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9,858,258 | 14 | 18 | 14. A data-processing method comprising: using a first computer, obtaining from one or more non-transitory computer-readable data storage media a copy of one or more sequences of instructions that are stored on the media and are arranged, when executed using a second computer among a plurality of other computers to cause the second computer to perform: using a computer, receiving an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; using the computer, based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; using the computer, assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; using the computer, comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; using the computer, based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; using the computer, based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; using the computer, based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. | 14. A data-processing method comprising: using a first computer, obtaining from one or more non-transitory computer-readable data storage media a copy of one or more sequences of instructions that are stored on the media and are arranged, when executed using a second computer among a plurality of other computers to cause the second computer to perform: using a computer, receiving an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; using the computer, based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; using the computer, assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; using the computer, comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; using the computer, based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; using the computer, based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; using the computer, based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. 18. The method of claim 14 , wherein the document schema of the document depends on a type of structured data included in the document, and wherein the type of the structured data is one or more of XML (Extensible Markup Language), JSON (JavaScript Object Notation), cXML (commerce eXtensible Markup Language), IDoc (Intermediate Document), or CSV (Comma Separated values). | 0.71997 |
9,965,043 | 15 | 16 | 15. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a gesture recommendation system to perform the operations comprising: receiving gesture data from one or more gesture detection sensors for each of the one or more gestures; determining a noise score, a proximity score, a shape score and a strength score based on the gesture data; determining a cumulative score using the noise score and at least one of the proximity score, the shape score, and the strength score, wherein the proximity score is calculated based on a first score determined based on a body proximity range and a second score determined based on a phone proximity range, and wherein the first score is indicative of a first distance between body parts of the user associated with the one or more gestures from the body of the user and the second score is indicative of a second distance between the body parts from the computing device; and recommending suggestions as to at least of improving the one or more gestures and changing the one or more gestures based on the cumulative score. | 15. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a gesture recommendation system to perform the operations comprising: receiving gesture data from one or more gesture detection sensors for each of the one or more gestures; determining a noise score, a proximity score, a shape score and a strength score based on the gesture data; determining a cumulative score using the noise score and at least one of the proximity score, the shape score, and the strength score, wherein the proximity score is calculated based on a first score determined based on a body proximity range and a second score determined based on a phone proximity range, and wherein the first score is indicative of a first distance between body parts of the user associated with the one or more gestures from the body of the user and the second score is indicative of a second distance between the body parts from the computing device; and recommending suggestions as to at least of improving the one or more gestures and changing the one or more gestures based on the cumulative score. 16. The non-transitory computer readable medium as claimed in claim 15 , wherein the instructions cause the processor to determine the shape score based on number of body parts required and angular movement of the body parts required to make the one or more gestures. | 0.632231 |
8,645,832 | 10 | 11 | 10. The apparatus of claim 7 , wherein said means for displaying, plotting, and playing back are configured to display an integrated graphical user interface, said graphical user interface comprising a plurality of computer display regions including a map region displaying the abstract map and plotted markers, and a playback region for playing back one of the plurality of traversal records associated with one of the plurality of markers in response to interactive selection of the one of the plurality of markers. | 10. The apparatus of claim 7 , wherein said means for displaying, plotting, and playing back are configured to display an integrated graphical user interface, said graphical user interface comprising a plurality of computer display regions including a map region displaying the abstract map and plotted markers, and a playback region for playing back one of the plurality of traversal records associated with one of the plurality of markers in response to interactive selection of the one of the plurality of markers. 11. The apparatus of claim 10 , wherein the graphical user interface further includes a worksheet region displaying a list of the plurality of traversal records and associated annotations. | 0.5 |
7,499,047 | 10 | 13 | 10. A process for associating an ink editor to an ink canvas, the process comprising: attaching the ink editor to the ink canvas, wherein the ink canvas comprises an ink canvas object that is configured to detect and respond to actions performed by the use of a mouse or stylus- based input device, wherein the ink editor manages behaviors associated with editing modes supported by the ink canvas object wherein the ink canvas object is configured to host one or more child elements and provide ink functionality to the one or more child elements, wherein ink comprises information captured from the use of the mouse or stylus-based input device; determining an editing mode using a processing unit; handling user input based on the determined editing mode, wherein the one or more child elements are rendered and at least one of the one or more child elements renders the ink for themselves. | 10. A process for associating an ink editor to an ink canvas, the process comprising: attaching the ink editor to the ink canvas, wherein the ink canvas comprises an ink canvas object that is configured to detect and respond to actions performed by the use of a mouse or stylus- based input device, wherein the ink editor manages behaviors associated with editing modes supported by the ink canvas object wherein the ink canvas object is configured to host one or more child elements and provide ink functionality to the one or more child elements, wherein ink comprises information captured from the use of the mouse or stylus-based input device; determining an editing mode using a processing unit; handling user input based on the determined editing mode, wherein the one or more child elements are rendered and at least one of the one or more child elements renders the ink for themselves. 13. The process according to claim 10 , further comprising: upon determining the editing mode is selection, then activating an ink selection behavior, the ink selection behavior facilitating a selection of a portion of one of the one or more child elements. | 0.707955 |
8,296,130 | 16 | 30 | 16. A computer-implemented system, comprising: a data processor; a computer-readable memory encoded with instructions for commanding the data processors to execute steps including: receiving a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B −(1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. | 16. A computer-implemented system, comprising: a data processor; a computer-readable memory encoded with instructions for commanding the data processors to execute steps including: receiving a plurality of offensive words, wherein each respective offensive word in the plurality of offensive words is associated with a severity score identifying the offensiveness of the respective word; receiving a string of words, wherein a candidate word is selected from the string of words; calculating, for each respective offensive word in the plurality of offensive words, a distance between the candidate word and the respective offensive word; calculating a plurality of offensiveness scores for the candidate word, each offensiveness score in the plurality of offensiveness scores based upon (i) the calculated distance between the candidate word and an offensive word in the plurality of offensive words and (ii) the severity score of the offensive word, wherein the plurality of offensiveness scores are calculated according to one or more of:
offensiveness score= A *(( B−C )/ B );
offensiveness score= A *(( B −(1/ C ))/ B );
offensiveness score=Max((( A−C )/ A ),0); and
offensiveness score=((( B−C )/ B )> T ); wherein A is the severity score for an offensive word in the plurality of offensive words; B is a function of a length of the offensive word; C is the calculated distance between the candidate word and the offensive word; and T is a threshold value; and determining whether the candidate word is an offender word based on whether the highest offensiveness score in the plurality of offensiveness scores for the candidate word exceeds an offensiveness threshold value. 30. The system of claim 16 , wherein the highest offensiveness score is one of: a smallest value offensiveness score calculated in comparing each of the plurality of offensive words with the candidate word, or a largest value offensiveness score calculated in comparing each of the plurality of offensive words with the candidate word. | 0.603081 |
8,352,405 | 12 | 13 | 12. A method of performing sentiment classification of content comprising: classifying the content as being related to a particular aspect of a plurality of aspects of information by an aspect classifier, wherein the aspect classifier incorporates at least a portion of a domain specific sentiment lexicon, wherein the domain specific sentiment lexicon is configured by (i) obtaining domain specific words and/or phrases by filtering an annotated corpus, (ii) obtaining domain specific words and/or phrases by searching the world wide web via the internet using a predetermined linguistic pattern and filtering returned search results, and (iii) performing a dictionary expansion operation on domain specific words and/or phrases obtained via (i) and (ii); classifying the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information by use of a polarity classifier, wherein the polarity classifier incorporates at least a portion of the domain specific sentiment lexicon; and aggregating received results of predictions by the aspect classifier and received results of predictions by the polarity classifier, wherein the method is performed using at least one electronic processor. | 12. A method of performing sentiment classification of content comprising: classifying the content as being related to a particular aspect of a plurality of aspects of information by an aspect classifier, wherein the aspect classifier incorporates at least a portion of a domain specific sentiment lexicon, wherein the domain specific sentiment lexicon is configured by (i) obtaining domain specific words and/or phrases by filtering an annotated corpus, (ii) obtaining domain specific words and/or phrases by searching the world wide web via the internet using a predetermined linguistic pattern and filtering returned search results, and (iii) performing a dictionary expansion operation on domain specific words and/or phrases obtained via (i) and (ii); classifying the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information by use of a polarity classifier, wherein the polarity classifier incorporates at least a portion of the domain specific sentiment lexicon; and aggregating received results of predictions by the aspect classifier and received results of predictions by the polarity classifier, wherein the method is performed using at least one electronic processor. 13. The method of claim 12 wherein the aspect classifier further incorporates a general purpose sentiment lexicon. | 0.681564 |
9,330,667 | 6 | 7 | 6. The method according to claim 1 , wherein before the obtaining each frame of audio record data, the method further comprises: receiving the audio record data and determining the audio record start frame of the audio record data. | 6. The method according to claim 1 , wherein before the obtaining each frame of audio record data, the method further comprises: receiving the audio record data and determining the audio record start frame of the audio record data. 7. The method according to claim 6 , wherein the determining the audio record start frame of the audio record data comprises: determining in turn whether each frame of the audio record data is the mute data or non-mute data, and using a first frame of the non-mute data as the audio record start frame. | 0.5 |
7,533,020 | 7 | 8 | 7. The method of claim 6 , wherein said user's current geographic location is acquired prior to acquiring said speech signal. | 7. The method of claim 6 , wherein said user's current geographic location is acquired prior to acquiring said speech signal. 8. The method of claim 7 , wherein said user's current geographic location is acquired periodically based on said user's travel. | 0.5 |
9,070,366 | 19 | 23 | 19. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: receiving text corresponding to a request of a user; processing the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the transcription, and in a second NLU module to generate a second interpretation of the transcription, wherein first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, and wherein the first interpretation is associated with a first score indicative of whether the first interpretation corresponds to an action requested by the user, and the second interpretation is associated with a second score indicative of whether the second interpretation corresponds to the action requested by the user; selecting the first interpretation based at least partly on the first score and the second score; and generating a response based at least partly on the first interpretation. | 19. One or more non-transitory computer readable media comprising executable code that, when executed, cause one or more computing devices to perform a process comprising: receiving text corresponding to a request of a user; processing the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the transcription, and in a second NLU module to generate a second interpretation of the transcription, wherein first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, and wherein the first interpretation is associated with a first score indicative of whether the first interpretation corresponds to an action requested by the user, and the second interpretation is associated with a second score indicative of whether the second interpretation corresponds to the action requested by the user; selecting the first interpretation based at least partly on the first score and the second score; and generating a response based at least partly on the first interpretation. 23. The one or more non-transitory computer readable media of claim 19 , the process further comprising determining a hint based at least partly on a previously received text, wherein processing the text in at least one of the first NLU module and the second NLU module is based at least partly on the hint. | 0.55117 |
7,716,579 | 2 | 3 | 2. The method of claim 1 , further comprising (a) receiving at least part of the partial text entry via a digital keyboard displayed in a graphical user interface; and (b) displaying the search list while not displaying the digital keyboard within the graphical user interface in response to obtaining the new list of completion candidates. | 2. The method of claim 1 , further comprising (a) receiving at least part of the partial text entry via a digital keyboard displayed in a graphical user interface; and (b) displaying the search list while not displaying the digital keyboard within the graphical user interface in response to obtaining the new list of completion candidates. 3. A computer-readable medium having stored instructions for directing a processor unit to execute the method of claim 2 . | 0.5 |
5,437,555 | 12 | 15 | 12. The system of claim 1, wherein the group leader terminal further comprises means for selecting an unanticipated multi-character response of a participant terminal and comparing the unanticipated multi-character response with the multi-character responses from other participant terminals. | 12. The system of claim 1, wherein the group leader terminal further comprises means for selecting an unanticipated multi-character response of a participant terminal and comparing the unanticipated multi-character response with the multi-character responses from other participant terminals. 15. The system of claim 12 wherein the participant terminals are provided with reinforcement means, for reinforcing a favorable comparison between the selected unanticipated response on the group leader terminal and the responses from other participant terminals. | 0.5 |
8,737,727 | 9 | 10 | 9. A system for sorting electronic color images of objects, the system comprising: a communication interface configured to receive, at a server from an end-user device, an input representation of a desired object, the input representation including first data representing a first color of the desired object, the first data being in a first color space; and a processing unit communicatively coupled to the communication interface and configured to: determine an indication of saturation of the first color of the received input representation; define a prescribed range of saturation indications based on the determined indication of the saturation of the first color; compare the prescribed range of saturation indications to a plurality of candidate saturation indications associated with a plurality of candidate images stored in a memory of the processing unit; in response to the candidate saturation indication associated with a presently compared one of the stored candidate images not being in the prescribed range of saturation indications, discard the presently compared candidate image as possibly including the desired object; and in response to the candidate saturation indication of the presently compared one of the stored candidate images being in the prescribed range of saturation indications, determine that the candidate image possibly includes the desired object. | 9. A system for sorting electronic color images of objects, the system comprising: a communication interface configured to receive, at a server from an end-user device, an input representation of a desired object, the input representation including first data representing a first color of the desired object, the first data being in a first color space; and a processing unit communicatively coupled to the communication interface and configured to: determine an indication of saturation of the first color of the received input representation; define a prescribed range of saturation indications based on the determined indication of the saturation of the first color; compare the prescribed range of saturation indications to a plurality of candidate saturation indications associated with a plurality of candidate images stored in a memory of the processing unit; in response to the candidate saturation indication associated with a presently compared one of the stored candidate images not being in the prescribed range of saturation indications, discard the presently compared candidate image as possibly including the desired object; and in response to the candidate saturation indication of the presently compared one of the stored candidate images being in the prescribed range of saturation indications, determine that the candidate image possibly includes the desired object. 10. The system of claim 9 wherein the processing unit is configured to convert first data in the first color space into second data in a second color space different than the first color space, wherein at least one of the first color space or the second color space includes a saturation parameter; and wherein the first color space or the second color space is relative RGB color space. | 0.805918 |
9,977,781 | 1 | 2 | 1. A computer-implemented method, comprising: obtaining, at a computing device having one or more processors, a parsable content feed from at least one server associated with a social network comprising a plurality of users, the parsable content feed comprising at least one of (i) user-generated text posts on the social network and (ii) user-generated text comments to posts on the social network; obtaining, at the computing device, a set of preferred languages for a user operating the computing device, the user being one of the plurality of users; identifying, at the computing device, a text portion in the parsable content feed, the text portion being a sub-portion of text of the parsable content feed; obtaining, at the computing device, a detected language for the text portion; comparing, at the computing device, the detected language to the set of preferred languages for the user; when the detected language does not match any of the set of preferred languages, displaying, by the computing device and proximate to the text portion in the parsable content feed, a clickable icon configured for displaying a machine translation of the text portion and the text portion, the machine translation of the text portion being to one of the set of preferred languages for the user; and displaying, by the computing device and in response to a user selection of the clickable icon, the machine translation of the text portion and the text portion in the parsable content feed. | 1. A computer-implemented method, comprising: obtaining, at a computing device having one or more processors, a parsable content feed from at least one server associated with a social network comprising a plurality of users, the parsable content feed comprising at least one of (i) user-generated text posts on the social network and (ii) user-generated text comments to posts on the social network; obtaining, at the computing device, a set of preferred languages for a user operating the computing device, the user being one of the plurality of users; identifying, at the computing device, a text portion in the parsable content feed, the text portion being a sub-portion of text of the parsable content feed; obtaining, at the computing device, a detected language for the text portion; comparing, at the computing device, the detected language to the set of preferred languages for the user; when the detected language does not match any of the set of preferred languages, displaying, by the computing device and proximate to the text portion in the parsable content feed, a clickable icon configured for displaying a machine translation of the text portion and the text portion, the machine translation of the text portion being to one of the set of preferred languages for the user; and displaying, by the computing device and in response to a user selection of the clickable icon, the machine translation of the text portion and the text portion in the parsable content feed. 2. The computer-implemented method of claim 1 , further comprising displaying, by the computing device, an indication of the machine translation of the text portion at a location proximate to the machine translation of the text portion. | 0.720379 |
7,937,416 | 1 | 11 | 1. A data management system comprising: a host server including a processor for processing digital data, a memory coupled to said processor for storing digital data, an input digitizer coupled to the processor for inputting digital data, an application program stored in said memory and accessible by said processor for directing processing of digital data by said processor, a display coupled to the processor and memory for displaying information derived from digital data processed by said processor; a database for storage of multi-dimensional data; a usage tracking engine configured to generate multi-dimensional tracking data including at least two of identification of a feature accessed by a user, identification of content accessed by a user, an identification of a user accessing said feature, a time of access to said feature, a duration of access to said feature, or user activity relative to said feature, wherein said user is at least one of a student or an instructor; a reporting engine configured to provide periodic reports based on said multi-dimensional data stored in said database; a predictive model configured to understand program performance, student retention, and learning outcomes; and, a multi-dimensional analysis engine configured to understand program performance, student retention, learning outcomes. | 1. A data management system comprising: a host server including a processor for processing digital data, a memory coupled to said processor for storing digital data, an input digitizer coupled to the processor for inputting digital data, an application program stored in said memory and accessible by said processor for directing processing of digital data by said processor, a display coupled to the processor and memory for displaying information derived from digital data processed by said processor; a database for storage of multi-dimensional data; a usage tracking engine configured to generate multi-dimensional tracking data including at least two of identification of a feature accessed by a user, identification of content accessed by a user, an identification of a user accessing said feature, a time of access to said feature, a duration of access to said feature, or user activity relative to said feature, wherein said user is at least one of a student or an instructor; a reporting engine configured to provide periodic reports based on said multi-dimensional data stored in said database; a predictive model configured to understand program performance, student retention, and learning outcomes; and, a multi-dimensional analysis engine configured to understand program performance, student retention, learning outcomes. 11. The system of claim 1 , further comprising an interface view listing a reported metric value and a corresponding target metric value and at least one of a status indicator or a trend indicator dependent on said reported metric value and said target metric value. | 0.611111 |
8,412,554 | 7 | 9 | 7. The method of claim 1 wherein the device description comprises a device functionality description and device grounding. | 7. The method of claim 1 wherein the device description comprises a device functionality description and device grounding. 9. The method of claim 7 , wherein the device grounding describes device control based on the functionality description. | 0.5 |
7,996,221 | 1 | 2 | 1. A method for processing a message received from a user to determine whether an estimate of intelligibility is below an intelligibility threshold, the method comprising: recognizing a portion of a user's message that contains at least one expected utterance from a list to yield a recognized portion; calculating via a processor an estimate of intelligibility for the recognized portion that contains at least one expected utterance to yield a calculated estimate; and if the calculated estimate is below an intelligibility threshold, prompting the user to repeat at least the recognized portion. | 1. A method for processing a message received from a user to determine whether an estimate of intelligibility is below an intelligibility threshold, the method comprising: recognizing a portion of a user's message that contains at least one expected utterance from a list to yield a recognized portion; calculating via a processor an estimate of intelligibility for the recognized portion that contains at least one expected utterance to yield a calculated estimate; and if the calculated estimate is below an intelligibility threshold, prompting the user to repeat at least the recognized portion. 2. The method of claim 1 , further comprising prompting the user to repeat at least a portion of the message if any of a measured speech level and a measured signal-to-noise ratio of the user's message are determined to be below their respective thresholds. | 0.5 |
9,106,603 | 4 | 5 | 4. The apparatus of claim 1 , wherein each protocol primitive in the intercepted communication, and the DTD, is representable as a tree structure including a root node and one or more leaf nodes, each leaf node representing a protocol information element, wherein comparing a protocol primitive in the intercepted communication with the DTD comprises: locating a sub-tree structure within the DTD that corresponds to the tree structure of the protocol primitive; and for each of the one or more protocol information elements of the protocol primitive, traversing the tree structure of the protocol primitive from the root node to the leaf node representing the protocol information element; and identifying, from the corresponding sub-tree structure within the DTD, the LI attributes of the leaf node representing the protocol information element to thereby identify the LI attributes of the respective protocol information element. | 4. The apparatus of claim 1 , wherein each protocol primitive in the intercepted communication, and the DTD, is representable as a tree structure including a root node and one or more leaf nodes, each leaf node representing a protocol information element, wherein comparing a protocol primitive in the intercepted communication with the DTD comprises: locating a sub-tree structure within the DTD that corresponds to the tree structure of the protocol primitive; and for each of the one or more protocol information elements of the protocol primitive, traversing the tree structure of the protocol primitive from the root node to the leaf node representing the protocol information element; and identifying, from the corresponding sub-tree structure within the DTD, the LI attributes of the leaf node representing the protocol information element to thereby identify the LI attributes of the respective protocol information element. 5. The apparatus of claim 4 , wherein comparing a protocol primitive in the intercepted communication with the DTD comprises, for each of the one or more protocol information elements of the protocol primitive, determining whether the LI attributes of the protocol information element satisfy conditions of a pre-designated LI request, and wherein preparing one or more of the protocol information elements in the intercepted communication for transmission comprises preparing the protocol information elements whose LI attributes satisfy the conditions of the LI request for transmission. | 0.5 |
6,092,044 | 1 | 4 | 1. A method of adding a word to a speech recognition vocabulary, comprising: receiving a spelling of the word, receiving an utterance of the word, creating a collection of possible phonetic pronunciations of the word by: comparing the spelling to a rules list of letter strings with associated phonemes, wherein the comparing includes searching the letter strings of the rules list for a letter string from the spelling of length greater than one letter, and limiting the collection of possible phonetic pronunciations to phonetic pronunciations containing phonemes associated with the letter string of length greater than one, using speech recognition to find a best-matching pronunciation from the collection that best matches the utterance of the word, and adding the word to the speech recognition vocabulary using the spelling and the best-matching pronunciation. | 1. A method of adding a word to a speech recognition vocabulary, comprising: receiving a spelling of the word, receiving an utterance of the word, creating a collection of possible phonetic pronunciations of the word by: comparing the spelling to a rules list of letter strings with associated phonemes, wherein the comparing includes searching the letter strings of the rules list for a letter string from the spelling of length greater than one letter, and limiting the collection of possible phonetic pronunciations to phonetic pronunciations containing phonemes associated with the letter string of length greater than one, using speech recognition to find a best-matching pronunciation from the collection that best matches the utterance of the word, and adding the word to the speech recognition vocabulary using the spelling and the best-matching pronunciation. 4. The method of claim 1 wherein the step of comparing includes starting the comparing with letter strings from the spelling beginning with a first letter of the spelling. | 0.5 |
9,405,807 | 1 | 16 | 1. An automated personnel recruitment system, comprising: a data storage; a database management system; at least one user's workstation having a processor and a memory for implementing the system; an automated search agent; an Internet data-collection agent configured to collect candidates' profile data from the Internet sources; a data-analyzing agent configured to analyze the candidates' profile data; a profile-comparing agent; an Internet data cache; and a cache data-extracting agent, wherein: the data storage contains verified candidates' profile data; the user's workstation is connected to the automated search agent and configured to receive search query parameters provided to the automated search agent; the database management system is configured to provide a search query input to the database and extract candidate-related data from the database according to the search query parameters; the data cache is configured to store the candidate-related data and group it according to candidates' identification data and Internet resources, from which the information was cached; the automated search agent is configured to search for data according to the query parameters entered by the user at the workstation and extract the candidate's profile data from the database according to the given criteria; the cache data-extracting agent is configured to search for entries corresponding to a search criteria and compare Internet profiles with the extracted database profiles, wherein the entries include a) his/her career progression based on the information in a resume or in a profile on a professional social network; (b) proficiency in a particular technology of companies the candidate worked at; or (c) “online reputation” of a candidate; the profile-comparing agent is configured to transfer cached data to the database, if the information, including professional skills and employment data, is verified against data from the Internet resources and corresponds to a real candidate's profile; and the profile-comparing agent is configured to store the data in the cache providing the database with a link to the cache entry, if the data is not verified and the correspondence is fuzzy. | 1. An automated personnel recruitment system, comprising: a data storage; a database management system; at least one user's workstation having a processor and a memory for implementing the system; an automated search agent; an Internet data-collection agent configured to collect candidates' profile data from the Internet sources; a data-analyzing agent configured to analyze the candidates' profile data; a profile-comparing agent; an Internet data cache; and a cache data-extracting agent, wherein: the data storage contains verified candidates' profile data; the user's workstation is connected to the automated search agent and configured to receive search query parameters provided to the automated search agent; the database management system is configured to provide a search query input to the database and extract candidate-related data from the database according to the search query parameters; the data cache is configured to store the candidate-related data and group it according to candidates' identification data and Internet resources, from which the information was cached; the automated search agent is configured to search for data according to the query parameters entered by the user at the workstation and extract the candidate's profile data from the database according to the given criteria; the cache data-extracting agent is configured to search for entries corresponding to a search criteria and compare Internet profiles with the extracted database profiles, wherein the entries include a) his/her career progression based on the information in a resume or in a profile on a professional social network; (b) proficiency in a particular technology of companies the candidate worked at; or (c) “online reputation” of a candidate; the profile-comparing agent is configured to transfer cached data to the database, if the information, including professional skills and employment data, is verified against data from the Internet resources and corresponds to a real candidate's profile; and the profile-comparing agent is configured to store the data in the cache providing the database with a link to the cache entry, if the data is not verified and the correspondence is fuzzy. 16. The system of claim 1 , wherein the candidate is ranked according to the level of correspondence of his profile to the profile of a potential superior. | 0.641204 |
8,224,523 | 15 | 16 | 15. A computer readable storage medium, storing instructions that, when executed by a processor in a vehicle computing system, cause the vehicle computing system to perform the method comprising: receiving a language designation or country code as part of a packet sent from a communication point and added to the packet by the communication point; and utilizing a local-language emergency database (LLED) whose language corresponds to the language designation as a basis for a vehicle-spoken language, wherein, if an emergency call is originated by a vehicle computing system (VCS), outgoing spoken communication produced by the VCS is based on words and/or phrases stored in the LLED. | 15. A computer readable storage medium, storing instructions that, when executed by a processor in a vehicle computing system, cause the vehicle computing system to perform the method comprising: receiving a language designation or country code as part of a packet sent from a communication point and added to the packet by the communication point; and utilizing a local-language emergency database (LLED) whose language corresponds to the language designation as a basis for a vehicle-spoken language, wherein, if an emergency call is originated by a vehicle computing system (VCS), outgoing spoken communication produced by the VCS is based on words and/or phrases stored in the LLED. 16. The computer readable storage medium of claim 15 , wherein the communication point is a cellular tower. | 0.916275 |
7,971,194 | 1 | 4 | 1. A method of processing a request from a client program, the method comprising: receiving a request for an application from a client program, wherein the client program is a modeling framework that enables applications to be developed; after receiving the request for the application from the client program, determining a first source code corresponding to the application, the first source code written in a first programming language, the first source code comprising code declaring at least a first object class that inherits from another object class; after the determining of the first source code corresponding to the application, compiling the first source code to generate a second source code in JavaScript, wherein the second source code is executable by the client program and usable in development of the applications to be developed; and executing the second source code using the client program, including: loading one or more classes identified in the second source code, loading one or more objects instantiated from the one or more classes, and partitioning, by a namespace manager of the client program, a namespace of the client program into at least a first namespace and a second namespace, wherein (1) a first class and a first object associated with the first programming language are loaded in the first namespace and (2) a second class and a second object associated with a JavaScript engine typically having a single global namespace are loaded in the second namespace. | 1. A method of processing a request from a client program, the method comprising: receiving a request for an application from a client program, wherein the client program is a modeling framework that enables applications to be developed; after receiving the request for the application from the client program, determining a first source code corresponding to the application, the first source code written in a first programming language, the first source code comprising code declaring at least a first object class that inherits from another object class; after the determining of the first source code corresponding to the application, compiling the first source code to generate a second source code in JavaScript, wherein the second source code is executable by the client program and usable in development of the applications to be developed; and executing the second source code using the client program, including: loading one or more classes identified in the second source code, loading one or more objects instantiated from the one or more classes, and partitioning, by a namespace manager of the client program, a namespace of the client program into at least a first namespace and a second namespace, wherein (1) a first class and a first object associated with the first programming language are loaded in the first namespace and (2) a second class and a second object associated with a JavaScript engine typically having a single global namespace are loaded in the second namespace. 4. The method of claim 1 wherein the first source code comprises one or more pragmas, the method further comprising: identifying, prior to the compiling, the one or more pragmas in the first source code; and substituting, prior to the compiling, each pragma in the one or more pragmas with a corresponding pragma output. | 0.5 |
10,048,765 | 1 | 5 | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause one or more processors to: acquire a depth image of a scene in a vicinity of a device, the first depth image having a first plurality of pixels, each pixel having a value indicative of a distance; store the depth image in a memory; develop a scene geometry based upon the depth image; determine that a user is engaging the device; identify a human hand in a region of space based on the values indicative of the distances of the first plurality of pixels; identify a three-dimensional region about the human hand, wherein the three-dimensional region includes at least some of the first plurality of pixels; partition the three-dimensional region about the human hand into a second plurality of sub-regions, each sub-region having a corresponding value and size, wherein the value of a particular sub-region comprises a number of human hand pixels within the particular sub-region, wherein the sizes of the sub-regions are configured so that the number of human hand pixels within each sub-region is approximately equal, and wherein the sizes of the sub-regions are non-uniform; generate a feature vector for the human hand based on the values of the second plurality of sub-regions; apply the feature vector to a classifier; determine that the human hand is making an identified gesture based on output from the classifier; and cause an action to be taken by the device, based, at least in part, upon the identified gesture and the scene geometry. | 1. A non-transitory program storage device, readable by a processor and comprising instructions stored thereon to cause one or more processors to: acquire a depth image of a scene in a vicinity of a device, the first depth image having a first plurality of pixels, each pixel having a value indicative of a distance; store the depth image in a memory; develop a scene geometry based upon the depth image; determine that a user is engaging the device; identify a human hand in a region of space based on the values indicative of the distances of the first plurality of pixels; identify a three-dimensional region about the human hand, wherein the three-dimensional region includes at least some of the first plurality of pixels; partition the three-dimensional region about the human hand into a second plurality of sub-regions, each sub-region having a corresponding value and size, wherein the value of a particular sub-region comprises a number of human hand pixels within the particular sub-region, wherein the sizes of the sub-regions are configured so that the number of human hand pixels within each sub-region is approximately equal, and wherein the sizes of the sub-regions are non-uniform; generate a feature vector for the human hand based on the values of the second plurality of sub-regions; apply the feature vector to a classifier; determine that the human hand is making an identified gesture based on output from the classifier; and cause an action to be taken by the device, based, at least in part, upon the identified gesture and the scene geometry. 5. The non-transitory program storage device of claim 1 , wherein the instructions to cause the one or more processors to identify a human hand comprise instructions to cause the one or more processors to use connected component analysis to identify one or more connected groups of pixels within the depth image. | 0.5 |
8,027,982 | 13 | 21 | 13. A computer program product embedded in a computer-readable storage medium for providing user-subscribed sources for secure search, comprising: program code for providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; program code for allowing a user to subscribe to the source using the template; program code for receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; program code for authenticating a crawler as the user on the source; program code for crawling the source as the user template with user-specified security credentials; program code for indexing documents for the user during the crawling in an index; and program code for stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user. | 13. A computer program product embedded in a computer-readable storage medium for providing user-subscribed sources for secure search, comprising: program code for providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; program code for allowing a user to subscribe to the source using the template; program code for receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; program code for authenticating a crawler as the user on the source; program code for crawling the source as the user template with user-specified security credentials; program code for indexing documents for the user during the crawling in an index; and program code for stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user. 21. A computer program product according to claim 13 , further comprising: program code for mapping the user-subscribed source to other secure sources. | 0.771903 |
6,041,355 | 3 | 4 | 3. The method of claim 1 wherein the completion decision determines whether only a partial transfer is allowed to occur. | 3. The method of claim 1 wherein the completion decision determines whether only a partial transfer is allowed to occur. 4. The method of claim 3 wherein text but not pictures are allowed to be transferred. | 0.5 |
6,092,035 | 17 | 21 | 17. A server device comprising: a source text input unit for inputting source text data in a predetermined language; a source text analyzing unit that analyzes the source text data by meaning and grammatical significance, the source text analyzing unit generating a plurality of candidates when vagueness in the source text data enables more than one interpretation of the source text data; and an analysis result display unit that automatically displays the plurality of candidates generated by the source text analyzing unit. | 17. A server device comprising: a source text input unit for inputting source text data in a predetermined language; a source text analyzing unit that analyzes the source text data by meaning and grammatical significance, the source text analyzing unit generating a plurality of candidates when vagueness in the source text data enables more than one interpretation of the source text data; and an analysis result display unit that automatically displays the plurality of candidates generated by the source text analyzing unit. 21. A server device as claimed in claim 17, wherein the analysis result display unit displays the plurality of candidates generated by the source text analyzing unit as sentences, each sentence including parentheses for indicating the corresponding interpretation of the source text data. | 0.50173 |
7,533,034 | 1 | 11 | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. 11. The method according to claim 1 , wherein determining the network routing is dependent in part on a business group that is selected on a template by the user. | 0.703297 |
9,471,064 | 10 | 12 | 10. A non-transitory article of manufacture tangibly embodying computer readable instructions, which when implemented, cause a computer to perform the steps of a method for controlling one or more drones to respond to a request for information, comprising; receiving a natural language request for information about a spatial location; parsing the natural language request into a plurality of data requests; searching for existing sources for the plurality of data requests: determining that there are one or more existing sources for one or more of the plurality of data requests; analyzing the existing sources to obtain first data responsive to the plurality of data requests; determining that there are no existing sources for two or more of the plurality of data requests and identifying the data requests with no existing source as missing data requests; configuring a flight plan for one or more drones over the spatial location based on the plurality of data requests and based on the missing data requests; controlling one or more drones to fly over the spatial location according to the configured flight plan to obtain a plurality of data types from the spatial location based on the plurality of data requests and based on the missing data requests; extracting a plurality of data points responsive to the plurality of data requests from the plurality of data types obtained by the one or more drones; obtaining labels from a user for one or more of the plurality of data points; determining whether there are unlabeled data points; predicting labels for the unlabeled data points from a learning algorithm using the labels obtained from the user; determining the predicted labels are true labels for the unlabeled data points; analyzing the responsive data to provide an answer to the natural language request for information, the analyzing including combining the first data, the user labeled data points and the true labeled data points to provide an answer to the first natural language request for information. | 10. A non-transitory article of manufacture tangibly embodying computer readable instructions, which when implemented, cause a computer to perform the steps of a method for controlling one or more drones to respond to a request for information, comprising; receiving a natural language request for information about a spatial location; parsing the natural language request into a plurality of data requests; searching for existing sources for the plurality of data requests: determining that there are one or more existing sources for one or more of the plurality of data requests; analyzing the existing sources to obtain first data responsive to the plurality of data requests; determining that there are no existing sources for two or more of the plurality of data requests and identifying the data requests with no existing source as missing data requests; configuring a flight plan for one or more drones over the spatial location based on the plurality of data requests and based on the missing data requests; controlling one or more drones to fly over the spatial location according to the configured flight plan to obtain a plurality of data types from the spatial location based on the plurality of data requests and based on the missing data requests; extracting a plurality of data points responsive to the plurality of data requests from the plurality of data types obtained by the one or more drones; obtaining labels from a user for one or more of the plurality of data points; determining whether there are unlabeled data points; predicting labels for the unlabeled data points from a learning algorithm using the labels obtained from the user; determining the predicted labels are true labels for the unlabeled data points; analyzing the responsive data to provide an answer to the natural language request for information, the analyzing including combining the first data, the user labeled data points and the true labeled data points to provide an answer to the first natural language request for information. 12. The non-transitory article of manufacture of claim 10 , wherein controlling the one or more drones comprises displaying the real-time telemetry and real-time flight conditions on a user interface (UI) in a mobile application. | 0.928882 |
8,626,509 | 1 | 9 | 1. A method comprising: receiving a first set of one or more features of at least a first part of a conversation between at least a first speaker and a second speaker; comparing, using at least one processor, the first set of one or more features of the at least the first part of the conversation to information regarding a node of a taxonomy of a domain specific model to determine whether the at least the first part of the conversation relates to a topic to which the node of the taxonomy corresponds, wherein the taxonomy of the domain specific model is hierarchical and comprises a plurality of nodes arranged in different levels of a hierarchy, wherein a higher-level node of the taxonomy corresponds to a broad topic and a lower-level node below the higher-level node in the taxonomy corresponds to a specific topic that relates to the broad topic and is more specific than the broad topic, and wherein comparing the first set of one or more features of the at least the first part of the conversation to the information regarding the node comprises comparing the first set of one or more features to information regarding the higher-level node of the taxonomy to determine whether the at least the first part of the conversation relates to the broad topic, wherein the comparing of the first set of one or more features to the information regarding the higher-level node has a first probability of providing a first prediction accuracy in identifying whether the at least the first part of the conversation relates to the broad topic; in response to determining that a result of the comparing indicates that the at least the first part of the conversation relates to the broad topic, presenting, to a user interface of a device operated by the first speaker, topic-specific information related to the broad topic; receiving a second set of one or more features of at least a second part of the conversation, the second part of the conversation including both the first part of the conversation and a subsequent part occurring in the conversation following the first part; in response to determining that the result of the comparing of the first set of the one or more features to the information regarding the higher-level node indicates that the at least the first part of the conversation relates to the broad topic, comparing the second set of one or more features of the first part and the subsequent part to information regarding the lower-level node to determine whether the at least the second part of the conversation relate to the specific topic related to the broad topic, wherein the comparing of the second set of one or more features to the information regarding the lower-level node has a second probability of providing a second prediction accuracy in identifying whether the at least the second part of the conversation relates to the specific topic, the second prediction accuracy being higher than the first prediction accuracy; and in response to determining that a result of the comparing of the second set of one or more features to the information regarding the lower-level node indicates that the at least the second part of the conversation relates to the specific topic, presenting to the first speaker topic-specific information related to the specific topic. | 1. A method comprising: receiving a first set of one or more features of at least a first part of a conversation between at least a first speaker and a second speaker; comparing, using at least one processor, the first set of one or more features of the at least the first part of the conversation to information regarding a node of a taxonomy of a domain specific model to determine whether the at least the first part of the conversation relates to a topic to which the node of the taxonomy corresponds, wherein the taxonomy of the domain specific model is hierarchical and comprises a plurality of nodes arranged in different levels of a hierarchy, wherein a higher-level node of the taxonomy corresponds to a broad topic and a lower-level node below the higher-level node in the taxonomy corresponds to a specific topic that relates to the broad topic and is more specific than the broad topic, and wherein comparing the first set of one or more features of the at least the first part of the conversation to the information regarding the node comprises comparing the first set of one or more features to information regarding the higher-level node of the taxonomy to determine whether the at least the first part of the conversation relates to the broad topic, wherein the comparing of the first set of one or more features to the information regarding the higher-level node has a first probability of providing a first prediction accuracy in identifying whether the at least the first part of the conversation relates to the broad topic; in response to determining that a result of the comparing indicates that the at least the first part of the conversation relates to the broad topic, presenting, to a user interface of a device operated by the first speaker, topic-specific information related to the broad topic; receiving a second set of one or more features of at least a second part of the conversation, the second part of the conversation including both the first part of the conversation and a subsequent part occurring in the conversation following the first part; in response to determining that the result of the comparing of the first set of the one or more features to the information regarding the higher-level node indicates that the at least the first part of the conversation relates to the broad topic, comparing the second set of one or more features of the first part and the subsequent part to information regarding the lower-level node to determine whether the at least the second part of the conversation relate to the specific topic related to the broad topic, wherein the comparing of the second set of one or more features to the information regarding the lower-level node has a second probability of providing a second prediction accuracy in identifying whether the at least the second part of the conversation relates to the specific topic, the second prediction accuracy being higher than the first prediction accuracy; and in response to determining that a result of the comparing of the second set of one or more features to the information regarding the lower-level node indicates that the at least the second part of the conversation relates to the specific topic, presenting to the first speaker topic-specific information related to the specific topic. 9. The method of claim 1 , wherein: the higher-level node of the taxonomy is associated with information comprising a first distribution of features in conversations related to the broad topic; the lower-level node of the taxonomy is associated with information comprising a second distribution of features in conversations related to the specific topic; comparing the first set of one or more features of the at least the first part of the conversation to the information regarding the higher-level node comprises comparing information regarding the first set of one or more features in the at least the first part of the conversation to the first distribution of features in conversations related to the broad topic to determine whether the at least the first part of the conversation relates to the broad topic; and comparing the second set of one or more features of the at least the second part of the conversation to the information regarding the lower-level node comprises comparing information regarding the second set of one or more features of the at least the second part of the conversation to the second distribution of features in conversations related to the specific topic to determine whether the at least the second part of the conversation relate to the specific topic. | 0.665802 |
8,484,028 | 1 | 10 | 1. A system for document navigation, comprising: a display; a display module displaying a text document on the display; a text-to-speech (“TTS”) engine converting a text of the text document into at least one audible sound; an audio module presenting the at least one audible sound; and a document navigation application displaying a section of the text document corresponding to the audible sound and navigating a displayed cursor indicating the text corresponding to the at least one audible sound as the at least one audible sound is played, wherein upon displaying the section of the document containing a link which points to a region of interest, the document navigation application pans to the region of interest pointed to by the link, when the link is referenced by the audible sound. | 1. A system for document navigation, comprising: a display; a display module displaying a text document on the display; a text-to-speech (“TTS”) engine converting a text of the text document into at least one audible sound; an audio module presenting the at least one audible sound; and a document navigation application displaying a section of the text document corresponding to the audible sound and navigating a displayed cursor indicating the text corresponding to the at least one audible sound as the at least one audible sound is played, wherein upon displaying the section of the document containing a link which points to a region of interest, the document navigation application pans to the region of interest pointed to by the link, when the link is referenced by the audible sound. 10. The system of claim 1 , further comprising a notification module that provides a notification if the TTS engine cannot convert a section of the text of the document into the at least one audible sound. | 0.5 |
8,150,697 | 1 | 4 | 1. A method of administering a plurality of managed systems in a managed network using a voice interface, the method comprising: storing a configuration data store comprising a system speech profile corresponding to at least one managed system of the plurality of managed systems, wherein the system speech profile specifies which capabilities of the at least one managed system are available on the managed network and which capabilities are to be voice-enabled and made accessible via a telephony interface; and automatically generating a grammar and a speech dialog for the at least one managed system using the system speech profile, wherein: the speech dialog for the at least one managed system includes at least one generated audio prompt that is played via a telephone in response to accessing, via the telephony interface, at least one of the capabilities of the at least one managed system that are specified in the system speech profile to be voice-enabled, and wherein the at least one of the voice enabled capabilities comprises at least one administrative function to administer the at least one managed system, the grammar is used to process speech input received from a user in response to the at least one generated audio prompt, the speech dialog allows the user to administer the at least one managed system by accessing the at least one administrative function via at least one voice command, and the at least one generated audio prompt comprises information extracted from a response from the at least one managed system responsive to the at least one voice command as dictated by the configuration data store. | 1. A method of administering a plurality of managed systems in a managed network using a voice interface, the method comprising: storing a configuration data store comprising a system speech profile corresponding to at least one managed system of the plurality of managed systems, wherein the system speech profile specifies which capabilities of the at least one managed system are available on the managed network and which capabilities are to be voice-enabled and made accessible via a telephony interface; and automatically generating a grammar and a speech dialog for the at least one managed system using the system speech profile, wherein: the speech dialog for the at least one managed system includes at least one generated audio prompt that is played via a telephone in response to accessing, via the telephony interface, at least one of the capabilities of the at least one managed system that are specified in the system speech profile to be voice-enabled, and wherein the at least one of the voice enabled capabilities comprises at least one administrative function to administer the at least one managed system, the grammar is used to process speech input received from a user in response to the at least one generated audio prompt, the speech dialog allows the user to administer the at least one managed system by accessing the at least one administrative function via at least one voice command, and the at least one generated audio prompt comprises information extracted from a response from the at least one managed system responsive to the at least one voice command as dictated by the configuration data store. 4. The method of claim 1 , further comprising an act of: providing an interface that enables a system administrator to manually edit the automatically generated speech dialog. | 0.666031 |
7,478,192 | 29 | 31 | 29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. | 29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. 31. An associative memory method according to claim 29 wherein observing into the network of feedback associative memory networks is preceded by: producing user-task IDs, related positive and/or negative evaluations and related selected data in response to selected data that has received a positive and/or negative evaluation from a respective user during a respective task; extracting entities from the related positive and/or negative evaluations and related selected data; and identifying observer entities and observed entities from the entities that are extracted. | 0.61642 |
7,761,844 | 1 | 14 | 1. A template-driven system for generating platform-specific artifacts from platform-independent service models, for implementing a service-oriented architecture the system comprising: a template storage with platform-specific templates, each template including platform-specific model transformation information; a repository with i. a plurality of platform-independent service model elements which are hierarchically structured and ii. two or more service models modeled from the service model elements wherein at least some of the service model elements are shared by two or more service models and wherein each service model is modeled from one or more first service model elements of a higher hierarchy level and one or more second service model elements of a lower hierarchy level and wherein an algorithm of a service model is specified by mappings between two or more service model elements; and a generator adapted to generate platform-specific artifacts by applying the platform-specific model transformation information included in the templates to the service models. | 1. A template-driven system for generating platform-specific artifacts from platform-independent service models, for implementing a service-oriented architecture the system comprising: a template storage with platform-specific templates, each template including platform-specific model transformation information; a repository with i. a plurality of platform-independent service model elements which are hierarchically structured and ii. two or more service models modeled from the service model elements wherein at least some of the service model elements are shared by two or more service models and wherein each service model is modeled from one or more first service model elements of a higher hierarchy level and one or more second service model elements of a lower hierarchy level and wherein an algorithm of a service model is specified by mappings between two or more service model elements; and a generator adapted to generate platform-specific artifacts by applying the platform-specific model transformation information included in the templates to the service models. 14. The system of claim 1 , further comprising a plurality of predefined platform types. | 0.803571 |
8,281,149 | 32 | 37 | 32. The computer-readable medium of claim 31 , wherein receiving the first representation of the access token from the IdP further comprises: generating an original token; modifying the original token to obtain a modified token; and providing the modified token to the IdP to obtain an access token for accessing the RP. | 32. The computer-readable medium of claim 31 , wherein receiving the first representation of the access token from the IdP further comprises: generating an original token; modifying the original token to obtain a modified token; and providing the modified token to the IdP to obtain an access token for accessing the RP. 37. The computer-readable medium of claim 32 , wherein one or more of the original token, the modified token, and the signed modified token encode a partial disclosure based on one or more characteristics of the user known to the IdP, the partial disclosure being a confirmation of at least some characteristics required for user access at the RP. | 0.5 |
7,698,254 | 13 | 14 | 13. The method of claim 1 , wherein rescoring includes calculating a phrase score for the query. | 13. The method of claim 1 , wherein rescoring includes calculating a phrase score for the query. 14. The method of claim 13 , wherein the phrase score is given by sp item = l - d phrase l where l is the length of the phrase and d phrase is the edit distance between the phrase and a reference phrase. | 0.5 |
9,881,610 | 1 | 5 | 1. An apparatus, comprising: a memory; and a processor operatively coupled to the memory and configured to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein, in the obtaining of the non-acoustic data, the processor is configured to capture visual data of the vicinity of the speech input; identify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein, in the identification of the subject speaker, the processor is configured to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system. | 1. An apparatus, comprising: a memory; and a processor operatively coupled to the memory and configured to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein, in the obtaining of the non-acoustic data, the processor is configured to capture visual data of the vicinity of the speech input; identify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein, in the identification of the subject speaker, the processor is configured to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system. 5. The apparatus of claim 1 , wherein the one or more non-acoustic attributes comprise one or more facial features of the subject speaker extracted from the selected face, and wherein the analysis of the extracted one or more non-acoustic attributes further comprises a mapping of the selected face to a cluster to infer one or more characteristics of the subject speaker. | 0.5 |
9,384,292 | 8 | 14 | 8. One or more computer storage media implemented at least in part on hardware and including executable instructions that, when executed by a computing device, cause the computing device to perform a method comprising: identifying, by a linguistic service and from content received from an application, an action to be performed that is not performable by the linguistic service, the content being usable to perform the action; responsive to identifying the action to be performed, accessing, by the linguistic service, a customization webpage that is configured to customize the content according to one or more criteria specified for the action to generate customized content, the one or more criteria specified by the application; accessing another webpage that is to perform the action based on the customized content, the other webpage being separate from the application; and causing, by the linguistic service, the customization webpage to communicate the customized content to the other webpage that is to perform the action. | 8. One or more computer storage media implemented at least in part on hardware and including executable instructions that, when executed by a computing device, cause the computing device to perform a method comprising: identifying, by a linguistic service and from content received from an application, an action to be performed that is not performable by the linguistic service, the content being usable to perform the action; responsive to identifying the action to be performed, accessing, by the linguistic service, a customization webpage that is configured to customize the content according to one or more criteria specified for the action to generate customized content, the one or more criteria specified by the application; accessing another webpage that is to perform the action based on the customized content, the other webpage being separate from the application; and causing, by the linguistic service, the customization webpage to communicate the customized content to the other webpage that is to perform the action. 14. The one or more computer storage media as described in claim 8 , the method further comprising: populating a file format with a set of parameters that are usable by the other webpage to perform the action; and passing the set of parameters to the other webpage that is to perform the action. | 0.567449 |
8,117,549 | 1 | 25 | 1. A method of capturing actions that are performed on at least one medical image of a patient during a medical imaging interpretation, the method being implemented using a computer system, the method comprising: (a) displaying a workflow template on a display of the computer system; (b) displaying the at least one medical image of the patient on said display; (c) automatically extracting data from an electronic medical record of the patient, or other data related to the patient, from a database, into said workflow template provided on said display; (d) capturing and storing one or more user actions as they are performed on the medical image of the patient, by an interpreting user during an entire medical imaging interpretation, using an auditing function of the computer system; (e) automatically generating user action information from the one or more captured actions, to prompt said user to perform certain actions; (f) storing the captured user actions and user action information, along with said data related to the patient, in said database, with the at least one medical image of the patient, as a new workflow sequence onto a new workflow template as a pre-defined protocol; (g) accessing said new workflow template having said pre-defined protocol from said database; (h) displaying to a new user, in said new workflow template, a recreation of the exact pre-defined protocol including said data related to the patient, stored by said previous interpreting user in said database, as a continuous replica of said previous interpreting user's actions and user action information stored in said workflow sequence, such that said new user may selectively review and modify clinically pertinent medical images and said data related to the patient, in a continuous manner that follows said stored workflow template as created by said previous interpreting user; and (i) repeating steps (b)-(f), such that a modified new workflow template is created and stored in said database: wherein each said modified new workflow template is a cumulative, refined, and dynamic workflow sequence of a series of said captured user actions and user action information, along with data related to each patient, with the at least one medical image of said patient, in order to provide best practice of said medical image interpretation for said user. | 1. A method of capturing actions that are performed on at least one medical image of a patient during a medical imaging interpretation, the method being implemented using a computer system, the method comprising: (a) displaying a workflow template on a display of the computer system; (b) displaying the at least one medical image of the patient on said display; (c) automatically extracting data from an electronic medical record of the patient, or other data related to the patient, from a database, into said workflow template provided on said display; (d) capturing and storing one or more user actions as they are performed on the medical image of the patient, by an interpreting user during an entire medical imaging interpretation, using an auditing function of the computer system; (e) automatically generating user action information from the one or more captured actions, to prompt said user to perform certain actions; (f) storing the captured user actions and user action information, along with said data related to the patient, in said database, with the at least one medical image of the patient, as a new workflow sequence onto a new workflow template as a pre-defined protocol; (g) accessing said new workflow template having said pre-defined protocol from said database; (h) displaying to a new user, in said new workflow template, a recreation of the exact pre-defined protocol including said data related to the patient, stored by said previous interpreting user in said database, as a continuous replica of said previous interpreting user's actions and user action information stored in said workflow sequence, such that said new user may selectively review and modify clinically pertinent medical images and said data related to the patient, in a continuous manner that follows said stored workflow template as created by said previous interpreting user; and (i) repeating steps (b)-(f), such that a modified new workflow template is created and stored in said database: wherein each said modified new workflow template is a cumulative, refined, and dynamic workflow sequence of a series of said captured user actions and user action information, along with data related to each patient, with the at least one medical image of said patient, in order to provide best practice of said medical image interpretation for said user. 25. The method according to claim 1 , wherein said workflow template is a continuous video replica of said previous interpreting user's actions and user action information, and is presented as a workflow movie in real-time. | 0.83675 |
8,175,583 | 1 | 3 | 1. A method executable on a wireless mobile device for automatically drafting blog entries, the method comprising: detecting a triggering event for generating a draft blog entry, the triggering event comprises browsing a webpage having a URL, on the wireless mobile device, for at least a predetermined threshold time period, the predetermined threshold time period being configurable according to user preference; upon detection of the triggering event, obtaining and storing GPS coordinates and automatically generating the draft blog entry in a predetermined format, the GPS coordinates being stored at least within the draft blog entry; and generating a blogging tour map based on the GPS coordinates within the draft blog entry, the blogging tour map comprising a plurality of nodes, each node representing an automatically generated blog entry, and where each node is situated on at a location on the geographical map based on the GPS coordinates. | 1. A method executable on a wireless mobile device for automatically drafting blog entries, the method comprising: detecting a triggering event for generating a draft blog entry, the triggering event comprises browsing a webpage having a URL, on the wireless mobile device, for at least a predetermined threshold time period, the predetermined threshold time period being configurable according to user preference; upon detection of the triggering event, obtaining and storing GPS coordinates and automatically generating the draft blog entry in a predetermined format, the GPS coordinates being stored at least within the draft blog entry; and generating a blogging tour map based on the GPS coordinates within the draft blog entry, the blogging tour map comprising a plurality of nodes, each node representing an automatically generated blog entry, and where each node is situated on at a location on the geographical map based on the GPS coordinates. 3. The method of claim 1 , further comprising automatically generating text for insertion into the draft blog entry in the predetermined format, and wherein some of the text is generated in dependence upon data relating to the defined triggering event. | 0.627219 |
8,057,517 | 9 | 10 | 9. The dynamic spine stabilization component of claim 1 , in combination with a bone screw, wherein: the dynamic spine stabilization component is mounted within a bore in a proximal end of the bone screw in alignment with a longitudinal axis of the bone screw and the fastener secures the component in the bone screw. | 9. The dynamic spine stabilization component of claim 1 , in combination with a bone screw, wherein: the dynamic spine stabilization component is mounted within a bore in a proximal end of the bone screw in alignment with a longitudinal axis of the bone screw and the fastener secures the component in the bone screw. 10. The dynamic spine stabilization of claim 9 , in combination with a vertical rod secured to the second end of the deflectable post. | 0.5 |
8,606,578 | 8 | 11 | 8. An apparatus comprising: a microphone to receive speech; a processor; and a computer-readable medium storing instructions that when executed by the processor: buffer N audio frames of a plurality of audio frames associated with an audio signal, where N is greater than 1; pre-compute scores for a subset of context dependent models (CDMs); perform a graphical model search associated with the N audio frames; determine that a score of a context independent model (CIM) associated with a CDM and an audio frame is to be used in lieu of a score for the CDM when a score for the CDM is required by the graphical model search and the score for the CDM has not been pre-computed; pre-compute all scores of CIMs associated with the N frames; and store the pre-computed scores associated with the CIMs in a context independent score cache (CI-CACHE) wherein determining the CIM score associated with the CDM comprises retrieving a score from the CI-CACHE based on a CIM to CDM mapping table. | 8. An apparatus comprising: a microphone to receive speech; a processor; and a computer-readable medium storing instructions that when executed by the processor: buffer N audio frames of a plurality of audio frames associated with an audio signal, where N is greater than 1; pre-compute scores for a subset of context dependent models (CDMs); perform a graphical model search associated with the N audio frames; determine that a score of a context independent model (CIM) associated with a CDM and an audio frame is to be used in lieu of a score for the CDM when a score for the CDM is required by the graphical model search and the score for the CDM has not been pre-computed; pre-compute all scores of CIMs associated with the N frames; and store the pre-computed scores associated with the CIMs in a context independent score cache (CI-CACHE) wherein determining the CIM score associated with the CDM comprises retrieving a score from the CI-CACHE based on a CIM to CDM mapping table. 11. The apparatus of claim 8 , further comprising instruction to: store the pre-computed scores in a current frame score buffer (CFSB); store data indicating a first plurality of active CDMs; and update the data to indicate a second plurality of active CDMs based on a Viterbi search. | 0.5 |
7,711,105 | 1 | 11 | 1. A method of processing a call received by a call center, comprising the steps of: obtaining a call at the call center; automatically identifying at least one of an accent and a language spoken by a caller making the call; directing the call to an appropriate operator at a first level of the call center based on at least one of the automatically identified accent and the automatically identified language; automatically translating speech associated with the call from at least one of the automatically identified accent and the automatically identified language spoken by the caller to at least one of an accent and a language understood by an operator at a second level of the call center; and directing the caller to the operator at the second level after the step of directing the call to an appropriate operator at a first level; wherein the call center comprises tiered levels of assistance comprising the first level providing primary assistance and the second level, providing more intense assistance. | 1. A method of processing a call received by a call center, comprising the steps of: obtaining a call at the call center; automatically identifying at least one of an accent and a language spoken by a caller making the call; directing the call to an appropriate operator at a first level of the call center based on at least one of the automatically identified accent and the automatically identified language; automatically translating speech associated with the call from at least one of the automatically identified accent and the automatically identified language spoken by the caller to at least one of an accent and a language understood by an operator at a second level of the call center; and directing the caller to the operator at the second level after the step of directing the call to an appropriate operator at a first level; wherein the call center comprises tiered levels of assistance comprising the first level providing primary assistance and the second level, providing more intense assistance. 11. The method of claim 1 , wherein the step of automatically identifying at least one of an accent and a language spoken by a caller making the call further comprises phonetically decoding at least a portion of the original speech in a particular language. | 0.574503 |
9,990,923 | 10 | 11 | 10. A system for automated execution of computer software using intelligent speech recognition techniques, the system comprising: a server computing device configured to capture a bitstream containing a digitized voice segment from a remote device as a speech file, the digitized voice segment corresponding to speech submitted by a user of the remote device during a voice call; parse the bitstream to locate the digitized voice segment; adjust compression of the bitstream containing the digitized voice segment to enhance audio quality of the bitstream; analyze the speech file to convert the speech file into text and extract a set of keywords from the converted text; determine one or more computer software applications accessible to the client computing device; and select at least one of the computer software applications that include functionality responsive to the keywords, comprising: generating, using a sequenced bag-of-words processing model, an input vector comprising a sequence of numeric values, each value associated with a keyword and weighted according to a relative position of the keyword in the set of keywords, matching, using a K-Nearest Neighbor processing model, the input vector against a predefined set of vectors to determine one or more vectors that are similar to the input vector, identifying a label corresponding to each matched vector, wherein the label is associated with computer software functionality, and selecting one or more computer software applications that are associated with a most common label of the identified labels; and a client computing device coupled to the server computing device, the client computing device configured to display the extracted keywords in a user interface of a display device; and execute the functionality of the selected computer software applications that is responsive to the keywords. | 10. A system for automated execution of computer software using intelligent speech recognition techniques, the system comprising: a server computing device configured to capture a bitstream containing a digitized voice segment from a remote device as a speech file, the digitized voice segment corresponding to speech submitted by a user of the remote device during a voice call; parse the bitstream to locate the digitized voice segment; adjust compression of the bitstream containing the digitized voice segment to enhance audio quality of the bitstream; analyze the speech file to convert the speech file into text and extract a set of keywords from the converted text; determine one or more computer software applications accessible to the client computing device; and select at least one of the computer software applications that include functionality responsive to the keywords, comprising: generating, using a sequenced bag-of-words processing model, an input vector comprising a sequence of numeric values, each value associated with a keyword and weighted according to a relative position of the keyword in the set of keywords, matching, using a K-Nearest Neighbor processing model, the input vector against a predefined set of vectors to determine one or more vectors that are similar to the input vector, identifying a label corresponding to each matched vector, wherein the label is associated with computer software functionality, and selecting one or more computer software applications that are associated with a most common label of the identified labels; and a client computing device coupled to the server computing device, the client computing device configured to display the extracted keywords in a user interface of a display device; and execute the functionality of the selected computer software applications that is responsive to the keywords. 11. The system of claim 10 , wherein when matching the input vector, the server computing device is configured to determine a distance between the input vector and each vector in the predefined set of vectors; and choose one or more of vectors in the predefined set of vectors where the distance is within a predetermined threshold. | 0.5 |
8,209,177 | 4 | 6 | 4. The system according to claim 1 , wherein said voice recognition unit performs voice recognition for each articulation period of the user, which is delimited at delimiting points detected by said articulation delimiting points detecting unit, and sets a voice-recognized character string for each articulation period as a partial character string, and said talk-back voice output unit outputs a voice which reads out, in the voice-recognized order, said partial character strings in a manner such that the character string is delimited into each partial character string. | 4. The system according to claim 1 , wherein said voice recognition unit performs voice recognition for each articulation period of the user, which is delimited at delimiting points detected by said articulation delimiting points detecting unit, and sets a voice-recognized character string for each articulation period as a partial character string, and said talk-back voice output unit outputs a voice which reads out, in the voice-recognized order, said partial character strings in a manner such that the character string is delimited into each partial character string. 6. The system according to claim 4 , wherein said talk-back voice output unit outputs a voice which reads out, in the voice-recognized order, said partial character strings in a manner such that the string is delimited by a predetermined sound effect. | 0.5 |
9,547,696 | 1 | 2 | 1. A computer-implemented method for providing ranked content to a user according to a location-based query log analysis, the method comprising: receiving, at one or more processors in a client device via a user interface, a selection of a viewport defining an area of interest corresponding to a region; receiving, at the one or more processors via the user interface, a geographic search query associated with the region; determining, by the one or more processors, a plurality of content items in response to the geographic search query and ranking each of the plurality of content items; truncating, by the one or more processors, at least one of the plurality of content items which is ranked below a predetermined threshold ranking, wherein a number of content items ranked above the predetermined threshold ranking is based on a size of the viewport to reduce an amount of information displayed on the viewport; and displaying, by the one or more processors on the user interface, the viewport annotated with indications of a smaller number of content items than the plurality of content items in accordance with the predetermined threshold ranking. | 1. A computer-implemented method for providing ranked content to a user according to a location-based query log analysis, the method comprising: receiving, at one or more processors in a client device via a user interface, a selection of a viewport defining an area of interest corresponding to a region; receiving, at the one or more processors via the user interface, a geographic search query associated with the region; determining, by the one or more processors, a plurality of content items in response to the geographic search query and ranking each of the plurality of content items; truncating, by the one or more processors, at least one of the plurality of content items which is ranked below a predetermined threshold ranking, wherein a number of content items ranked above the predetermined threshold ranking is based on a size of the viewport to reduce an amount of information displayed on the viewport; and displaying, by the one or more processors on the user interface, the viewport annotated with indications of a smaller number of content items than the plurality of content items in accordance with the predetermined threshold ranking. 2. The method of claim 1 , wherein determining a plurality of content items in response to the geographic search query includes: transmitting, by the one or more processors, the area of interest corresponding to the region and the geographic search query associated with the region to a content management system; and receiving, at the one or more processors, the plurality of content items from the content management system based on the area of interest and the geographic search query. | 0.5 |
10,057,305 | 12 | 16 | 12. A system, comprising: one or more processors; a display that supports a user interface (UI) for interacting with a local device; and a memory storing computer-readable instructions which, when executed by the one or more processors, cause the processors to: configure a portion of the UI for preparation of a presentation of content selected for sharing that is yet to be shared and for separation of the content selected for sharing that is yet to be shared from a collection of shareable content, separate an active sharing window on the UI from the portion of the UI configured for preparation of a presentation of the content selected for sharing that is yet to be shared so that privacy is maintained for the content selected for sharing that is not placed in the active sharing window for sharing with a remote device, provide tools on the local device for creating credits for the content selected for sharing, the credits including one or more of animation, identification of shared content that is tagged, links to related content, or links to related user experiences, receive an instruction to control the active sharing window membership by adding the subset of the content selected for sharing to the active sharing window and deleting content from the active sharing window, share content from the active sharing window with the remote device over a network, the active sharing window being configured so that the local device controls pacing of content sharing from the active sharing window, and provide, from the local device, temporary control to the remote device such that the remote device is provided permission to temporarily control a presentation of the content displayed on the local and remote devices. | 12. A system, comprising: one or more processors; a display that supports a user interface (UI) for interacting with a local device; and a memory storing computer-readable instructions which, when executed by the one or more processors, cause the processors to: configure a portion of the UI for preparation of a presentation of content selected for sharing that is yet to be shared and for separation of the content selected for sharing that is yet to be shared from a collection of shareable content, separate an active sharing window on the UI from the portion of the UI configured for preparation of a presentation of the content selected for sharing that is yet to be shared so that privacy is maintained for the content selected for sharing that is not placed in the active sharing window for sharing with a remote device, provide tools on the local device for creating credits for the content selected for sharing, the credits including one or more of animation, identification of shared content that is tagged, links to related content, or links to related user experiences, receive an instruction to control the active sharing window membership by adding the subset of the content selected for sharing to the active sharing window and deleting content from the active sharing window, share content from the active sharing window with the remote device over a network, the active sharing window being configured so that the local device controls pacing of content sharing from the active sharing window, and provide, from the local device, temporary control to the remote device such that the remote device is provided permission to temporarily control a presentation of the content displayed on the local and remote devices. 16. The system of claim 12 in which the memory further comprises instructions that cause the processor to arrange the active sharing window to show content items in the shared content one at a time under control of the local device. | 0.57971 |
7,577,682 | 1 | 2 | 1. A computer-implemented method of providing access to information stored in diverse formats, the method comprising: receiving from an application a semantic request having a request name that semantically identifies a type of information sought by the request, the semantic request comprising a uniform resource identifier; converting, at a semantic object provider, the received semantic request to a generic request having corresponding request parameters, the semantic object provider comprising a semantic object class defining an application programming interface to create an object, a semantic object implementation class to provide persistency to information related to a class, and an object registry to interact with a class implemented by a repository; initiating, by the semantic object provider, a creation of the object for receiving and converting the semantic request; opening a database connection within a data access system corresponding to the semantic request; requesting properties of data corresponding to the semantic request, if a database connection has not previously been opened; transmitting the converted request to the a data access system; receiving data from the data access system corresponding to the converted request; and providing the data to the application. | 1. A computer-implemented method of providing access to information stored in diverse formats, the method comprising: receiving from an application a semantic request having a request name that semantically identifies a type of information sought by the request, the semantic request comprising a uniform resource identifier; converting, at a semantic object provider, the received semantic request to a generic request having corresponding request parameters, the semantic object provider comprising a semantic object class defining an application programming interface to create an object, a semantic object implementation class to provide persistency to information related to a class, and an object registry to interact with a class implemented by a repository; initiating, by the semantic object provider, a creation of the object for receiving and converting the semantic request; opening a database connection within a data access system corresponding to the semantic request; requesting properties of data corresponding to the semantic request, if a database connection has not previously been opened; transmitting the converted request to the a data access system; receiving data from the data access system corresponding to the converted request; and providing the data to the application. 2. The computer-implemented method of claim 1 , further comprising typecasting the data received from the data access system before providing the data to the application. | 0.5 |
9,305,085 | 1 | 2 | 1. A method of handling queries for an online discussion forum, said method comprising: receiving a query; automatically classifying the query as subjective or objective; thereupon calculating, for discussion threads of the query, at least one of: a subjectivity score and an objectivity score; said calculating comprising: applying a maximum entropy model; and incorporating, with respect to at least one discussion thread, at least one member taken from the group consisting of: a number of posts in a discussion thread; average number of words in posts, presence of a predetermined pattern among posts, a number of authors of posts within a discussion thread, average depth of each post, maximum depth of a post, and length of at least one reply; and determining a degree of relevance to the query of: the discussion threads, and at least one post in the at least one discussion thread; said determining of the degree of relevance of the query to the discussion threads comprising: iteratively determining a relevance score with respect to each post in a discussion thread and then accepting a maximum relevance score with respect to a post in a discussion thread; determining a penalty or reward regulizer with respect to choosing a predetermined number of posts for calculating a relevance score of a thread; and including at least one of: a subjectivity score of the thread and an objectivity score of the thread; and ranking the discussion threads based on said calculating and determining of a degree of relevance of the query to the discussion threads. | 1. A method of handling queries for an online discussion forum, said method comprising: receiving a query; automatically classifying the query as subjective or objective; thereupon calculating, for discussion threads of the query, at least one of: a subjectivity score and an objectivity score; said calculating comprising: applying a maximum entropy model; and incorporating, with respect to at least one discussion thread, at least one member taken from the group consisting of: a number of posts in a discussion thread; average number of words in posts, presence of a predetermined pattern among posts, a number of authors of posts within a discussion thread, average depth of each post, maximum depth of a post, and length of at least one reply; and determining a degree of relevance to the query of: the discussion threads, and at least one post in the at least one discussion thread; said determining of the degree of relevance of the query to the discussion threads comprising: iteratively determining a relevance score with respect to each post in a discussion thread and then accepting a maximum relevance score with respect to a post in a discussion thread; determining a penalty or reward regulizer with respect to choosing a predetermined number of posts for calculating a relevance score of a thread; and including at least one of: a subjectivity score of the thread and an objectivity score of the thread; and ranking the discussion threads based on said calculating and determining of a degree of relevance of the query to the discussion threads. 2. The method according to claim 1 , wherein said determining comprises determining a degree of relevance to the query of both of: the discussion threads, and at least one post in the discussion threads. | 0.757177 |
9,253,134 | 1 | 6 | 1. A computer-implemented method comprising: determining, at a server, a first topic for a conversation received from a first user; determining, at the server, location information related to a first location of a computing device associated with the first user; creating, at the server, one or more conversation objects that include the first topic; tagging the one or more conversation objects with the location information; indexing the one or more conversation objects in one or more indexes that include one or more other conversation objects that include the first topic by: updating the one or more indexes of conversation objects to include the one or more conversation objects based on one or more conversation parameters, and wherein the one or more conversation parameters include the first topic, messages associated with each of the one or more conversation objects, and the location information associated with each of the one or more conversation objects; and sorting the one or more conversation objects and the one or more other conversation objects included in the one or more indexes based on a level of message activity over a certain period of time for the messages associated with each conversation object and other messages associated with each other conversation object; receiving one or more search parameters from a second user, wherein the one or more search parameters include at least one second topic corresponding to the first topic for the conversation and at least one second location corresponding to the first location associated with the one or more conversation objects; and providing the sorted one or more conversation objects and the one or more other conversation topics to the second user in response to receiving the one or more search parameters. | 1. A computer-implemented method comprising: determining, at a server, a first topic for a conversation received from a first user; determining, at the server, location information related to a first location of a computing device associated with the first user; creating, at the server, one or more conversation objects that include the first topic; tagging the one or more conversation objects with the location information; indexing the one or more conversation objects in one or more indexes that include one or more other conversation objects that include the first topic by: updating the one or more indexes of conversation objects to include the one or more conversation objects based on one or more conversation parameters, and wherein the one or more conversation parameters include the first topic, messages associated with each of the one or more conversation objects, and the location information associated with each of the one or more conversation objects; and sorting the one or more conversation objects and the one or more other conversation objects included in the one or more indexes based on a level of message activity over a certain period of time for the messages associated with each conversation object and other messages associated with each other conversation object; receiving one or more search parameters from a second user, wherein the one or more search parameters include at least one second topic corresponding to the first topic for the conversation and at least one second location corresponding to the first location associated with the one or more conversation objects; and providing the sorted one or more conversation objects and the one or more other conversation topics to the second user in response to receiving the one or more search parameters. 6. The method of claim 1 , further comprising: receiving a request from the first user to create the one or more conversation objects, and wherein: determining the location information related to the first location of the computing device associated with the first user comprises receiving the location information that indicates the first location of the first user at a time the request to create the one or more conversation objects was received from the first user; and tagging the one or more conversation objects with the location information comprises: tagging the one or more conversation objects with the first location of the first user at the time the request to create the one or more conversation objects was received from the first user; and maintaining the first location with the one or more conversation objects regardless of whether a current location of the first user changes. | 0.5 |
9,864,509 | 10 | 14 | 10. A method comprising: at an electronic device with one or more processors and memory: generating a user interface for display on a display device, wherein the user interface includes a candidate character region; while the user interface is displayed on the display device, receiving an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device; in response to detecting the movement of the contact, identifying a first candidate character that corresponds to the movement, and updating the user interface to include the first candidate character in the candidate character region; receiving a request to delete the first candidate character; and in response to receiving the request to delete the first candidate character and prior to receiving an input to replace the first candidate character with a different candidate character from a first plurality of other candidate characters, updating the user interface by: deleting the first candidate character in the candidate character region; and displaying a first plurality of other candidate characters that correspond to the movement of the contact in place of the first candidate character. | 10. A method comprising: at an electronic device with one or more processors and memory: generating a user interface for display on a display device, wherein the user interface includes a candidate character region; while the user interface is displayed on the display device, receiving an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device; in response to detecting the movement of the contact, identifying a first candidate character that corresponds to the movement, and updating the user interface to include the first candidate character in the candidate character region; receiving a request to delete the first candidate character; and in response to receiving the request to delete the first candidate character and prior to receiving an input to replace the first candidate character with a different candidate character from a first plurality of other candidate characters, updating the user interface by: deleting the first candidate character in the candidate character region; and displaying a first plurality of other candidate characters that correspond to the movement of the contact in place of the first candidate character. 14. The method of claim 10 , wherein the candidate character region in the user interface comprises a text entry field. | 0.949704 |
8,359,342 | 9 | 12 | 9. An XML database management system (XDBMS) for generating at least one index over XML documents in an XML database, the system comprising: at least one processor configured to execute at least one indexing function that takes as input an XML document and returns at least one computed result; and a non-transitory computer readable storage medium configured to store: at least one library module comprising the at least one indexing function defined in the XQuery language, each said indexing function being configured to accept an XML document as input and to return at least one computed result; the at least one computed result from the at least one indexing function as a key of the corresponding index, wherein the at least one indexing function is configured to return at least one XML substructure and wherein the at least one processor is further configured to map each said XML substructure onto a tuple of type values and to store each of the tuples as a key of the index. | 9. An XML database management system (XDBMS) for generating at least one index over XML documents in an XML database, the system comprising: at least one processor configured to execute at least one indexing function that takes as input an XML document and returns at least one computed result; and a non-transitory computer readable storage medium configured to store: at least one library module comprising the at least one indexing function defined in the XQuery language, each said indexing function being configured to accept an XML document as input and to return at least one computed result; the at least one computed result from the at least one indexing function as a key of the corresponding index, wherein the at least one indexing function is configured to return at least one XML substructure and wherein the at least one processor is further configured to map each said XML substructure onto a tuple of type values and to store each of the tuples as a key of the index. 12. The system of claim 9 , wherein the at least one processor is further configured to optimize an XQuery that comprises at least one call of an indexing function by scanning the corresponding index of the indexing function when processing the XQuery. | 0.633721 |
8,548,951 | 5 | 7 | 5. The method of claim 1 , further comprising forming a blurred feature-based representation of the document by modifying the feature-based vector based on the reconstructed feature-based vector. | 5. The method of claim 1 , further comprising forming a blurred feature-based representation of the document by modifying the feature-based vector based on the reconstructed feature-based vector. 7. The method of claim 5 , wherein the unified representation for the document is constructed further based on the blurred feature-based representation of the document. | 0.816193 |
7,567,895 | 1 | 13 | 1. A method in a computer system for classifying sentences, the method comprising: providing training sentences and their classifications; generating feature representations of the sentences; training a sentence classifier to classify sentences based on the generated feature representations and the classifications of the sentences they represent; receiving a sentence; generating a feature representation of the sentence; and applying the trained sentence classifier to the generated feature representation of the sentence to classify the sentence; wherein the feature representations include a pattern feature, and wherein the pattern feature is based on support of a generalized sentence of a sentence to be a generalized sentence pattern of sentences within training data. | 1. A method in a computer system for classifying sentences, the method comprising: providing training sentences and their classifications; generating feature representations of the sentences; training a sentence classifier to classify sentences based on the generated feature representations and the classifications of the sentences they represent; receiving a sentence; generating a feature representation of the sentence; and applying the trained sentence classifier to the generated feature representation of the sentence to classify the sentence; wherein the feature representations include a pattern feature, and wherein the pattern feature is based on support of a generalized sentence of a sentence to be a generalized sentence pattern of sentences within training data. 13. The method of claim 1 wherein the receiving, generating, and applying are performed for each sentence of an electronic mail message. | 0.82058 |
9,851,958 | 5 | 7 | 5. A computer program product for generating at least one of a serializer and a deserializer for compiling a query, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to infer a type of serialization for each generation site of compiling a query; program instructions to execute the inferred type of serialization, while transcribing identification information assigned to each generation site to a type as an annotation; program instructions to specialize a serializer for each generation site, based on the inferred type of serialization and a type of serialization that is actually used at a generation site; program instructions to recursively compare the inferred type of serialization and the type of serialization that is actually used at a generation site; and program instructions to serialize a data value using the specialized serializer for each generation site. | 5. A computer program product for generating at least one of a serializer and a deserializer for compiling a query, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to infer a type of serialization for each generation site of compiling a query; program instructions to execute the inferred type of serialization, while transcribing identification information assigned to each generation site to a type as an annotation; program instructions to specialize a serializer for each generation site, based on the inferred type of serialization and a type of serialization that is actually used at a generation site; program instructions to recursively compare the inferred type of serialization and the type of serialization that is actually used at a generation site; and program instructions to serialize a data value using the specialized serializer for each generation site. 7. The computer program product according to claim 5 , wherein in a case of generating a serializer of a selection type in which a first type is selected from a plurality of types, the program instructions to specialize a serializer for each generation site, further comprise program instructions to: in response to determining that a second type is a subtype of only the selected first type, generating code for outputting a numeric value; and generating code for serializing a data value, based on the second type and the selected first type. | 0.670303 |
9,253,306 | 1 | 8 | 1. A method, comprising: determining, by a processor executable mashup stimulus module, at least one of a role, context, presence, or location of a user, wherein at least one of the role or context is determined based on a first telephone call and wherein a specified mashup is determined based on an Instant Message session and the first telephone call being simultaneous; identifying that the Instant Message session and the first telephone call are on different computational devices; and in response to identifying that the Instant Message session and the first telephone call are on different computational devices, transferring the Instant Message session and the first telephone call to a common computational device for displaying the first telephone call and the Instant Message session by using the specified mashup for a user interface of the common computational device. | 1. A method, comprising: determining, by a processor executable mashup stimulus module, at least one of a role, context, presence, or location of a user, wherein at least one of the role or context is determined based on a first telephone call and wherein a specified mashup is determined based on an Instant Message session and the first telephone call being simultaneous; identifying that the Instant Message session and the first telephone call are on different computational devices; and in response to identifying that the Instant Message session and the first telephone call are on different computational devices, transferring the Instant Message session and the first telephone call to a common computational device for displaying the first telephone call and the Instant Message session by using the specified mashup for a user interface of the common computational device. 8. The method of claim 1 , wherein at least one of the different computational devices has a web browser and wherein the at least one of the different computational devices comprises information that comprises a web hyperlink and further comprising: determining that the common computational device does not support a web browser; and in response to determining that the common computational device does not support the web browser, excluding the web hyperlink on the common computational device. | 0.718821 |
9,043,197 | 4 | 8 | 4. A method implemented by a computing system, the method comprising: receiving, by the system, one or more seed fact pairs, each seed fact pair associating a seed fact first phrase with a seed fact second phrase, wherein the seed fact first phrase is a seed fact subject and the seed fact second phrase is a piece of information; receiving, by the system, a set of one or more candidate fact pairs, each candidate fact pair associating a candidate fact first phrase and a candidate fact second phrase, wherein the candidate fact first phrase is a candidate fact subject and the candidate fact second phrase is a piece of information; receiving similarity score data, wherein the similarity score data identifies, for each of a plurality of pairs of distributionally similar words, a respective similarity score between the distributionally similar words in the pair that defines how similar the distributionally similar words in the pair are; and calculating, by the system, a similarity score for each candidate fact pair with respect to at least one seed fact pair, wherein the similarity scores represent measures of similarity between respective ones of the candidate fact pairs and the at least one seed fact pair, and wherein calculating the similarity score for each candidate fact pair comprises: determining a respective first similarity score for each word in the candidate fact first phrase that represents the similarity of the word to words from the seed fact first phrases from the at least one seed fact using the similarity score data, determining a respective second similarity score for each word in the candidate fact second phrase that represents the similarity of the word to words from the seed fact second phrases from the at least one seed fact using the similarity score data, and computing the similarity score for the candidate fact pair by combining the first and second similarity scores. | 4. A method implemented by a computing system, the method comprising: receiving, by the system, one or more seed fact pairs, each seed fact pair associating a seed fact first phrase with a seed fact second phrase, wherein the seed fact first phrase is a seed fact subject and the seed fact second phrase is a piece of information; receiving, by the system, a set of one or more candidate fact pairs, each candidate fact pair associating a candidate fact first phrase and a candidate fact second phrase, wherein the candidate fact first phrase is a candidate fact subject and the candidate fact second phrase is a piece of information; receiving similarity score data, wherein the similarity score data identifies, for each of a plurality of pairs of distributionally similar words, a respective similarity score between the distributionally similar words in the pair that defines how similar the distributionally similar words in the pair are; and calculating, by the system, a similarity score for each candidate fact pair with respect to at least one seed fact pair, wherein the similarity scores represent measures of similarity between respective ones of the candidate fact pairs and the at least one seed fact pair, and wherein calculating the similarity score for each candidate fact pair comprises: determining a respective first similarity score for each word in the candidate fact first phrase that represents the similarity of the word to words from the seed fact first phrases from the at least one seed fact using the similarity score data, determining a respective second similarity score for each word in the candidate fact second phrase that represents the similarity of the word to words from the seed fact second phrases from the at least one seed fact using the similarity score data, and computing the similarity score for the candidate fact pair by combining the first and second similarity scores. 8. The method of claim 4 , further comprising increasing, by the system, the similarity score for a candidate fact pair if the candidate fact pair is similar to more than one seed fact pair, a candidate fact pair being similar to a seed fact pair if the similarity score for the candidate fact pair with respect to the seed fact pair exceeds a threshold score. | 0.5 |
8,244,578 | 4 | 12 | 4. A method, comprising: retrieving, using at least one computing device, over a network, a plurality of content items from a plurality of content sources; identifying, using the at least one computing device, a plurality of advertisements embedded in the plurality of content items; identifying, using the at least one computing device, keywords of the plurality of advertisements; determining, sing the at least one computing device, similarity rankings of the plurality of advertisements based at least in part on the keywords; selecting, using the at least one computing device, a keyword based at least in part on the similarity rankings, where a historical price from a keyword seller for the keyword is less, by a defined amount, than a historical price from a click buyer; and purchasing, using the at least one computing device, the keyword from the keyword seller for placement of a first linked advertisement, the first linked advertisement configured to be selected to cause the presentation of a second advertisement of the click buyer. | 4. A method, comprising: retrieving, using at least one computing device, over a network, a plurality of content items from a plurality of content sources; identifying, using the at least one computing device, a plurality of advertisements embedded in the plurality of content items; identifying, using the at least one computing device, keywords of the plurality of advertisements; determining, sing the at least one computing device, similarity rankings of the plurality of advertisements based at least in part on the keywords; selecting, using the at least one computing device, a keyword based at least in part on the similarity rankings, where a historical price from a keyword seller for the keyword is less, by a defined amount, than a historical price from a click buyer; and purchasing, using the at least one computing device, the keyword from the keyword seller for placement of a first linked advertisement, the first linked advertisement configured to be selected to cause the presentation of a second advertisement of the click buyer. 12. The method of claim 4 , further comprising: counting a number of websites or webpages that display advertisements within a specified similarity ranking to select the keyword. | 0.876902 |
7,707,642 | 28 | 29 | 28. The software product of claim 27 , wherein the operations further comprise: initiating presentation of a consent query that requests consent to an audit event to be recorded by the document control system for the electronic document tethered to the document control system; and receiving information corresponding to a consent indication with respect to a consent statement relating to the audit event, the consent indication information configured to be included with the actions-taken information relating to the electronic document. | 28. The software product of claim 27 , wherein the operations further comprise: initiating presentation of a consent query that requests consent to an audit event to be recorded by the document control system for the electronic document tethered to the document control system; and receiving information corresponding to a consent indication with respect to a consent statement relating to the audit event, the consent indication information configured to be included with the actions-taken information relating to the electronic document. 29. The software product of claim 28 , wherein the operations further comprise altering one or more permissions associated with the electronic document in accordance with the consent indication information. | 0.5 |
8,260,813 | 6 | 7 | 6. A computer system for flexible data archival using a model-driven approach, the computer system having a context and further having an application having content, the computer system comprising: a CPU, a computer readable memory and a computer readable storage media; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to analyze the application content; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to create a data archive specification model based on the application content, wherein the program instructions to create the data archive specification model create the data archive specification model in a general-purpose visual modeling language, and wherein the data archive specification model is based on a meta-model comprising an archive operation schedule indicating whether archive data should be saved or purged; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to transform the data archive specification model; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to generate a second data archive specification; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to deploy the second data archive specification to create a data archive; and program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to construct an archive application based on the second data archive specification the context. | 6. A computer system for flexible data archival using a model-driven approach, the computer system having a context and further having an application having content, the computer system comprising: a CPU, a computer readable memory and a computer readable storage media; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to analyze the application content; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to create a data archive specification model based on the application content, wherein the program instructions to create the data archive specification model create the data archive specification model in a general-purpose visual modeling language, and wherein the data archive specification model is based on a meta-model comprising an archive operation schedule indicating whether archive data should be saved or purged; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to transform the data archive specification model; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to generate a second data archive specification; program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to deploy the second data archive specification to create a data archive; and program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to construct an archive application based on the second data archive specification the context. 7. The computer system as defined in claim 6 further comprising program instructions, stored on the computer readable storage media for execution by the CPU via the computer readable memory, to test the data archive. | 0.5 |
7,917,515 | 1 | 3 | 1. A method of incrementally processing XML documents, the method comprising: receiving a packet comprising data of at least one XML document, wherein each XML document comprises a plurality of elements that define a hierarchy, said hierarchy containing context information for each element relative to a position within the XML document; identifying which of the XML documents is associated with the packet; identifying at least one element of the XML document in the packet; identifying a specified portion of the document, said specified portion comprising the at least one received element; generating a digest value based on the specified portion, the digest value indicative of the hierarchy of at least the specified portion of the XML document; deriving speculative data by performing at least one function of the processing of the XML document; storing, in a cache indexed by the digest value, the derived speculative data, wherein the speculative data comprises data representing an XML structure of at least the specified portion of the XML document; and processing a subsequently received XML document based at least partly on the stored data, wherein processing the subsequently received XML document further comprises: generating a digest value based on a specified portion of the subsequently received XML document; comparing the digest value of the specified portion of the subsequently received XML document to digest values stored in the cache; retrieving the data corresponding to the XML structure from the cache if the digest value of the specified portion of the subsequently received XML document matches a digest value stored in the cache; employing the data retrieved from the cache to process at least part of the subsequently XML document; and discarding received elements of the XML file corresponding to the XML structure. | 1. A method of incrementally processing XML documents, the method comprising: receiving a packet comprising data of at least one XML document, wherein each XML document comprises a plurality of elements that define a hierarchy, said hierarchy containing context information for each element relative to a position within the XML document; identifying which of the XML documents is associated with the packet; identifying at least one element of the XML document in the packet; identifying a specified portion of the document, said specified portion comprising the at least one received element; generating a digest value based on the specified portion, the digest value indicative of the hierarchy of at least the specified portion of the XML document; deriving speculative data by performing at least one function of the processing of the XML document; storing, in a cache indexed by the digest value, the derived speculative data, wherein the speculative data comprises data representing an XML structure of at least the specified portion of the XML document; and processing a subsequently received XML document based at least partly on the stored data, wherein processing the subsequently received XML document further comprises: generating a digest value based on a specified portion of the subsequently received XML document; comparing the digest value of the specified portion of the subsequently received XML document to digest values stored in the cache; retrieving the data corresponding to the XML structure from the cache if the digest value of the specified portion of the subsequently received XML document matches a digest value stored in the cache; employing the data retrieved from the cache to process at least part of the subsequently XML document; and discarding received elements of the XML file corresponding to the XML structure. 3. The method of claim 1 , wherein the at least one XML element comprises an element tag and a body, and wherein the data indicative of the hierarchy of the elements comprises a string that excludes that at least the body of the at least one XML document. | 0.5 |
9,910,554 | 17 | 20 | 17. A data processing system, comprising: a processor; a data storage device coupled to the processor; and program code stored within the data storage device that, when executed by the processor, causes the data processing system to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transformation rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. | 17. A data processing system, comprising: a processor; a data storage device coupled to the processor; and program code stored within the data storage device that, when executed by the processor, causes the data processing system to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transformation rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. 20. The data processing system of claim 17 , wherein: the first GUI includes a fifth interface element of an image interface element type; the program code, when executed, further causes the computer to perform: locating in the rule repository a second transformation rule that specifies the image interface element type; utilizing a second action specified by the second transformation rule, transforming the fifth interface element into a sixth interface element associated with the second cultural background; and providing the second GUI includes providing the second GUI including the sixth interface element. | 0.5 |
9,400,790 | 10 | 12 | 10. The system of claim 9 , wherein the operations further comprise receiving, from an information source, information about the user. | 10. The system of claim 9 , wherein the operations further comprise receiving, from an information source, information about the user. 12. The system of claim 10 , wherein the advertisement to publish to the user is selected based at least in part on both the continuous string of characters associated with the voice mail message and the information about the user provided by the information source. | 0.5 |
8,498,983 | 7 | 8 | 7. The computer-assisted method of claim 1 , wherein the step of obtaining a first context term list comprises: matching the queried term to a searchable term in the database, wherein the searchable term is stored in association with one or more context terms selected from the documents potentially relevant to the searchable term in a database; and retrieving the one or more context terms associated with the searchable term as the first context term list. | 7. The computer-assisted method of claim 1 , wherein the step of obtaining a first context term list comprises: matching the queried term to a searchable term in the database, wherein the searchable term is stored in association with one or more context terms selected from the documents potentially relevant to the searchable term in a database; and retrieving the one or more context terms associated with the searchable term as the first context term list. 8. The computer-assisted method of claim 7 , further comprising: identifying one or more topic terms in a document collection comprising a plurality of documents potentially relevant to the searchable term; calculating a document topic score for each of the one or more topic terms; selecting at least one of the one or more topic terms based on its document topic score; and storing the one of the one or more topic terms as a context term list in association with the searchable term in the database. | 0.5 |
8,606,803 | 11 | 13 | 11. A system for translating a relational database query into a multidimensional expression language (MDX) database query comprising: a component configured to: parse a relational database query into one or more relational database query tokens; filter zero or more of the one or more relational database query tokens based at least in part on business logic to create a set of filtered relational database query tokens, the filtering comprising: removing a relational database query token, from the one or more relational database query tokens, responsive to determining that the relational database query token corresponds to a field not supported by a multidimensional database or is associated with a return of a dataset that exceeds a threshold; identify relevant metadata, from a metadata store, associated with metadata associated with the set of filtered relational database query tokens, the relevant metadata comprising current multidimensional metadata and trend related multidimensional metadata; translate at least some relational database query tokens of the set of filtered relational database query tokens into one or more work item query language (WIQL) tokens; retrieve a first group of one or more MDX tokens based at least in part on the relevant metadata; retrieve a second group of one or more MDX tokens based at least in part on the one or more WIQL tokens; arrange at least some of the one or more MDX tokens of the first group and at least some of the one or more MDX tokens of the second group based at least in part on the metadata associated with the set of filtered relational database query tokens; and generate one or more MDX database queries for trend related information and current information based at least in part on at least some of the arranged MDX tokens. | 11. A system for translating a relational database query into a multidimensional expression language (MDX) database query comprising: a component configured to: parse a relational database query into one or more relational database query tokens; filter zero or more of the one or more relational database query tokens based at least in part on business logic to create a set of filtered relational database query tokens, the filtering comprising: removing a relational database query token, from the one or more relational database query tokens, responsive to determining that the relational database query token corresponds to a field not supported by a multidimensional database or is associated with a return of a dataset that exceeds a threshold; identify relevant metadata, from a metadata store, associated with metadata associated with the set of filtered relational database query tokens, the relevant metadata comprising current multidimensional metadata and trend related multidimensional metadata; translate at least some relational database query tokens of the set of filtered relational database query tokens into one or more work item query language (WIQL) tokens; retrieve a first group of one or more MDX tokens based at least in part on the relevant metadata; retrieve a second group of one or more MDX tokens based at least in part on the one or more WIQL tokens; arrange at least some of the one or more MDX tokens of the first group and at least some of the one or more MDX tokens of the second group based at least in part on the metadata associated with the set of filtered relational database query tokens; and generate one or more MDX database queries for trend related information and current information based at least in part on at least some of the arranged MDX tokens. 13. The system of claim 11 , the multidimensional database comprising an online analytical processing cube. | 0.810954 |
9,646,273 | 1 | 10 | 1. An IT system technical solution analysis and development improvement method comprising: receiving, by a computer processor of a computing system, requirements (NRQ) associated with hardware components for an IT system for design, assumptions associated with said requirements (NRQ), dependency data associated with said requirements (NRQ), stakeholder data associated with said requirements (NRQ), and entry criteria readiness data associated with said requirements (NRQ); building, by said processor, said requirements (NRQ) into internal logic of a requirements analytical engine software module of a quality evaluation hardware circuit; evaluating, by said computer processor executing said requirements analytical engine software module, a quality level of said requirements (NRQ); calculating, by said computer processor executing a requirements quality score hardware circuit based on said quality level, a requirements quality sub-score (RSC) for each requirement of said requirements (NRQ); evaluating, by said computer processor executing an assumptions analytical engine of a validate assumptions hardware circuit, said assumptions for hidden requirements of said requirements (NRQ); generating, by said computer processor executing a validate assumptions hardware circuit based on said hidden requirements, an assumptions score for said assumptions; evaluating, by said computer processor executing a dependencies analytical engine of a validate dependencies hardware circuit, said dependency data; generating, by said computer processor executing dependencies score hardware circuit based on results of said evaluating said dependency data, a dependencies score for said dependencies data; evaluating, by said computer processor executing a stakeholder analytical engine, said stakeholder data; generating, by said computer processor based on results of said evaluating said stakeholder data, a stakeholder approval level score for said stakeholder data; evaluating, by said computer processor executing a criteria analytical engine, said entry criteria readiness data; generating, by said computer processor based on results of said evaluating said entry criteria readiness data, an entry criteria readiness score (ECRS) for entry criteria readiness data; building, by said processor, defects internal logic into said requirements analytical engine software module; evaluating, by said computer processor executing said defects internal logic, defects of said hardware components for said IT system for design; generating, by said computer processor, an overall score summary summarizing each said requirements quality score, said assumptions score, said dependencies score, said stakeholder score, and said criteria readiness score, wherein said generating said overall score summary comprises: assigning priorities and weights to said requirements quality score, said assumptions score, said dependencies score, said stakeholder score, and said criteria readiness score, wherein said overall score summary depicts a quality of a technical solution for said IT system under development thereby automatically enabling a system engineer, associated with said IT system for design, to execute a quality analysis against said overall score summary, and wherein said quality analysis results in hardware enabled prompts, links, and automation processes to support and enable said system engineer to develop said IT system for design thereby improving a requirement quality of said IT system; integrating, by said computer processor, a technical solution for improving said requirements (NRQ) associated with said hardware components for said IT system for design; creating and deploying an improved IT system based on said technical solution for improving said requirements (NRQ) associated with said hardware components for said IT system for design; and presenting, by said computer processor via a plotter hardware device over a network, graphical and numerical charts indicating said overall score summary. | 1. An IT system technical solution analysis and development improvement method comprising: receiving, by a computer processor of a computing system, requirements (NRQ) associated with hardware components for an IT system for design, assumptions associated with said requirements (NRQ), dependency data associated with said requirements (NRQ), stakeholder data associated with said requirements (NRQ), and entry criteria readiness data associated with said requirements (NRQ); building, by said processor, said requirements (NRQ) into internal logic of a requirements analytical engine software module of a quality evaluation hardware circuit; evaluating, by said computer processor executing said requirements analytical engine software module, a quality level of said requirements (NRQ); calculating, by said computer processor executing a requirements quality score hardware circuit based on said quality level, a requirements quality sub-score (RSC) for each requirement of said requirements (NRQ); evaluating, by said computer processor executing an assumptions analytical engine of a validate assumptions hardware circuit, said assumptions for hidden requirements of said requirements (NRQ); generating, by said computer processor executing a validate assumptions hardware circuit based on said hidden requirements, an assumptions score for said assumptions; evaluating, by said computer processor executing a dependencies analytical engine of a validate dependencies hardware circuit, said dependency data; generating, by said computer processor executing dependencies score hardware circuit based on results of said evaluating said dependency data, a dependencies score for said dependencies data; evaluating, by said computer processor executing a stakeholder analytical engine, said stakeholder data; generating, by said computer processor based on results of said evaluating said stakeholder data, a stakeholder approval level score for said stakeholder data; evaluating, by said computer processor executing a criteria analytical engine, said entry criteria readiness data; generating, by said computer processor based on results of said evaluating said entry criteria readiness data, an entry criteria readiness score (ECRS) for entry criteria readiness data; building, by said processor, defects internal logic into said requirements analytical engine software module; evaluating, by said computer processor executing said defects internal logic, defects of said hardware components for said IT system for design; generating, by said computer processor, an overall score summary summarizing each said requirements quality score, said assumptions score, said dependencies score, said stakeholder score, and said criteria readiness score, wherein said generating said overall score summary comprises: assigning priorities and weights to said requirements quality score, said assumptions score, said dependencies score, said stakeholder score, and said criteria readiness score, wherein said overall score summary depicts a quality of a technical solution for said IT system under development thereby automatically enabling a system engineer, associated with said IT system for design, to execute a quality analysis against said overall score summary, and wherein said quality analysis results in hardware enabled prompts, links, and automation processes to support and enable said system engineer to develop said IT system for design thereby improving a requirement quality of said IT system; integrating, by said computer processor, a technical solution for improving said requirements (NRQ) associated with said hardware components for said IT system for design; creating and deploying an improved IT system based on said technical solution for improving said requirements (NRQ) associated with said hardware components for said IT system for design; and presenting, by said computer processor via a plotter hardware device over a network, graphical and numerical charts indicating said overall score summary. 10. The method of claim 1 , wherein said evaluating said dependency data comprises: documenting dependency descriptions (DEDi) and dependency numbers (DUNi) for dependencies of said dependency data; assessing dependency clarity for said dependencies; assessing a dependency clarity impact/risk for said dependencies; assessing a dependency identification for an owner of said dependencies; and assessing a documented dependency milestones for said dependencies. | 0.708597 |
9,400,788 | 10 | 12 | 10. The apparatus of claim 9 , the operations further comprising: receiving a reply message, in a first language, from the second user to the first user; accessing a client processing device associated with the first user to determine a second preferred language of the first user; and translating the reply message to the second preferred language when the first language is not the same as the second preferred language. | 10. The apparatus of claim 9 , the operations further comprising: receiving a reply message, in a first language, from the second user to the first user; accessing a client processing device associated with the first user to determine a second preferred language of the first user; and translating the reply message to the second preferred language when the first language is not the same as the second preferred language. 12. The apparatus of claim 10 , the operations further comprising: broadcasting the reply message in the second preferred language to a plurality of users in a chat session. | 0.55641 |
8,310,179 | 1 | 6 | 1. An apparatus comprising: a receiver of multisensory digital audio input from a plurality of input devices, the receiver of multisensory digital audio input; a command-extractor that is operable to extract from the multisensory digital audio input a command that is relevant to a patient-movement-actuator, the command-extractor being operably coupled to the receiver; a lift-device-controller that is operable to receive the command from the command-extractor and that is operable to generate at least one electrical signal from the command, the lift-device-controller being electrically coupled to the command-extractor; and a patient-movement-actuator that is operable to receive at least one electrical signal and operable to perform motion in accordance with the at least one electrical signal and in response to the at least one electrical signal. | 1. An apparatus comprising: a receiver of multisensory digital audio input from a plurality of input devices, the receiver of multisensory digital audio input; a command-extractor that is operable to extract from the multisensory digital audio input a command that is relevant to a patient-movement-actuator, the command-extractor being operably coupled to the receiver; a lift-device-controller that is operable to receive the command from the command-extractor and that is operable to generate at least one electrical signal from the command, the lift-device-controller being electrically coupled to the command-extractor; and a patient-movement-actuator that is operable to receive at least one electrical signal and operable to perform motion in accordance with the at least one electrical signal and in response to the at least one electrical signal. 6. The apparatus of claim 1 wherein the plurality of input devices further comprises: a keyboard; a microphone; and a synaptic activity sensor. | 0.934941 |
9,348,499 | 21 | 28 | 21. One or more non-transitory computer-readable media storing instructions for sharing information, which instructions, when executed by one or more processors, cause performance of steps including: at a first server of a first data system, receiving a request to send a copy of a document to a second server of a second data system; wherein the first data system comprises at least the first server and a first repository that is accessible to the first server, wherein the document comprises a reference to a first object that is stored outside of the document and within the first repository, the document further comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data that belongs to the first object; at the first server, based at least partially upon the retrieved data belonging to the first object, generating evidence data that describes one or more aspects of the first object; wherein the evidence data is not identical to the reference or the retrieved data; responsive to the request to send the copy of the document to the second server, the first server at the first data system sending, to the second server at the second data system, the copy of the document and the evidence data. | 21. One or more non-transitory computer-readable media storing instructions for sharing information, which instructions, when executed by one or more processors, cause performance of steps including: at a first server of a first data system, receiving a request to send a copy of a document to a second server of a second data system; wherein the first data system comprises at least the first server and a first repository that is accessible to the first server, wherein the document comprises a reference to a first object that is stored outside of the document and within the first repository, the document further comprising one or more instructions configured to cause generation of one or more presented components of the document based on retrieving data that belongs to the first object; at the first server, based at least partially upon the retrieved data belonging to the first object, generating evidence data that describes one or more aspects of the first object; wherein the evidence data is not identical to the reference or the retrieved data; responsive to the request to send the copy of the document to the second server, the first server at the first data system sending, to the second server at the second data system, the copy of the document and the evidence data. 28. The one or more non-transitory computer-readable media of claim 21 , wherein the evidence data includes data indicating at least one of the type of the first object or a plurality of structural characteristics of the retrieved data belonging to the first object. | 0.62 |
9,892,075 | 17 | 18 | 17. The apparatus of claim 16 , wherein the apparatus is further configured for programming a packet classifier in the I/O adapter to filter storage traffic local to the apparatus. | 17. The apparatus of claim 16 , wherein the apparatus is further configured for programming a packet classifier in the I/O adapter to filter storage traffic local to the apparatus. 18. The apparatus of claim 17 , wherein the apparatus is further configured for populating a flow table in the I/O adapter with actions according to the policy context. | 0.5 |
8,046,222 | 1 | 6 | 1. A method comprising: receiving a probability of a n-gram identifying a word; determining a number of atomic units in the n-gram; identifying a scaling weight depending on the number of atomic units in the n-gram; and applying, using one or more computers, the scaling weight to the probability of the n-gram identifying a word to determine a scaled probability of the n-gram identifying a word. | 1. A method comprising: receiving a probability of a n-gram identifying a word; determining a number of atomic units in the n-gram; identifying a scaling weight depending on the number of atomic units in the n-gram; and applying, using one or more computers, the scaling weight to the probability of the n-gram identifying a word to determine a scaled probability of the n-gram identifying a word. 6. The method of claim 1 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the n-gram; receiving probabilities corresponding to each of the lesser order n-grams identifying words; comparing the probability of the n-gram identifying a word to the probabilities of combinations of the lesser order n-grams identifying words; and when a probability of a combination of lesser order n-grams identifying a word differs from the probability of the n-gram identifying a word by a specified threshold amount, modifying the scaling weight corresponding to the probability of the n-gram identifying a word. | 0.5 |
10,104,264 | 8 | 10 | 8. An system for adding an electronic property to electronically converted documents, the system comprising: a memory; and one or more processors electronically coupled to the memory, the one or more processors, in conjunction with the memory, programmed to cause the system to perform: automatically fragmenting a converted electronic document into fragments; identifying content of each fragment of the converted electronic document; searching for one or more electronic documents corresponding to the converted electronic document using the content from multiple fragments; identifying a first electronic document corresponding to a first fragment; identifying a second electronic document corresponding to a second fragment, the first and second electronic documents comprising different documents; extracting electronic properties from the first and second electronic documents; and applying the electronic properties extracted from the first and second electronic documents to the content of the converted electronic document. | 8. An system for adding an electronic property to electronically converted documents, the system comprising: a memory; and one or more processors electronically coupled to the memory, the one or more processors, in conjunction with the memory, programmed to cause the system to perform: automatically fragmenting a converted electronic document into fragments; identifying content of each fragment of the converted electronic document; searching for one or more electronic documents corresponding to the converted electronic document using the content from multiple fragments; identifying a first electronic document corresponding to a first fragment; identifying a second electronic document corresponding to a second fragment, the first and second electronic documents comprising different documents; extracting electronic properties from the first and second electronic documents; and applying the electronic properties extracted from the first and second electronic documents to the content of the converted electronic document. 10. The system as claimed in claim 8 , wherein searching comprises: identifying a document, having at least document-threshold-value of similarity with the content of the converted electronic document. | 0.74812 |
8,180,633 | 10 | 11 | 10. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors by concatenating vectors using a plurality of lookup tables referencing features obtained during indexing; integrating verb position in the input sentence of the verb of interest by employing a time delay neural network linear layer that is adapted to the input sentence; removing a time dimension by employing a max over time layer; and applying a squashing function to interpret outputs of the linear layer as class probabilities for semantic role labels. | 10. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors by concatenating vectors using a plurality of lookup tables referencing features obtained during indexing; integrating verb position in the input sentence of the verb of interest by employing a time delay neural network linear layer that is adapted to the input sentence; removing a time dimension by employing a max over time layer; and applying a squashing function to interpret outputs of the linear layer as class probabilities for semantic role labels. 11. The method as recited in claim 10 , wherein integrating verb position includes employing a matrix with a block-column form that depends on the input sentence. | 0.621495 |
9,858,348 | 10 | 13 | 10. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a computing device, perform a method comprising: generating a database that stores associations between each of a plurality of media objects and temporal, social or topical data including, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data and interaction data; receiving a request, from a requesting device associated with a user, for media; parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; when the request includes social criteria, determining media associated with the one or more people or types of people defined by the social criteria based on the association; when the request includes topical criteria, identifying topics associated with the request and determining media associated with the identified topics based on the association; when the request includes temporal criteria, identifying a time associated with the request and determining media associated with the identified time based on the association; locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and transmitting the plurality of media files over the network to the requesting device. | 10. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a computing device, perform a method comprising: generating a database that stores associations between each of a plurality of media objects and temporal, social or topical data including, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data and interaction data; receiving a request, from a requesting device associated with a user, for media; parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; when the request includes social criteria, determining media associated with the one or more people or types of people defined by the social criteria based on the association; when the request includes topical criteria, identifying topics associated with the request and determining media associated with the identified topics based on the association; when the request includes temporal criteria, identifying a time associated with the request and determining media associated with the identified time based on the association; locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and transmitting the plurality of media files over the network to the requesting device. 13. The non-transitory computer-readable storage medium of claim 10 wherein the request is transmitted from the requesting device when an advertisement is displayed or selected on the requesting device. | 0.793033 |
8,543,563 | 16 | 18 | 16. A domain-specific translation method comprising: receiving an input query in a source language; with a machine translation system that is not adapted to a specific domain, translating the query to generate a set of candidate translations of the query in a target language; extracting a set of features from each of the candidate translations in the set, the set of features including at least one domain specific feature which is based on a comparison of at least one term in the candidate translation with words in an associated domain-specific corpus of documents in the target language; scoring each of the candidate translations with a scoring function in which the extracted features are weighted with respective weights, the weights having been learned on features extracted from translated queries, each generated by translation of an original query into the target language, and a measure of information retrieval performance of each the translated queries for each original query in a set of original queries, the information retrieval performance being assessed on a domain-specific target document collection in which documents in the collection are annotated based on relevance to the original queries; and outputting a target query based on the scores of the candidate translations, wherein the at least one domain-specific feature is selected from the group consisting of: a) a language model feature; b) an out of vocabulary word feature; c) a query performance predictor which is computed with an equation that correlates with the measure of information retrieval performance; and combinations thereof. | 16. A domain-specific translation method comprising: receiving an input query in a source language; with a machine translation system that is not adapted to a specific domain, translating the query to generate a set of candidate translations of the query in a target language; extracting a set of features from each of the candidate translations in the set, the set of features including at least one domain specific feature which is based on a comparison of at least one term in the candidate translation with words in an associated domain-specific corpus of documents in the target language; scoring each of the candidate translations with a scoring function in which the extracted features are weighted with respective weights, the weights having been learned on features extracted from translated queries, each generated by translation of an original query into the target language, and a measure of information retrieval performance of each the translated queries for each original query in a set of original queries, the information retrieval performance being assessed on a domain-specific target document collection in which documents in the collection are annotated based on relevance to the original queries; and outputting a target query based on the scores of the candidate translations, wherein the at least one domain-specific feature is selected from the group consisting of: a) a language model feature; b) an out of vocabulary word feature; c) a query performance predictor which is computed with an equation that correlates with the measure of information retrieval performance; and combinations thereof. 18. The method of claim 16 , wherein the at least one domain-specific feature comprises an out of vocabulary word feature which, for a candidate translation, is based on a number of terms in the candidate translation that are not present within the domain-specific corpus, where each of the terms comprises a word of the candidate translation or a lemma form thereof. | 0.528278 |
9,002,696 | 16 | 20 | 16. A computer-readable storage device having computer-readable program instructions stored on the computer-readable storage device, wherein the computer-readable program instructions are executed by a CPU to translate a natural-language text document, wherein the computer-readable program instructions comprise: computer-readable program instructions for receiving the natural-language text document for translation; computer-readable program instructions for dividing each of a plurality of sentences in the document into a plurality of portions based on a set of rules that specify how to divide up each of the plurality of sentences based on content of the plurality of sentences, and avoiding disclosure of any of the plurality of sentences in its entirety to a same human translator; computer-readable program instructions for translating a first portion of the portions of each of the plurality of sentences to form an initially translated first portion, using a translation engine; computer-readable program instructions for sending the portions of each of the plurality of sentences to a plurality of respective, human translators, for correction and translation, wherein none of the plurality of human translators is sent any of the plurality of sentences in its entirety for translation, wherein the computer-readable program instructions for sending the portions of each of the plurality of sentences to the plurality of respective, human translators, include computer-readable program instructions for sending the initially translated first portion along with the first portion; and computer-readable program instructions for combining the translations for the respective portions to form consolidated translations for each of the plurality of sentences in response to receiving translations from the plurality of human translators for respective portions of each of the plurality of sentences, and updating at least one model used by the translation engine based on corrections made by the human translators. | 16. A computer-readable storage device having computer-readable program instructions stored on the computer-readable storage device, wherein the computer-readable program instructions are executed by a CPU to translate a natural-language text document, wherein the computer-readable program instructions comprise: computer-readable program instructions for receiving the natural-language text document for translation; computer-readable program instructions for dividing each of a plurality of sentences in the document into a plurality of portions based on a set of rules that specify how to divide up each of the plurality of sentences based on content of the plurality of sentences, and avoiding disclosure of any of the plurality of sentences in its entirety to a same human translator; computer-readable program instructions for translating a first portion of the portions of each of the plurality of sentences to form an initially translated first portion, using a translation engine; computer-readable program instructions for sending the portions of each of the plurality of sentences to a plurality of respective, human translators, for correction and translation, wherein none of the plurality of human translators is sent any of the plurality of sentences in its entirety for translation, wherein the computer-readable program instructions for sending the portions of each of the plurality of sentences to the plurality of respective, human translators, include computer-readable program instructions for sending the initially translated first portion along with the first portion; and computer-readable program instructions for combining the translations for the respective portions to form consolidated translations for each of the plurality of sentences in response to receiving translations from the plurality of human translators for respective portions of each of the plurality of sentences, and updating at least one model used by the translation engine based on corrections made by the human translators. 20. The computer-readable storage device of claim 16 , wherein the portions of each of the plurality of sentences in the natural-language text document are phrases, wherein metadata is associated with each portion of the plurality of portions that identify a sequence of the each portion. | 0.737226 |
9,152,735 | 8 | 13 | 8. A method for generating a modified view query against a relational database to produce an XML document, comprising the step of: composing an XSLT stylesheet with an XML view on said relational database to produce said modified view query; generating a first graph representing processing done by said XSLT stylesheet; and combining said first graph with a second graph to produce a combined graph, wherein said second graph represents an initial view query that defines said XML view on said relational database by matching pairs of nodes from the first and second graphs, wherein said combined graph is a context transition graph for an XSLT stylesheet executed on said initial view query, wherein said context transition graph captures context transitions that occur when evaluating said XSLT stylesheet on said XML document produced by said initial view query. | 8. A method for generating a modified view query against a relational database to produce an XML document, comprising the step of: composing an XSLT stylesheet with an XML view on said relational database to produce said modified view query; generating a first graph representing processing done by said XSLT stylesheet; and combining said first graph with a second graph to produce a combined graph, wherein said second graph represents an initial view query that defines said XML view on said relational database by matching pairs of nodes from the first and second graphs, wherein said combined graph is a context transition graph for an XSLT stylesheet executed on said initial view query, wherein said context transition graph captures context transitions that occur when evaluating said XSLT stylesheet on said XML document produced by said initial view query. 13. The method of claim 8 , wherein an obtained XML document is substantially similar to a second XML document produced by applying said XSLT stylesheet on said XML document produced by said initial view query. | 0.524887 |
8,024,320 | 7 | 8 | 7. The method of claim 1 , comprising: accumulating query fragments associated with the rule scope; accumulating query fragments associated with the desired state; and merging the accumulated query fragments into a query for applying the compliance rule to data corresponding to the IT infrastructure, wherein at least one query fragment, the query, or both the query and the at least one query fragment, includes the path expression for one of the identified paths. | 7. The method of claim 1 , comprising: accumulating query fragments associated with the rule scope; accumulating query fragments associated with the desired state; and merging the accumulated query fragments into a query for applying the compliance rule to data corresponding to the IT infrastructure, wherein at least one query fragment, the query, or both the query and the at least one query fragment, includes the path expression for one of the identified paths. 8. The method of claim 7 , wherein the rule scope comprises at least one conditional expression with configuration items satisfying the at least one conditional expression being considered as within the rule scope, wherein the at least one conditional expression includes the path expression for one of the identified paths. | 0.52907 |
10,133,819 | 1 | 11 | 1. A method for ingesting and delivering video comprising: crawling a video reference source for references to videos hosted at a video host that is different from the video reference source; if a reference meets one or more predetermined ingest criteria, ingesting comments relevant to the video from the video host and comments relevant to the video from the video reference source; parsing the ingested comments to identify moments in the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; and delivering the video together with moments identified in the video and dynamically displaying and hiding the moments based on times of the moments and a delivery progression of the video, wherein the crawling step is performed by a crawler component executed by a processor, the ingesting step is performed by an ingest component executed by a processor, the parsing step is performed by an analysis component executed by a processor, and the delivery step is performed by a delivery component executed by a processor and wherein the predetermined ingest criteria include a criterion that is based on a metric of video popularity established by the video reference source. | 1. A method for ingesting and delivering video comprising: crawling a video reference source for references to videos hosted at a video host that is different from the video reference source; if a reference meets one or more predetermined ingest criteria, ingesting comments relevant to the video from the video host and comments relevant to the video from the video reference source; parsing the ingested comments to identify moments in the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; and delivering the video together with moments identified in the video and dynamically displaying and hiding the moments based on times of the moments and a delivery progression of the video, wherein the crawling step is performed by a crawler component executed by a processor, the ingesting step is performed by an ingest component executed by a processor, the parsing step is performed by an analysis component executed by a processor, and the delivery step is performed by a delivery component executed by a processor and wherein the predetermined ingest criteria include a criterion that is based on a metric of video popularity established by the video reference source. 11. The method of claim 1 , wherein a moment is identified if a comment includes link to a video that includes within the link a reference to a time in the video. | 0.711744 |
7,835,911 | 10 | 11 | 10. The method of claim 1 , wherein: sub-dividing the application categorization into a plurality of sub-categories comprises sub-dividing the application categorization into a plurality of sub-categories at least one branch within said application categorization; building a second language model configuration comprising a plurality of statistical language models comprises: building a statistical language model for each of said at least one branch corresponding to the plurality of sub-categories; and saving a configuration file describing a sequential interconnection of each statistical language model of the plurality of statistical language models; and the method further comprises evaluating the interpretation accuracy of the second language model configuration by passing sentences of test data through said statistical language models of the second language model configuration in a sequence described by said configuration file. | 10. The method of claim 1 , wherein: sub-dividing the application categorization into a plurality of sub-categories comprises sub-dividing the application categorization into a plurality of sub-categories at least one branch within said application categorization; building a second language model configuration comprising a plurality of statistical language models comprises: building a statistical language model for each of said at least one branch corresponding to the plurality of sub-categories; and saving a configuration file describing a sequential interconnection of each statistical language model of the plurality of statistical language models; and the method further comprises evaluating the interpretation accuracy of the second language model configuration by passing sentences of test data through said statistical language models of the second language model configuration in a sequence described by said configuration file. 11. The method of claim 10 , further comprising logging a history of a performance accuracy for each new configuration, comparing a historic performance accuracy of a previous configuration to a new performance accuracy of said new configuration, and reverting to said historic configuration if said new performance accuracy is less than said historic performance accuracy, wherein if no further partitioning is possible, then of the previous partitions, the model configuration that yielded the best performance accuracy on the test data is considered as the optimum model configuration. | 0.5 |
8,954,469 | 1 | 15 | 1. A method in a computing system for facilitating providing augmented information, comprising: receiving one or more previously generated query templates, each previously generated query template including a relationship query specification that specifies a relationship query that includes an input specification and an output presentation specification as part of the relationship query; storing the received one or more query templates in a data repository; in response to receiving an indication of an entity, an entity type, or a link that triggers a match of one or more query templates, retrieving one or more of the matching query templates from the data repository; and for each of the retrieved one or more matching query templates, causing a user interface to be presented to obtain user input based upon the input specification of the relationship query specified by the relationship query specification and supplying the obtained user input to the matching query template; for each of the retrieved one or more matching query templates, automatically invoking the retrieved query template to cause the relationship query specified by the relationship query specification of the retrieved query template to be executed using the obtained user input according to the relationship query specification, and presenting search results according to the output presentation specification of the relationship query specified by the relationship query specification of the retrieved query template to provide information that augments the indicated entity in a manner specified by the query template. | 1. A method in a computing system for facilitating providing augmented information, comprising: receiving one or more previously generated query templates, each previously generated query template including a relationship query specification that specifies a relationship query that includes an input specification and an output presentation specification as part of the relationship query; storing the received one or more query templates in a data repository; in response to receiving an indication of an entity, an entity type, or a link that triggers a match of one or more query templates, retrieving one or more of the matching query templates from the data repository; and for each of the retrieved one or more matching query templates, causing a user interface to be presented to obtain user input based upon the input specification of the relationship query specified by the relationship query specification and supplying the obtained user input to the matching query template; for each of the retrieved one or more matching query templates, automatically invoking the retrieved query template to cause the relationship query specified by the relationship query specification of the retrieved query template to be executed using the obtained user input according to the relationship query specification, and presenting search results according to the output presentation specification of the relationship query specified by the relationship query specification of the retrieved query template to provide information that augments the indicated entity in a manner specified by the query template. 15. The method of claim 1 wherein at least some of the previously generated query templates include trigger tags and further comprising matching the trigger tags against a received indication of an entity or entity type to determine which query templates match. | 0.715066 |
7,715,635 | 22 | 24 | 22. A computer-implemented method for categorizing similarly formed paragraphs in at least one page image of reflowable textual content, the method comprising: obtaining at least one page image; identifying a plurality of paragraphs of reflowable textual content in each page of the at least one page image; determining a plurality of paragraph metrics regarding each of the plurality of identified paragraphs; clustering the identified paragraphs into at least one cluster of paragraphs according to at least some of the paragraph metrics; associating a paragraph category with each cluster of paragraphs; and generating a paragraph style for each paragraph category, wherein each paragraph style corresponds to at least some paragraph metrics of a typical paragraph of the corresponding categorized cluster. | 22. A computer-implemented method for categorizing similarly formed paragraphs in at least one page image of reflowable textual content, the method comprising: obtaining at least one page image; identifying a plurality of paragraphs of reflowable textual content in each page of the at least one page image; determining a plurality of paragraph metrics regarding each of the plurality of identified paragraphs; clustering the identified paragraphs into at least one cluster of paragraphs according to at least some of the paragraph metrics; associating a paragraph category with each cluster of paragraphs; and generating a paragraph style for each paragraph category, wherein each paragraph style corresponds to at least some paragraph metrics of a typical paragraph of the corresponding categorized cluster. 24. The method of claim 22 , wherein clustering the identified paragraphs into at least one cluster of paragraphs according to at least some of the paragraph metrics comprises performing a clustering analysis of at least some of the paragraph metrics, the result yielding a clustering of the identified paragraphs. | 0.5 |
8,842,660 | 11 | 20 | 11. A system for collecting and transmitting contextual information relating to a conversation on a communication channel between a first client and a second client, comprising: a processor; and a computer readable memory having computer executable instructions, which when executed by the processor, perform the method of: obtaining caller contextual information from a caller that is exchanged using a voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and a callee; obtaining callee contextual information based on a callee rule used in determining the callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; and updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information. | 11. A system for collecting and transmitting contextual information relating to a conversation on a communication channel between a first client and a second client, comprising: a processor; and a computer readable memory having computer executable instructions, which when executed by the processor, perform the method of: obtaining caller contextual information from a caller that is exchanged using a voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and a callee; obtaining callee contextual information based on a callee rule used in determining the callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; and updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information. 20. The computer readable memory device of claim 11 , wherein updating the callee contextual information includes identifying information to be deleted from the callee contextual information, storing the identified information in storage, and deleting the identified information from the callee contextual information. | 0.5 |
9,864,809 | 1 | 3 | 1. A method implemented on a computer having at least one processor, storage, and communication platform for facilitating selection of a preferred language associated with a website, comprising the steps of: receiving, via the communication platform, information relating to a referrer URL of a referrer website from which a user requests and accesses an original website in a first language, wherein the referrer URL indicates a webpage containing a link the user clicked on to access the original website; analyzing automatically the received information to estimate a preferred language that the user likely prefers to view content from the original website, the preferred language being estimated based on a keyword included in the referrer URL; displaying a selector, with one or more selectable languages determined based on the estimated preferred language, that allows the user to select a second language from the one or more selectable languages; and in response to the user's selection, directly redirecting the user to a translated website in the second language that corresponds to the original website. | 1. A method implemented on a computer having at least one processor, storage, and communication platform for facilitating selection of a preferred language associated with a website, comprising the steps of: receiving, via the communication platform, information relating to a referrer URL of a referrer website from which a user requests and accesses an original website in a first language, wherein the referrer URL indicates a webpage containing a link the user clicked on to access the original website; analyzing automatically the received information to estimate a preferred language that the user likely prefers to view content from the original website, the preferred language being estimated based on a keyword included in the referrer URL; displaying a selector, with one or more selectable languages determined based on the estimated preferred language, that allows the user to select a second language from the one or more selectable languages; and in response to the user's selection, directly redirecting the user to a translated website in the second language that corresponds to the original website. 3. The method of claim 1 , wherein the selector is displayed only when the preferred language is different from the first language. | 0.750951 |
8,484,218 | 1 | 7 | 1. A computer-implemented method comprising: grouping a first keyword into one or more first groups of related keywords; translating, using a machine translation process and after grouping the first keyword into one or more first groups of related keywords, a first keyword from a source language into a plurality of second keywords in a target language; after translating the first keywords into the second keywords, grouping the second keywords into one or more second groups of keywords based on the first groups and the first keyword from which each of the second keyword was translated; identifying the one or more pre-determined word clusters for the second keywords based on the second groups of keywords; augmenting the second keywords to include additional keywords in the target language that each have at least a threshold association with one or more of the second keywords, wherein the additional keywords are determined to have at least the threshold association with the one or more second keywords based on the additional keywords and the one or more second keywords being included in the one or more pre-determined word clusters; determining, by a computer system after augmenting the second keywords, frequencies with which each of the second keywords occur in a corpus associated with the target language, wherein the corpus comprises one or more corpora used by a search engine, and wherein determining the frequencies includes, at least in part, conducting a search for each of the second keywords using the search engine; selecting, by the computer system, a particular keyword from the second keywords to use in the target language based on the determined frequencies of occurrence; associating the particular keyword in the target language with an advertisement in the target language; receiving a search query comprising one or more search terms in the target language; determining, by the computer system, whether to provide the advertisement with search results for the search query based, at least, on a comparison of the particular keyword and the one or more search terms of the search query; and based on the determination of whether to provide the advertisement, providing the advertisement. | 1. A computer-implemented method comprising: grouping a first keyword into one or more first groups of related keywords; translating, using a machine translation process and after grouping the first keyword into one or more first groups of related keywords, a first keyword from a source language into a plurality of second keywords in a target language; after translating the first keywords into the second keywords, grouping the second keywords into one or more second groups of keywords based on the first groups and the first keyword from which each of the second keyword was translated; identifying the one or more pre-determined word clusters for the second keywords based on the second groups of keywords; augmenting the second keywords to include additional keywords in the target language that each have at least a threshold association with one or more of the second keywords, wherein the additional keywords are determined to have at least the threshold association with the one or more second keywords based on the additional keywords and the one or more second keywords being included in the one or more pre-determined word clusters; determining, by a computer system after augmenting the second keywords, frequencies with which each of the second keywords occur in a corpus associated with the target language, wherein the corpus comprises one or more corpora used by a search engine, and wherein determining the frequencies includes, at least in part, conducting a search for each of the second keywords using the search engine; selecting, by the computer system, a particular keyword from the second keywords to use in the target language based on the determined frequencies of occurrence; associating the particular keyword in the target language with an advertisement in the target language; receiving a search query comprising one or more search terms in the target language; determining, by the computer system, whether to provide the advertisement with search results for the search query based, at least, on a comparison of the particular keyword and the one or more search terms of the search query; and based on the determination of whether to provide the advertisement, providing the advertisement. 7. The computer-implemented method of claim 1 , further comprising: receiving a request to translate the first keyword into a target language that is associated with a geographic region; and selecting, from a plurality of corpora, the corpus for use in determining the frequencies of the second keywords based on the corpus being associated with the target language and the geographic region. | 0.5 |
8,949,803 | 1 | 10 | 1. A method comprising: generating a configuration file comprising one or more constructs predetermined to be unsafe for execution as identified by a user; extracting a first set of program code from a second set of program code; parsing the extracted first set of program code to generate a parsed structure; examining the parsed structure generated from the first set of program code for one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution, wherein the examining step further comprises providing a looping guard to verify if the entire first set of program code has been examined; detecting the one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution that are contained in the first set of program code, wherein the detecting step further comprises flagging each of the one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution that are contained in the first set of program code; and generating an unsafe-expression flagged version of the first set of program code for editing by a user; wherein the extracting, parsing, examining, detecting and generating steps are performed in accordance with a processor device. | 1. A method comprising: generating a configuration file comprising one or more constructs predetermined to be unsafe for execution as identified by a user; extracting a first set of program code from a second set of program code; parsing the extracted first set of program code to generate a parsed structure; examining the parsed structure generated from the first set of program code for one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution, wherein the examining step further comprises providing a looping guard to verify if the entire first set of program code has been examined; detecting the one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution that are contained in the first set of program code, wherein the detecting step further comprises flagging each of the one or more expressions that use at least one of the one or more constructs predetermined to be unsafe for execution that are contained in the first set of program code; and generating an unsafe-expression flagged version of the first set of program code for editing by a user; wherein the extracting, parsing, examining, detecting and generating steps are performed in accordance with a processor device. 10. The method of claim 1 , wherein the second set of program code is deployable in a shared computing environment. | 0.860775 |
9,251,129 | 12 | 13 | 12. The method of claim 1 , wherein: receiving the query identifying the one or more search parameters comprises receiving a query identifying a dictation source; and determining that the one or more existing electronic medical documents satisfy the one or more search parameters comprises determining that the one or more existing electronic medical documents were dictated by the dictation source. | 12. The method of claim 1 , wherein: receiving the query identifying the one or more search parameters comprises receiving a query identifying a dictation source; and determining that the one or more existing electronic medical documents satisfy the one or more search parameters comprises determining that the one or more existing electronic medical documents were dictated by the dictation source. 13. The method of claim 12 , wherein: receiving a query identifying a dictation source comprises receiving input identifying a medical department; and determining that the one or more existing electronic medical documents were dictated by the dictation source comprises determining that the one or more existing electronic medical documents were dictated by an individual associated with the medical department. | 0.5 |
9,100,722 | 11 | 19 | 11. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the system to perform a method of selecting content items for presentation to a user, the method comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion. | 11. A machine readable non-transitory storage medium storing executable program instructions which when executed by a data processing system cause the system to perform a method of selecting content items for presentation to a user, the method comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion. 19. The medium of claim 11 wherein the content items comprises one or more of: (a) audiovisual content items; (b) commercials or advertisements; or (c) audio content items. | 0.763736 |
7,549,119 | 11 | 12 | 11. A computer implemented method according to claim 9 wherein processing step (g3) further comprises the steps of: (g3a) breaking the content up into a plurality of strings, wherein each successive one of said plurality of strings begins with a successive character of the content; (g3b) processing a first of said plurality of strings through a recursive matching comparison subroutine to attempt to identify said at least one matching phrase that is similar to a one of said previously identified undesirable terms stored in said secondary database of undesirable terms; (g3c) determining if said at least one matching phrase has been identified in said first of said plurality of strings; (g3d) when said determining step (g3c) result is no, determining if there are more of said plurality of strings to be processed; (g3e) when said determining step (g3d) result is yes, passing control to said processing step (g3b) for a next of said plurality of strings; (g3f) when said determining step (g3d) result is no, passing control to said determining step (g4); (g3g) when said determining step (g3c) result is yes, determining if an option to look for only a one of said at least one matching phrase has been selected; (g3h) when said determining step (g3g) result is no, storing said at least one matching phrase in a memory and passing control to said determining step (g3d); and (g3i) when said determining step (g3g) result is yes, passing control to said determining step (g4). | 11. A computer implemented method according to claim 9 wherein processing step (g3) further comprises the steps of: (g3a) breaking the content up into a plurality of strings, wherein each successive one of said plurality of strings begins with a successive character of the content; (g3b) processing a first of said plurality of strings through a recursive matching comparison subroutine to attempt to identify said at least one matching phrase that is similar to a one of said previously identified undesirable terms stored in said secondary database of undesirable terms; (g3c) determining if said at least one matching phrase has been identified in said first of said plurality of strings; (g3d) when said determining step (g3c) result is no, determining if there are more of said plurality of strings to be processed; (g3e) when said determining step (g3d) result is yes, passing control to said processing step (g3b) for a next of said plurality of strings; (g3f) when said determining step (g3d) result is no, passing control to said determining step (g4); (g3g) when said determining step (g3c) result is yes, determining if an option to look for only a one of said at least one matching phrase has been selected; (g3h) when said determining step (g3g) result is no, storing said at least one matching phrase in a memory and passing control to said determining step (g3d); and (g3i) when said determining step (g3g) result is yes, passing control to said determining step (g4). 12. A computer implemented method according to claim 11 wherein processing step (g3b) further comprises the steps of: (g3b1) checking a first character of a first of said plurality of strings against a predefined alias character list, wherein each of said alias characters is a predefined character mapping where more than one character in an ordered sequence is mapped to a single character; (g3b2) when a match is found in said step (g3b1) for said first character of said first of said plurality of strings, building a temporary alias character list for said first character; (g3b3) comparing said first character against a first character of all said previously identified undesirable terms in said secondary database of undesirable terms for a match; (g3b4) when a match is found, counting the match toward a predetermined total of counted matches needed to identify said at least one matching phrase; (g3b5) for said match, determining if a flag has been set in a current position of said previously identified undesirable term in said secondary database of undesirable terms, indicating an end of said previously identified undesirable term; (g3b6) when said determining step (g3b5) result is no, passing control to step (g3b10); (g3b7) when said determining step (g3b5) result is yes, determining if a total of said counted matches is equal to said predetermined total of counted matches needed to identify said at least one matching phrase; (g3b8) when said determining step (g3b7) result is yes, saving said first of said plurality of strings as said at least one matching phrase; (g3b9) when said determining step (g3b7) result is no, passing control to step (g3b10); (g3b10) determining if said recursive matching comparison subroutine has reached an end of said first of said plurality of strings; (g3b11) when said determining step (g3b10) result is no, calling, by said recursive matching comparison subroutine, said recursive matching comparison subroutine recursively; (g3b12) moving to a next character in said first of said plurality of strings and passing control to said checking step (g3b1) for said next character; (g3b13) repeating steps (g3b1) through (g3b12) for said next character; and (g3b14) repeating step (g3b13) for each remaining character in said first of said plurality of strings. | 0.5 |
8,775,465 | 16 | 17 | 16. A non-transitory computer readable medium having information recorded thereon for updating an electronic document, wherein the information, when read by a computer, causes the computer to perform the following: determining a web-based source from which a section of content in an electronic document was copied based, at least in part, on attribution information provided in the electronic document for the section of content; determining one or more updates relative to the section of content based, at least in part, on a copy of the web-based source downloaded by a web crawler configured to methodically browse a World Wide Web for documents to copy and download web content; and providing the determined one or more updates relative to the section of the content to be indicated in the electronic document, wherein the one or more updates relative to the section of the content occur after the section of content being copied from the web-based source to the electronic document. | 16. A non-transitory computer readable medium having information recorded thereon for updating an electronic document, wherein the information, when read by a computer, causes the computer to perform the following: determining a web-based source from which a section of content in an electronic document was copied based, at least in part, on attribution information provided in the electronic document for the section of content; determining one or more updates relative to the section of content based, at least in part, on a copy of the web-based source downloaded by a web crawler configured to methodically browse a World Wide Web for documents to copy and download web content; and providing the determined one or more updates relative to the section of the content to be indicated in the electronic document, wherein the one or more updates relative to the section of the content occur after the section of content being copied from the web-based source to the electronic document. 17. The medium of claim 16 , wherein said determining one or more updates relative to the section of content comprises: locating the copy of the web-based source downloaded by the web crawler; and determining whether the located copy of the web-based source is more up-to-date relative to the section of content in the electronic document. | 0.5 |
9,589,019 | 1 | 2 | 1. A method for performance analysis of a database, comprising: receiving, at a processor, a proposed data model; generating a hypothetical query workload, the generating comprising using a plurality of sample query templates representing different query constructs for the proposed data model, identifying fact tables and dimension tables using foreign key constraints between tables in the proposed data model, substituting join predicates based on the foreign key constraints, randomly selecting dimension properties and fact measures from table definitions, randomly selecting local predicates from the dimension tables for slice and filter conditions, and randomly substituting literal values based on a data-type of an associated dimension column; generating hypothetical optimizer statistics using predefined generating rules that include a projected cardinality for the proposed data model; creating a sample unpopulated database and database schema using the proposed data model; applying, by the processor, the hypothetical optimizer statistics to the sample unpopulated database; based on generating the hypothetical optimizer statistics, applying, by the processor, each query construct of the hypothetical query workload to the database schema; and estimating, by the processor, a cost of the hypothetical query workload for the proposed data model. | 1. A method for performance analysis of a database, comprising: receiving, at a processor, a proposed data model; generating a hypothetical query workload, the generating comprising using a plurality of sample query templates representing different query constructs for the proposed data model, identifying fact tables and dimension tables using foreign key constraints between tables in the proposed data model, substituting join predicates based on the foreign key constraints, randomly selecting dimension properties and fact measures from table definitions, randomly selecting local predicates from the dimension tables for slice and filter conditions, and randomly substituting literal values based on a data-type of an associated dimension column; generating hypothetical optimizer statistics using predefined generating rules that include a projected cardinality for the proposed data model; creating a sample unpopulated database and database schema using the proposed data model; applying, by the processor, the hypothetical optimizer statistics to the sample unpopulated database; based on generating the hypothetical optimizer statistics, applying, by the processor, each query construct of the hypothetical query workload to the database schema; and estimating, by the processor, a cost of the hypothetical query workload for the proposed data model. 2. A method as claimed in claim 1 , further comprising refining the proposed data model and iterating estimating the cost of the hypothetical query workload. | 0.775072 |
9,342,301 | 5 | 7 | 5. The method of claim 1 , in which obtaining the at least one translation transformation rule from the library further comprises extracting a schema from the at least one variable in the input script from a first user device and obtaining at least one transformation rule from the library, in which the at least one transformation rule comprises a template and a natural language translation, in which the natural language translation is appropriate for the schema. | 5. The method of claim 1 , in which obtaining the at least one translation transformation rule from the library further comprises extracting a schema from the at least one variable in the input script from a first user device and obtaining at least one transformation rule from the library, in which the at least one transformation rule comprises a template and a natural language translation, in which the natural language translation is appropriate for the schema. 7. The method of claim 5 , further comprising: generating at least one default translation transformation rule relevant to the schema if there is not an appropriate translation transformation rule for the schema in the library; allowing the first user to correct the at least one default translation transformation rule to create a schema-specific translation transformation rule; and storing the schema-specific translation transformation rule in the library. | 0.5 |
7,610,545 | 1 | 11 | 1. A method for automatically relating documents, comprising: selecting a first item in a first document that is associated with a first document type; selecting a second item wherein the second item is related to the first item; annotating the second item in a second document that is associated with a second document type with an annotation, wherein the annotation refers to the first item, and wherein the annotation comprises provenance information that includes association between the first item in the first document type and the second item in the second document type; creating annotation maps that enable an interactive editor to provide error checking, code completion, and contextual viewing, wherein each annotation map contains one or more associations between an item in the first document and an annotated item in the second document; and adding an entry for a new association for the annotation in a selected annotation map based on an annotation type of the annotation. | 1. A method for automatically relating documents, comprising: selecting a first item in a first document that is associated with a first document type; selecting a second item wherein the second item is related to the first item; annotating the second item in a second document that is associated with a second document type with an annotation, wherein the annotation refers to the first item, and wherein the annotation comprises provenance information that includes association between the first item in the first document type and the second item in the second document type; creating annotation maps that enable an interactive editor to provide error checking, code completion, and contextual viewing, wherein each annotation map contains one or more associations between an item in the first document and an annotated item in the second document; and adding an entry for a new association for the annotation in a selected annotation map based on an annotation type of the annotation. 11. The method of claim 1 , further comprising: yielding the second item when the first item is selected. | 0.83119 |
9,684,639 | 6 | 7 | 6. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause: a repository receiving a first request to store a XML document; wherein a first process within a first session is running within said repository; wherein a second process within a second session is running within said repository; in response to receiving said first request, said first process validating said XML document based on a XML schema defined by one or more XML schema documents, wherein validating said XML document includes said first process storing, in a shared volatile memory, a compile-time generated static structures comprising validation data and specifically generated for XML document validation based on said XML schema, wherein said XML schema is registered with said repository; said repository receiving a subsequent request to store one or more XML documents associated with said XML schema; in response to receiving said subsequent request, said second process subsequently validating said one or more XML documents based on said XML schema; wherein subsequently validating said one or more XML document comprises: said second process copying from said shared volatile memory said compile-time generated static structures into private memory that is private to said second process, and said second process using said compile-time generated static structures that are stored in said private memory to validate said one or more XML documents. | 6. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause: a repository receiving a first request to store a XML document; wherein a first process within a first session is running within said repository; wherein a second process within a second session is running within said repository; in response to receiving said first request, said first process validating said XML document based on a XML schema defined by one or more XML schema documents, wherein validating said XML document includes said first process storing, in a shared volatile memory, a compile-time generated static structures comprising validation data and specifically generated for XML document validation based on said XML schema, wherein said XML schema is registered with said repository; said repository receiving a subsequent request to store one or more XML documents associated with said XML schema; in response to receiving said subsequent request, said second process subsequently validating said one or more XML documents based on said XML schema; wherein subsequently validating said one or more XML document comprises: said second process copying from said shared volatile memory said compile-time generated static structures into private memory that is private to said second process, and said second process using said compile-time generated static structures that are stored in said private memory to validate said one or more XML documents. 7. The non-transitory computer-readable medium of claim 6 , wherein said one or more XML schema documents define a set of constructs that include more constructs than exist in said XML document; wherein validating said XML document includes: making a determination of which constructs of said set of constructs should exist in said XML document; and generating validation structures based on said determination of which constructs should exist in said XML document. | 0.5 |
8,565,526 | 18 | 20 | 18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. | 18. A system for searching optical character recognition results of image text documents comprising: an image text transformer linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results, and creating reflection files corresponding to the image text documents from the edited text results; a reflection repository storing the reflection files therein; a search engine searching the reflection files; and a user device displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. 20. A system as recited in claim 18 wherein the reflection repository and the content repository are co-located. | 0.714286 |
9,613,153 | 1 | 9 | 1. A method comprising: identifying, by a social networking system, a target user of the social networking system as being engaged in malicious activity performed on the social networking system; identifying, by the social networking system, an object maintained by the social networking system associated with the malicious activity; identifying, by the social networking system, objects connected to the target user through the social networking system and disabled by the social networking system; retrieving, by the social networking system, information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor of the social networking system, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a relationship between the target user and the identified objects that were disabled by the social networking system; and performing, by the social networking system, an action affecting the object associated with the malicious activity based on the calculated disabled connectivity score. | 1. A method comprising: identifying, by a social networking system, a target user of the social networking system as being engaged in malicious activity performed on the social networking system; identifying, by the social networking system, an object maintained by the social networking system associated with the malicious activity; identifying, by the social networking system, objects connected to the target user through the social networking system and disabled by the social networking system; retrieving, by the social networking system, information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor of the social networking system, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a relationship between the target user and the identified objects that were disabled by the social networking system; and performing, by the social networking system, an action affecting the object associated with the malicious activity based on the calculated disabled connectivity score. 9. The method of claim 1 , wherein identifying, by the social networking system, an object maintained by the social networking system associated with the malicious activity, comprises: receiving a report that identifies an object maintained by the social networking system associated with the malicious activity. | 0.768889 |
7,606,428 | 12 | 35 | 12. A computer readable recording medium having encoded thereon an XMT style sheet for parsing an input XMT (extensible MPEG-4 textual format) file including depth image-based representation (DIBR) data using a schema of claim 1 for the DIBR data, the XMT style sheet comprising: an XMT2BIFS style sheet used to generate a scene file for the DIBR data; and an XMT2MUX style sheet used to generate an mux file for the DIBR data. | 12. A computer readable recording medium having encoded thereon an XMT style sheet for parsing an input XMT (extensible MPEG-4 textual format) file including depth image-based representation (DIBR) data using a schema of claim 1 for the DIBR data, the XMT style sheet comprising: an XMT2BIFS style sheet used to generate a scene file for the DIBR data; and an XMT2MUX style sheet used to generate an mux file for the DIBR data. 35. The computer readable medium of claim 12 , wherein the XMT2MUX style sheet comprises a decConfigDescr template, which is called when decConfigDescr is found in a predetemirned upper template, and an slConfigDescr template, which is called when slConfigDescr is found in the predetermined upper template, wherein the decConfigDescr template outputs decConfigDescr DecoderConfigDescriptor { to the mux file when decConfigDescr is found by the parsing, calls a DecoderConfigDescriptor template, and outputs } to the mux file, and the slConfigDescr template outputs slConfigDescr SLConfigDescriptor { to the mux file when slConfigDescr is found by the parsing, calls an SLConfigoescriptor template, and outputs } to the mux file. | 0.534483 |
9,239,865 | 1 | 4 | 1. A computer-implemented method for determining recommended entities for a user based on the user's social graph, the method comprising: receiving, at one or more processors, a search query from the user and an identifier for a subset of the user's social graph, wherein the subset of the user's social graph includes a plurality of contacts of the user and is selected by the user from among a plurality of subsets also each having a plurality of contacts of the user; identifying, by one or more processors, a plurality of entities that match the search query; identifying, by one or more processors, one or more contacts in a subset of the user's social graph based on the identifier; determining, by one or more processors, a selected one of the plurality of entities associated with one or more of the identified contacts; and providing, by one or more processors, the plurality of entities including the selected one of the plurality of entities as search results responsive to the search query in a search results display, wherein the selected entity is annotated with association information for at least one of the identified contacts including review text or a rating of the selected entity by the at least one identified contact and the selected entity is annotated with an indication of the at least one identified contact. | 1. A computer-implemented method for determining recommended entities for a user based on the user's social graph, the method comprising: receiving, at one or more processors, a search query from the user and an identifier for a subset of the user's social graph, wherein the subset of the user's social graph includes a plurality of contacts of the user and is selected by the user from among a plurality of subsets also each having a plurality of contacts of the user; identifying, by one or more processors, a plurality of entities that match the search query; identifying, by one or more processors, one or more contacts in a subset of the user's social graph based on the identifier; determining, by one or more processors, a selected one of the plurality of entities associated with one or more of the identified contacts; and providing, by one or more processors, the plurality of entities including the selected one of the plurality of entities as search results responsive to the search query in a search results display, wherein the selected entity is annotated with association information for at least one of the identified contacts including review text or a rating of the selected entity by the at least one identified contact and the selected entity is annotated with an indication of the at least one identified contact. 4. The method of claim 1 , wherein the selected entity is presented in a first display mode and any of the plurality of entities that are not associated with the one or more contacts are presented in a second display mode. | 0.80895 |
8,515,816 | 1 | 37 | 1. A method performed by a processor in a computing system for analyzing text capture operation traffic, the method comprising: receiving, by the computing system, a plurality of indications of operations for capturing text from rendered documents, each of the plurality of the received indications specifying a text sequence captured as part of the indicated text capture sequence; for each of the plurality of received indications, identifying, by the processor, an electronic document containing the captured text sequence; performing, by the processor, collective analysis on the plurality of received indications and the electronic documents; and outputting, by the processor, a result produced by the performed analysis. | 1. A method performed by a processor in a computing system for analyzing text capture operation traffic, the method comprising: receiving, by the computing system, a plurality of indications of operations for capturing text from rendered documents, each of the plurality of the received indications specifying a text sequence captured as part of the indicated text capture sequence; for each of the plurality of received indications, identifying, by the processor, an electronic document containing the captured text sequence; performing, by the processor, collective analysis on the plurality of received indications and the electronic documents; and outputting, by the processor, a result produced by the performed analysis. 37. The method of claim 1 wherein at least one of the text capture operations indicated by a received indication yielded a text sequence, and wherein the text capture operation involved capturing image data from a nonrectangular region of the rendered document. | 0.672111 |
9,076,347 | 11 | 17 | 11. A method for identifying a mispronounced word spoken by a user of a non-native language, comprising: presenting to the user a curriculum comprising a plurality of tracks, each track corresponding to a selected set of phrases; prompting the user to create an utterance corresponding to a phrase selected from among the plurality of tracks; analyzing, one or more electronic processors, the utterance using a speech recognition system, the speech recognition system returning a ranked list of two or more recognized phrases; comparing, the one or more electronic processors, each of the ranked list of two or more recognized phrases to a series of mispronunciations corresponding to the phrase; matching, using the one or more electronic processors, one of the ranked list of two or more recognized phrases to a mispronunciation; identifying, using the one or more electronic processors, guidance for the user to correct the matched mispronunciation based upon the match of the one of the ranked list of two or more recognized phrases to a mispronunciation; and displaying the guidance to the user. | 11. A method for identifying a mispronounced word spoken by a user of a non-native language, comprising: presenting to the user a curriculum comprising a plurality of tracks, each track corresponding to a selected set of phrases; prompting the user to create an utterance corresponding to a phrase selected from among the plurality of tracks; analyzing, one or more electronic processors, the utterance using a speech recognition system, the speech recognition system returning a ranked list of two or more recognized phrases; comparing, the one or more electronic processors, each of the ranked list of two or more recognized phrases to a series of mispronunciations corresponding to the phrase; matching, using the one or more electronic processors, one of the ranked list of two or more recognized phrases to a mispronunciation; identifying, using the one or more electronic processors, guidance for the user to correct the matched mispronunciation based upon the match of the one of the ranked list of two or more recognized phrases to a mispronunciation; and displaying the guidance to the user. 17. The method of claim 11 , further comprising logically arranging the series of mispronunciations corresponding to the phrase in a star configuration comprising a central node corresponding to the phrase, and a ray corresponding to a mispronunciation of the phrase, wherein the phonetic transcription of the ray differs by no more than three elements from the phonetic transcription of the central node. | 0.5 |
10,034,028 | 7 | 8 | 7. The method of claim 6 comprising providing at least one search engine with access to the time based text. | 7. The method of claim 6 comprising providing at least one search engine with access to the time based text. 8. The method of claim 7 , wherein at least two of the first processing unit, the second processing unit, and the third processing unit are executed by a single computing device. | 0.5 |
9,489,657 | 10 | 11 | 10. The computer-implemented method of claim 1 wherein a node is displayed whenever a participant contributes to the chat room. | 10. The computer-implemented method of claim 1 wherein a node is displayed whenever a participant contributes to the chat room. 11. The computer-implemented method of claim 10 , wherein an area occupied by the node represents a volume of traffic present in the corresponding chat room at a particular time. | 0.531579 |
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