored series of events and context views each including at least a portion of the visual context for the storyline; determining a first display view based on a first orientation of the display device; displaying, via the display device, a first portion of the visual experience based on the first display view; receiving a first selection of a first display view representing a first view into the visual experience for display via the display of the mobile device; determining that the first display view corresponds to a context view based on an amount of a respective story view visually contained within the first view; responsive to the determining that the first display view corresponds to the context view: presenting the visual context via the display device; and pausing progression through the authored series of events at a respective event; determining a second display view based on a second orientation of the display device that is different than the first orientation; displaying, via the display device, a second portion of the visual experience based on the second display view, the second portion different than the first portion; determining that the second display view corresponds to a story view based on an amount of the respective event visually contained within the second display view; and responsive to the second display view corresponding to the story view, presenting the respective event at which the progression through the authored series of events was paused. | 11. A method comprising: presenting a visual experience capable of telling a story via a display device associated with a mobile device, the story including an authored series of events and visual context, the authored series of events representing a storyline of the story, the visual context providing context for the storyline, the visual experience including story views each having at least a portion of a respective event of the authored series of events and context views each including at least a portion of the visual context for the storyline; determining a first display view based on a first orientation of the display device; displaying, via the display device, a first portion of the visual experience based on the first display view; receiving a first selection of a first display view representing a first view into the visual experience for display via the display of the mobile device; determining that the first display view corresponds to a context view based on an amount of a respective story view visually contained within the first view; responsive to the determining that the first display view corresponds to the context view: presenting the visual context via the display device; and pausing progression through the authored series of events at a respective event; determining a second display view based on a second orientation of the display device that is different than the first orientation; displaying, via the display device, a second portion of the visual experience based on the second display view, the second portion different than the first portion; determining that the second display view corresponds to a story view based on an amount of the respective event visually contained within the second display view; and responsive to the second display view corresponding to the story view, presenting the respective event at which the progression through the authored series of events was paused. 14. The method as recited in claim 11 , wherein: the visual context for the storyline is presented during presentation of the respective event at which the progression through the authored series of events was paused based on the first display view; and the presenting of the respective event at which the storyline was paused includes repeating the respective event from a starting point of the respective event. | 0.5 |
8,319,736 | 10 | 12 | 10. A touch sensitive computing device, comprising: a touch sensitive display configured to selectively display a plurality of hierarchically flat sequentially arranged journal page graphics; a touch input recognition module configured to receive touch input in the form of a marking so that the marking is graphically disposed on a selected one of the plurality of journal page graphics via the touch sensitive display; a gesture recognition module configured to recognize from the touch input a recognized gesture from a plurality of predefined gestures; a user interface configured to apply the marking from the selected one of the plurality of journal page graphics to a selected one of a plurality of PIM schemas in response to recognition of the recognized gesture; and an aging module configured to control aging appearance characteristics for each of the journal page graphics according to predetermined temporal conditions and predetermined use conditions. | 10. A touch sensitive computing device, comprising: a touch sensitive display configured to selectively display a plurality of hierarchically flat sequentially arranged journal page graphics; a touch input recognition module configured to receive touch input in the form of a marking so that the marking is graphically disposed on a selected one of the plurality of journal page graphics via the touch sensitive display; a gesture recognition module configured to recognize from the touch input a recognized gesture from a plurality of predefined gestures; a user interface configured to apply the marking from the selected one of the plurality of journal page graphics to a selected one of a plurality of PIM schemas in response to recognition of the recognized gesture; and an aging module configured to control aging appearance characteristics for each of the journal page graphics according to predetermined temporal conditions and predetermined use conditions. 12. The touch sensitive computing device of claim 10 , where the plurality of PIM schemas include a calendar schema, a tasks schema and a contacts schema. | 0.793566 |
9,373,323 | 1 | 6 | 1. A method comprising: at a turn in a dialog between a user and a spoken dialog system: nominating, via a processor configured to perform speech recognition, a set of dialog actions and a set of contextual features, wherein the processor uses a partially observable Markov decision process in parallel with a conventional dialog state to perform the nominating; and generating an audible response in the dialog based on the set of contextual features, via a machine learning algorithm, from the set of dialog actions. | 1. A method comprising: at a turn in a dialog between a user and a spoken dialog system: nominating, via a processor configured to perform speech recognition, a set of dialog actions and a set of contextual features, wherein the processor uses a partially observable Markov decision process in parallel with a conventional dialog state to perform the nominating; and generating an audible response in the dialog based on the set of contextual features, via a machine learning algorithm, from the set of dialog actions. 6. The method of claim 1 , wherein a lower-dimensional feature vector represents one of the set of dialog actions. | 0.740909 |
9,568,993 | 1 | 3 | 1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood. | 1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood. 3. The method of claim 1 , further comprising receiving data from a real world source to determine occurrence of a mood changing condition in the real world. | 0.859821 |
9,418,117 | 10 | 14 | 10. A method for displaying a relevant conversation, comprising: receiving, by a client device, a reverse chronological stream of messages broadcasted to a recipient account of a messaging platform from a plurality of authoring accounts, the plurality of authoring accounts having a predefined graph relationship with the recipient account; identifying, among the stream of messages, a first message selected for inclusion in a relevant conversation among messages of a conversation graph; identifying a previously broadcasted second message selected for inclusion in the relevant conversation from among messages of the conversation graph, wherein the second message is an ancestor of the first message in a branch of the conversation graph; and displaying, by the client device and concurrently with the first message in the stream of messages, an indication of the second message and a display element indicating that the second message is the ancestor of the first message. | 10. A method for displaying a relevant conversation, comprising: receiving, by a client device, a reverse chronological stream of messages broadcasted to a recipient account of a messaging platform from a plurality of authoring accounts, the plurality of authoring accounts having a predefined graph relationship with the recipient account; identifying, among the stream of messages, a first message selected for inclusion in a relevant conversation among messages of a conversation graph; identifying a previously broadcasted second message selected for inclusion in the relevant conversation from among messages of the conversation graph, wherein the second message is an ancestor of the first message in a branch of the conversation graph; and displaying, by the client device and concurrently with the first message in the stream of messages, an indication of the second message and a display element indicating that the second message is the ancestor of the first message. 14. The method of claim 10 , wherein an authoring account of the second message is outside of the predefined graph relationship. | 0.820225 |
9,390,706 | 8 | 11 | 8. A method for assisting a user, which comprises: receiving, by one or more processors, at least one request from the user; entering, by the one or more processors, the at least one request into an algorithm trained to output a personality type of the user from three or more personality types based on the at least one user request generating, by the one more processors, a set of outputs, wherein the set of outputs comprises a plurality of different modalities of a device and physical actions to control the device, responsive to the at least one input; ranking and selecting, by the one or more processors, an output from the set of outputs based on the one personality type; delivering, by the one or more processors, the ranked and selected output to the user in a modality of the device, wherein the modality of the device is determined based on the personality type and type of the device configured to deliver the output to the user; and determining a distress level or engagement level of the user, or both, based on the ranked and selected output and the modality of delivery, and weighting the ranked and selected output for one or more future interactions with the user based on the determined distress level and/or engagement level. | 8. A method for assisting a user, which comprises: receiving, by one or more processors, at least one request from the user; entering, by the one or more processors, the at least one request into an algorithm trained to output a personality type of the user from three or more personality types based on the at least one user request generating, by the one more processors, a set of outputs, wherein the set of outputs comprises a plurality of different modalities of a device and physical actions to control the device, responsive to the at least one input; ranking and selecting, by the one or more processors, an output from the set of outputs based on the one personality type; delivering, by the one or more processors, the ranked and selected output to the user in a modality of the device, wherein the modality of the device is determined based on the personality type and type of the device configured to deliver the output to the user; and determining a distress level or engagement level of the user, or both, based on the ranked and selected output and the modality of delivery, and weighting the ranked and selected output for one or more future interactions with the user based on the determined distress level and/or engagement level. 11. The method of claim 8 , Which further comprises updating the personality type based on additional input. | 0.72449 |
8,533,665 | 18 | 20 | 18. An apparatus comprising: one or more processors; object transform logic configured for generating a JavaScript Object Notation (JSON) object, comprising: annotation receiving logic configured to receive and store one or more annotations that annotate one or more attribute declarations of a base object of an object-oriented programming environment, wherein the one or more annotations denote one or more JavaScript Object Notation (JSON) attributes; a JSON object creating unit configured to generate, at runtime of an executable computer program that has been created using the base object, a JSON object based upon the base object; a JSON object header unit configured to retrieve the annotations and to create creating a JSON header that comprises the annotations in a format compatible with a function library that expects name-value pair declarations and to attach the JSON header to the JSON object; a JSON object modifying unit configured to rename an attribute of the JSON object to an items attribute. | 18. An apparatus comprising: one or more processors; object transform logic configured for generating a JavaScript Object Notation (JSON) object, comprising: annotation receiving logic configured to receive and store one or more annotations that annotate one or more attribute declarations of a base object of an object-oriented programming environment, wherein the one or more annotations denote one or more JavaScript Object Notation (JSON) attributes; a JSON object creating unit configured to generate, at runtime of an executable computer program that has been created using the base object, a JSON object based upon the base object; a JSON object header unit configured to retrieve the annotations and to create creating a JSON header that comprises the annotations in a format compatible with a function library that expects name-value pair declarations and to attach the JSON header to the JSON object; a JSON object modifying unit configured to rename an attribute of the JSON object to an items attribute. 20. The apparatus of claim 18 , wherein the annotation receiving logic is further configured to receive and store the one or more annotations by obtaining and storing a configuration file that comprises a class name, and one or more tags, each tag associating a name of a class attributes used in the class with a JSON attribute. | 0.56366 |
8,655,664 | 1 | 3 | 1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance. | 1. A text presentation apparatus presenting text for a speaker to read aloud for voice recording, the apparatus comprising: a text storing unit configured to store first text; a presenting unit configured to present the first text; a determination unit configured to determine whether or not the first text needs to be replaced, on the basis of a speaker's input for the first text presented; a preliminary text storing unit configured to store preliminary text; a select unit configured to select, if it is determined that the first text needs to be replaced, second text to replace the first text from among the preliminary text, the selecting being performed on the basis of attribute information describing an attribute of the first text and on the basis of at least one of attribute information describing pronunciation of the first text and attribute information describing a stress type of the first text; and a control unit configured to control the presenting unit so that the presenting unit presents the second text, wherein: the pieces of attribute information are associated with respective degrees of importance; and the select unit, if it is determined that the first text needs to be replaced, calculates, for each piece of the preliminary text that is associated with the attribute information having an attribute value matching that of at least one of the pieces of attribute information on the first text, the sum of the degrees of importance that are associated with pieces of attribute information having matching attribute values, and selects the second text that maximizes the sum of the degrees of importance. 3. The apparatus according to claim 1 , further comprising a voice input unit into which speaker's voice is input, wherein the determination unit determines that the first text needs to be replaced when a speaker's voice to give an instruction to replace the first text is input into the voice input unit. | 0.708969 |
9,703,548 | 30 | 31 | 30. The non-transitory computer readable storage medium as claimed in claim 18 , wherein the project template data comprises filesystem directory structure data representing a directory structure and further comprising instructions for structuring a directory in accordance with the filesystem directory structure data. | 30. The non-transitory computer readable storage medium as claimed in claim 18 , wherein the project template data comprises filesystem directory structure data representing a directory structure and further comprising instructions for structuring a directory in accordance with the filesystem directory structure data. 31. The non-transitory computer readable storage medium as claimed in claim 30 , wherein the filesystem directory structure data comprises template data representing a template for inclusion in a specified directory and further comprising instructions for storing, in the specified directory the template data. | 0.5 |
9,177,558 | 1 | 9 | 1. A computer-implemented method of assessing speech pronunciation, comprising: receiving speech for analysis via a computer-readable storage medium; performing automatic speech recognition on speech using a processor to generate word hypotheses for the speech, the word hypotheses identifying a set words recognized by an automated speech recognizer in the speech using one or more data processors; performing time alignment between the speech and the word hypotheses using the automatic speech recognizer to associate the word hypotheses with corresponding sounds of the speech; calculating statistics regarding individual words and phonemes of the word hypotheses using the processor based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics using the processor; and calculating an assessment score based on one or more of the calculated features. | 1. A computer-implemented method of assessing speech pronunciation, comprising: receiving speech for analysis via a computer-readable storage medium; performing automatic speech recognition on speech using a processor to generate word hypotheses for the speech, the word hypotheses identifying a set words recognized by an automated speech recognizer in the speech using one or more data processors; performing time alignment between the speech and the word hypotheses using the automatic speech recognizer to associate the word hypotheses with corresponding sounds of the speech; calculating statistics regarding individual words and phonemes of the word hypotheses using the processor based on said alignment; calculating a plurality of features for use in assessing pronunciation of the speech based on the statistics using the processor; and calculating an assessment score based on one or more of the calculated features. 9. The method of claim 1 , wherein the assessment score is based on one or more features selected from the group consisting of: an average likelihood across all letters: L 1 /m, where L 1 is a summation of likelihoods of all individual words: L 1 = ∑ i = 1 n L ( x i ) , where L(x i ) is a likelihood of word x i being spoken given an observed audio signal, where n is a number of words in a response, where m is a number of letters in the response; an average likelihood across all words: L 1 /n; an average likelihood per second normalized by a rate of speech: L 4 /R, where L 4 =L 1 /T, where T is the summation of a duration of all words in the response, where R=m/T s , where T s is a duration of the response; an average likelihood density across all words normalized by a rate of speech, L 5 /R, where L 5 = ∑ i = 1 n L ( x i ) t i n , where t i is a duration of word i in a response; an average vowel duration shift: S _ = ∑ i = 1 N v S v i N v , where N v is a total number of vowels, where S v i is the duration shift of vowel v i , which is measured as an absolute value of the difference between a duration of vowel v i and a standard value of a duration of a vowel estimated on native speech data, where S v i =|P v i −D v i |, where P v i is the duration of vowel v i and D v i is the standard average duration of vowel v i ; and an average normalized vowel duration shifts: S _ n = ∑ i = 1 N v Sn v i N v , where Sn v i is a normalized duration shift of vowel v i , which is measured as an absolute value of a normalized difference between a duration of vowel v i and a standard value of a duration of a vowel estimated on the native speech data, where Sn v i is calculated as P v i P - D v i D , where P v i is the duration of vowel v i , P is an average vowel duration across all vowels in the response being scored, D v i is a standard average duration of vowel v i , and D is a standard vowel duration estimated on all vowels in native speech data. | 0.5 |
8,185,517 | 1 | 2 | 1. A method for providing assistance, comprising: receiving a query from a user via a first mode of interaction; developing a query context using information related to the query and identity information related to the user; searching first data for first results, wherein the searching is limited by the query context; and providing first results to the user via a second mode of interaction that is different than the first mode of interaction; wherein the identity information related to the user is obtained using the first mode of interaction via which the query is received; wherein the first mode of interaction is one of an Interactive Voice Recognition (“IVR”) delivery system configured to receive a voice inquiry, an internet services system configured to receive an Internet query, and a text messaging system configured to receive a text message query; and wherein the second mode of interaction is another of the IVR delivery system, the internet services system, and the text messaging system, so that: if the first mode of interaction is the IVR system and thus the identity information related to the user is obtained using the IVR system and the query is received via the IVR system, then the second mode of interaction is either the internet services system or the text messaging system and thus the first results are provided to the user via either the internet services system or the text messaging system; if the first mode of interaction is the internet services system and thus the identity information related to the user is obtained using the internet services system and the query is received via the internet services system, then the second mode of interaction is either the text messaging system or the IVR system and thus the first results are provided to the user via either the text messaging system or the IVR system; and if the first mode of interaction is the text messaging system and thus the identity information related to the user is obtained using the text messaging system and the query is received via the text messaging system, then the second mode of interaction is either the IVR system or the internet services system and thus the first results are provided to the user via either the IVR system or the internet services system. | 1. A method for providing assistance, comprising: receiving a query from a user via a first mode of interaction; developing a query context using information related to the query and identity information related to the user; searching first data for first results, wherein the searching is limited by the query context; and providing first results to the user via a second mode of interaction that is different than the first mode of interaction; wherein the identity information related to the user is obtained using the first mode of interaction via which the query is received; wherein the first mode of interaction is one of an Interactive Voice Recognition (“IVR”) delivery system configured to receive a voice inquiry, an internet services system configured to receive an Internet query, and a text messaging system configured to receive a text message query; and wherein the second mode of interaction is another of the IVR delivery system, the internet services system, and the text messaging system, so that: if the first mode of interaction is the IVR system and thus the identity information related to the user is obtained using the IVR system and the query is received via the IVR system, then the second mode of interaction is either the internet services system or the text messaging system and thus the first results are provided to the user via either the internet services system or the text messaging system; if the first mode of interaction is the internet services system and thus the identity information related to the user is obtained using the internet services system and the query is received via the internet services system, then the second mode of interaction is either the text messaging system or the IVR system and thus the first results are provided to the user via either the text messaging system or the IVR system; and if the first mode of interaction is the text messaging system and thus the identity information related to the user is obtained using the text messaging system and the query is received via the text messaging system, then the second mode of interaction is either the IVR system or the internet services system and thus the first results are provided to the user via either the IVR system or the internet services system. 2. The method of claim 1 , further comprising: refining the query context, wherein refining the query context includes: presenting one or more search result contexts related to the first results to the user; receiving input from the user regarding a user-chosen search result context; and modifying the query context based on the user-chosen search result context; searching second data for second results, wherein the searching is limited by the refined query context; and providing second results to the user. | 0.5 |
8,601,367 | 13 | 18 | 13. A non-transitory computer readable storage medium having program instructions stored thereon that, when executed by a processor, cause the processor to carry out a computer based method, the method comprising: receiving at least one of numerical and textual input from at least one of: a user input device, a data file containing spreadsheet based data, and a data file containing word processor based data; generating a first human readable document including numerical and textual data; generating an XBRL representation of the first document; generating a second human readable document based on the first document including a subset of the numerical and textual data from the first document and an interpretive context determined by performing the following operations: retrieving fact details for a navkey that references an XBRL fact; retrieving one or more extended links associated with the selected XBRL fact; and receiving a user-selection of one or more extended links that are associated with the navkey; generating an XBRL representation of the second document; generating an HTML representation of at least one of the first and second documents when a user selectable option is selected; storing first and second source files associated with the respective first and second documents; automatically validating the XBRL representations of the first and second documents; providing access to at least one of the first and second documents over the internet; and generating a reference locator to be used to access the at least one of the first and second documents, wherein the reference locator can comprise a URL or a QR code. | 13. A non-transitory computer readable storage medium having program instructions stored thereon that, when executed by a processor, cause the processor to carry out a computer based method, the method comprising: receiving at least one of numerical and textual input from at least one of: a user input device, a data file containing spreadsheet based data, and a data file containing word processor based data; generating a first human readable document including numerical and textual data; generating an XBRL representation of the first document; generating a second human readable document based on the first document including a subset of the numerical and textual data from the first document and an interpretive context determined by performing the following operations: retrieving fact details for a navkey that references an XBRL fact; retrieving one or more extended links associated with the selected XBRL fact; and receiving a user-selection of one or more extended links that are associated with the navkey; generating an XBRL representation of the second document; generating an HTML representation of at least one of the first and second documents when a user selectable option is selected; storing first and second source files associated with the respective first and second documents; automatically validating the XBRL representations of the first and second documents; providing access to at least one of the first and second documents over the internet; and generating a reference locator to be used to access the at least one of the first and second documents, wherein the reference locator can comprise a URL or a QR code. 18. The storage medium of claim 13 , further comprising program instructions that, when executed by the processor, cause the processor to: determine interpretive contexts for selected values, wherein the determining comprises: retrieving fact details for a navkey that references an XBRL fact, wherein the fact details include at least one of: a fact value; an XBRL element; a context ID; a date ID; and a unit ID; retrieving an extended link associated with an XBRL fact; determining whether multiple extended links are associated with a navkey; receiving a selection, from a user, of a primary extended link when extended links are associated with a navkey; determining an association between each navkey and the roleURI of each extended link selected by the user; and storing all fact details and the interpretive context as generation instructions. | 0.5 |
9,984,133 | 14 | 18 | 14. A computer-implemented method of accessing one or more databases in substantially real-time to identify and link data associated with particular physical components with representations of the particular physical components illustrated in a schematic layout of the physical components in an interactive user interface, the computer-implemented method comprising: accessing a digital image, wherein the digital image includes a schematic layout of a plurality of physical components; parsing the digital image to identify first text in the digital image; comparing the first text with identities of physical components that are included in entries stored in a parts database; identifying a first identity stored in the parts database that matches the first text; retrieving, from the parts database, data associated with a first physical component in the plurality of physical components identified by the first identity in the parts database; creating a link in the parts database between the data associated with the first physical component and one or more of the first text in the digital image or an area in the digital image covered by the first physical component; generating user interface data such that the interactive user interface displays the digital image in a first window and an interactive link at one or more of a location of the first text in the digital image or the area in the digital image covered by the first physical component, wherein the interactive link, when selected, causes the interactive user interface to display the data associated with the first physical component; in response to selection of the first physical component in the interactive user interface, updating the user interface data such that the interactive user interface concurrently displays the first window and a second window, wherein the second window overlaps the first window, and wherein the second window includes first data measured by the first physical component; and in response to selection of a second physical component in the plurality of physical components in the interactive user interface, updating the user interface data such that the interactive user interface concurrently displays the first window, the second window, and a third window, wherein the third window is different than the first and second windows and is linked to the second window, wherein the third window overlaps the first window, wherein the third window includes second data measured by the second physical component, and wherein a change to a zoom level of a graph depicting the second data in the third window causes a matching change to a zoom level of a graph depicting the first data in the second window, wherein the second window is displayed near the first physical component and the third window is displayed near the second physical component, each of the second window and the third window obscuring respective portions of the digital image in the interactive user interface. | 14. A computer-implemented method of accessing one or more databases in substantially real-time to identify and link data associated with particular physical components with representations of the particular physical components illustrated in a schematic layout of the physical components in an interactive user interface, the computer-implemented method comprising: accessing a digital image, wherein the digital image includes a schematic layout of a plurality of physical components; parsing the digital image to identify first text in the digital image; comparing the first text with identities of physical components that are included in entries stored in a parts database; identifying a first identity stored in the parts database that matches the first text; retrieving, from the parts database, data associated with a first physical component in the plurality of physical components identified by the first identity in the parts database; creating a link in the parts database between the data associated with the first physical component and one or more of the first text in the digital image or an area in the digital image covered by the first physical component; generating user interface data such that the interactive user interface displays the digital image in a first window and an interactive link at one or more of a location of the first text in the digital image or the area in the digital image covered by the first physical component, wherein the interactive link, when selected, causes the interactive user interface to display the data associated with the first physical component; in response to selection of the first physical component in the interactive user interface, updating the user interface data such that the interactive user interface concurrently displays the first window and a second window, wherein the second window overlaps the first window, and wherein the second window includes first data measured by the first physical component; and in response to selection of a second physical component in the plurality of physical components in the interactive user interface, updating the user interface data such that the interactive user interface concurrently displays the first window, the second window, and a third window, wherein the third window is different than the first and second windows and is linked to the second window, wherein the third window overlaps the first window, wherein the third window includes second data measured by the second physical component, and wherein a change to a zoom level of a graph depicting the second data in the third window causes a matching change to a zoom level of a graph depicting the first data in the second window, wherein the second window is displayed near the first physical component and the third window is displayed near the second physical component, each of the second window and the third window obscuring respective portions of the digital image in the interactive user interface. 18. The computer-implemented method of claim 14 , further comprising, in response to a command to zoom in on the second window to a first zoom level corresponding to a first data range along a y-axis, updating the user interface data such that the interactive user interface zooms in on the third window to the first zoom level so that the first data measured by the first physical component is displayed for the first data range along the y-axis and the second data measured by the second physical component is displayed for the first data range along the y-axis. | 0.5 |
8,687,792 | 26 | 27 | 26. A system for dialog management within a call handling system, comprising: a call handling system to initiate a dialog between a contact and an operator; a monitor to monitor an anger dialog attribute and a subject matter dialog attribute, wherein the monitoring of the subject matter dialog attribute includes analyzing a subject matter of the dialog and generating the subject matter dialog attribute which describes the subject matter of the dialog; and a computer executing machine readable instructions to determine a value for the anger dialog attribute and a value for the subject matter dialog attribute; compare the value for the anger dialog attribute and the value for the subject matter dialog attribute to a set of dialog rules; and effect a dialog rule from the set of dialog rules in response to the comparison. | 26. A system for dialog management within a call handling system, comprising: a call handling system to initiate a dialog between a contact and an operator; a monitor to monitor an anger dialog attribute and a subject matter dialog attribute, wherein the monitoring of the subject matter dialog attribute includes analyzing a subject matter of the dialog and generating the subject matter dialog attribute which describes the subject matter of the dialog; and a computer executing machine readable instructions to determine a value for the anger dialog attribute and a value for the subject matter dialog attribute; compare the value for the anger dialog attribute and the value for the subject matter dialog attribute to a set of dialog rules; and effect a dialog rule from the set of dialog rules in response to the comparison. 27. The system of claim 26 , wherein the monitor is further to: identify computational resources required to calculate dialog attribute scores for a plurality of dialog attributes of the dialog; generate dialog attribute scores hierarchically beginning with the dialog attribute score requiring a least amount of computational resources; and stop generation of the dialog attribute scores once the combined dialog attribute score exceeds a predetermined threshold. | 0.5 |
8,568,451 | 2 | 5 | 2. The anchor assembly of claim 1 wherein said compression unit has a first end and a second end and wherein said first recess is located on said first end and said second recess is located on said other end. | 2. The anchor assembly of claim 1 wherein said compression unit has a first end and a second end and wherein said first recess is located on said first end and said second recess is located on said other end. 5. The anchor assembly of claim 2 wherein said first recess is positioned about 90 degrees from said second recess. | 0.5 |
8,645,394 | 9 | 11 | 9. One or more computer storage media configured to store instructions that are executable by one or more processing devices to perform operations comprising: accessing a cluster of a plurality of resources associated with a name context; generating a quality score for a resource, the quality score being independent of inclusion of the resource in the cluster and independent of inclusion of other resources in the cluster and indicative of a quality measure of the resource; generating a cluster relation score for the resource, the cluster relation score being dependent on the other resources in the cluster and indicative of an authority of the resource relative to authorities of the other resources in the cluster; generating a resource ranking score for the resource, with the resource ranking score at least partly based on the quality score and the cluster relation score; and ranking the resources in the cluster at least partly based on the resource ranking score. | 9. One or more computer storage media configured to store instructions that are executable by one or more processing devices to perform operations comprising: accessing a cluster of a plurality of resources associated with a name context; generating a quality score for a resource, the quality score being independent of inclusion of the resource in the cluster and independent of inclusion of other resources in the cluster and indicative of a quality measure of the resource; generating a cluster relation score for the resource, the cluster relation score being dependent on the other resources in the cluster and indicative of an authority of the resource relative to authorities of the other resources in the cluster; generating a resource ranking score for the resource, with the resource ranking score at least partly based on the quality score and the cluster relation score; and ranking the resources in the cluster at least partly based on the resource ranking score. 11. The one or more computer storage media of claim 9 , wherein the resource comprises a first resource, and wherein the cluster relation score is at least partly based on a connectivity of the first resource to a second resource in the cluster. | 0.782028 |
9,158,858 | 1 | 6 | 1. A method for managing an Extensible Markup Language (XML) Document Management (XDM) Server history, the method comprising the steps of: receiving, by the XDM Server, XML Documents and Filtering Rules within a filter body in an XCAP request from a first XDM Client Device, wherein the Filtering Rules define operation information performed on specific XML Documents to store as history information and further define when to store the history information of the XML Documents; storing the XML Documents and the Filtering Rules on the XDM Server; and when a second XDM Client Device has access to perform one or more operations on the XML Documents stored in the XDM Server, storing, by the XDM Server, the history information of the XML Documents according to the Filtering Rules by the XDM Server and the one or more operations performed. | 1. A method for managing an Extensible Markup Language (XML) Document Management (XDM) Server history, the method comprising the steps of: receiving, by the XDM Server, XML Documents and Filtering Rules within a filter body in an XCAP request from a first XDM Client Device, wherein the Filtering Rules define operation information performed on specific XML Documents to store as history information and further define when to store the history information of the XML Documents; storing the XML Documents and the Filtering Rules on the XDM Server; and when a second XDM Client Device has access to perform one or more operations on the XML Documents stored in the XDM Server, storing, by the XDM Server, the history information of the XML Documents according to the Filtering Rules by the XDM Server and the one or more operations performed. 6. The method for managing an XDM Server history as claimed in claim 1 , wherein the step of storing the history information according to the Filtering Rules is performed by storing the history information as a XML Resource in the form of XML. | 0.781081 |
4,866,634 | 1 | 9 | 1. An expert system shell comprising: (a) a computer having a display device, an entry device, and a memory for string a knowledge base; said knowledge base comprising: (1) variables having values represented by tables of probabitlity distributions keyed by zero, one or more formal parameters; (2) functions defining relationships between the values of each dependent variable and the values of its corresponding argument variables; (3) means for computing the probability distribution of the values of a dependent variable from the probability distribution of the values of the corresponding argument variables; and (b) means for propagating the consequences of a change in the value of a variable to maintain the functional relationships among a selected subset of the dependent variables. | 1. An expert system shell comprising: (a) a computer having a display device, an entry device, and a memory for string a knowledge base; said knowledge base comprising: (1) variables having values represented by tables of probabitlity distributions keyed by zero, one or more formal parameters; (2) functions defining relationships between the values of each dependent variable and the values of its corresponding argument variables; (3) means for computing the probability distribution of the values of a dependent variable from the probability distribution of the values of the corresponding argument variables; and (b) means for propagating the consequences of a change in the value of a variable to maintain the functional relationships among a selected subset of the dependent variables. 9. The system of claim 1, said propagating means further comprising means for minimizing the computation required during propagation by assuring that the final distributions for all arguments to a function are known before the distribution for the dependent variable is computed. | 0.622973 |
8,381,099 | 6 | 8 | 6. A method of generating a document for printing, the method comprising: generating the document template, by: defining a variable-data printing template, the template comprising a layout of document pages with at least one set of the document pages comprising a flow that contains content which is variable in response to input data, the flow spanning across the at least one set of document pages, wherein the flow comprises a series of linked copy holes; defining a plurality of document versions, wherein in at least some of the different document versions, at least one document page across which the flow spans is absent from the at least one set of document pages, and defining the respective document versions further includes indicating the desired variable content of the flow; and generating one of the respective document versions for printing by providing input selection data to the template via variable data merging at the time of printing to automatically select one of the respective document versions, while automatically maintaining continuity of the flow, when a respective one of the at least some document versions is automatically selected in which at least one document page is absent, is performed according to a conditional choose function via: in the event that a first page of the at least one set exists in the input data, applying a first page sequence definition that maps the flow to begin at the first page and includes all subsequent pages of the at least one set; and in the event that the first page of the at least one set is non-existent in the input data, applying a second page sequence definition that maps the flow to begin at a second page of the at least one set and includes all subsequent pages of the at least one set while omitting the non-existent first page of the at least one set holes, wherein the non-existent first page corresponds to a first copy-hole of the linked copy holes. | 6. A method of generating a document for printing, the method comprising: generating the document template, by: defining a variable-data printing template, the template comprising a layout of document pages with at least one set of the document pages comprising a flow that contains content which is variable in response to input data, the flow spanning across the at least one set of document pages, wherein the flow comprises a series of linked copy holes; defining a plurality of document versions, wherein in at least some of the different document versions, at least one document page across which the flow spans is absent from the at least one set of document pages, and defining the respective document versions further includes indicating the desired variable content of the flow; and generating one of the respective document versions for printing by providing input selection data to the template via variable data merging at the time of printing to automatically select one of the respective document versions, while automatically maintaining continuity of the flow, when a respective one of the at least some document versions is automatically selected in which at least one document page is absent, is performed according to a conditional choose function via: in the event that a first page of the at least one set exists in the input data, applying a first page sequence definition that maps the flow to begin at the first page and includes all subsequent pages of the at least one set; and in the event that the first page of the at least one set is non-existent in the input data, applying a second page sequence definition that maps the flow to begin at a second page of the at least one set and includes all subsequent pages of the at least one set while omitting the non-existent first page of the at least one set holes, wherein the non-existent first page corresponds to a first copy-hole of the linked copy holes. 8. The method of claim 6 , wherein the flow is represented as an Extensible Stylesheet Language Formatting Object (XSL-FO), wherein the variable-data printing document template is represented as a Personalized Print Markup Language Template (PPML/T), and wherein the input selection comprises data represented as Extensible Markup Language (XML). | 0.5 |
9,665,564 | 10 | 16 | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive a natural language content upon which a reasoning operation is to be performed; generate a first parse representation of the natural language content by performing natural language processing on the natural language content; generate a logical parse of the first parse by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content; and perform a reasoning operation on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content, wherein the computer readable program further causes the data processing system to generate the first parse representation of the natural language content at least by: parsing the natural language content into one or more atomic logical terms that lack explicit or implicit logic; and connecting the one or more atomic logical terms by logical operators in the first parse representation to specify a logical relationship between the one or more atomic logical terms. | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a data processing system, causes the data processing system to: receive a natural language content upon which a reasoning operation is to be performed; generate a first parse representation of the natural language content by performing natural language processing on the natural language content; generate a logical parse of the first parse by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content; and perform a reasoning operation on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content, wherein the computer readable program further causes the data processing system to generate the first parse representation of the natural language content at least by: parsing the natural language content into one or more atomic logical terms that lack explicit or implicit logic; and connecting the one or more atomic logical terms by logical operators in the first parse representation to specify a logical relationship between the one or more atomic logical terms. 16. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to generate a logical parse of the first parse representation of the natural language content at least by: processing each logical operator in the logical parse within a scope of the logical operator, where upper scopes are processed before lower scopes to thereby elevate a logical operator above a top unprocessed node in the logical parse and set a sub-tree under the logical operator as a first argument of the logical operator and a copy of the sub-tree as a second argument of the logical operator. | 0.5 |
7,653,876 | 31 | 33 | 31. The software product of claim 30 , further comprising the operations of receiving, at a third party, the reversible electronic document over the network from a server, and preprocessing the reversible electronic document, wherein the preprocessing comprises pre-populating the reversible electronic document with data at the third party. | 31. The software product of claim 30 , further comprising the operations of receiving, at a third party, the reversible electronic document over the network from a server, and preprocessing the reversible electronic document, wherein the preprocessing comprises pre-populating the reversible electronic document with data at the third party. 33. The software product of claim 31 , wherein sending the reversible electronic document over the network comprises electronically publishing the reversible electronic document. | 0.5 |
7,991,781 | 13 | 15 | 13. A computer readable storage medium containing program code that when processed by a computer causes the following method to be performed: setting a first text encoding as a default text encoding because said first text encoding corresponds to a first language that said computing system's display is configured to render information in; recording in a storage medium that said first text encoding has been used; receiving a first user input corresponding to a first filename for a first file storage request, said first filename rendered on said display in said first language; referring to said default text encoding to identify that said first text encoding is used to render text on said display; converting said first filename from said first text encoding to Unicode text encoding to form a first Unicode filename; storing first information identified by said first Unicode filename; setting a second text encoding as said default text encoding because said second text encoding corresponds to a second, different language that said computing system's display is configured to render information in, said first text encoding being different than said second text encoding; recording in said storage medium that said second text encoding has been used; receiving a second filename as part of an information retrieval request; converting said second filename from an encoding identified by said default text encoding's current setting to Unicode to form a second Unicode filename, said default text encoding's current setting being different than said first text encoding and said second text encoding; recognizing that no file exists with said second Unicode filename; referring to said storage medium to identify said first and second text encodings; converting said second filename from said first text encoding to Unicode to form a third Unicode filename; and, searching for a file having said third Unicode filename. | 13. A computer readable storage medium containing program code that when processed by a computer causes the following method to be performed: setting a first text encoding as a default text encoding because said first text encoding corresponds to a first language that said computing system's display is configured to render information in; recording in a storage medium that said first text encoding has been used; receiving a first user input corresponding to a first filename for a first file storage request, said first filename rendered on said display in said first language; referring to said default text encoding to identify that said first text encoding is used to render text on said display; converting said first filename from said first text encoding to Unicode text encoding to form a first Unicode filename; storing first information identified by said first Unicode filename; setting a second text encoding as said default text encoding because said second text encoding corresponds to a second, different language that said computing system's display is configured to render information in, said first text encoding being different than said second text encoding; recording in said storage medium that said second text encoding has been used; receiving a second filename as part of an information retrieval request; converting said second filename from an encoding identified by said default text encoding's current setting to Unicode to form a second Unicode filename, said default text encoding's current setting being different than said first text encoding and said second text encoding; recognizing that no file exists with said second Unicode filename; referring to said storage medium to identify said first and second text encodings; converting said second filename from said first text encoding to Unicode to form a third Unicode filename; and, searching for a file having said third Unicode filename. 15. The computer readable storage medium of claim 13 wherein said first text encoding is Roman text encoding. | 0.924306 |
8,949,874 | 8 | 13 | 8. A system comprising: a memory; and a processing device coupled with the memory to: receive a query corresponding to one of a plurality of query types, the one of the plurality of query types being associated with a subset of a plurality of feature metrics of a plurality of content channels, each of the content channels comprising a plurality of media items; evaluate a content channel of the plurality of content channels based on the subset of feature metrics of the content channel to produce a channel score of the content channel for the query type; assign the channel score of the content channel to the plurality of media items of the content channel; and provide the channel score to position at least one of the plurality of media items of the content channel in a query result of the query. | 8. A system comprising: a memory; and a processing device coupled with the memory to: receive a query corresponding to one of a plurality of query types, the one of the plurality of query types being associated with a subset of a plurality of feature metrics of a plurality of content channels, each of the content channels comprising a plurality of media items; evaluate a content channel of the plurality of content channels based on the subset of feature metrics of the content channel to produce a channel score of the content channel for the query type; assign the channel score of the content channel to the plurality of media items of the content channel; and provide the channel score to position at least one of the plurality of media items of the content channel in a query result of the query. 13. The system of claim 8 , wherein the processing device is further to: determine a plurality of channel scores for the channel, the plurality of channel scores corresponding to the plurality of query types; and assign the plurality of channel scores for the channel to the one or more media items of the channel. | 0.5 |
8,150,842 | 18 | 23 | 18. A computer-readable medium having instructions encoded thereon, which, when executed by a processor, cause the processor to perform operations comprising: receiving a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) reviews scores of the online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be and in response to a query for online content, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. | 18. A computer-readable medium having instructions encoded thereon, which, when executed by a processor, cause the processor to perform operations comprising: receiving a plurality of online content items authored by a plurality of authors for online publication; and for each online content item, determining a reputation score for an author of the online content item, where the reputation score is based at least in part on: (a) reviews scores of the online content items authored by the author, the scores provided by one or more reviewers other than the author; and (b) an authentication score for the author, the authentication score being a function of determinations made to identify that the author is who the author purports to be and in response to a query for online content, generating a set of search results including an online content item from the plurality of online content items; and determining a ranking of the online content item in the set based at least in part on a reputation score of the author. 23. The computer-readable medium of claim 18 , wherein the reputation score is further based on a previous reputation score of the author calculated in relation to one or more different online content items of the author that were previously published. | 0.745968 |
8,650,182 | 1 | 3 | 1. A computer-implemented method for generating a response to a search request comprising: receiving a search request comprising one or more keywords; retrieving, from an index, a set of location indicators, wherein each location indicator of the set of location indicators is stored in association with at least one keyword of the one or more keywords; wherein a location indicator of the set of location indicators includes: a document identifier identifying a particular XML document in a collection of XML documents containing a particular keyword of the one or more keywords; an order key specifying a hierarchical position of a node within the particular XML document that contains the particular keyword; and a path representation representing a path of the node within the particular XML document that contains the particular keyword; and displaying one or more nodes of the particular XML document that contains the particular keyword, wherein the one or more nodes includes the node located at the hierarchical position specified by the order key. | 1. A computer-implemented method for generating a response to a search request comprising: receiving a search request comprising one or more keywords; retrieving, from an index, a set of location indicators, wherein each location indicator of the set of location indicators is stored in association with at least one keyword of the one or more keywords; wherein a location indicator of the set of location indicators includes: a document identifier identifying a particular XML document in a collection of XML documents containing a particular keyword of the one or more keywords; an order key specifying a hierarchical position of a node within the particular XML document that contains the particular keyword; and a path representation representing a path of the node within the particular XML document that contains the particular keyword; and displaying one or more nodes of the particular XML document that contains the particular keyword, wherein the one or more nodes includes the node located at the hierarchical position specified by the order key. 3. The method of claim 1 , wherein: the index is stored as a balanced search tree; the particular keyword is a key into the index; and all location indicators of the set of location indicators included in an index entry are stored together as a single element in the balanced search tree. | 0.656325 |
8,095,870 | 14 | 18 | 14. A non-transitory computer-readable medium storing computer-executable code for generating documents in native application formats, the computer-readable medium comprising: code for receiving a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined application native format, the first document file providing an overall document layout for the data stored in the first document file; code for generating an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first Excel spreadsheet document file for the different data; code for generating an XDTL execution document based on the XDTL template; and code for rendering a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. | 14. A non-transitory computer-readable medium storing computer-executable code for generating documents in native application formats, the computer-readable medium comprising: code for receiving a first document file in a predetermined native application format, data stored in the first document file formatted according to the predetermined application native format, the first document file providing an overall document layout for the data stored in the first document file; code for generating an XDTL template that represents a document template of at least the overall document layout for the data stored in the first document file in response to parsing the first document file according to the predetermined native application format, the XDTL template including one or more tags configured as data placeholders for different data, the one or more tags replicating locations of the data stored in the first Excel spreadsheet document file for the different data; code for generating an XDTL execution document based on the XDTL template; and code for rendering a second document file in the predetermined native application format based on the XDTL document template, data stored in the second document file being different from the data stored in the first document file, the data stored in the second document file formatted according to the predetermined native application format and having the same overall document layout as provided by the first document file for the data stored in the first document file. 18. The computer-readable medium of claim 14 wherein the code for rendering the second document in the native format comprises: code for receiving additional layout information not associated with the overall document layout provided by the first document file for the data stored in the first document file; and code for rendering the second document based on the additional layout information. | 0.524096 |
8,239,366 | 34 | 42 | 34. At least one tangible computer-readable medium encoded with instructions that, when executed by at least one hardware computer processor, perform a method of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. | 34. At least one tangible computer-readable medium encoded with instructions that, when executed by at least one hardware computer processor, perform a method of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. 42. The at least one computer-readable medium of claim 34 , wherein the second language model is one that was trained on content indexed by the second of the plurality of search engines. | 0.886585 |
8,090,722 | 7 | 8 | 7. The non-transitory computer-readable medium of claim 1 , where the method includes providing a signal that identifies a set of documents whose relevance to the query exceeds a threshold. | 7. The non-transitory computer-readable medium of claim 1 , where the method includes providing a signal that identifies a set of documents whose relevance to the query exceeds a threshold. 8. The non-transitory computer-readable medium of claim 7 , where the set of documents may only include documents identified by a document identifier in an index entry. | 0.657143 |
8,713,003 | 28 | 30 | 28. The method of claim 17 , wherein the one or more interaction events comprise at least one of: application installation count, time spent using the application, application content printing, application content saving, application content copying, application content bookmarking, application content address copying, application content number of visits, application content scrolling, application content pointer clicking, application content zooming, application content switching, time spent reading application content, application content highlighting, application content emailing, application content address emailing, or application address emailing. | 28. The method of claim 17 , wherein the one or more interaction events comprise at least one of: application installation count, time spent using the application, application content printing, application content saving, application content copying, application content bookmarking, application content address copying, application content number of visits, application content scrolling, application content pointer clicking, application content zooming, application content switching, time spent reading application content, application content highlighting, application content emailing, application content address emailing, or application address emailing. 30. The method of claim 28 , wherein the one or more interaction events comprise at least one of: levels completed in a gaming application, scenes completed in a gaming application, or checkpoints completed in a gaining application. | 0.654762 |
10,146,776 | 9 | 10 | 9. The computing system of claim 7 , wherein the operations further comprise: identifying, by the computing system, that a second user input selected, from among a third set of search results provided to a computing device responsive to a third query, a particular search result that references the first electronic document; and generating, by the computing system and in response to identifying that the second user input selected the particular search result that references the first electronic document, a second association between the first electronic document and the one or more terms derived from the third query. | 9. The computing system of claim 7 , wherein the operations further comprise: identifying, by the computing system, that a second user input selected, from among a third set of search results provided to a computing device responsive to a third query, a particular search result that references the first electronic document; and generating, by the computing system and in response to identifying that the second user input selected the particular search result that references the first electronic document, a second association between the first electronic document and the one or more terms derived from the third query. 10. The computing system of claim 9 , wherein the operations comprise, after generating the second association between the first electronic document and the one or more terms derived from the third query: receiving a fourth query; determining a relevance of the first electronic document to the fourth query based at least in part on a level of similarity between (i) the one or more terms derived from the third query and associated with the first electronic document and (ii) one or more terms derived from the fourth query; generating a fourth set of search results responsive to the fourth query, including selecting or ranking the first electronic document in the fourth set of search results based on the determined relevance; and transmitting the fourth set of search results. | 0.5 |
7,711,573 | 1 | 12 | 1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 12. The system of claim 1 , wherein to store the resume, the processor is further configured to: store the resume as a public resume, wherein the resume database is accessible by at least one recruiter, and the public resume is accessible by every recruiter. | 0.738866 |
9,075,862 | 1 | 3 | 1. A computer-implemented method, comprising: receiving, at a data processing apparatus, first content authored by a first author; determining, by the data processing apparatus, that the first author has no assigned rating; and in response to determining that the first author has no assigned rating: identifying attributes of the first author; identifying other authors that are not authors of the first content, each other author having one or more attributes in common one or more identified attributes of the first author and not an author of the first content, and wherein at least one of the other authors has at least one attribute not in common with the first author; for each identified attribute of the first author in common with an attribute of one or more other authors, generating a rating for the identified attribute based on ratings that are assigned to the other authors having the attribute, the ratings that are assigned to other authors being based on user feedback; generating an initial content rating for the first content based on the ratings for the identified attributes; and assigning the initial content rating to the first content. | 1. A computer-implemented method, comprising: receiving, at a data processing apparatus, first content authored by a first author; determining, by the data processing apparatus, that the first author has no assigned rating; and in response to determining that the first author has no assigned rating: identifying attributes of the first author; identifying other authors that are not authors of the first content, each other author having one or more attributes in common one or more identified attributes of the first author and not an author of the first content, and wherein at least one of the other authors has at least one attribute not in common with the first author; for each identified attribute of the first author in common with an attribute of one or more other authors, generating a rating for the identified attribute based on ratings that are assigned to the other authors having the attribute, the ratings that are assigned to other authors being based on user feedback; generating an initial content rating for the first content based on the ratings for the identified attributes; and assigning the initial content rating to the first content. 3. The computer-implemented method of claim 1 , further comprising: receiving user feedback based ratings for the first content; and generating a content rating for the first content that is proportional to a combination of the assigned initial content rating and the received user feedback based ratings. | 0.5 |
9,430,738 | 16 | 20 | 16. A computer-implemented social media intelligence system comprising: a. a digital processor performing a computer program comprising executable instructions stored on a memory device; b. the computer program providing a social media intelligence application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; iv. a fourth software module conducting hierarchical clustering based on that distance metric; and vi. a fifth software module outputting a result associated with said hierarchical clustering. | 16. A computer-implemented social media intelligence system comprising: a. a digital processor performing a computer program comprising executable instructions stored on a memory device; b. the computer program providing a social media intelligence application comprising: i. a first software module obtaining real-time social media conversations; ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale; iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm; iv. a fourth software module conducting hierarchical clustering based on that distance metric; and vi. a fifth software module outputting a result associated with said hierarchical clustering. 20. The system of claim 16 , wherein the knowledge base further comprises words or phrases not expressing sentiment. | 0.66474 |
7,516,468 | 7 | 9 | 7. A method for receiving interactive television information in a receiver and providing interactive television to a user, comprising: receiving a stream comprising a script and a compiled business data in binary form, wherein said business data comprises descriptions of products and wherein said business data is compiled for use by a set-top box; processing said compiled business data in binary form according to said script; and processing requests within the script, independent from a further user interaction, to map an item of the business data into a position within an authored page template, wherein a video presentation of the business data is presented to the user. | 7. A method for receiving interactive television information in a receiver and providing interactive television to a user, comprising: receiving a stream comprising a script and a compiled business data in binary form, wherein said business data comprises descriptions of products and wherein said business data is compiled for use by a set-top box; processing said compiled business data in binary form according to said script; and processing requests within the script, independent from a further user interaction, to map an item of the business data into a position within an authored page template, wherein a video presentation of the business data is presented to the user. 9. The method of claim 7 further including: processing a request within the script to construct a message containing business data, based on a user action; and transmitting the selection to a transaction server, the transaction server for implementing a transaction in accordance with the user action. | 0.5 |
4,819,271 | 16 | 17 | 16. Apparatus for constructing a Markov model word baseform for a word in a vocabulary from multiple utterances thereof comprising: acoustic processor means for generating a string of labels in response to an uttered speech input; means, coupled to receive label string outputs from the acoustic processor means, for storing labels for multiple strings of labels generated by the acoustic processor in response to multiple utterances of a subject word; means for retrieving a prototype string from among the stored strings for the subject word; means, coupled to receive as input a retrieved prototype string, for forming a singleton word baseform for the retrieved prototype string; means, coupled to retrieve label strings from the label string storing means and coupled to the singleton baseform forming means, for aligning the labels in strings other than the selected prototype string against the singleton baseform, each string being divided into successive substrings respectively aligned against successive fenemic Markov models in the singleton baseform; and correlator means, coupled to receive input alignment data from the aligning means, for grouping the ith substrings of the multiple strings; each group of ith substrings corresponding to a common word segment. | 16. Apparatus for constructing a Markov model word baseform for a word in a vocabulary from multiple utterances thereof comprising: acoustic processor means for generating a string of labels in response to an uttered speech input; means, coupled to receive label string outputs from the acoustic processor means, for storing labels for multiple strings of labels generated by the acoustic processor in response to multiple utterances of a subject word; means for retrieving a prototype string from among the stored strings for the subject word; means, coupled to receive as input a retrieved prototype string, for forming a singleton word baseform for the retrieved prototype string; means, coupled to retrieve label strings from the label string storing means and coupled to the singleton baseform forming means, for aligning the labels in strings other than the selected prototype string against the singleton baseform, each string being divided into successive substrings respectively aligned against successive fenemic Markov models in the singleton baseform; and correlator means, coupled to receive input alignment data from the aligning means, for grouping the ith substrings of the multiple strings; each group of ith substrings corresponding to a common word segment. 17. Apparatus as in claim 16 further comprising: model constructor means for determining the fenemic Markov model or fenemic Markov model sequence having the highest joint probability of producing the labels in a group of substrings formed by the correlator means. | 0.5 |
7,693,719 | 23 | 26 | 23. A system for synthesizing speech from a text comprising: a server in communication via a network, with a browser on a client computer of a user; a text-to-speech (TTS) application, in communication with the client computer of the user, operable to generate a voice font based on speech waveforms, wherein the user creates a personalized speech audio data on the client computer, and the personalized speech audio data is encoded into one or more waveforms at the client computer, wherein the waveforms are transmitted from the client computer remotely accessing a voice font generator of the TTS application via the network, wherein generating the voice font after the waveforms are transmitted comprises: associating the waveforms transmitted to the voice font generator with corresponding basic phonetic units, wherein the plurality of predetermined utterances is parsed into one or more basic phonetic units comprising at least one of phonemes, diphones, semi-syllables, or syllables, identifying the one or more basic phonetic units based on corresponding characteristics of a basic phonetic unit, and associating the one or more basic phonetic units with corresponding segments of the waveforms in a data structure, wherein the data structure comprises a table having one column correspond to one or more identifiers of the one or more basic phonetic units, and having another column correspond to the segments of the waveforms, wherein each identifier corresponds to one or more segments of the waveforms in the table; a text to speech engine to concatenate a personalized voice font into a chain according to an order of the basic phonetic units in the text, the basic phonetic units are parsed into phonemes, diphones, semi-syllables, or syllables and identified by an associated diphone, a triphone, a semi-syllable, or a syllable that is associated with a corresponding segment in a waveform; the text to speech engine to download concatenated speech segments to the client computer; and a TTS web service having a user interface, wherein the user interface is a function selector, a voice font selector and other services configured to allow a user to remotely perform text-to-speech through the network. | 23. A system for synthesizing speech from a text comprising: a server in communication via a network, with a browser on a client computer of a user; a text-to-speech (TTS) application, in communication with the client computer of the user, operable to generate a voice font based on speech waveforms, wherein the user creates a personalized speech audio data on the client computer, and the personalized speech audio data is encoded into one or more waveforms at the client computer, wherein the waveforms are transmitted from the client computer remotely accessing a voice font generator of the TTS application via the network, wherein generating the voice font after the waveforms are transmitted comprises: associating the waveforms transmitted to the voice font generator with corresponding basic phonetic units, wherein the plurality of predetermined utterances is parsed into one or more basic phonetic units comprising at least one of phonemes, diphones, semi-syllables, or syllables, identifying the one or more basic phonetic units based on corresponding characteristics of a basic phonetic unit, and associating the one or more basic phonetic units with corresponding segments of the waveforms in a data structure, wherein the data structure comprises a table having one column correspond to one or more identifiers of the one or more basic phonetic units, and having another column correspond to the segments of the waveforms, wherein each identifier corresponds to one or more segments of the waveforms in the table; a text to speech engine to concatenate a personalized voice font into a chain according to an order of the basic phonetic units in the text, the basic phonetic units are parsed into phonemes, diphones, semi-syllables, or syllables and identified by an associated diphone, a triphone, a semi-syllable, or a syllable that is associated with a corresponding segment in a waveform; the text to speech engine to download concatenated speech segments to the client computer; and a TTS web service having a user interface, wherein the user interface is a function selector, a voice font selector and other services configured to allow a user to remotely perform text-to-speech through the network. 26. A system as recited in claim 23 wherein the TTS application comprises one or more personalized voice fonts that can be selected for use by the user of the client computer. | 0.622845 |
9,171,079 | 1 | 6 | 1. A method comprising, by one or more computer systems: building a profile for the end user based on one or more learned preferences of the end user; receiving a query, from the end user, for particular sensor data among a plurality of sensor data from a plurality of sensors, the received query comprising a unique resource locator that uniquely identifies a particular one of the plurality of sensors, the plurality of sensor data being indexed according to a multi-dimensional array, one or more first ones of the dimensions comprising time and one or more second ones of the dimensions comprising one or more pre-determined sensor-data attributes; translating the query to correspond to the indexing of the plurality of sensor data, the translated query comprising one or more values for one or more of the dimensions of the multi-dimensional array; appending, based on the unique resource locator that identifies the particular one of the plurality of sensors in the query received from the end user, the unique resource locator to the translated query, the unique resource locator specifying the particular one of the plurality of sensors; communicating the translated query to search among the plurality of sensor data according to the indexing of the plurality of sensor data to identify sensor data associated with the particular one of the plurality of sensors; receiving a list of matching sensor data; tailoring the list of matching sensor data based on the user profile of the end user to provide a representation expected by the end user; receiving query results comprising meta data associated with a subset of the plurality of sensors; selecting a particular one of the subset of sensors; and requesting the data available at the particular one of the subset of sensors. | 1. A method comprising, by one or more computer systems: building a profile for the end user based on one or more learned preferences of the end user; receiving a query, from the end user, for particular sensor data among a plurality of sensor data from a plurality of sensors, the received query comprising a unique resource locator that uniquely identifies a particular one of the plurality of sensors, the plurality of sensor data being indexed according to a multi-dimensional array, one or more first ones of the dimensions comprising time and one or more second ones of the dimensions comprising one or more pre-determined sensor-data attributes; translating the query to correspond to the indexing of the plurality of sensor data, the translated query comprising one or more values for one or more of the dimensions of the multi-dimensional array; appending, based on the unique resource locator that identifies the particular one of the plurality of sensors in the query received from the end user, the unique resource locator to the translated query, the unique resource locator specifying the particular one of the plurality of sensors; communicating the translated query to search among the plurality of sensor data according to the indexing of the plurality of sensor data to identify sensor data associated with the particular one of the plurality of sensors; receiving a list of matching sensor data; tailoring the list of matching sensor data based on the user profile of the end user to provide a representation expected by the end user; receiving query results comprising meta data associated with a subset of the plurality of sensors; selecting a particular one of the subset of sensors; and requesting the data available at the particular one of the subset of sensors. 6. The method of claim 1 , further comprising communicating the query directly to the specific sensor. | 0.818505 |
8,185,372 | 1 | 12 | 1. An example-based translation apparatus comprising: a storage unit that stores source examples of a source language and target examples of a target language in a many-to-many relationship meaning that each of the source examples is associated with one or more of the target examples having the same or similar meaning, and each of the target examples is associated with one or more of the source examples having the same or similar meaning; an input receiving unit that receives an input of a sentence in the source language; a source example search unit that searches the storage unit to identify one or more of the source examples based on the sentence in the source language; a target example search unit that, for each of the first source examples, searches the storage unit to identify one or more of the target examples that have similar meanings as the identified first source example: a determining unit that determines whether there are a plurality of identified target examples; a first acquisition unit that, for each of the identified target examples, acquires from the storage unit one or more second source examples that correspond to the identified target example, when there are the plurality of identified target examples; a second acquisition unit that, for each of the second source examples, acquires from the storage unit one or more target examples that correspond to the second source example; a choice generating unit that chooses one of the second source examples that is associated with the fewest number of the acquired target examples; and an output control unit that outputs the chosen second source example. | 1. An example-based translation apparatus comprising: a storage unit that stores source examples of a source language and target examples of a target language in a many-to-many relationship meaning that each of the source examples is associated with one or more of the target examples having the same or similar meaning, and each of the target examples is associated with one or more of the source examples having the same or similar meaning; an input receiving unit that receives an input of a sentence in the source language; a source example search unit that searches the storage unit to identify one or more of the source examples based on the sentence in the source language; a target example search unit that, for each of the first source examples, searches the storage unit to identify one or more of the target examples that have similar meanings as the identified first source example: a determining unit that determines whether there are a plurality of identified target examples; a first acquisition unit that, for each of the identified target examples, acquires from the storage unit one or more second source examples that correspond to the identified target example, when there are the plurality of identified target examples; a second acquisition unit that, for each of the second source examples, acquires from the storage unit one or more target examples that correspond to the second source example; a choice generating unit that chooses one of the second source examples that is associated with the fewest number of the acquired target examples; and an output control unit that outputs the chosen second source example. 12. The example-based translation apparatus according to claim 1 , wherein when there are a plurality of the source examples that have the same meaning, the storage unit sets the source examples having the same meaning as a source example group, and collectively stores the source example group in association with the target examples, when there are a plurality of the target examples that have the same meaning, the storage unit sets the target examples having the same meaning as a target example group, and collectively stores the target example group in association with the source examples, the source example search unit searches the storage unit to identify one of the first source examples or the first source example group; the target example search unit searches to identify the target examples and the target example group corresponding to the first source example or the first source example group, the determining unit determines whether there is more than one identified target example or identified target example group, when the determining unit determines that there is more than one identified target example or target example group, the first acquisition unit acquires a second source example or a second source example group associated with each of the identified target examples or the identified target example groups, the second acquisition unit acquires a target example or a target example group corresponding to the second source example or the second source example group, and the choice generating unit chooses the second source example or the second source example group associated with the fewest number of the acquired target examples. | 0.5 |
9,645,817 | 7 | 8 | 7. The method of claim 5 , further comprising filtering the context group by a particular attribute. | 7. The method of claim 5 , further comprising filtering the context group by a particular attribute. 8. The method of claim 7 , wherein the particular attribute is a geographic location, team membership, or a level of seniority. | 0.5 |
8,914,738 | 4 | 5 | 4. The method of claim 1 , wherein receiving includes receiving a plurality of first annotations associated with a UI element. | 4. The method of claim 1 , wherein receiving includes receiving a plurality of first annotations associated with a UI element. 5. The method of claim 4 , further comprising displaying annotations of the plurality of annotations in rank order based on respective counts associated with each annotation. | 0.5 |
10,133,755 | 18 | 25 | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. 25. The method of claim 18 , further comprising: after normalizing the legal data, receiving input from an administrator to input supplemental legal data, modify the legal data, or both. | 0.600858 |
10,122,732 | 10 | 11 | 10. A method, comprising: managing, by an identity manager, a plurality of user identities of a user, and select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from an environment; evaluating, by a privacy engine, at least one privacy preference of the one or more selected user identities against a privacy policy obtained from the environment; and generating, by a policy editor, a reduced version of a privacy policy from the environment and supply the reduced version of the privacy policy as the privacy policy used by the privacy engine evaluation. | 10. A method, comprising: managing, by an identity manager, a plurality of user identities of a user, and select one or more of the user identities of the user that satisfy a set of identity requirements of a security policy obtained from an environment; evaluating, by a privacy engine, at least one privacy preference of the one or more selected user identities against a privacy policy obtained from the environment; and generating, by a policy editor, a reduced version of a privacy policy from the environment and supply the reduced version of the privacy policy as the privacy policy used by the privacy engine evaluation. 11. The method of claim 10 , further comprises: receiving from the environment the security policy having requirements; processing the security policy to determine whether any of the user identities satisfies the security policy requirements; and the evaluating further includes using the privacy preference of any user identity determined to satisfy the security policy requirements. | 0.5 |
8,024,415 | 7 | 11 | 7. The system of claim 1 , wherein the classifier is provided with at least one of explicit and implicit training. | 7. The system of claim 1 , wherein the classifier is provided with at least one of explicit and implicit training. 11. The system of claim 7 , further comprises at least one of a training folder, a semantic label, a date, a time, an organizational chart, a sender-recipient relationship, a length of message, and a language tense to provide the at least one of explicit and implicit training. | 0.5 |
7,912,724 | 19 | 20 | 19. A method, comprising: performing by a computer: receiving an indication of requested content; analyzing the requested content, wherein said analyzing is based on comparing at least one sequence of one or more phonemes present within audio data of the requested content to a limited number of previously identified phoneme sequences, wherein each of the limited number of previously identified phoneme sequences is associated with one or more of a given collection of advertising files; and matching one of the given collection of advertising files to the requested content, wherein said matching is based on said analyzing. | 19. A method, comprising: performing by a computer: receiving an indication of requested content; analyzing the requested content, wherein said analyzing is based on comparing at least one sequence of one or more phonemes present within audio data of the requested content to a limited number of previously identified phoneme sequences, wherein each of the limited number of previously identified phoneme sequences is associated with one or more of a given collection of advertising files; and matching one of the given collection of advertising files to the requested content, wherein said matching is based on said analyzing. 20. The method of claim 19 , wherein the limited number of previously identified phoneme sequences is associated with a limited number of corresponding product categories. | 0.5 |
7,852,240 | 15 | 16 | 15. The communication system according to claim 14 , a) wherein said processing unit of the first computer is further configured to modify said table of varying length representations based upon said identifying value; and, b) wherein the processing unit of the second computer is further configured to modify said table of varying length representations based upon said identifying value. | 15. The communication system according to claim 14 , a) wherein said processing unit of the first computer is further configured to modify said table of varying length representations based upon said identifying value; and, b) wherein the processing unit of the second computer is further configured to modify said table of varying length representations based upon said identifying value. 16. The communication system according to claim 15 , wherein the first computer further includes a transmitting unit configured to communicate said encrypted message to the second computer. | 0.5 |
9,064,211 | 1 | 5 | 1. A method for emulating human cognition in electronic form, comprising: receiving information in a form of a textual or voice input in a natural language; parsing the received input into pre-determined semantic phrases based on a stored set of language rules for the natural language; defining a plurality of concept neurons that each represent a unique concept and stored in a database of concept neurons, each of the concept neurons having relational associations with other of the concept neurons through unique weighting factors, the relational associations defining the concept associated with the concept neuron, certain of the concept neurons associated with phrases representing idioms that are associated with a unique idiom concept; determining if the parsed semantic phrases define one of the unique idiom concepts associated with phrases representing that idiom and their associated concept neurons and, if so: then creating a plurality of weighted relational associations to other concept neurons stored in the database that represent in the natural language a body of concepts in an ordered list of the weighted relational associations for each item in the ordered list, the created weighted relational associations operable to create a weighted relationship as the related associations to the other concept neurons from the determined defined one of the associated concept neurons and associating the ordered list with the determined defined one of the associated concept neurons associated with one or more of the concepts associated with the parsed semantic phrases determined to define the concept; and determining if the parsed phrases determined to define the unique idiom concept associated with the phrase constitute a query and, if so, then using the weighted relational associations to make a decision to the query. | 1. A method for emulating human cognition in electronic form, comprising: receiving information in a form of a textual or voice input in a natural language; parsing the received input into pre-determined semantic phrases based on a stored set of language rules for the natural language; defining a plurality of concept neurons that each represent a unique concept and stored in a database of concept neurons, each of the concept neurons having relational associations with other of the concept neurons through unique weighting factors, the relational associations defining the concept associated with the concept neuron, certain of the concept neurons associated with phrases representing idioms that are associated with a unique idiom concept; determining if the parsed semantic phrases define one of the unique idiom concepts associated with phrases representing that idiom and their associated concept neurons and, if so: then creating a plurality of weighted relational associations to other concept neurons stored in the database that represent in the natural language a body of concepts in an ordered list of the weighted relational associations for each item in the ordered list, the created weighted relational associations operable to create a weighted relationship as the related associations to the other concept neurons from the determined defined one of the associated concept neurons and associating the ordered list with the determined defined one of the associated concept neurons associated with one or more of the concepts associated with the parsed semantic phrases determined to define the concept; and determining if the parsed phrases determined to define the unique idiom concept associated with the phrase constitute a query and, if so, then using the weighted relational associations to make a decision to the query. 5. The method of claim 1 , wherein the step of if the parsed phrases define a concept comprises determining if the parsed phrase includes a triad of a speaker, the person/object spoken to, and the person, object or subject spoken of. | 0.5 |
9,026,428 | 1 | 3 | 1. A method for data input on a touchscreen of a mobile device, the method comprising: receiving a first user input, wherein the first user input is handwritten input received on the touchscreen of the mobile device; determining a first recognized sequence based on the first user input; wherein the first recognized sequence is a best match of the first user input; writing the first recognized sequence to a memory storage buffer of the mobile device; generating a first candidate sequence, wherein the first candidate sequence is a best match of one or more recognized sequences; presenting the first candidate sequence to the user, wherein the presenting includes displaying the first candidate sequence to the user and allowing the user to edit the first candidate sequence; identifying at least a first sequence portion of the first candidate sequence wherein the identifying is at least partially based on one or more rules or dictionaries of words accessible to the mobile device; removing the first sequence portion from the memory storage buffer, wherein the removing is performed in the absence of receiving user input editing the first candidate sequence, representing a space character, or selecting a word; and sending the first sequence portion to an application running on the mobile device. | 1. A method for data input on a touchscreen of a mobile device, the method comprising: receiving a first user input, wherein the first user input is handwritten input received on the touchscreen of the mobile device; determining a first recognized sequence based on the first user input; wherein the first recognized sequence is a best match of the first user input; writing the first recognized sequence to a memory storage buffer of the mobile device; generating a first candidate sequence, wherein the first candidate sequence is a best match of one or more recognized sequences; presenting the first candidate sequence to the user, wherein the presenting includes displaying the first candidate sequence to the user and allowing the user to edit the first candidate sequence; identifying at least a first sequence portion of the first candidate sequence wherein the identifying is at least partially based on one or more rules or dictionaries of words accessible to the mobile device; removing the first sequence portion from the memory storage buffer, wherein the removing is performed in the absence of receiving user input editing the first candidate sequence, representing a space character, or selecting a word; and sending the first sequence portion to an application running on the mobile device. 3. The method of claim 1 , further comprising: determining at least a second candidate sequence based on the first user input; and presenting at least the second candidate sequence to the user. | 0.703077 |
8,607,138 | 12 | 21 | 12. A method of presenting reports over a network, comprising: receiving, at a network server that includes a first physical computing device, a request for a report from a user system through an instance of a web browser, wherein the network server that returns control of the instance of the web browser to enable a user to use the same instance of the web browser to perform one or more other requests through the instance of the web browser while the report request is being processed; processing the report at an on-line analytical processing (OLAP) system that includes a second physical computing device and that is communicatively connected to the network server; storing the report processed by the OLAP system in a server cache that includes a computer usable storage medium, wherein the server cache stores the report processed by the OLAP system in the computer usable storage medium; formatting the report at a server system communicatively connected to the server cache and the network server, wherein the server system includes a third physical computing device that formats the report for presentation at the instance of the web browser of the user system using a spreadsheet application displayed within the instance of the web browser; and transmitting, by the network server, the formatted report within a page over the network to the instance of the web browser of the user system through which the request was received, and wherein the spreadsheet application displayed within the instance of the web browser presents the report at the user system. | 12. A method of presenting reports over a network, comprising: receiving, at a network server that includes a first physical computing device, a request for a report from a user system through an instance of a web browser, wherein the network server that returns control of the instance of the web browser to enable a user to use the same instance of the web browser to perform one or more other requests through the instance of the web browser while the report request is being processed; processing the report at an on-line analytical processing (OLAP) system that includes a second physical computing device and that is communicatively connected to the network server; storing the report processed by the OLAP system in a server cache that includes a computer usable storage medium, wherein the server cache stores the report processed by the OLAP system in the computer usable storage medium; formatting the report at a server system communicatively connected to the server cache and the network server, wherein the server system includes a third physical computing device that formats the report for presentation at the instance of the web browser of the user system using a spreadsheet application displayed within the instance of the web browser; and transmitting, by the network server, the formatted report within a page over the network to the instance of the web browser of the user system through which the request was received, and wherein the spreadsheet application displayed within the instance of the web browser presents the report at the user system. 21. The method of claim 12 , further comprising: dynamically refreshing, by the spreadsheet application, the report presented at the instance of the web browser. | 0.833333 |
7,480,408 | 8 | 11 | 8. An apparatus for establishing a degraded dictionary, comprising: degraded pattern generating means for generating a plurality of degraded patterns from an original character image, based on a plurality of degradation parameters; degraded dictionary generating means for generating a plurality of degraded dictionaries based on the plurality of degradation parameters, respectively; and dictionary matching means for selecting one of the plurality of dictionaries which matches the degradation level of a test sample set best, as the final degraded dictionary. | 8. An apparatus for establishing a degraded dictionary, comprising: degraded pattern generating means for generating a plurality of degraded patterns from an original character image, based on a plurality of degradation parameters; degraded dictionary generating means for generating a plurality of degraded dictionaries based on the plurality of degradation parameters, respectively; and dictionary matching means for selecting one of the plurality of dictionaries which matches the degradation level of a test sample set best, as the final degraded dictionary. 11. The apparatus of claim 8 , further comprising: feature extracting means for extracting features from an input image pattern, wherein the degraded dictionary generating means generates the plurality of degraded dictionaries from the features extracted by the feature extracting means. | 0.764754 |
6,163,785 | 7 | 9 | 7. A computer-based system for translating source language input text to a foreign language comprising: a text editor adapted to accept interactively from an author the input text written in a source language; a language editor, which is an extension of said text editor, which interacts with said author to produce from said input text an unambiguous constrained source text by interactively enforcing vocabulary and grammatical constraints against a constrained source language; a machine translation system, responsive to said language editor, which is configured to translate said unambiguous constrained source text into the foreign language; and a domain model, which communicates with said language editor and said machine translation system, and which provides predetermined domain knowledge and linguistic semantic knowledge about lexical units and of their combinations, so as to aid in producing said unambiguous constrained source text and in said translation to the foreign language, wherein said domain model is a tripartite domain model, said tripartite domain model comprising, a kernel which contains lexical information that is required by said language editor and said machine translation system, wherein said lexical information includes lexical items within said constrained source language along with associated semantic concepts, parts of speech, and morphological information, a language editor domain model which contains information that is required only by said language editor, wherein said information includes at least one of a subset of synonyms for items not within said constrained source language, a dictionary definitions of said lexical items, and a set of examples of using said lexical items, and a machine translation domain model which contains information which is required by only said machine translation system, said machine translation domain model includes a hierarchy of concepts used for unambiguous mapping and semantic verification in translation. | 7. A computer-based system for translating source language input text to a foreign language comprising: a text editor adapted to accept interactively from an author the input text written in a source language; a language editor, which is an extension of said text editor, which interacts with said author to produce from said input text an unambiguous constrained source text by interactively enforcing vocabulary and grammatical constraints against a constrained source language; a machine translation system, responsive to said language editor, which is configured to translate said unambiguous constrained source text into the foreign language; and a domain model, which communicates with said language editor and said machine translation system, and which provides predetermined domain knowledge and linguistic semantic knowledge about lexical units and of their combinations, so as to aid in producing said unambiguous constrained source text and in said translation to the foreign language, wherein said domain model is a tripartite domain model, said tripartite domain model comprising, a kernel which contains lexical information that is required by said language editor and said machine translation system, wherein said lexical information includes lexical items within said constrained source language along with associated semantic concepts, parts of speech, and morphological information, a language editor domain model which contains information that is required only by said language editor, wherein said information includes at least one of a subset of synonyms for items not within said constrained source language, a dictionary definitions of said lexical items, and a set of examples of using said lexical items, and a machine translation domain model which contains information which is required by only said machine translation system, said machine translation domain model includes a hierarchy of concepts used for unambiguous mapping and semantic verification in translation. 9. The system of claim 7, wherein said machine translation system operates in a translation server environment which allows multiple authors to use the system. | 0.680723 |
8,793,332 | 19 | 20 | 19. The computer-readable medium of claim 18 , the operations further comprising identifying the user of the second device using content of the digital file, the nametag, and the identifiers. | 19. The computer-readable medium of claim 18 , the operations further comprising identifying the user of the second device using content of the digital file, the nametag, and the identifiers. 20. The computer-readable medium of claim 19 , wherein identifying the user further comprises applying pattern recognition techniques to the content. | 0.5 |
7,861,161 | 6 | 13 | 6. A computer-implemented method of creating a report to be executed on a reporting system the method comprising the steps of: selecting a template with one or more template properties; selecting a filter with one or more filter properties; and specifying one or more of the template or filter properties with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report and separate from the one or more templates or filters such that the prompt object may be used more than once in a single report or may be used in more than one report. | 6. A computer-implemented method of creating a report to be executed on a reporting system the method comprising the steps of: selecting a template with one or more template properties; selecting a filter with one or more filter properties; and specifying one or more of the template or filter properties with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report and separate from the one or more templates or filters such that the prompt object may be used more than once in a single report or may be used in more than one report. 13. The method of claim 6 wherein the template comprises a set of templates properties and the filter comprises a set of filter properties and wherein every template and filter property may be specified as a prompt object. | 0.626263 |
9,269,072 | 30 | 32 | 30. An article of manufacture comprising computer-readable instructions thereon for facilitating navigation of previously presented screen data in an ongoing online meeting, the article of manufacture comprising: instructions to store, in computer memory, screen data representing a previously presented portion of an ongoing online meeting; instructions to capture, in response to a trigger event, a screenshot of the screen data for the ongoing online meeting; instructions to cause the display, on a viewer computing device while the ongoing online meeting is still ongoing, of an image thumbnail generated from the screenshot, the image thumbnail facilitating navigation, on the viewer computing device, of the previously presented portion of the ongoing online meeting; instructions to receive, at the viewer computing device while the ongoing online meeting is still ongoing, a selection of the image thumbnail; and instructions to cause the display, in response to the selection of the image thumbnail, on the viewer computing device, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to the screenshot, wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data; wherein the trigger event comprises a size of an accumulative bounding box encapsulating changes to the stored screen data increasing past a threshold. | 30. An article of manufacture comprising computer-readable instructions thereon for facilitating navigation of previously presented screen data in an ongoing online meeting, the article of manufacture comprising: instructions to store, in computer memory, screen data representing a previously presented portion of an ongoing online meeting; instructions to capture, in response to a trigger event, a screenshot of the screen data for the ongoing online meeting; instructions to cause the display, on a viewer computing device while the ongoing online meeting is still ongoing, of an image thumbnail generated from the screenshot, the image thumbnail facilitating navigation, on the viewer computing device, of the previously presented portion of the ongoing online meeting; instructions to receive, at the viewer computing device while the ongoing online meeting is still ongoing, a selection of the image thumbnail; and instructions to cause the display, in response to the selection of the image thumbnail, on the viewer computing device, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to the screenshot, wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data; wherein the trigger event comprises a size of an accumulative bounding box encapsulating changes to the stored screen data increasing past a threshold. 32. The article of manufacture of claim 30 , further comprising instructions to transmit the image thumbnail to a plurality of viewer computing devices. | 0.712121 |
9,122,744 | 1 | 9 | 1. A method comprising: receiving from a client device and displaying on the client device a user inquiry associated with a user, the user inquiry having a linguistic pattern including a verb; generating a follow up question based on the user inquiry; displaying on the client device the follow up question; receiving from the client device and displaying on the client device a follow up answer from the user; determining a task to be performed at least in part by an intelligent assistant based at least in part on the follow up answer from the user, the task including at least one of buying an item or service, selling an item or service, publishing, sending a message, offering, comparing, making, automating, calling, setting, learning, saving, scheduling, subscribing, posting, starting, stopping, modifying, alerting, booking, or summarizing; causing the task to be performed at least in part by the intelligent assistant; and generating and displaying on the client device a response regarding the task. | 1. A method comprising: receiving from a client device and displaying on the client device a user inquiry associated with a user, the user inquiry having a linguistic pattern including a verb; generating a follow up question based on the user inquiry; displaying on the client device the follow up question; receiving from the client device and displaying on the client device a follow up answer from the user; determining a task to be performed at least in part by an intelligent assistant based at least in part on the follow up answer from the user, the task including at least one of buying an item or service, selling an item or service, publishing, sending a message, offering, comparing, making, automating, calling, setting, learning, saving, scheduling, subscribing, posting, starting, stopping, modifying, alerting, booking, or summarizing; causing the task to be performed at least in part by the intelligent assistant; and generating and displaying on the client device a response regarding the task. 9. The method of claim 1 , further comprising: generating and displaying a result based on the user inquiry and the follow up answer. | 0.836609 |
10,073,928 | 7 | 9 | 7. A device for analysis of shape optimization, for optimizing a part of a structural body model having a movable portion, by combining a multi-body dynamics analysis and an optimization analysis and using two-dimensional elements or three-dimensional elements, the device comprising a display device and a computer with a central processing unit and memory that: sets, as a design space, a portion to be optimized in the movable portion; generates, in the set design space, an optimization block model formed of three-dimensional elements and is subjected to analysis processing of optimization; connects the generated optimization block model with the structural body model including the movable portion; sets a material property for the optimization block model; sets an optimization analysis condition to determine an optimum shape of the optimization block model; sets a multi-body dynamics analysis condition including a centrifugal force, a reaction force and an inertial force to perform multi-body dynamics analysis on the structural body model including the movable portion with which the optimization block model has been connected; executes, based on the set multi-body dynamics analysis condition, the multi-body dynamics analysis on the structural body model including the movable portion incorporating the optimization block model; executes, based on the set optimization analysis condition, the optimization analysis; and finds the optimum shape of the optimization block model, and utilizes the analysis of shape optimization for configuring optimization of the movable portion of the structural body configured of a thin sheet; wherein the computer generates the optimization block model by: setting nodes in a portion connected with the two-dimensional elements or three-dimensional elements forming the structural body model; and stacking the three-dimensional elements along a plane including the nodes set in the connected portion, and the display device displays the structural body model including the moveable portion based on the optimum shape. | 7. A device for analysis of shape optimization, for optimizing a part of a structural body model having a movable portion, by combining a multi-body dynamics analysis and an optimization analysis and using two-dimensional elements or three-dimensional elements, the device comprising a display device and a computer with a central processing unit and memory that: sets, as a design space, a portion to be optimized in the movable portion; generates, in the set design space, an optimization block model formed of three-dimensional elements and is subjected to analysis processing of optimization; connects the generated optimization block model with the structural body model including the movable portion; sets a material property for the optimization block model; sets an optimization analysis condition to determine an optimum shape of the optimization block model; sets a multi-body dynamics analysis condition including a centrifugal force, a reaction force and an inertial force to perform multi-body dynamics analysis on the structural body model including the movable portion with which the optimization block model has been connected; executes, based on the set multi-body dynamics analysis condition, the multi-body dynamics analysis on the structural body model including the movable portion incorporating the optimization block model; executes, based on the set optimization analysis condition, the optimization analysis; and finds the optimum shape of the optimization block model, and utilizes the analysis of shape optimization for configuring optimization of the movable portion of the structural body configured of a thin sheet; wherein the computer generates the optimization block model by: setting nodes in a portion connected with the two-dimensional elements or three-dimensional elements forming the structural body model; and stacking the three-dimensional elements along a plane including the nodes set in the connected portion, and the display device displays the structural body model including the moveable portion based on the optimum shape. 9. The device for analysis of shape optimization according to claim 7 , wherein, at a time a part where the optimization block model has been connected in the structural body model is formed of two-dimensional elements, the computer sets a Young's modulus in the three-dimensional elements of the optimization block model lower than a Young's modulus in the two-dimensional elements. | 0.5 |
7,996,416 | 12 | 13 | 12. The machine-readable storage medium of claim 11 , wherein the query analysis is configured to translate the first SQL query statement to a format compatible with the relational database. | 12. The machine-readable storage medium of claim 11 , wherein the query analysis is configured to translate the first SQL query statement to a format compatible with the relational database. 13. The machine-readable storage medium of claim 12 , wherein the first SQL query statement is translated by a query translator implemented using ANTLR (Another Tool for Language Recognition) compatible techniques. | 0.5 |
9,959,886 | 11 | 14 | 11. The method of claim 1 , wherein the plurality of predetermined candidate pitches are included in a frequency range associated with the voiced sounds. | 11. The method of claim 1 , wherein the plurality of predetermined candidate pitches are included in a frequency range associated with the voiced sounds. 14. The method of claim 11 , wherein one of the plurality of predetermined candidate pitches is selected for each of a plurality of temporal frames using a corresponding plurality of voice activity indicator values for each temporal frame. | 0.819486 |
8,595,621 | 17 | 21 | 17. A system for truncating character strings in a computing environment, comprising: a hardware processor; and a user interface device that uses the hardware processor for receiving a list including plural character strings, and truncating one or more of the character strings for generating a display list of unique character strings based on determining a truncation location within each string by: for each character string, comparing the string and corresponding Uniform Resource Identifier (URI), if the string is different from the URI, then truncating the beginning of the string, otherwise if the string matches the URI, then truncating the end of the string; wherein the user interface device uses the hardware processor to display the character strings of the display list in context with each other on a user interface. | 17. A system for truncating character strings in a computing environment, comprising: a hardware processor; and a user interface device that uses the hardware processor for receiving a list including plural character strings, and truncating one or more of the character strings for generating a display list of unique character strings based on determining a truncation location within each string by: for each character string, comparing the string and corresponding Uniform Resource Identifier (URI), if the string is different from the URI, then truncating the beginning of the string, otherwise if the string matches the URI, then truncating the end of the string; wherein the user interface device uses the hardware processor to display the character strings of the display list in context with each other on a user interface. 21. The system of claim 17 , wherein the computing environment comprises a service oriented architecture (SOA) computing environment including a service registry of character strings. | 0.894948 |
5,579,466 | 27 | 30 | 27. A method in a computer system for implementing a rich text edit field in a dialog window, the computer system having an application program having code for inserting and displaying data in document structures, the method comprising the computer-implemented steps of: creating a dialog window; allocating space in the dialog window for the rich text edit field; allocating a document structure for storing data that is placed in the rich text edit field; associating the allocated document structure with the rich text edit field; initializing the allocated document structure according to initial format characteristics; displaying the dialog window with the rich text edit field; in response to receiving user input of data for the rich text edit field, invoking the code for inserting and displaying data; and under control of the invoked code for inserting and displaying data, inserting the received data in the allocated document structure associated with the rich text edit field, such that the received data is displayed in the rich text edit field according to the initial format characteristics. | 27. A method in a computer system for implementing a rich text edit field in a dialog window, the computer system having an application program having code for inserting and displaying data in document structures, the method comprising the computer-implemented steps of: creating a dialog window; allocating space in the dialog window for the rich text edit field; allocating a document structure for storing data that is placed in the rich text edit field; associating the allocated document structure with the rich text edit field; initializing the allocated document structure according to initial format characteristics; displaying the dialog window with the rich text edit field; in response to receiving user input of data for the rich text edit field, invoking the code for inserting and displaying data; and under control of the invoked code for inserting and displaying data, inserting the received data in the allocated document structure associated with the rich text edit field, such that the received data is displayed in the rich text edit field according to the initial format characteristics. 30. The method of claim 27, the application program being a word processing program that displays data in a user document, wherein the code that displays the received data in the rich text edit field is the same code that is used to display data in the user document. | 0.62605 |
5,529,496 | 1 | 27 | 1. A method for teaching a language based on the use of kanji characters, comprising the steps of: displaying a compilation of key kanji in a systematic order; providing a first corresponding compilation of on-yomi readings of said key kanji; and reinforcing the understanding of the first compilation of on-yomi readings by presenting a second corresponding compilation of on-yomi readings. | 1. A method for teaching a language based on the use of kanji characters, comprising the steps of: displaying a compilation of key kanji in a systematic order; providing a first corresponding compilation of on-yomi readings of said key kanji; and reinforcing the understanding of the first compilation of on-yomi readings by presenting a second corresponding compilation of on-yomi readings. 27. The method of claim 1, 15 or 24, further comprising the step presenting the kun-yomi reading of said key kanji. | 0.800347 |
9,514,230 | 6 | 7 | 6. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a plurality of user nodes corresponding to a plurality of users of the online social network, respectively; and a plurality of concept nodes corresponding to a plurality of concepts associated with the online social network, respectively; wherein each query in the first set of queries corresponds to a particular user node, and each retrieved object corresponds to a user node or concept node of the plurality of nodes. | 6. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a plurality of user nodes corresponding to a plurality of users of the online social network, respectively; and a plurality of concept nodes corresponding to a plurality of concepts associated with the online social network, respectively; wherein each query in the first set of queries corresponds to a particular user node, and each retrieved object corresponds to a user node or concept node of the plurality of nodes. 7. The method of claim 6 , wherein each query of the first set of queries is a structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges. | 0.5 |
8,423,583 | 12 | 13 | 12. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting a subset of content items to the user as a hierarchy of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. | 12. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting a subset of content items to the user as a hierarchy of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. 13. The method of claim 12 , further comprising: receiving input entered by the user for browsing through the presented subset of content items for identifying and selecting desired content items; and in response to a selection by the user of a content item, presenting said content item to the user and adjusting the associated relevance weight of the content item. | 0.5 |
8,185,813 | 1 | 2 | 1. A method comprising: performing, by a computer system, an automated keyword analysis of an electronic document to identify a set of keywords associated with the electronic document; displaying, by the computer system, the set of keywords; accepting, by the computer system, user input indicating user-specified concepts of interest, wherein the user input includes at least one keyword identified by the automated keyword analysis and at least one keyword not identified by the automated keyword analysis; analyzing, by the computer system, the electronic document to identify locations of discussion of the user-specified concepts of interest; and displaying, by the computer system, a graph representing the electronic document and illustrating persistence values associated with the user-specified concepts of interest at locations in the electronic document, wherein, for a given location in the electronic document, the graph illustrates a persistence value indicating a frequency of discussion of a user-specified concept of interest at that location relative to other locations in the electronic document. | 1. A method comprising: performing, by a computer system, an automated keyword analysis of an electronic document to identify a set of keywords associated with the electronic document; displaying, by the computer system, the set of keywords; accepting, by the computer system, user input indicating user-specified concepts of interest, wherein the user input includes at least one keyword identified by the automated keyword analysis and at least one keyword not identified by the automated keyword analysis; analyzing, by the computer system, the electronic document to identify locations of discussion of the user-specified concepts of interest; and displaying, by the computer system, a graph representing the electronic document and illustrating persistence values associated with the user-specified concepts of interest at locations in the electronic document, wherein, for a given location in the electronic document, the graph illustrates a persistence value indicating a frequency of discussion of a user-specified concept of interest at that location relative to other locations in the electronic document. 2. The method of claim 1 wherein accepting user input further comprises: displaying an editable text input field; and receiving, via the editable text input field, text input indicating one or more keywords related to the user-specified concepts of interest. | 0.706818 |
9,176,978 | 6 | 7 | 6. A system, comprising: a receiver comprising a hardware processor that receives data that has been classified into a deduplication classification in accordance with a classification policy, where the classification policy includes a plurality of different deduplication classifications for indicating different deduplicating methodologies for different types of data, where the different deduplicating methodologies perform deduplication using different block sizes, where the different block sizes are based, at least in part, on the classification policy; and a storage processing block comprising a hardware processor that processes the data according to a predefined data deduplication methodology associated with the deduplication classification. | 6. A system, comprising: a receiver comprising a hardware processor that receives data that has been classified into a deduplication classification in accordance with a classification policy, where the classification policy includes a plurality of different deduplication classifications for indicating different deduplicating methodologies for different types of data, where the different deduplicating methodologies perform deduplication using different block sizes, where the different block sizes are based, at least in part, on the classification policy; and a storage processing block comprising a hardware processor that processes the data according to a predefined data deduplication methodology associated with the deduplication classification. 7. The system of claim 6 , comprising: a plurality of repositories that separately store data associated with different deduplication classifications. | 0.662162 |
8,909,616 | 13 | 14 | 13. The method of claim 12 , wherein refining the query includes selecting a particular database or a particular search engine based on the taxonomy selected. | 13. The method of claim 12 , wherein refining the query includes selecting a particular database or a particular search engine based on the taxonomy selected. 14. The method of claim 13 , wherein the selection is made algorithmically based on the taxonomy selected and user input from the client access device. | 0.5 |
8,566,303 | 1 | 2 | 1. A method, comprising: determining one or more categories that correspond to a plurality of queries; sorting the plurality of queries into one or more groups based at least in part on the determined categories of the plurality of queries; segmenting queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determining occurrence probabilities for the first plurality of phrases; determining word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; and performing a search based at least in part on the determined word information entropies, wherein performing the search includes: receiving a subsequent query; segmenting the subsequent query into a second plurality of phrases; selecting at least one phrase from the second plurality of phrases based at least in part on the stored determined word information entropies; searching based at least in part on the selected phrase; wherein the category is determined by a preset correspondence relationship for a portion of one of the plurality of queries; updating the determined word information entropies based at least in part on receiving a predetermined number of queries; and updating the determined word information entropies based at least in part on an expiration of a predetermined period of time; wherein the word information entropies for the first plurality of phrases are proportional to summations of the occurrence probabilities for the first plurality of phrases. | 1. A method, comprising: determining one or more categories that correspond to a plurality of queries; sorting the plurality of queries into one or more groups based at least in part on the determined categories of the plurality of queries; segmenting queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determining occurrence probabilities for the first plurality of phrases; determining word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; and performing a search based at least in part on the determined word information entropies, wherein performing the search includes: receiving a subsequent query; segmenting the subsequent query into a second plurality of phrases; selecting at least one phrase from the second plurality of phrases based at least in part on the stored determined word information entropies; searching based at least in part on the selected phrase; wherein the category is determined by a preset correspondence relationship for a portion of one of the plurality of queries; updating the determined word information entropies based at least in part on receiving a predetermined number of queries; and updating the determined word information entropies based at least in part on an expiration of a predetermined period of time; wherein the word information entropies for the first plurality of phrases are proportional to summations of the occurrence probabilities for the first plurality of phrases. 2. The method of claim 1 , wherein segmenting is based at least in part on phrase meanings within the queries. | 0.691011 |
8,725,517 | 15 | 18 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. 18. The computer-readable storage device of claim 15 , wherein the selected top level flow controller interacts independent of an associated decision model. | 0.551724 |
9,785,617 | 8 | 16 | 8. A non-transitory computer readable medium storing a computer program which when executed by at least one processor selects content in a document created from a template comprising a set of template pages preconfigured with fields and placeholder content, the computer program comprising sets of instructions for: displaying a page of the document based on one of the preconfigured template pages of the template used to create the document, said page comprising a field storing template-based placeholder content or storing user-generated content, wherein the preconfigured template pages are initially populated with the placeholder content that is replaceable with the user-generated content; receiving, at the document, a selection of a portion of the content, wherein the selection is based on a click operation within the field of either the placeholder content or user-generated content; and in response to receiving, at the document, the selection: determining whether the field contains the placeholder content or the user-generated content; when the field contains the placeholder content: automatically selecting within the field all of the placeholder content of the field when the selection comprises clicking on the placeholder content of the field; and when the field contains the user-generated content: selecting within the field only the portion of the user-generated content of the field. | 8. A non-transitory computer readable medium storing a computer program which when executed by at least one processor selects content in a document created from a template comprising a set of template pages preconfigured with fields and placeholder content, the computer program comprising sets of instructions for: displaying a page of the document based on one of the preconfigured template pages of the template used to create the document, said page comprising a field storing template-based placeholder content or storing user-generated content, wherein the preconfigured template pages are initially populated with the placeholder content that is replaceable with the user-generated content; receiving, at the document, a selection of a portion of the content, wherein the selection is based on a click operation within the field of either the placeholder content or user-generated content; and in response to receiving, at the document, the selection: determining whether the field contains the placeholder content or the user-generated content; when the field contains the placeholder content: automatically selecting within the field all of the placeholder content of the field when the selection comprises clicking on the placeholder content of the field; and when the field contains the user-generated content: selecting within the field only the portion of the user-generated content of the field. 16. The non-transitory computer readable medium of claim 8 , wherein the user-generated content of the field is previously-inserted text content that replaced template-based placeholder text content. | 0.659247 |
9,373,325 | 1 | 6 | 1. A method comprising: generating, via a processor, a feature coefficient based on a speech signal from a user; comparing the feature coefficient to a user-specific codebook associated with the user, to yield a similarity value, wherein the user-specific codebook utilizes utterances from both the user and a group of non-users; and when the similarity value meets a threshold: adding the speech signal to a database of reference speech signals associated with the user-specific codebook; and adding the feature coefficient to the user-specific codebook. | 1. A method comprising: generating, via a processor, a feature coefficient based on a speech signal from a user; comparing the feature coefficient to a user-specific codebook associated with the user, to yield a similarity value, wherein the user-specific codebook utilizes utterances from both the user and a group of non-users; and when the similarity value meets a threshold: adding the speech signal to a database of reference speech signals associated with the user-specific codebook; and adding the feature coefficient to the user-specific codebook. 6. The method of claim 1 , further comprising: when the similarity value does not meet the threshold, requesting the speech signal be repeated. | 0.662736 |
8,671,109 | 4 | 12 | 4. The method defined in claim 3 , wherein each of the query data elements is associated with a respective one of the video frames in the query video stream, and wherein said deriving the set of query data elements comprises, for each particular video frame in the query video stream: extracting at least one feature for each of a plurality of regions of the particular video frame in the query video stream, wherein the query data element associated with the particular video frame in the query video stream comprises the at least one extracted feature. | 4. The method defined in claim 3 , wherein each of the query data elements is associated with a respective one of the video frames in the query video stream, and wherein said deriving the set of query data elements comprises, for each particular video frame in the query video stream: extracting at least one feature for each of a plurality of regions of the particular video frame in the query video stream, wherein the query data element associated with the particular video frame in the query video stream comprises the at least one extracted feature. 12. The method defined in claim 4 , wherein at least one feature for at least one region of the video frame in the reference video stream is temporally normalized and wherein at least one feature for at least one region of the video frame in the query video stream is temporally normalized. | 0.629156 |
8,892,350 | 1 | 6 | 1. A computer-implemented method comprising: converting, by one or more computing devices, a set of driver history data to a set of learning parameters; analyzing, by the one or more computing devices, the set of learning parameters and current journey data describing a current journey to generate estimated journey data describing one or more potential journeys; retrieving, by the one or more computing devices, a set of current status data; determining, by the one or more computing devices, a destination for each of the one or more potential journeys, a direction for each of the one or more potential journeys, a time of day for each of the one or more potential journeys, and day of the week for each of the one or more potential journeys; calculating, by the one or more computing devices, a joint conditional probability metric for each potential journey of the one or more potential journeys based on the destination, the direction, the time of day, and the day of the week associated with the potential journey; determining by the one or more computing devices, a quality score for each potential journey of the one or more potential journeys based on the joint conditional probability metric associated with the potential journey; outputting, by the one or more computing devices, display data for depicting the one or more potential journeys and the quality score associated with each of the one or more potential journeys on a display; and storing, by the one or more computing devices, the current journey data as additional driver history data. | 1. A computer-implemented method comprising: converting, by one or more computing devices, a set of driver history data to a set of learning parameters; analyzing, by the one or more computing devices, the set of learning parameters and current journey data describing a current journey to generate estimated journey data describing one or more potential journeys; retrieving, by the one or more computing devices, a set of current status data; determining, by the one or more computing devices, a destination for each of the one or more potential journeys, a direction for each of the one or more potential journeys, a time of day for each of the one or more potential journeys, and day of the week for each of the one or more potential journeys; calculating, by the one or more computing devices, a joint conditional probability metric for each potential journey of the one or more potential journeys based on the destination, the direction, the time of day, and the day of the week associated with the potential journey; determining by the one or more computing devices, a quality score for each potential journey of the one or more potential journeys based on the joint conditional probability metric associated with the potential journey; outputting, by the one or more computing devices, display data for depicting the one or more potential journeys and the quality score associated with each of the one or more potential journeys on a display; and storing, by the one or more computing devices, the current journey data as additional driver history data. 6. The method of claim 1 , wherein the estimated journey data describes three potential journeys. | 0.888249 |
10,013,672 | 6 | 7 | 6. A system, comprising: at least one processor; memory storing instructions, that when executed by the processor, cause the system to: receive a communication from a sender comprising a plurality of words, wherein at least one of the words is a zip code comprising five numerical digits; assign a score to each of the words, wherein the score assigned to each of the words is based on a ratio of a first frequency of usage of the respective word in a language relative to a second frequency of usage of the respective word in the language, and wherein a first set of words comprises a first total number of words used as an address, a second set of words comprises a second total number of words including words used other than as an address, the first frequency is determined by counting occurrence of the respective word in the first set of words relative to the first total, the second frequency is determined by counting occurrence of the respective word in the second set relative to the second total, and the first total is less than the second total, and wherein the assigning the score further comprises determining a score for a numerical digit sequence based on treating any numerical digit sequence of a given digit length as being the same word; determine a respective total sum for each of a plurality of contiguous word sequences in the communication, the respective total sum determined as a sum of the scores for each word in the respective contiguous word sequence; identify a first word sequence of the word sequences having a total sum that is greater than a threshold value; apply at least one filter to the first word sequence, the at least one filter comprising determining a ratio of number tokens to character tokens in the first word sequence, and comparing the ratio to a predetermined value to determine whether the first word sequence passes the at least one filter, and the at least one filter further comprising determining whether the first word sequence includes a token that scores below a predetermined threshold, wherein determining that the first word sequence includes a token that scores below the predetermined threshold disqualifies the first word sequence from being identified as an address; in response to determining that the first word sequence passes the at least one filter, extract the first word sequence from the plurality of words of the received communication as a first address of the sender, wherein the first word sequence contains the zip code; and store, in a data repository, the first address in a first person profile of the sender, wherein the data repository stores a plurality of person profiles including the first person profile. | 6. A system, comprising: at least one processor; memory storing instructions, that when executed by the processor, cause the system to: receive a communication from a sender comprising a plurality of words, wherein at least one of the words is a zip code comprising five numerical digits; assign a score to each of the words, wherein the score assigned to each of the words is based on a ratio of a first frequency of usage of the respective word in a language relative to a second frequency of usage of the respective word in the language, and wherein a first set of words comprises a first total number of words used as an address, a second set of words comprises a second total number of words including words used other than as an address, the first frequency is determined by counting occurrence of the respective word in the first set of words relative to the first total, the second frequency is determined by counting occurrence of the respective word in the second set relative to the second total, and the first total is less than the second total, and wherein the assigning the score further comprises determining a score for a numerical digit sequence based on treating any numerical digit sequence of a given digit length as being the same word; determine a respective total sum for each of a plurality of contiguous word sequences in the communication, the respective total sum determined as a sum of the scores for each word in the respective contiguous word sequence; identify a first word sequence of the word sequences having a total sum that is greater than a threshold value; apply at least one filter to the first word sequence, the at least one filter comprising determining a ratio of number tokens to character tokens in the first word sequence, and comparing the ratio to a predetermined value to determine whether the first word sequence passes the at least one filter, and the at least one filter further comprising determining whether the first word sequence includes a token that scores below a predetermined threshold, wherein determining that the first word sequence includes a token that scores below the predetermined threshold disqualifies the first word sequence from being identified as an address; in response to determining that the first word sequence passes the at least one filter, extract the first word sequence from the plurality of words of the received communication as a first address of the sender, wherein the first word sequence contains the zip code; and store, in a data repository, the first address in a first person profile of the sender, wherein the data repository stores a plurality of person profiles including the first person profile. 7. The system of claim 6 , wherein the determining the total sum for the first word sequence comprises: determining an additional score for a starting word of the first word sequence, wherein the additional score for the starting word is associated with a probability that the starting word is part of an address; determining an additional score for an ending word of the first word sequence, wherein the additional score for the ending word is associated with a probability that the ending word is part of an address; and adding the additional score for the starting word and the additional score for the ending word to the sum of scores for the first word sequence to obtain the total sum. | 0.5 |
8,850,581 | 14 | 16 | 14. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; an abstract syntax data structure representation of a software program code residing in the memory; a start state of a virtual machine residing in the memory, the start state being a state of the virtual machine during a run of the software program code on the virtual machine, and in particular being a state of the virtual machine for which a determination is made that the software program code should be investigated as a possible carrier of malware; a set of one or more variables of interest residing in the memory and including at least one variable which is visible in the start state, namely, a variable which is within scope in the start state and could be assigned a value; a set of previously executed states of the virtual machine; and a signature candidate generator including code which upon execution by the logical processor will utilize the abstract syntax data structure representation and the virtual machine start state to identify a set of assignments of interest at least in part by searching previously executed states of the virtual machine for any assignment of a variable that belongs to the set of variables of interest and putting in the set of assignments of interest at least one assignment in the software program code that is visible to at least one variable of the start state, and wherein the set of assignments of interest includes said assignment on the basis of said visibility in that without said visibility said assignment would not be included in the set of assignments of interest, and when the set of assignments of interest contains a nonterminated assignment having at least one source parameter variable, placing the source parameter variable(s) of that nonterminated assignment in the set of variables of interest and then repeating the searching, and when the set of assignments of interest does not contain a nonterminated assignment having at least one source parameter variable, identifying as a malware detection signature generation candidate a region of code which is defined by the set of assignments of interest. | 14. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; an abstract syntax data structure representation of a software program code residing in the memory; a start state of a virtual machine residing in the memory, the start state being a state of the virtual machine during a run of the software program code on the virtual machine, and in particular being a state of the virtual machine for which a determination is made that the software program code should be investigated as a possible carrier of malware; a set of one or more variables of interest residing in the memory and including at least one variable which is visible in the start state, namely, a variable which is within scope in the start state and could be assigned a value; a set of previously executed states of the virtual machine; and a signature candidate generator including code which upon execution by the logical processor will utilize the abstract syntax data structure representation and the virtual machine start state to identify a set of assignments of interest at least in part by searching previously executed states of the virtual machine for any assignment of a variable that belongs to the set of variables of interest and putting in the set of assignments of interest at least one assignment in the software program code that is visible to at least one variable of the start state, and wherein the set of assignments of interest includes said assignment on the basis of said visibility in that without said visibility said assignment would not be included in the set of assignments of interest, and when the set of assignments of interest contains a nonterminated assignment having at least one source parameter variable, placing the source parameter variable(s) of that nonterminated assignment in the set of variables of interest and then repeating the searching, and when the set of assignments of interest does not contain a nonterminated assignment having at least one source parameter variable, identifying as a malware detection signature generation candidate a region of code which is defined by the set of assignments of interest. 16. The system of claim 14 , wherein the signature candidate generator includes code which upon execution by the logical processor will determine whether an assignment of interest is a terminated assignment. | 0.638112 |
8,595,317 | 19 | 20 | 19. The system of claim 18 , wherein the geofeed creation module is further configured to: determine a creation location from which at least one of social media content from the respective set of results received from the user-selectable plurality of social media content providers, wherein the creation location is within the one or more geographically definable locations, wherein the at least one of the social media content is spatially arranged based on the creation location. | 19. The system of claim 18 , wherein the geofeed creation module is further configured to: determine a creation location from which at least one of social media content from the respective set of results received from the user-selectable plurality of social media content providers, wherein the creation location is within the one or more geographically definable locations, wherein the at least one of the social media content is spatially arranged based on the creation location. 20. The system of claim 19 , wherein the geofeed creation module further configured to: extract an automatically generated geotag from the at least one of the social media content. | 0.5 |
8,359,312 | 1 | 2 | 1. A method for generating, by a monitoring program, a list of relevant documents, related to a first search query, comprising: tracking activities of a first user pursuant to retrieval of a first list of primary documents resulting from the first search query; monitoring a secondary document the first user interacts with, the secondary document whose identifier is referenced within the contents of a primary document or another secondary document; assigning a user interest score to the secondary document whose identifier is referenced within the contents of a primary document or another secondary document, and wherein the user interest score is based on measuring user interactions with the secondary document; adding the identifier of each such secondary document whose identifier is referenced within the contents of a primary document or another secondary document and the user interest score of each such secondary document, whose identifier is referenced within the contents of a primary or another secondary document, to a new list of relevant documents; persisting said new list of relevant documents to storage in a manner so that each such persisted said new list, submitted by said first user, is only accessible to said first user and is associated with said first search query; returning said persisted said new list of relevant documents as said list of relevant documents, in response to a second query, by said first user, if and only if, said second query matches said associated first query. | 1. A method for generating, by a monitoring program, a list of relevant documents, related to a first search query, comprising: tracking activities of a first user pursuant to retrieval of a first list of primary documents resulting from the first search query; monitoring a secondary document the first user interacts with, the secondary document whose identifier is referenced within the contents of a primary document or another secondary document; assigning a user interest score to the secondary document whose identifier is referenced within the contents of a primary document or another secondary document, and wherein the user interest score is based on measuring user interactions with the secondary document; adding the identifier of each such secondary document whose identifier is referenced within the contents of a primary document or another secondary document and the user interest score of each such secondary document, whose identifier is referenced within the contents of a primary or another secondary document, to a new list of relevant documents; persisting said new list of relevant documents to storage in a manner so that each such persisted said new list, submitted by said first user, is only accessible to said first user and is associated with said first search query; returning said persisted said new list of relevant documents as said list of relevant documents, in response to a second query, by said first user, if and only if, said second query matches said associated first query. 2. The method of claim 1 further including, automatically opening one or more documents included in said list of relevant documents returned. | 0.929711 |
9,900,392 | 1 | 5 | 1. A method comprising: maintaining one or more groups at an online system, each group including one or more users of the online system, with each user associated with a location; determining a location associated with each of the one or more groups, the location associated with a group based at least in part on locations associated with users in the group, comprising: determining a centroid of the locations associated with users in the group; determining distances between locations associated with each user in the group and the centroid; generating a histogram of the determined distances; and determining the centroid as the location associated with the group in response to at least a threshold percentile of the determined distances from the histogram being less than or equal to a threshold distance; receiving a request from a requesting user of a social networking system to identify one or more groups maintained by the social networking system; determining a plurality of candidate groups for the requesting user from the one or more groups based at least in part on a distance between a location associated with the requesting user and locations associated with each of the one or more groups, a candidate group associated with a location within a threshold distance of the location associated with the user; including the plurality of candidate groups in one or more selection processes selecting a set of groups; and communicating information identifying the selected set of groups to a client device associated with the requesting user for presentation. | 1. A method comprising: maintaining one or more groups at an online system, each group including one or more users of the online system, with each user associated with a location; determining a location associated with each of the one or more groups, the location associated with a group based at least in part on locations associated with users in the group, comprising: determining a centroid of the locations associated with users in the group; determining distances between locations associated with each user in the group and the centroid; generating a histogram of the determined distances; and determining the centroid as the location associated with the group in response to at least a threshold percentile of the determined distances from the histogram being less than or equal to a threshold distance; receiving a request from a requesting user of a social networking system to identify one or more groups maintained by the social networking system; determining a plurality of candidate groups for the requesting user from the one or more groups based at least in part on a distance between a location associated with the requesting user and locations associated with each of the one or more groups, a candidate group associated with a location within a threshold distance of the location associated with the user; including the plurality of candidate groups in one or more selection processes selecting a set of groups; and communicating information identifying the selected set of groups to a client device associated with the requesting user for presentation. 5. The method of claim 1 , wherein determining the plurality of candidate groups for the requesting user from the one or more groups based at least in part on the distance between the location associated with the requesting user and locations associated with each of the one or more groups comprises: identifying a geographic region including the location associated with the requesting user, the geographic region including locations within a specified geographic area; and identifying groups associated with locations included in the identified geographic region; and selecting identified groups satisfying at least a threshold number of criteria as candidate groups. | 0.696736 |
9,678,857 | 2 | 5 | 2. The method according to claim 1 , wherein the first task is associated with a first task category and a first customer name, and wherein ranking the one or more previous machine instances corresponding to the one or more similar tasks comprises assigning the priority ranking, wherein the priority ranking is selected from the group consisting of: a highest rank priority to a machine instance corresponding to a previous task performed by the user within the computing environment; a second highest rank priority to a machine instance corresponding to a similar task associated with the first task category and the first customer name; a third highest rank priority to a machine instance corresponding to a similar task associated with the first task category; and a fourth highest rank priority to a machine instance corresponding to a similar task associated with the first customer name. | 2. The method according to claim 1 , wherein the first task is associated with a first task category and a first customer name, and wherein ranking the one or more previous machine instances corresponding to the one or more similar tasks comprises assigning the priority ranking, wherein the priority ranking is selected from the group consisting of: a highest rank priority to a machine instance corresponding to a previous task performed by the user within the computing environment; a second highest rank priority to a machine instance corresponding to a similar task associated with the first task category and the first customer name; a third highest rank priority to a machine instance corresponding to a similar task associated with the first task category; and a fourth highest rank priority to a machine instance corresponding to a similar task associated with the first customer name. 5. The method according to claim 2 , wherein a plurality of machine instances are assigned to a single priority ranking, and wherein the plurality of machine instances assigned to the single priority ranking are further ranked from a most recently used machine instance to a least recently used machine instance. | 0.5 |
9,032,338 | 1 | 15 | 1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document; detecting a first horizontal gesture at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed; in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display in accordance with a direction of the first horizontal gesture, and maintaining the insertion marker at the first position in the text; and, in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, moving the insertion marker by one character in the text from the first position to a second position in the text in accordance with the direction of the first horizontal gesture. | 1. An electronic device, comprising: a display; a touch-sensitive surface; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document; detecting a first horizontal gesture at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed; in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display in accordance with a direction of the first horizontal gesture, and maintaining the insertion marker at the first position in the text; and, in response to a determination that the first horizontal gesture at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, moving the insertion marker by one character in the text from the first position to a second position in the text in accordance with the direction of the first horizontal gesture. 15. The device of claim 1 , including instructions for: in response to a determination that the first horizontal gesture satisfies a sixth set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions and the second set of one or more predefined conditions, moving the insertion marker to a beginning or an end of a line of text containing the first position in accordance with the direction of the first horizontal gesture. | 0.733184 |
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