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8,548,246 | 15 | 16 | 15. A system for preprocessing an image for optical character recognition (OCR), wherein the image comprises a plurality of columns, each column of the plurality of columns comprising at least one of Arabic text and non-text items, the system comprising: a memory; a processor coupled to the memory, the processor configured to determine a plurality of components associated with at least one of the Arabic text and the non-text items of the plurality of columns, a component comprising a series of connected pixels; calculate a line height and a column spacing associated with the plurality of components; associate at least one component of the plurality of components with a column of the plurality of columns based on the line height and the column spacing; calculate a first set of characteristic parameters for each column of the plurality of columns; merge the plurality of components of each column of the plurality of columns based on the first set of characteristic parameters to form at least one of at least one sub-word and at least one word; merge a first plurality of words, subwords, or a combination thereof to be processed as a first region; merge a second plurality of words, subwords, or a combination thereof to be processed as a second region wherein at least a portion of the second region vertically overlaps at least a portion of the first region; wherein the first set of characteristic parameters comprises one of a line height associated with each column, a word spacing associated with each column, a line spacing associated with each column, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, a density of each component, or an aspect ratio of each component; and wherein for calculating the line spacing associated with each column, the processor: creates a histogram of a plurality of horizontal projections of the plurality of components associated with each column, a horizontal projection of the plurality of horizontal projections indicating a number of pixels associated with the plurality of components corresponding to each sweep of a raster scan, calculates an average distance between two consecutive horizontal projections, and computes the line spacing based on the average distance. | 15. A system for preprocessing an image for optical character recognition (OCR), wherein the image comprises a plurality of columns, each column of the plurality of columns comprising at least one of Arabic text and non-text items, the system comprising: a memory; a processor coupled to the memory, the processor configured to determine a plurality of components associated with at least one of the Arabic text and the non-text items of the plurality of columns, a component comprising a series of connected pixels; calculate a line height and a column spacing associated with the plurality of components; associate at least one component of the plurality of components with a column of the plurality of columns based on the line height and the column spacing; calculate a first set of characteristic parameters for each column of the plurality of columns; merge the plurality of components of each column of the plurality of columns based on the first set of characteristic parameters to form at least one of at least one sub-word and at least one word; merge a first plurality of words, subwords, or a combination thereof to be processed as a first region; merge a second plurality of words, subwords, or a combination thereof to be processed as a second region wherein at least a portion of the second region vertically overlaps at least a portion of the first region; wherein the first set of characteristic parameters comprises one of a line height associated with each column, a word spacing associated with each column, a line spacing associated with each column, a number of pixels corresponding to each component, a width of each component, a height of each component, coordinates of each component, a density of each component, or an aspect ratio of each component; and wherein for calculating the line spacing associated with each column, the processor: creates a histogram of a plurality of horizontal projections of the plurality of components associated with each column, a horizontal projection of the plurality of horizontal projections indicating a number of pixels associated with the plurality of components corresponding to each sweep of a raster scan, calculates an average distance between two consecutive horizontal projections, and computes the line spacing based on the average distance. 16. The system of claim 15 , wherein the processor is further configured to perform at least one of: converting at least one of a grayscale image and a color image into a binary image; filtering salt and pepper noise; and correcting skew using a modified Hough transform. | 0.794697 |
8,245,134 | 2 | 7 | 2. A method of creating a session document for differential dynamic content delivery, the method comprising: identifying a presentation document for a presentation, said presentation document comprising a presentation grammar and a structured document including a plurality of structural elements classified with classification identifiers; identifying a user participant for the presentation, said user participant being associated with a user profile that includes one or more user classifications each describing at least one attribute of the user participant; filtering the presentation document to obtain a plurality of extracted structural elements; filtering the presentation grammar of the presentation document based on said plurality of extracted structural elements to obtain a session grammar; and storing the session document, wherein a data volume of the session document is less than a data volume of the presentation document. | 2. A method of creating a session document for differential dynamic content delivery, the method comprising: identifying a presentation document for a presentation, said presentation document comprising a presentation grammar and a structured document including a plurality of structural elements classified with classification identifiers; identifying a user participant for the presentation, said user participant being associated with a user profile that includes one or more user classifications each describing at least one attribute of the user participant; filtering the presentation document to obtain a plurality of extracted structural elements; filtering the presentation grammar of the presentation document based on said plurality of extracted structural elements to obtain a session grammar; and storing the session document, wherein a data volume of the session document is less than a data volume of the presentation document. 7. The method of claim 2 , further comprising: extracting the plurality of extracted structural elements based on the classification identifiers that correspond to said one or more user classifications; and writing the plurality of extracted structural elements into the session document. | 0.5 |
9,047,275 | 8 | 19 | 8. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; performing a lexico-morphological analysis of the first and the second fragments using linguistic descriptions; performing a syntactic analysis of the first and the second fragments using linguistic descriptions and generating a syntactic structure for the first fragment and a syntactic structure for the second fragment; generating a semantic structure for the first fragment and a semantic structure for the second fragment, wherein the semantic structures are directional acyclic graphs with nodes that are assigned elements of semantic hierarchy; estimating the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment, wherein estimating the degree of correspondence between the semantic structures includes identifying correspondence of tree structure, deep slots, non-tree links, and semantic classes; and if the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment satisfies a predetermined threshold, saving the generated syntactic and semantic structures for the first fragment in connection with the first fragment; and saving the generated syntactic and semantic structures for the second fragment in connection with the second fragment. | 8. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; performing a lexico-morphological analysis of the first and the second fragments using linguistic descriptions; performing a syntactic analysis of the first and the second fragments using linguistic descriptions and generating a syntactic structure for the first fragment and a syntactic structure for the second fragment; generating a semantic structure for the first fragment and a semantic structure for the second fragment, wherein the semantic structures are directional acyclic graphs with nodes that are assigned elements of semantic hierarchy; estimating the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment, wherein estimating the degree of correspondence between the semantic structures includes identifying correspondence of tree structure, deep slots, non-tree links, and semantic classes; and if the degree of correspondence between the semantic structure for the first fragment and the semantic structure for the second fragment satisfies a predetermined threshold, saving the generated syntactic and semantic structures for the first fragment in connection with the first fragment; and saving the generated syntactic and semantic structures for the second fragment in connection with the second fragment. 19. The method of claim 8 , wherein estimating the correspondence between the semantic structures comprises mapping graphs to produce a set of node pairs and computing node distances for the pairs. | 0.645683 |
7,975,121 | 1 | 11 | 1. A method, comprising: receiving a low level language instruction that accesses a word in a memory, the word having a first type and the memory including one of a stack or a heap; labeling positions in each of the stack or the heap as one or more specified positions and one or more unspecified positions; assigning a second type to the memory, the second type including the first type, the word being at one of the one or more unspecified positions or the one or more specified positions; and determining whether the low level language instruction is well-typed by applying one or more rules to the instruction and to the second type. | 1. A method, comprising: receiving a low level language instruction that accesses a word in a memory, the word having a first type and the memory including one of a stack or a heap; labeling positions in each of the stack or the heap as one or more specified positions and one or more unspecified positions; assigning a second type to the memory, the second type including the first type, the word being at one of the one or more unspecified positions or the one or more specified positions; and determining whether the low level language instruction is well-typed by applying one or more rules to the instruction and to the second type. 11. The method of claim 1 , wherein the one or more rules include an instruction typing rule that verifies that one of an instruction that loads the word from a stack location or an instruction that stores the word into the stack location is well-typed, the stack location being one of the one or more unspecified positions or the one or more specified positions. | 0.596667 |
9,934,785 | 1 | 7 | 1. A method of processing audio signals, comprising the steps of: retrieving at least one content object generated by an audio signal processing system, the at least one content object including (1) one or more text objects corresponding to one or more words and (2) one or more text object data elements representing (i) a type representing the one or more text objects as at least one of a sentence, a verb, a noun phrase a determiner, and an adjective (ii) an emphasis level value representing a level of emphasis of the one or more words, correspondingly and (iii) an electronically generated confidence level value representing a confidence level that the audio signal processing system has properly identified the one or more words from an audio signal; retrieving content metadata generated by the audio signal processing system, the content metadata corresponding to the one or more words and including (i) one or more content metadata objects and (ii) a content metadata object confidence level value representing the confidence level that the audio signal processing system has properly identified the one or more content metadata objects, wherein the one or more content metadata objects include at least one of an emotion object, a gender object, an age object and an accent object; retrieving environmental metadata, generated by the audio signal processing system, the environmental metadata corresponding to the background noise and including (i) one or more environmental metadata objects and (ii) an environmental metadata object confidence level value representing the audio signal processing system has properly identified the one or more environmental metadata objects from the audio signal; retrieving, from a profile database, a user profile containing historical listening practices of a user; determining, based on the user profile, the at least one content object, the content metadata and the environmental metadata, at least one of (i) media content and (ii) a recommended next media track; and outputting, on an electronic device, at least one of the media content and the recommended next media track, wherein the outputting comprises playing the media content or displaying the recommended next media track, correspondingly, wherein when the recommended next media track is selected, media content corresponding to the recommended next media track is played. | 1. A method of processing audio signals, comprising the steps of: retrieving at least one content object generated by an audio signal processing system, the at least one content object including (1) one or more text objects corresponding to one or more words and (2) one or more text object data elements representing (i) a type representing the one or more text objects as at least one of a sentence, a verb, a noun phrase a determiner, and an adjective (ii) an emphasis level value representing a level of emphasis of the one or more words, correspondingly and (iii) an electronically generated confidence level value representing a confidence level that the audio signal processing system has properly identified the one or more words from an audio signal; retrieving content metadata generated by the audio signal processing system, the content metadata corresponding to the one or more words and including (i) one or more content metadata objects and (ii) a content metadata object confidence level value representing the confidence level that the audio signal processing system has properly identified the one or more content metadata objects, wherein the one or more content metadata objects include at least one of an emotion object, a gender object, an age object and an accent object; retrieving environmental metadata, generated by the audio signal processing system, the environmental metadata corresponding to the background noise and including (i) one or more environmental metadata objects and (ii) an environmental metadata object confidence level value representing the audio signal processing system has properly identified the one or more environmental metadata objects from the audio signal; retrieving, from a profile database, a user profile containing historical listening practices of a user; determining, based on the user profile, the at least one content object, the content metadata and the environmental metadata, at least one of (i) media content and (ii) a recommended next media track; and outputting, on an electronic device, at least one of the media content and the recommended next media track, wherein the outputting comprises playing the media content or displaying the recommended next media track, correspondingly, wherein when the recommended next media track is selected, media content corresponding to the recommended next media track is played. 7. The method according to claim 1 , wherein the media content is music. | 0.928994 |
9,378,740 | 17 | 18 | 17. The non-transitory computer readable medium of claim 16 , wherein the computer-executable module causes the computing device to store the intent definition by storing a slot definition identifying a data type, and wherein the process further comprises: identifying a user of the client device; obtaining an example text value of the data type for the slot definition based on the identified user; and generating the second text comprises using the example text value. | 17. The non-transitory computer readable medium of claim 16 , wherein the computer-executable module causes the computing device to store the intent definition by storing a slot definition identifying a data type, and wherein the process further comprises: identifying a user of the client device; obtaining an example text value of the data type for the slot definition based on the identified user; and generating the second text comprises using the example text value. 18. The non-transitory computer readable medium of claim 17 , wherein the computer-executable module causes the computing device to obtain the example text value of the data type by obtaining the example text value from a content library for the identified user. | 0.5 |
9,990,359 | 1 | 10 | 1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment. | 1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment. 10. The processor-implemented method of claim 1 , further comprising: identifying a first excerpt associated with the first concept and the online discussion; identifying a plurality of additional excerpts associated with the first concept, the second concept and the online discussion; and augmenting a ranking score corresponding to the first excerpt based on the additional excerpts being associated with the first concept and with the second concept. | 0.5 |
9,829,984 | 52 | 53 | 52. The method of claim 51 , further comprising: presenting a plurality of visual gesture recognition types on a computer display. | 52. The method of claim 51 , further comprising: presenting a plurality of visual gesture recognition types on a computer display. 53. The method of claim 52 , wherein the plurality of visual gesture types include a shaped-based gesture, a position-based gesture, a motion-assisted gesture and a mixed gesture. | 0.5 |
9,754,209 | 8 | 11 | 8. A system for use in managing knowledge-based authentication systems, the system comprising a knowledge-based authentication system comprising a processor configured to: evaluate questions based on a set of parameters, each question being associated with a ranking value, wherein the questions are created from organization based information gathered from a set of distributed organizational information sources under control of an organization, wherein the set of parameters include user configuration information provided by a user, the user being a part of the organization, wherein the user configuration information indicates types of questions suitable for a use case scenario, historical information associated with questions and facts used previously for authenticating the user, and feedback information indicating how a user responds to each question presented to the user, wherein the historical information is stored in a velocity database, wherein the organization based information includes information that is private and confidential to the organization, wherein the organization based information is gathered periodically; select, based on the evaluation, a set of questions from the questions and a set of responses for each question of the set of questions for the use case scenario based on respective ranking value associated with each question and quality of facts used for creating the questions, wherein the quality of a fact determines a quality of a question created from the fact, wherein the quality of a question indicates whether the question is suitable for authenticating the user, wherein a question of a high quality is considered suitable for authenticating the user and a question of a low quality is not considered suitable for authenticating the user, wherein the user is authenticated in the use case scenario by a knowledge-based authentication system using the set of questions, wherein the knowledge-based authentication system includes a question picker component providing a respective ranking value for each question based on the historical information, wherein the question picker component selects the set of questions with highest ranking values based on the use case scenario, wherein the use case scenario is associated with a risk level and configuration information, wherein the set of questions are selected based on the risk level associated with the use case scenario, wherein the use case scenario is configurable and specified by the user; and update the historical information of the velocity database for adaptively improving the selection of the set of questions, wherein a velocity of a fact indicates historical information associated with the fact indicating how recently the fact has been used to previously authenticate the user. | 8. A system for use in managing knowledge-based authentication systems, the system comprising a knowledge-based authentication system comprising a processor configured to: evaluate questions based on a set of parameters, each question being associated with a ranking value, wherein the questions are created from organization based information gathered from a set of distributed organizational information sources under control of an organization, wherein the set of parameters include user configuration information provided by a user, the user being a part of the organization, wherein the user configuration information indicates types of questions suitable for a use case scenario, historical information associated with questions and facts used previously for authenticating the user, and feedback information indicating how a user responds to each question presented to the user, wherein the historical information is stored in a velocity database, wherein the organization based information includes information that is private and confidential to the organization, wherein the organization based information is gathered periodically; select, based on the evaluation, a set of questions from the questions and a set of responses for each question of the set of questions for the use case scenario based on respective ranking value associated with each question and quality of facts used for creating the questions, wherein the quality of a fact determines a quality of a question created from the fact, wherein the quality of a question indicates whether the question is suitable for authenticating the user, wherein a question of a high quality is considered suitable for authenticating the user and a question of a low quality is not considered suitable for authenticating the user, wherein the user is authenticated in the use case scenario by a knowledge-based authentication system using the set of questions, wherein the knowledge-based authentication system includes a question picker component providing a respective ranking value for each question based on the historical information, wherein the question picker component selects the set of questions with highest ranking values based on the use case scenario, wherein the use case scenario is associated with a risk level and configuration information, wherein the set of questions are selected based on the risk level associated with the use case scenario, wherein the use case scenario is configurable and specified by the user; and update the historical information of the velocity database for adaptively improving the selection of the set of questions, wherein a velocity of a fact indicates historical information associated with the fact indicating how recently the fact has been used to previously authenticate the user. 11. The system of claim 8 , wherein the set of parameters includes history of a previously used question and facts used to create the previously used question. | 0.772857 |
10,019,514 | 13 | 20 | 13. A system of searching for an element in speech related documents, the system comprising: a non-transitory memory; and a hardware controller configured to: transcribe a set of speech recordings stored in a speech recording database to a set of phoneme strings and include the phoneme strings in a set of phonetic transcriptions, reverse-index, using one or more parser rules, the phonetic transcriptions according to one or more phonemes, and store the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string, transcribe a textual search term into a set of search phoneme strings, and use the set of search phoneme strings to search for an element in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents. | 13. A system of searching for an element in speech related documents, the system comprising: a non-transitory memory; and a hardware controller configured to: transcribe a set of speech recordings stored in a speech recording database to a set of phoneme strings and include the phoneme strings in a set of phonetic transcriptions, reverse-index, using one or more parser rules, the phonetic transcriptions according to one or more phonemes, and store the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string, transcribe a textual search term into a set of search phoneme strings, and use the set of search phoneme strings to search for an element in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents. 20. The system of claim 13 , wherein the controller is configured to: statistically calculate a probability of a recognition error for a phoneme; and based on relating a fuzziness parameter value to the probability, select to include or exclude a phonetic transcription in or from a result of searching for an element in the set of phonetic transcriptions. | 0.5 |
7,805,714 | 7 | 8 | 7. The computer readable storage medium of claim 5 , wherein the syntax structure specification is defined using a grammar comprising: a syntax search, for identifying a syntax structure, being a syntax name followed by a colon. | 7. The computer readable storage medium of claim 5 , wherein the syntax structure specification is defined using a grammar comprising: a syntax search, for identifying a syntax structure, being a syntax name followed by a colon. 8. The computer readable storage medium of claim 7 , wherein the syntax name is a string. | 0.602679 |
9,286,377 | 12 | 13 | 12. A method according to claim 11 , further comprising: determining the relevance score by applying scoring rules to the possible relevant candidates. | 12. A method according to claim 11 , further comprising: determining the relevance score by applying scoring rules to the possible relevant candidates. 13. A method according to claim 12 , wherein the scoring rules comprise determining a number of query key tokens present in each possible relevant candidate and a type of each query key token in each possible relevant candidate. | 0.755365 |
9,852,455 | 13 | 15 | 13. A system comprising: a database including a feedback table; and a database engine server communicatively coupled to the database and having one or more processors, the database engine server being configured to perform operations comprising: receiving, over a network, a first message from a client machine associated with a first user, the first message including a request from to leave feedback related to a second user; generating, a set of predefined feedback comments, the generating being responsive to identifying a conclusion of a transaction for an item in an ecommerce system, the set of predefined feedback comments being related to the item; determining not to communicate a prompt to enter a freeform feedback comment and further to communicate the set of predefined feedback comments if responsive to identifying the first user as being associated with a predefined group of national states having laws relating to published content; communicating, over the network, the set of predefined feedback comments to the client machine: identifying a first predefined feedback comment from the set of predefined feedback comments responsive to receiving a selection from the first user; and storing an indicator signifying the first predefined feedback comment in a database record of a user table, the indicator distinguishing the first predefined feedback comment from the other predefined feedback comments in the set of predefined feedback comments. | 13. A system comprising: a database including a feedback table; and a database engine server communicatively coupled to the database and having one or more processors, the database engine server being configured to perform operations comprising: receiving, over a network, a first message from a client machine associated with a first user, the first message including a request from to leave feedback related to a second user; generating, a set of predefined feedback comments, the generating being responsive to identifying a conclusion of a transaction for an item in an ecommerce system, the set of predefined feedback comments being related to the item; determining not to communicate a prompt to enter a freeform feedback comment and further to communicate the set of predefined feedback comments if responsive to identifying the first user as being associated with a predefined group of national states having laws relating to published content; communicating, over the network, the set of predefined feedback comments to the client machine: identifying a first predefined feedback comment from the set of predefined feedback comments responsive to receiving a selection from the first user; and storing an indicator signifying the first predefined feedback comment in a database record of a user table, the indicator distinguishing the first predefined feedback comment from the other predefined feedback comments in the set of predefined feedback comments. 15. The system of claim 13 , wherein the operations further comprise: communicating the set of predefined feedback comments includes communicating a name of the item; and communicating the name of the item includes accessing an item table from a network-based transaction system, the item table storing a plurality of item names including the name of the item. | 0.57346 |
8,301,578 | 1 | 5 | 1. A method of tagging signals of interest in time variant data, the method causing a computing device to perform steps comprising: classifying, via a processor, data from an input signal using a short-term classifier, wherein there are at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also bypasses data that is known to be of no interest; collapsing via the processor the input data in the short-term classifier that is classified as having no identified outputs, thereby creating time-variant data; and tagging via the processor a known signal of interest in the time-variant data that was classified as having at least one potential signal of interest. | 1. A method of tagging signals of interest in time variant data, the method causing a computing device to perform steps comprising: classifying, via a processor, data from an input signal using a short-term classifier, wherein there are at least two classifications available comprising a first classification of the data as having no identified outputs and a second classification of the data as at least one potential signal of interest, wherein the short-term classifier also bypasses data that is known to be of no interest; collapsing via the processor the input data in the short-term classifier that is classified as having no identified outputs, thereby creating time-variant data; and tagging via the processor a known signal of interest in the time-variant data that was classified as having at least one potential signal of interest. 5. The method of claim 1 , wherein the method takes place in one pass of the input signal without the need for pre-segmentation. | 0.808955 |
7,877,344 | 1 | 5 | 1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of concepts; identifying a plurality of meaning loaded entities within the meaning taxonomy; identifying a group of syntactic structures including at least one normalized syntactic structure and a plurality of non-normalized syntactic structures, the at least one normalized syntactic structure being used to standardize the plurality of non-normalized syntactic structures; associating the at least one normalized syntactic structure with at least one of the plurality of concepts; associating at least one of the plurality of non-normalized syntactic structures with the at least one normalized syntactic structure; and associating at least one of the plurality of documents with the at least one of the plurality of concepts based on a relationship between the at least one of the plurality of documents and the at least one of the plurality of non-normalized syntactic structures. | 1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of concepts; identifying a plurality of meaning loaded entities within the meaning taxonomy; identifying a group of syntactic structures including at least one normalized syntactic structure and a plurality of non-normalized syntactic structures, the at least one normalized syntactic structure being used to standardize the plurality of non-normalized syntactic structures; associating the at least one normalized syntactic structure with at least one of the plurality of concepts; associating at least one of the plurality of non-normalized syntactic structures with the at least one normalized syntactic structure; and associating at least one of the plurality of documents with the at least one of the plurality of concepts based on a relationship between the at least one of the plurality of documents and the at least one of the plurality of non-normalized syntactic structures. 5. The method according to claim 1 , wherein associating the at least one normalized syntactic structure comprises associating a plurality of normalized syntactic structures with the at least one of the plurality of concepts. | 0.754367 |
8,972,442 | 1 | 8 | 1. A method for generating a search template, comprising: capturing a user input defining at least one search tag and provided by a user using a user input subsystem; selecting a search template from a template database subsystem and using a template retrieval subsystem according to said user input, said search template defining a plurality of search sources and a plurality of logical relations therebetween; acquiring search results by using said search template to search search source accessible via a network; presenting the search results to the user; making the search template available to users other than the user via the network; and using crowdsourcing to update the search template so that the users input parameters from the users other than the user are used to update the search template. | 1. A method for generating a search template, comprising: capturing a user input defining at least one search tag and provided by a user using a user input subsystem; selecting a search template from a template database subsystem and using a template retrieval subsystem according to said user input, said search template defining a plurality of search sources and a plurality of logical relations therebetween; acquiring search results by using said search template to search search source accessible via a network; presenting the search results to the user; making the search template available to users other than the user via the network; and using crowdsourcing to update the search template so that the users input parameters from the users other than the user are used to update the search template. 8. The method of claim 1 , wherein said search template is a mashup. | 0.907357 |
8,019,709 | 1 | 4 | 1. A system for filtering content of multimedia data containers, comprising: a network interface for receiving said multimedia data containers from a network; and a plurality of server units, each server unit comprising a set of processors and a set of memory devices, having installed thereon: a filter-definition module, having computer readable instructions stored in a computer readable storage medium, for acquisition of definitions of a set of filters from a user, each filter specifying a definition of a content descriptor, a descriptor criterion, and an operator; a rule-construction module, having computer readable instructions stored in a computer readable storage medium, for acquisition of a set of content-filtering rules from said user, each rule specifying a Boolean expression of a subset of said filters and a filtering action; a module for characterizing content of each component of a multimedia data container, determining said content descriptor, applying said operator, and determining a state of said each filter; a module for determining a binary output of each said rule; and a module for performing a filtering action relevant to said content subject to a preset value of said binary output. | 1. A system for filtering content of multimedia data containers, comprising: a network interface for receiving said multimedia data containers from a network; and a plurality of server units, each server unit comprising a set of processors and a set of memory devices, having installed thereon: a filter-definition module, having computer readable instructions stored in a computer readable storage medium, for acquisition of definitions of a set of filters from a user, each filter specifying a definition of a content descriptor, a descriptor criterion, and an operator; a rule-construction module, having computer readable instructions stored in a computer readable storage medium, for acquisition of a set of content-filtering rules from said user, each rule specifying a Boolean expression of a subset of said filters and a filtering action; a module for characterizing content of each component of a multimedia data container, determining said content descriptor, applying said operator, and determining a state of said each filter; a module for determining a binary output of each said rule; and a module for performing a filtering action relevant to said content subject to a preset value of said binary output. 4. The system of claim 1 , further comprising a module for enabling said user to provide said Boolean expression according to algebraic syntax. | 0.837868 |
6,054,990 | 1 | 7 | 1. A computer system for sketching an illustration and for writing annotations by a user, said computer system comprising: a processor; a memory device coupled to said processor; a display device coupled to said processor; an input device adapted to receive a user annotation or a sketch; a keypad coupled to said processor; a lens coupled to said processor, said lens adapted to capture an image; a shutter coupled to said processor; an image sensor coupled to said processor for detecting photographic conditions; a photographic media adapted to receive said image and said user annotation; a non-cursive handwriting recognizer adapted to receive a predetermined set of non-cursive characters from the input device; and an encoder adapted to be coupled to said processor and to said photographic media, said encoder adapted to archive said annotation and sketch and said image onto the photographic media. | 1. A computer system for sketching an illustration and for writing annotations by a user, said computer system comprising: a processor; a memory device coupled to said processor; a display device coupled to said processor; an input device adapted to receive a user annotation or a sketch; a keypad coupled to said processor; a lens coupled to said processor, said lens adapted to capture an image; a shutter coupled to said processor; an image sensor coupled to said processor for detecting photographic conditions; a photographic media adapted to receive said image and said user annotation; a non-cursive handwriting recognizer adapted to receive a predetermined set of non-cursive characters from the input device; and an encoder adapted to be coupled to said processor and to said photographic media, said encoder adapted to archive said annotation and sketch and said image onto the photographic media. 7. The computer system of claim 1, further comprising a compression engine coupled to said processor and said encoder for compressing said image before archiving said image and text onto said media. | 0.856729 |
7,519,589 | 13 | 16 | 13. The method of claim 12 , further comprising: establishing an actor heartbeat based on an activity level, the activity level differentiated between the modalities of communication. | 13. The method of claim 12 , further comprising: establishing an actor heartbeat based on an activity level, the activity level differentiated between the modalities of communication. 16. The method of claim 13 , wherein the modalities include: telephone; instant messaging, calendar, in-person meetings, creation of documents, editing of documents. | 0.5 |
9,465,814 | 2 | 4 | 2. The method of claim 1 wherein obtaining the image associated with the particular website further comprises: checking a specific location in a directory tree of the particular website for a file with a designated name; and sending a copy of the file to a server for storage. | 2. The method of claim 1 wherein obtaining the image associated with the particular website further comprises: checking a specific location in a directory tree of the particular website for a file with a designated name; and sending a copy of the file to a server for storage. 4. The method of claim 2 wherein obtaining the image associated with the particular website further comprises altering the image. | 0.5 |
9,218,546 | 11 | 19 | 11. A system, comprising: a data processing apparatus; and a memory coupled to the data processing apparatus having instructions stored thereon which, when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving data specifying a first image; receiving text labels for the first image; for each of one or more of the text labels: receiving search results in response to a web search performed using the text label as a query, each search result referencing a web resource; assigning a text label ranking score to the text label based on a number of the resources referenced by the received search results that include an image matching the first image; ranking the text labels, at least in part, based on the text label ranking scores assigned to text labels; and selecting an image label for the first image from the ranked text labels, the image label being selected based on the ranking. | 11. A system, comprising: a data processing apparatus; and a memory coupled to the data processing apparatus having instructions stored thereon which, when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving data specifying a first image; receiving text labels for the first image; for each of one or more of the text labels: receiving search results in response to a web search performed using the text label as a query, each search result referencing a web resource; assigning a text label ranking score to the text label based on a number of the resources referenced by the received search results that include an image matching the first image; ranking the text labels, at least in part, based on the text label ranking scores assigned to text labels; and selecting an image label for the first image from the ranked text labels, the image label being selected based on the ranking. 19. The system of claim 11 wherein the text label ranking score for each text label is based on a median search result score calculated according to search result scores associated with the search results, a number of search results returned by the web search, and an original rank position of the received text labels. | 0.5 |
8,515,980 | 1 | 3 | 1. A computer-implemented method comprising: processing a query to identify, a set of item listings, each item listing associated with an item or service being offered for sale and assigned to a leaf-level category; obtaining for the query a click probability score for each leaf-level category to which an item listing satisfying the query has been assigned, the click probability score for a particular leaf-level category derived by dividing a number of clicks for the particular leaf-level category by the total number of clicks for all leaf-level categories to which an item listing satisfying the query has been assigned; identifying up to a predetermined number of leaf-level categories with click probability scores exceeding a threshold score; for each of the identified leaf-level categories, calculating a category boost score for use in determining the order in which the item listings are to be presented in a search results page; and presenting a search results page with the item listings ordered based in part on the category boost score for the leaf-level category, to which each item listing is assigned. | 1. A computer-implemented method comprising: processing a query to identify, a set of item listings, each item listing associated with an item or service being offered for sale and assigned to a leaf-level category; obtaining for the query a click probability score for each leaf-level category to which an item listing satisfying the query has been assigned, the click probability score for a particular leaf-level category derived by dividing a number of clicks for the particular leaf-level category by the total number of clicks for all leaf-level categories to which an item listing satisfying the query has been assigned; identifying up to a predetermined number of leaf-level categories with click probability scores exceeding a threshold score; for each of the identified leaf-level categories, calculating a category boost score for use in determining the order in which the item listings are to be presented in a search results page; and presenting a search results page with the item listings ordered based in part on the category boost score for the leaf-level category, to which each item listing is assigned. 3. The computer-implemented method of claim 1 , wherein the threshold score is derived by dividing the click probability score of the leaf-level category with the highest click probability score by one less than the predetermined number. | 0.799492 |
9,566,092 | 1 | 8 | 1. A bone anchor assembly comprising: a) a shank having an elongate body and a head, the head having a radiused surface, the body comprising a bone fixation structure; b) a receiver having a top portion and a base, the base having an outer surface, the receiver top portion defining a channel for receiving a longitudinal connecting member, the base defining a cavity therewithin, the channel communicating with the cavity, the cavity communicating with a bottom surface of the base through a receiver lower opening; c) a sleeve with a central opening defining an interior surface, the interior surface of the central opening being sized and shaped to substantially surround and engage the receiver base outer surface; d) a retainer having a compressible upper portion and an expandable lower portion, the compressible upper portion having a capture structure to be captured within the cavity of the receiver as the retainer is inserted through the receiver lower opening, the expandable lower portion expandable about the shank head when the shank is inserted into the retainer, the interior surface of the sleeve to engage an outer surface of the expandable lower portion to prohibit expansion of the expandable lower portion after the shank head is inserted into the retainer; and e) a compression insert to engage both an inner surface of the compressible upper portion of the retainer and the head radiused surface in a friction fit engagement. | 1. A bone anchor assembly comprising: a) a shank having an elongate body and a head, the head having a radiused surface, the body comprising a bone fixation structure; b) a receiver having a top portion and a base, the base having an outer surface, the receiver top portion defining a channel for receiving a longitudinal connecting member, the base defining a cavity therewithin, the channel communicating with the cavity, the cavity communicating with a bottom surface of the base through a receiver lower opening; c) a sleeve with a central opening defining an interior surface, the interior surface of the central opening being sized and shaped to substantially surround and engage the receiver base outer surface; d) a retainer having a compressible upper portion and an expandable lower portion, the compressible upper portion having a capture structure to be captured within the cavity of the receiver as the retainer is inserted through the receiver lower opening, the expandable lower portion expandable about the shank head when the shank is inserted into the retainer, the interior surface of the sleeve to engage an outer surface of the expandable lower portion to prohibit expansion of the expandable lower portion after the shank head is inserted into the retainer; and e) a compression insert to engage both an inner surface of the compressible upper portion of the retainer and the head radiused surface in a friction fit engagement. 8. The bone anchor assembly of claim 1 , the retainer to be continuously rotatable relative to the receiver base when the capture structure of the compressible upper portion of the retainer is captured within the cavity of the receiver. | 0.676712 |
10,120,948 | 4 | 6 | 4. The computer-implemented method of claim 1 , further comprising: receiving, by the one or more computing devices, an input from the user indicative of the selection of the geofencing element; providing, by the one or more computing devices, data indicative of the selected geofencing element to the remote computing device; receiving, by the one or more computing devices, data indicative of the geofence to be established around the geographical location associated with the geofencing element; and establishing the geofence around the geographical location associated with the geofencing element based at least in part on the received data indicative of the geofence. | 4. The computer-implemented method of claim 1 , further comprising: receiving, by the one or more computing devices, an input from the user indicative of the selection of the geofencing element; providing, by the one or more computing devices, data indicative of the selected geofencing element to the remote computing device; receiving, by the one or more computing devices, data indicative of the geofence to be established around the geographical location associated with the geofencing element; and establishing the geofence around the geographical location associated with the geofencing element based at least in part on the received data indicative of the geofence. 6. The computer-implemented method of claim 4 , further comprising: receiving, by the one or more computing devices, location data indicative of a current geographic location of the user; and detecting, by the one or more computing devices, entry into the established geofence based at least in part on the received location data. | 0.5 |
8,712,953 | 1 | 2 | 1. A computer-implemented method comprising: receiving a semantic data object defining access in a service-oriented architecture (SOA) network of an enterprise to data content in a defined context, where the SOA network includes a backend enterprise server hosting a data store to provide data to enterprise frontend devices, the semantic data object a modeled object defining services to interact with data in different contexts, the semantic data object representing data content of the data store in the defined context via the services, the defined context having an associated access and navigation of the data content in the frontend; associating a metadata description with the semantic data object to enrich the semantic data object by defining associations and access to the data content of the semantic data object, and by defining standard views that each define access to and navigation of the data content of the semantic data object for various usage scenarios for the defined context, where each of the standard views differently defines a user interface projection of selected technical characteristics of the data content of the semantic data object; generating an enriched semantic data object having the associated metadata description and having service definitions defining access to the data content through a request to the enriched semantic data object as a service interface to the data content in a usage scenario; exposing the enriched semantic data object as a service interface for the access to the associated data in the usage scenario, the enriched semantic data object to provide access to the data content in an associated view and navigation of the data object in response to a runtime access to the enriched semantic data object; accessing a navigation pattern that defines a transition from one view to another view in response to a request for a function of a user interface incorporating the service interface; and applying the navigation pattern at runtime of the enriched semantic data object to transition from one view of the user interface to another based on the associations described in the metadata description. | 1. A computer-implemented method comprising: receiving a semantic data object defining access in a service-oriented architecture (SOA) network of an enterprise to data content in a defined context, where the SOA network includes a backend enterprise server hosting a data store to provide data to enterprise frontend devices, the semantic data object a modeled object defining services to interact with data in different contexts, the semantic data object representing data content of the data store in the defined context via the services, the defined context having an associated access and navigation of the data content in the frontend; associating a metadata description with the semantic data object to enrich the semantic data object by defining associations and access to the data content of the semantic data object, and by defining standard views that each define access to and navigation of the data content of the semantic data object for various usage scenarios for the defined context, where each of the standard views differently defines a user interface projection of selected technical characteristics of the data content of the semantic data object; generating an enriched semantic data object having the associated metadata description and having service definitions defining access to the data content through a request to the enriched semantic data object as a service interface to the data content in a usage scenario; exposing the enriched semantic data object as a service interface for the access to the associated data in the usage scenario, the enriched semantic data object to provide access to the data content in an associated view and navigation of the data object in response to a runtime access to the enriched semantic data object; accessing a navigation pattern that defines a transition from one view to another view in response to a request for a function of a user interface incorporating the service interface; and applying the navigation pattern at runtime of the enriched semantic data object to transition from one view of the user interface to another based on the associations described in the metadata description. 2. The method of claim 1 , wherein generating the enriched semantic data object further comprises: generating standardized methods for accessing the enriched semantic data object, the standardized methods accessible via service requests. | 0.758656 |
7,941,384 | 8 | 9 | 8. The system of claim 5 further comprising: a plurality of source ontologies populated in the inference engine, the source ontologies describing the metadata from one or more source databases; and a canonical ontology populated in the inference engine, the canonical ontology representing the lexical and semantic rules that will be used to normalize the data to a destination canonical structure; wherein the source ontologies and the canonical ontology are utilized to read and assert the transactions. | 8. The system of claim 5 further comprising: a plurality of source ontologies populated in the inference engine, the source ontologies describing the metadata from one or more source databases; and a canonical ontology populated in the inference engine, the canonical ontology representing the lexical and semantic rules that will be used to normalize the data to a destination canonical structure; wherein the source ontologies and the canonical ontology are utilized to read and assert the transactions. 9. The system of claim 8 , wherein the inference engine is utilized to transform transactions to destination canonical instances of the destination canonical structure by mapping the data structures of the database transactions, into the canonical structure, thereby providing normalized data, and wherein the normalized data is stored. | 0.5 |
8,386,262 | 1 | 6 | 1. A method comprising: partitioning, via a processor, a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; generating a semantic representation using the dialog act and the object; and recursively extending the semantic representation by qualifying the object in each of the independent clauses. | 1. A method comprising: partitioning, via a processor, a speech recognizer output into independent clauses; identifying, independent of domain, a dialog act for each of the independent clauses; identifying, dependent on domain, an object within each of the independent clauses; generating a semantic representation using the dialog act and the object; and recursively extending the semantic representation by qualifying the object in each of the independent clauses. 6. The method of claim 1 , wherein generating the semantic representation further comprises identifying relationships between the dialog act and the object. | 0.633803 |
7,516,162 | 1 | 2 | 1. An apparatus for managing electronically recorded document files, comprising: an input device for inputting by an operator; a virtual combination editor for editing a virtual combination object based on the information inputted in said input device, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; an index editor for editing an index object based on the information inputted in said input device, the index object denoting an object that has a second data region and manages at lest one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, as a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a document file manager for managing and processing the document files based on information recorded in the virtual combination object and information recorded in the index object. | 1. An apparatus for managing electronically recorded document files, comprising: an input device for inputting by an operator; a virtual combination editor for editing a virtual combination object based on the information inputted in said input device, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; an index editor for editing an index object based on the information inputted in said input device, the index object denoting an object that has a second data region and manages at lest one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, as a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a document file manager for managing and processing the document files based on information recorded in the virtual combination object and information recorded in the index object. 2. The apparatus according to claim 1 , wherein said virtual combination editor edits the virtual combination object to create or delete the virtual combination object, combine or unbind the document files to or from the virtual combination object, and set or reset an index object. | 0.807902 |
7,865,519 | 10 | 11 | 10. The computer program product of claim 7 wherein the matching algorithm selects terms using the topic map to combine terms to generate each proposed name. | 10. The computer program product of claim 7 wherein the matching algorithm selects terms using the topic map to combine terms to generate each proposed name. 11. The computer program product of claim 10 wherein the matching algorithm selects terms based on at least one limitation for the business data component selected from the group consisting of a constraint, a characteristic, one or more valid values, and a specified context. | 0.5 |
9,477,908 | 1 | 2 | 1. A computer-implemented method for detecting objects in an input image, comprising: receiving a set of training images and associated annotations, the annotations labeling categories and locations of objects which appear in the images; determining one or more subcategories for each of the categories of objects, wherein the number of subcategories for an object category is inferred from the training images and the associated annotations via a clustering technique in which the number of subcategories is driven by appearance variations within the object category, and wherein the clustering technique does not require the number of subcategories for the object category to be specified as an input to the clustering technique; training classifiers for detecting the subcategories; training a respective structured model for each of the categories of objects, the respective structured model accounting for relationships between detected subcategories; and detecting the objects in the input image using the trained subcategory classifiers and structured models. | 1. A computer-implemented method for detecting objects in an input image, comprising: receiving a set of training images and associated annotations, the annotations labeling categories and locations of objects which appear in the images; determining one or more subcategories for each of the categories of objects, wherein the number of subcategories for an object category is inferred from the training images and the associated annotations via a clustering technique in which the number of subcategories is driven by appearance variations within the object category, and wherein the clustering technique does not require the number of subcategories for the object category to be specified as an input to the clustering technique; training classifiers for detecting the subcategories; training a respective structured model for each of the categories of objects, the respective structured model accounting for relationships between detected subcategories; and detecting the objects in the input image using the trained subcategory classifiers and structured models. 2. The method of claim 1 , wherein the training of the classifiers is coupled. | 0.946866 |
9,715,333 | 1 | 13 | 1. A method of improving data input in a portable device having an input device, a display device and a processor operatively coupled to the input device and the display device, the portable device implementing the method being a portable device, the input device of the portable device including first and second input devices, the first input device and the display device disposed on a front of the portable device, and the second input device disposed on a back of the portable device, the second input device including means for selecting the selectable dynamic keys associated with the displayed set of words, the method comprising: ascertaining, by the processor, a set of words for display to a user of the portable device based on an already displayed word by the display device immediately preceding a text insertion point, each of the words in the set being ascertained based on a respective frequency of usage of the respective word with the already displayed word in a predetermined language; first displaying, by the display device, each word in the ascertained set in association with a respective selectable dynamic key; receiving, by the input device, an input data entry representing selection by the user of one of the selectable dynamic keys; second displaying, by the display device, at the text insertion point the respective word in the ascertained set associated with the selected dynamic key as represented by the received input data entry, the set of words including nine words displayed in a table having three rows and three columns by the display device, and the second input device includes three buttons disposed on a left portion on the back of the portable cellular device for selecting each of the three words displayed in a left-most column of the table, and the second input device includes three buttons disposed on a right portion on the back of the portable cellular device for selecting each of the three words displayed in a right-most column of the table, and wherein simultaneous depression of respective left and right buttons on the back of the portable cellular device selects each of the three words displayed in a middle column of the table. | 1. A method of improving data input in a portable device having an input device, a display device and a processor operatively coupled to the input device and the display device, the portable device implementing the method being a portable device, the input device of the portable device including first and second input devices, the first input device and the display device disposed on a front of the portable device, and the second input device disposed on a back of the portable device, the second input device including means for selecting the selectable dynamic keys associated with the displayed set of words, the method comprising: ascertaining, by the processor, a set of words for display to a user of the portable device based on an already displayed word by the display device immediately preceding a text insertion point, each of the words in the set being ascertained based on a respective frequency of usage of the respective word with the already displayed word in a predetermined language; first displaying, by the display device, each word in the ascertained set in association with a respective selectable dynamic key; receiving, by the input device, an input data entry representing selection by the user of one of the selectable dynamic keys; second displaying, by the display device, at the text insertion point the respective word in the ascertained set associated with the selected dynamic key as represented by the received input data entry, the set of words including nine words displayed in a table having three rows and three columns by the display device, and the second input device includes three buttons disposed on a left portion on the back of the portable cellular device for selecting each of the three words displayed in a left-most column of the table, and the second input device includes three buttons disposed on a right portion on the back of the portable cellular device for selecting each of the three words displayed in a right-most column of the table, and wherein simultaneous depression of respective left and right buttons on the back of the portable cellular device selects each of the three words displayed in a middle column of the table. 13. The method of claim 1 , wherein the frequency of usage of words with the already displayed word is based on frequency of usage by a general public in combination with frequency of usage by the user of the portable device. | 0.81405 |
9,224,396 | 1 | 6 | 1. A method comprising: establishing a call connection between at least a first and a second terminal; monitoring, by at least the first terminal, a conversation during the call in order to detect at least one predetermined context-related keyword received in one of the first or the second terminal and repeated in the other of the first or the second terminal; and in response to detecting at least one repeated predetermined context-related keyword, providing an indication about the detected context-related keyword to a user of at least the first terminal, said indication enabling opening an application linked to said context-related keyword. | 1. A method comprising: establishing a call connection between at least a first and a second terminal; monitoring, by at least the first terminal, a conversation during the call in order to detect at least one predetermined context-related keyword received in one of the first or the second terminal and repeated in the other of the first or the second terminal; and in response to detecting at least one repeated predetermined context-related keyword, providing an indication about the detected context-related keyword to a user of at least the first terminal, said indication enabling opening an application linked to said context-related keyword. 6. The method according to claim 1 , further comprising: comparing the detected context-related keyword to context data stored in connection with at least the first terminal; and mapping the detected context-related keyword to a closest-matching context data in order to obtain explicit information representing said keyword. | 0.669043 |
9,268,675 | 11 | 14 | 11. A computerized system for auditing a script code, the system comprising: a parser module stored on a computer and, when executed by the computer, configured to: parse the script code to generate script code metadata; and allow selection of one or more portions of the script code; a rules module stored on the computer and configured to audit the script code by applying rules to the selected one or more portions of the script code when the rules module is executed by the computer; and a reporting module stored on the computer and configured to use the script code metadata to generate a result of the audit when the reporting module is executed by the computer; wherein the parser module is configured to read the script code from an input script code file, the script code comprising at least one of a Quick Test Professional (QTP) script and a Load-runner script wherein the rules include a plurality of review points, the result includes a respective severity level associated with each of the plurality of review points, and applying the rules to the selected one or more portions of the script code includes checking a first review point of the plurality of review points against the selected one or more portions of the script code; recording a deviation if the selected one or more portions of the script code do not comply with the first review point; and checking a remainder of the review points of the plurality of review points against the selected one or more portions of the script code and recording deviations for each review point that the selected one or more portions of the script code does not comply with; wherein each of the plurality of review points is associated with a portion of the selected one or more portions of the script code to be audited; and wherein the result includes a respective (i) review field, (ii) review comment field, and (iii) status field associated with each of the plurality of review points. | 11. A computerized system for auditing a script code, the system comprising: a parser module stored on a computer and, when executed by the computer, configured to: parse the script code to generate script code metadata; and allow selection of one or more portions of the script code; a rules module stored on the computer and configured to audit the script code by applying rules to the selected one or more portions of the script code when the rules module is executed by the computer; and a reporting module stored on the computer and configured to use the script code metadata to generate a result of the audit when the reporting module is executed by the computer; wherein the parser module is configured to read the script code from an input script code file, the script code comprising at least one of a Quick Test Professional (QTP) script and a Load-runner script wherein the rules include a plurality of review points, the result includes a respective severity level associated with each of the plurality of review points, and applying the rules to the selected one or more portions of the script code includes checking a first review point of the plurality of review points against the selected one or more portions of the script code; recording a deviation if the selected one or more portions of the script code do not comply with the first review point; and checking a remainder of the review points of the plurality of review points against the selected one or more portions of the script code and recording deviations for each review point that the selected one or more portions of the script code does not comply with; wherein each of the plurality of review points is associated with a portion of the selected one or more portions of the script code to be audited; and wherein the result includes a respective (i) review field, (ii) review comment field, and (iii) status field associated with each of the plurality of review points. 14. The computerized system of claim 11 , wherein the audit includes identification of a location a portion of the script code complying with a coding standard. | 0.532164 |
9,323,826 | 1 | 12 | 1. A method of analyzing micro-blog activity to detect emerging and viral events comprising: examining a plurality of received micro-blog messages to predict an effect on society of a single event described in each micro-blog message included in a subset of micro-blog messages, wherein the subset of micro-blog messages comprises a plurality of micro-blog messages contained in the plurality of received micro-blog messages; forming a prediction about the effect on society of the single event described in each of the micro-blog messages contained in the subset of micro-blog messages; and alerting a user when the predicted effect exceeds a threshold. | 1. A method of analyzing micro-blog activity to detect emerging and viral events comprising: examining a plurality of received micro-blog messages to predict an effect on society of a single event described in each micro-blog message included in a subset of micro-blog messages, wherein the subset of micro-blog messages comprises a plurality of micro-blog messages contained in the plurality of received micro-blog messages; forming a prediction about the effect on society of the single event described in each of the micro-blog messages contained in the subset of micro-blog messages; and alerting a user when the predicted effect exceeds a threshold. 12. The method of claim 1 , wherein the examining step comprises comparing a level of sentiment in micro-blog message traffic relating to the single event in a current time interval with a level of sentiment in micro-blog message traffic relating to the single event in at least one earlier time interval. | 0.635167 |
8,731,920 | 11 | 16 | 11. A non-transitory computer-readable medium comprising computer program instructions executable to perform a method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. | 11. A non-transitory computer-readable medium comprising computer program instructions executable to perform a method for use with a system, the system including a first document, the first document containing at least some information in common with a spoken audio stream, the method comprising: (A) identifying text in the first document, wherein the text represents a concept; (B) identifying, based on the identified text and a repository of finite state grammars, a plurality of spoken forms of the concept, including at least one spoken form not contained in the first document, wherein all of the plurality of spoken forms have the same content as each other; (C) replacing the identified text with a finite state grammar specifying the plurality of spoken forms of the concept to produce a second document; (D) generating a document-specific language model based on the second document, comprising generating at least some of the document-specific language model based on the finite state grammar. 16. The non-transitory computer-readable medium of claim 11 , wherein the method further comprises: (F) before (A), generating the first document based on the spoken audio stream. | 0.731231 |
4,393,502 | 2 | 10 | 2. The method of claim 1 wherein said sequence of digital information words is formed of 2N information words, and each of said sequences of odd and even information words is formed of N information words. | 2. The method of claim 1 wherein said sequence of digital information words is formed of 2N information words, and each of said sequences of odd and even information words is formed of N information words. 10. The method of claim 2 wherein each of said steps of encoding the respective odd and even information words in an error correcting code comprises generating a P-parity word and a Q-parity word in response to said N information words, the Q-parity word being a function of a generating matrix of (b.times.b), where b is the bit length of each word; interleaving the N information words and the P-parity and Q-parity words; and inserting the interleaved words into said transmission block. | 0.5 |
7,908,371 | 11 | 18 | 11. A system for classifying activity performed on a computer system, wherein the system comprises at least one electronic device having one or more hardware components configured to: monitor the activity performed on the computer system, wherein the monitored activity includes a plurality of actions performed on the computer system and a plurality of objects accessed in the plurality of actions performed on the computer system; determine a chronological timeline for the plurality of actions performed on the computer system; infer one or more relationships between the plurality of objects and the plurality of actions in the chronological timeline; classify each of the plurality of objects and each of the plurality of actions in one or more of the plurality of categories based on the one or more inferred relationships; and display the one or more inferred relationships on a display device. | 11. A system for classifying activity performed on a computer system, wherein the system comprises at least one electronic device having one or more hardware components configured to: monitor the activity performed on the computer system, wherein the monitored activity includes a plurality of actions performed on the computer system and a plurality of objects accessed in the plurality of actions performed on the computer system; determine a chronological timeline for the plurality of actions performed on the computer system; infer one or more relationships between the plurality of objects and the plurality of actions in the chronological timeline; classify each of the plurality of objects and each of the plurality of actions in one or more of the plurality of categories based on the one or more inferred relationships; and display the one or more inferred relationships on a display device. 18. The system of claim 11 , wherein the chronological timeline for the plurality of actions comprises a first chronological timeline for a first computer system, and wherein the one or more hardware components associated with the at least one electronic device are further configured to: monitor activity performed on a second computer system, wherein the monitored activity performed on the second computer system includes one or more actions performed on the second computer system and one or more objects accessed in the one or more actions performed on the second computer system; determine a second chronological timeline for the one or more actions performed on the second computer system, wherein the one or more actions performed on the second computer system each occur at a respective chronological position in the second chronological timeline; and display an aggregate timeline for the first computer system and the second computer system on the display device, wherein the aggregate timeline includes the plurality of actions performed on the first computer system and the one or more actions performed on the second computer system. | 0.5 |
8,903,894 | 27 | 28 | 27. A method according to claim 23 , further comprising sending, via a network connection to the second apparatus, the HTTP response having been injected with the Javascript page load event handler. | 27. A method according to claim 23 , further comprising sending, via a network connection to the second apparatus, the HTTP response having been injected with the Javascript page load event handler. 28. A method according to claim 27 , wherein the second apparatus executes the injected Javascript page load event handler, which generates the second HTTP request as a HTTP GET request in response to the finishing of loading by the web browser of the second apparatus of the web page. | 0.5 |
8,897,151 | 1 | 2 | 1. A computer-implemented system for application protocol field extraction, comprising: an extraction specification that specifies data elements to be extracted from data packets and is expressed in terms of a context-free grammar, where the grammar defines grammatical structures of data packets transmitted in accordance with an application protocol and is defined as a tuple having nonterminals, terminals, counters, production rules and a start nonterminal, such that the counters are variables with an integer value used to chronicle parsing history of the production rules, and at least one of the production rules includes an action association with a terminal or nonterminal comprising body of the production rule and the action is an expression for updating a value of a counter defined by the grammar; an automata generator configured to receive the extraction specification and generate a counting automaton; and a field extractor configured to receive a data flow comprised of a plurality of data packets traversing through a network and extract data elements from the data packets in accordance with the counting automaton, where the field extractor is implemented by an integrated circuit. | 1. A computer-implemented system for application protocol field extraction, comprising: an extraction specification that specifies data elements to be extracted from data packets and is expressed in terms of a context-free grammar, where the grammar defines grammatical structures of data packets transmitted in accordance with an application protocol and is defined as a tuple having nonterminals, terminals, counters, production rules and a start nonterminal, such that the counters are variables with an integer value used to chronicle parsing history of the production rules, and at least one of the production rules includes an action association with a terminal or nonterminal comprising body of the production rule and the action is an expression for updating a value of a counter defined by the grammar; an automata generator configured to receive the extraction specification and generate a counting automaton; and a field extractor configured to receive a data flow comprised of a plurality of data packets traversing through a network and extract data elements from the data packets in accordance with the counting automaton, where the field extractor is implemented by an integrated circuit. 2. The system of claim 1 wherein the production rules are in the form of <predicate>: <nonterminal>→<body>, such that the body is an ordered sequence of terminals and nonterminals and each predicate is expressed in terms of at least one counter. | 0.83265 |
7,849,077 | 13 | 17 | 13. A non-transitory computer-readable storage medium storing processor executable instructions operable to perform a method, the method comprising: receiving a query, the query being configured to cause a search logic to retrieve one or more documents, the documents comprising text elements and metadata elements; creating from the query a series of sub-queries {SQ 1 , . . . SQ N }, N being an integer greater than 1, the series of sub-queries including one or more of, a sub-query based on one or more of, a numeric metadata link score, and a numeric metadata URL depth, where the numeric metadata link score is directly proportional to document relevance and where the numeric metadata URL depth is inversely proportional to document relevance; the series of sub-queries being configured so that a sub-query SQ X will cause the search logic to retrieve fewer documents than a sub-query SQ Y when X<Y; the series of sub-queries being configured so that a sub-query SQA will cause the search logic to retrieve documents having a higher relevancy than a sub-query SQB when A<B; and providing, in order providing, in order one or more sub-queries from the series of sub-queries, one or more sub-queries from the series of sub-queries to the search logic until a pre-determined number of documents are retrieved by the search logic. | 13. A non-transitory computer-readable storage medium storing processor executable instructions operable to perform a method, the method comprising: receiving a query, the query being configured to cause a search logic to retrieve one or more documents, the documents comprising text elements and metadata elements; creating from the query a series of sub-queries {SQ 1 , . . . SQ N }, N being an integer greater than 1, the series of sub-queries including one or more of, a sub-query based on one or more of, a numeric metadata link score, and a numeric metadata URL depth, where the numeric metadata link score is directly proportional to document relevance and where the numeric metadata URL depth is inversely proportional to document relevance; the series of sub-queries being configured so that a sub-query SQ X will cause the search logic to retrieve fewer documents than a sub-query SQ Y when X<Y; the series of sub-queries being configured so that a sub-query SQA will cause the search logic to retrieve documents having a higher relevancy than a sub-query SQB when A<B; and providing, in order providing, in order one or more sub-queries from the series of sub-queries, one or more sub-queries from the series of sub-queries to the search logic until a pre-determined number of documents are retrieved by the search logic. 17. The non-transitory computer-readable medium of claim 13 , where the series of sub-queries includes a linguistic-centric sub-query and further where the linguistic-centric sub-query includes one or more of, a sub-query that matches terms in the query to one or more text elements on a phrase level, a sub-query that matches terms in the query to one or more text elements on a proximity level, and a sub-query that matches terms in the query to one or more text elements on a Boolean AND level. | 0.527567 |
8,401,987 | 24 | 26 | 24. The article of manufacture of claim 20 , wherein generating the at least one model comprises: using a first data mining algorithm to generate at least one model to validate values in at least one column in the records of the first data set; using a second data mining algorithm to generate at least one model to validate values in at least one column in the records of the first data set; wherein applying each model in the data quality model to the records in the second data set comprises: determining a metric for each result of applying the models generated by the first and second data mining algorithms for each record in the second data set; and generating a summary metric for each record in the second data set that is a function of the metrics resulting from applying the models to the record. | 24. The article of manufacture of claim 20 , wherein generating the at least one model comprises: using a first data mining algorithm to generate at least one model to validate values in at least one column in the records of the first data set; using a second data mining algorithm to generate at least one model to validate values in at least one column in the records of the first data set; wherein applying each model in the data quality model to the records in the second data set comprises: determining a metric for each result of applying the models generated by the first and second data mining algorithms for each record in the second data set; and generating a summary metric for each record in the second data set that is a function of the metrics resulting from applying the models to the record. 26. The article of manufacture of claim 24 , wherein the models generated by the first data mining algorithm comprise a plurality of association rule models, wherein each association rule model includes at least one association rule to predict a value in one column based on at least one value in at least one predictor column, and wherein the models generated by the second data mining algorithm comprise a predictive model predicting values in a user selected column; wherein determining the metrics for each record in the second data set comprises: determining for each association model association rules not satisfied by the data in the record; for each association rule model having association rules not satisfied by data in the record, determining an association rule model metric as a function of statistical values of the association rules in the association rule model not satisfied; determining from the predictive model a confidence level of a value in each column predicted by one predictive model; determining a predictive model metric for each predictive model as a function of the determined confidence level for each predictive model applied to the record. | 0.5 |
8,712,946 | 14 | 20 | 14. A processor implemented method for provisioning of enhanced interactive constructs or materials, according to approaches used by experienced problem solvers; said method comprising activities implemented through the execution of one or more processors, said activities comprising: receipt or input or both of at least one input item, said input item comprising at least one topic, problem, question, query, conclusion, solution, answer, information construct, analysis construct, or at least one portion of at least one model or specification or enhanced interactive construct, or a combination thereof; evaluation of at least one said input item, said evaluation accomplished at least in part relative to at least one of an exemplary archetype process for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, an exemplary archetype structure for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, a customized archetype process for facilitating exemplary user problem solving, a customized archetype structure for facilitating exemplary user problem solving, archetype expectations, a target enhanced interactive construct, or related archives, or a combination thereof; provisioning in display, output, or storage, or a combination thereof, of at least one portion of at least one enhanced interactive construct. | 14. A processor implemented method for provisioning of enhanced interactive constructs or materials, according to approaches used by experienced problem solvers; said method comprising activities implemented through the execution of one or more processors, said activities comprising: receipt or input or both of at least one input item, said input item comprising at least one topic, problem, question, query, conclusion, solution, answer, information construct, analysis construct, or at least one portion of at least one model or specification or enhanced interactive construct, or a combination thereof; evaluation of at least one said input item, said evaluation accomplished at least in part relative to at least one of an exemplary archetype process for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, an exemplary archetype structure for facilitating exemplary user problem solving or thinking and documenting regarding an arbitrary problem, a customized archetype process for facilitating exemplary user problem solving, a customized archetype structure for facilitating exemplary user problem solving, archetype expectations, a target enhanced interactive construct, or related archives, or a combination thereof; provisioning in display, output, or storage, or a combination thereof, of at least one portion of at least one enhanced interactive construct. 20. The processor implemented method of claim 14 further comprising the accomplishment or use, or both, of monitoring, recording, tracking, evaluating, scoring, storing, aggregation, analysis, gap analysis, pattern analysis, pattern identification, or a combination thereof, of at least one related item, comprising at least one of a user action, user interaction, user specification, user response, system event, archetype process history, archetype process action, archetype structure component, archetype structure history, comment, score, reward, ranking, rating, link, enhanced interactive construct, enhanced interactive component, related model, related content, suggestion, suggestion response, related reference, related system, related search, related source, target construct, or a combination thereof. | 0.66405 |
4,718,094 | 24 | 25 | 24. Apparatus as in claim 23 including means for determining each of at least some of the start-time distributions from the end-time distribution of the most recent previous phone. | 24. Apparatus as in claim 23 including means for determining each of at least some of the start-time distributions from the end-time distribution of the most recent previous phone. 25. Apparatus as in claim 24 wherein the minimum length is zero, the apparatus further comprising: means for characterizing the probability of each end time in the end-time distribution by a value .theta..sub.n which is equal to the end time probability at time t.sub.n divided by the uniform length probability; and means for computing .theta..sub.n for successive times t.sub.n as: EQU .theta..sub.n =q.sub.n +.theta..sub.n-1 p'.sub.n wherein p'.sub.n represents the replacement value for the incoming string label that is to be generated at time t.sub.n by the phone machine to yield the corresponding end time. | 0.5 |
9,135,555 | 16 | 18 | 16. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: retrieve, from one or more data stores, information associated with one or more nodes, a node comprising a user node or a concept node, each node being connected by edges to other nodes of a social graph; detect that a first user is entering an input term, the first user being associated with a first user node of the social graph; provide predictive typeahead results as the first user enters the input term, the predictive typeahead results being based on the input term, each predictive typeahead result corresponding to at least one node of the social graph, each predictive typeahead result including at least one image associated with one of the at least one node. | 16. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: retrieve, from one or more data stores, information associated with one or more nodes, a node comprising a user node or a concept node, each node being connected by edges to other nodes of a social graph; detect that a first user is entering an input term, the first user being associated with a first user node of the social graph; provide predictive typeahead results as the first user enters the input term, the predictive typeahead results being based on the input term, each predictive typeahead result corresponding to at least one node of the social graph, each predictive typeahead result including at least one image associated with one of the at least one node. 18. The system of claim 16 , wherein: at least one node in the social graph comprises a concept node associated with a concept; and the processors that are operable when executing the instructions to provide a predictive typeahead result comprise processors that are operable when executing the instructions to provide, based on a measure of affinity between the first user and the concept corresponding to the concept node, a predictive typeahead result corresponding to the concept node. | 0.640969 |
7,756,871 | 17 | 20 | 17. The method of claim 7 comprising: wherein applying the decision combiner includes: scoring a first particular transition between an N body text region in a first reading order alternative and a hypothetical sequential M body text region in the first reading order alternative based on the text flow analysis in terms of probability; scoring a second particular transition between the N body text region in a second reading order alternative and a hypothetical sequential P body text region in the second reading order alternative based on the text flow analysis in terms of probability; comparing probabilities of the first and second particular transitions; and choosing and storing the particular transition with a higher probability score as part of a determined reading order in an article of the document. | 17. The method of claim 7 comprising: wherein applying the decision combiner includes: scoring a first particular transition between an N body text region in a first reading order alternative and a hypothetical sequential M body text region in the first reading order alternative based on the text flow analysis in terms of probability; scoring a second particular transition between the N body text region in a second reading order alternative and a hypothetical sequential P body text region in the second reading order alternative based on the text flow analysis in terms of probability; comparing probabilities of the first and second particular transitions; and choosing and storing the particular transition with a higher probability score as part of a determined reading order in an article of the document. 20. The method of claim 17 further comprising comparing the probabilities of the first and second particular transitions with a third particular transition in a third reading order. | 0.903723 |
8,074,199 | 1 | 6 | 1. A computer-implemented system for programming a unified messaging (UM) application, comprising: a user interface; a programming environment operating on at least one computing device and accessed via the user interface for composing in an eXtensible Markup Language (XML) a UM finite state machine (FSM) comprising menu states defined by a plurality of user prompts and transitions between user prompts, each transition defined by a particular user response to a prompt; a UM software component including an external software component called by the UM FSM; an XML feature utilized by the programming environment to create a valid menu state based upon the UM software component, wherein the XML feature includes a function wrapper that is used by the programming environment to validate the external software component during a compilation phase when the external software component is present and generate a binary UM FSM, and to generate an error when the external software component is absent during the compilation phase; and a verification tool invoked during execution of the binary UM FSM that confirms that a version of the external software component present during a compilation phase is the same as a version of the external software component available at execution. | 1. A computer-implemented system for programming a unified messaging (UM) application, comprising: a user interface; a programming environment operating on at least one computing device and accessed via the user interface for composing in an eXtensible Markup Language (XML) a UM finite state machine (FSM) comprising menu states defined by a plurality of user prompts and transitions between user prompts, each transition defined by a particular user response to a prompt; a UM software component including an external software component called by the UM FSM; an XML feature utilized by the programming environment to create a valid menu state based upon the UM software component, wherein the XML feature includes a function wrapper that is used by the programming environment to validate the external software component during a compilation phase when the external software component is present and generate a binary UM FSM, and to generate an error when the external software component is absent during the compilation phase; and a verification tool invoked during execution of the binary UM FSM that confirms that a version of the external software component present during a compilation phase is the same as a version of the external software component available at execution. 6. The computer-implemented system of claim 1 , wherein the UM software component comprises an XML snippet, the XML feature comprising an importation element utilized by the programming environment to replicate the XML snippet upon compilation. | 0.562724 |
9,077,933 | 15 | 19 | 15. An article of manufacture including a non-transitory medium for storing machine readable instructions which, when loaded and executed by a processor, cause the processor to perform operations, the operations comprising: tabulating for each program in a program guide an occurrence count corresponding to each term of a plurality of terms, the occurrence count indicating a number of times the respective term is associated with a corresponding program; computing for each program in the program guide a relevance ranking score by multiplying an average of occurrence counts associated with a corresponding program by how many times the corresponding program is listed in the program guide; selecting a list of programs from the program guide based on a respective relevance ranking score of each program; and outputting the list of programs. | 15. An article of manufacture including a non-transitory medium for storing machine readable instructions which, when loaded and executed by a processor, cause the processor to perform operations, the operations comprising: tabulating for each program in a program guide an occurrence count corresponding to each term of a plurality of terms, the occurrence count indicating a number of times the respective term is associated with a corresponding program; computing for each program in the program guide a relevance ranking score by multiplying an average of occurrence counts associated with a corresponding program by how many times the corresponding program is listed in the program guide; selecting a list of programs from the program guide based on a respective relevance ranking score of each program; and outputting the list of programs. 19. The article of manufacture as defined in claim 15 , wherein the operations further comprise weighting the relevance ranking score based on a user profile. | 0.685259 |
9,208,784 | 15 | 20 | 15. A method of broadcasting information by a Transcription Engine comprising: registering and authenticating automatically, by at least one server of the Transcription Engine, a broadcaster or an end user based on broadcaster equipment information or end user equipment information received by the at least one server; transcribing, in real time by the at least one server, received voice communications from the registered broadcaster equipment into associated text and broadcasting, by the at least one server, the associated text over a communication network to the authenticated and registered end user equipment or registered and authenticated broadcaster equipment and accepting or denying, by the at least one server, a request from a registered end user equipment to ask questions during the broadcast and confirm the broadcasting of the questions. | 15. A method of broadcasting information by a Transcription Engine comprising: registering and authenticating automatically, by at least one server of the Transcription Engine, a broadcaster or an end user based on broadcaster equipment information or end user equipment information received by the at least one server; transcribing, in real time by the at least one server, received voice communications from the registered broadcaster equipment into associated text and broadcasting, by the at least one server, the associated text over a communication network to the authenticated and registered end user equipment or registered and authenticated broadcaster equipment and accepting or denying, by the at least one server, a request from a registered end user equipment to ask questions during the broadcast and confirm the broadcasting of the questions. 20. The method of claim 15 where transcribing received voice communications into associated text and broadcasting the associated text comprises downloading broadcasting software, voice recognition software and speech tuning algorithms onto a broadcaster equipment to allow the broadcaster equipment to broadcast the associated text. | 0.5 |
9,177,074 | 27 | 28 | 27. The non-transitory computer readable storage medium of claim 25 , wherein the authorship identifier includes an email address for a purported author of or contributor to the first document, and wherein the email address is an email address in the first domain. | 27. The non-transitory computer readable storage medium of claim 25 , wherein the authorship identifier includes an email address for a purported author of or contributor to the first document, and wherein the email address is an email address in the first domain. 28. The non-transitory computer readable storage medium of claim 27 , wherein prior to conditionally confirming the authorship of the first document, the at least one program includes instructions to request that the entity confirm that the email address associated with the profile for the entity is the email address that the entity includes in documents authored by the entity. | 0.5 |
7,565,012 | 1 | 2 | 1. A method of generating an electronic document, the method comprising: photographing a document having a plurality of pages to generate moving picture data; detecting data of one page of the document by performing motion estimation on the moving picture data, performing document recognition on the data of the one page of the document, and storing the data of the one page of the document as first text data; detecting whether data of a next page is input by performing motion estimation on the moving picture data, and if the data of the next page is detected, performing document recognition on the data of the next page and storing the data of the next page as second text data; and storing the first text data and the second text data as one electronic document. | 1. A method of generating an electronic document, the method comprising: photographing a document having a plurality of pages to generate moving picture data; detecting data of one page of the document by performing motion estimation on the moving picture data, performing document recognition on the data of the one page of the document, and storing the data of the one page of the document as first text data; detecting whether data of a next page is input by performing motion estimation on the moving picture data, and if the data of the next page is detected, performing document recognition on the data of the next page and storing the data of the next page as second text data; and storing the first text data and the second text data as one electronic document. 2. The method of claim 1 , further comprising, before the photographing of the document: setting a photographing mode for the document recognition via a user interface unit; setting a mode corresponding to one of a double-sided document having a left side and a right side, a double-sided document having a top side and a bottom side, and a single-sided document; and selecting a format for a file in which the document is stored after being converted into the electronic document. | 0.562727 |
7,827,032 | 1 | 4 | 1. A method for adapting a model for a speech recognition system using an adaptation process, the method comprising: with an apparatus using at least one hardware-implemented processor, determining an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and adjusting an adaptation process for the model for the word or various models for the various words, based on the error rate. | 1. A method for adapting a model for a speech recognition system using an adaptation process, the method comprising: with an apparatus using at least one hardware-implemented processor, determining an error rate, corresponding to either recognition of instances of a word or recognition of instances of various words among a set of words; and adjusting an adaptation process for the model for the word or various models for the various words, based on the error rate. 4. The method of claim 1 , wherein adjusting an adaptation process comprises adapting the model or the various models or withholding adapting the model or the various models based on the error rate. | 0.633333 |
7,827,028 | 32 | 33 | 32. The article of manufacture of claim 31 , comprising computer readable program code for generating the translingual parsing model. | 32. The article of manufacture of claim 31 , comprising computer readable program code for generating the translingual parsing model. 33. The article of manufacture of claim 32 , wherein said computer readable program code for generating the translingual parsing model comprises computer readable program code for: receiving, at a parser training module, a destination language treebank having parse trees of a plurality of destination language sentences, the parse trees of said destination language sentences having nodes labeled with the syntactic labels; generating, using the destination language treebank, a destination language parsing model, including parameters for ranking candidate parse trees for a destination language sentence; receiving, at the parsing module, a second plurality of destination language sentences from a parallel corpus, the parallel corpus including the second plurality of destination language sentences and their respective source language equivalents; applying the destination language parsing model to the second plurality of destination language sentences to generate a ranked list of candidate parse trees for each sentence of the second plurality of destination language sentences; transforming the candidate parse trees by applying, with a tree transformer, a rule set associated with linguistic characteristics of the source and destination languages; assigning, with a role labeler, a linguistic role label to nodes of the candidate parse trees, the role label corresponding to the linguistic role of a node within its respective parse tree; extracting grammar constraints from portions of each candidate parse tree; and estimating the translingual parsing model using the extracted grammar constraints and source language sentences of the parallel corpus; the translingual parsing model including parameters sufficient to rank candidate parses, wherein the parameters relate elements of the candidate parses including source language words, destination language words, syntactic labels, and role labels. | 0.5 |
9,146,126 | 1 | 2 | 1. A method comprising: receiving, on a graphical user interface, a first user input for a destination; calculating a first route from an origin to the destination; displaying a representation of the first route on the graphical user interface; displaying, on the graphical user interface, an interactive sign icon representative of a real world sign from alongside a first road of the first route from the origin to the destination, wherein the interactive sign icon includes a representation of a second road that leads to the destination; receiving, on the graphical user interface, a second user input for the interactive icon representative of the real world sign; calculating a second route to the destination including the second road from the interactive sign icon, wherein the second route is an alternative route to the destination; and displaying the second route on the graphical user interface. | 1. A method comprising: receiving, on a graphical user interface, a first user input for a destination; calculating a first route from an origin to the destination; displaying a representation of the first route on the graphical user interface; displaying, on the graphical user interface, an interactive sign icon representative of a real world sign from alongside a first road of the first route from the origin to the destination, wherein the interactive sign icon includes a representation of a second road that leads to the destination; receiving, on the graphical user interface, a second user input for the interactive icon representative of the real world sign; calculating a second route to the destination including the second road from the interactive sign icon, wherein the second route is an alternative route to the destination; and displaying the second route on the graphical user interface. 2. The method of claim 1 , wherein the interactive sign icon includes a scalable vector graphics image. | 0.825424 |
8,041,565 | 13 | 16 | 13. A method of converting speech into text comprising: receiving audio information representing speech of a person; delivering said audio information to a plurality of speech-to-text conversion engines; converting said audio information by said conversion engines into a plurality of text files, each conversion engine producing one of said text files; fragmenting each of said text files into a plurality of overlapping text fragments, each of said text files being fragmented according to a set of previously determined time boundaries, said set of boundaries being the same for each of said text files, said overlapping creating duplicative information; comparing said plurality of text fragments a set at a time, each set corresponding to a single portion of said audio information; outputting a hybrid text fragment for each of said sets, each of said hybrid text fragments corresponding to a distinct portion of said audio information; and concatenating said hybrid text fragments into a text file that represents said audio information by deleting said duplicative information. | 13. A method of converting speech into text comprising: receiving audio information representing speech of a person; delivering said audio information to a plurality of speech-to-text conversion engines; converting said audio information by said conversion engines into a plurality of text files, each conversion engine producing one of said text files; fragmenting each of said text files into a plurality of overlapping text fragments, each of said text files being fragmented according to a set of previously determined time boundaries, said set of boundaries being the same for each of said text files, said overlapping creating duplicative information; comparing said plurality of text fragments a set at a time, each set corresponding to a single portion of said audio information; outputting a hybrid text fragment for each of said sets, each of said hybrid text fragments corresponding to a distinct portion of said audio information; and concatenating said hybrid text fragments into a text file that represents said audio information by deleting said duplicative information. 16. A method as recited in claim 13 further comprising: creating said hybrid text fragment by using an equivalence table. | 0.786972 |
9,361,331 | 10 | 11 | 10. A computer based method executed by one or more processors, the method comprising: receiving a search query, which includes at least a first phrase and a second phrase, at a server that is in communication with an index server system storing a plurality of posting lists, at least some of the posting lists being associated with a phrase and including document identifiers for documents containing the phrase, and wherein the document identifiers in at least some posting lists are partitioned based on a relevance score that indicates a respective document's relevance to the phrase of the posting list, such that a first portion of the posting list contains document identifiers of documents with a higher relevance score than documents identified in a second portion of the posting list; responsive to the first phrase having a partitioned posting list and the second phrase having a partitioned posting list, intersecting the first portion of the posting list of the first phrase with the first portion of the posting list of the second phrase; determining that the intersection includes a sufficient result set; and ranking the documents in the result set. | 10. A computer based method executed by one or more processors, the method comprising: receiving a search query, which includes at least a first phrase and a second phrase, at a server that is in communication with an index server system storing a plurality of posting lists, at least some of the posting lists being associated with a phrase and including document identifiers for documents containing the phrase, and wherein the document identifiers in at least some posting lists are partitioned based on a relevance score that indicates a respective document's relevance to the phrase of the posting list, such that a first portion of the posting list contains document identifiers of documents with a higher relevance score than documents identified in a second portion of the posting list; responsive to the first phrase having a partitioned posting list and the second phrase having a partitioned posting list, intersecting the first portion of the posting list of the first phrase with the first portion of the posting list of the second phrase; determining that the intersection includes a sufficient result set; and ranking the documents in the result set. 11. The computer based method of claim 10 , further comprising: determining that the intersection fails to include a sufficient result set; and intersecting the second portion of the posting list for the first phrase with the first portion of the posting list for the second phrase; and including the intersection of the second portion and the first portion in the result set. | 0.5 |
8,023,962 | 1 | 6 | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. | 1. A system for providing geographic information comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device connectable to the database from a remote location, the mobile device having a controller, a position sensor for determining a location of the mobile device and a pointing device adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, geographical feature or location of interest to a user, the controller being adapted to receive a thematic query from a user, the controller being further adapted retrieve a portion of the geographic information from the database selected by a combination of the location of the mobile device, a pointing direction of the device and the thematic query, and the geographical information is about the particular object, geographical feature or location. 6. The system of claim 1 further comprising a display connected to the mobile device for presenting the information of interest to a user. | 0.782334 |
9,824,682 | 5 | 6 | 5. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a speech; recognizing the speech using a phonotactic grammar to generate a phone lattice; removing silence and filler words from the phone lattice, to yield a revised phone lattice; normalizing costs in the revised phone lattice such that a cost of a best path is set to zero; generating a cost-normalized query using factors of interest, wherein an index of words is indexed by the factors of interest; generating, by performing a first pass of entries in a database, a shortlist of recognized speech possibilities using the revised phone lattice, the index of words, and indices contained in the cost-normalized query; performing a second pass on the shortlist of recognized speech possibilities using a grammar generated from the entries in the database to obtain a final result; and providing a response to the speech based on the final result. | 5. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving a speech; recognizing the speech using a phonotactic grammar to generate a phone lattice; removing silence and filler words from the phone lattice, to yield a revised phone lattice; normalizing costs in the revised phone lattice such that a cost of a best path is set to zero; generating a cost-normalized query using factors of interest, wherein an index of words is indexed by the factors of interest; generating, by performing a first pass of entries in a database, a shortlist of recognized speech possibilities using the revised phone lattice, the index of words, and indices contained in the cost-normalized query; performing a second pass on the shortlist of recognized speech possibilities using a grammar generated from the entries in the database to obtain a final result; and providing a response to the speech based on the final result. 6. The system of claim 5 , wherein the index of words is generated based on a plurality of training phoneme lattices and factors of interest from valid entries in a database, wherein the factors of interest comprise trigrams. | 0.5 |
8,064,688 | 17 | 18 | 17. A method of providing assistance in detecting the presence of a three-dimensional (3D) object in a two-dimensional (2D) image containing a 2D representation of said 3D object, said method comprising: receiving, using one or more data processors, a digitized version of said 2D image from a client site and over a communication network; determining, using the one or more data processors, a location of said 3D object in said 2D image using a Bayesian network-based classifier, wherein said classifier is configured to analyze said 2D image based on a ratio of a plurality of Bayesian networks; wherein said classifier is determined by: applying a view-based classifier to said 2D image, wherein said classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of said plurality of sub-classifiers, wherein said log-likelihood ratio is a ratio of two graphical probability models; wherein a graphical probability model comprises a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and sending a notification of said location of said 3D object to said client site over said communication network. | 17. A method of providing assistance in detecting the presence of a three-dimensional (3D) object in a two-dimensional (2D) image containing a 2D representation of said 3D object, said method comprising: receiving, using one or more data processors, a digitized version of said 2D image from a client site and over a communication network; determining, using the one or more data processors, a location of said 3D object in said 2D image using a Bayesian network-based classifier, wherein said classifier is configured to analyze said 2D image based on a ratio of a plurality of Bayesian networks; wherein said classifier is determined by: applying a view-based classifier to said 2D image, wherein said classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of said plurality of sub-classifiers, wherein said log-likelihood ratio is a ratio of two graphical probability models; wherein a graphical probability model comprises a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and sending a notification of said location of said 3D object to said client site over said communication network. 18. The method of claim 17 , further comprising: determining orientation of said 3D object in said 2D image; and sending information about said orientation as part of said notification. | 0.5 |
10,116,604 | 5 | 11 | 5. A machine implemented method of communicating, comprising: (i) receiving an electronic message, via a server having a processing unit and program code stored on a storage device of said server; (ii) receiving a well-known animation character, via the server; (iii) converting the electronic message into speech using one of synthesized voice and actual voice of a voice impersonator of the well-known animation character, via the server; (iv) generating moving images of the well-known animation character, via the server; (v) transmitting the speech, via the server; and (vi) transmitting the moving images, via the server. | 5. A machine implemented method of communicating, comprising: (i) receiving an electronic message, via a server having a processing unit and program code stored on a storage device of said server; (ii) receiving a well-known animation character, via the server; (iii) converting the electronic message into speech using one of synthesized voice and actual voice of a voice impersonator of the well-known animation character, via the server; (iv) generating moving images of the well-known animation character, via the server; (v) transmitting the speech, via the server; and (vi) transmitting the moving images, via the server. 11. The method of claim 5 , wherein the step of converting the electronic message into speech comprises synthesizing speech of a voice impersonator of the well-known animation character. | 0.685811 |
7,962,328 | 16 | 20 | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. 20. The apparatus of claim 16 , wherein the means for generating comprises means for generating the data structure to include a plurality of fields, wherein each of the plurality of fields represents a corresponding one of the plurality of answers. | 0.5 |
8,370,364 | 5 | 6 | 5. The method of claim 1 , further including, previous to querying the plurality of time zone offsets, determining if a time zone setting is known. | 5. The method of claim 1 , further including, previous to querying the plurality of time zone offsets, determining if a time zone setting is known. 6. The method of claim 5 , wherein if the time zone setting is known, selecting the time zone setting to format a time stamped output. | 0.5 |
8,027,988 | 21 | 26 | 21. A system, comprising: a processor coupled to a memory, where the memory stores instructions that, when executed by the processor, causes the processor to: receive a search query from a client device; identify a plurality of documents based on the search query; obtain a score for each document in the plurality of documents; identify one or more categories associated with the plurality of documents; determine a score for each category of the one or more categories, where the score for a given category is based on the obtained score of one or more documents, in the plurality of documents, associated with the category, and select one of the one or more categories to present, as a category suggestion, in connection with the plurality of documents, the one of the one or more categories being selected based on the scores determined for the one or more categories. | 21. A system, comprising: a processor coupled to a memory, where the memory stores instructions that, when executed by the processor, causes the processor to: receive a search query from a client device; identify a plurality of documents based on the search query; obtain a score for each document in the plurality of documents; identify one or more categories associated with the plurality of documents; determine a score for each category of the one or more categories, where the score for a given category is based on the obtained score of one or more documents, in the plurality of documents, associated with the category, and select one of the one or more categories to present, as a category suggestion, in connection with the plurality of documents, the one of the one or more categories being selected based on the scores determined for the one or more categories. 26. The system of claim 21 , where processor further executes instructions to present information regarding the plurality of documents and the category suggestion in response to the search query. | 0.742744 |
4,864,501 | 4 | 8 | 4. Apparatus for annotating digitally encoded natural language text words, such apparatus comprising a dictionary database including a plurality of word records, each record including a set of tags indicative of properties of a word look up means for looking up a text word in the dictionary database and retrieving its set of tags when the text word is identified in the dictionary database, and morphological analyzer means, operative on a text word which is not identified in the dictionary database, for determining a set of tags and dummy base form by inspection of the morphology or context of such word. | 4. Apparatus for annotating digitally encoded natural language text words, such apparatus comprising a dictionary database including a plurality of word records, each record including a set of tags indicative of properties of a word look up means for looking up a text word in the dictionary database and retrieving its set of tags when the text word is identified in the dictionary database, and morphological analyzer means, operative on a text word which is not identified in the dictionary database, for determining a set of tags and dummy base form by inspection of the morphology or context of such word. 8. Apparatus according to claim 4, wherein the morphological analyzer means comprises means for identifying a word consisting of a permissible literal-numeric combination. | 0.788889 |
8,375,022 | 1 | 6 | 1. A computing device for determination of keywords, the computing device comprising: a processor to: determine a total number of occurrences of a particular word in a plurality of documents, determine a document-specific number of occurrences of the particular word in a particular document of the plurality of documents, determine a weight of meaningfulness for the particular word based on a relationship between the document-specific number of occurrences and an expected value of the document-specific number of occurrences determined using the total number of occurrences, wherein weight of meaningfulness for the particular word is determined according to: weight of meaningfulness = K ! m ! ( K - m ) ! · 1 N m - 1 , where: K is the total number of occurrences of the particular word, m is the document-specific number of occurrences, and N is a total number of documents, and selectively add the particular word to a set of keywords for the particular document based on the weight of meaningfulness determined for the particular word. | 1. A computing device for determination of keywords, the computing device comprising: a processor to: determine a total number of occurrences of a particular word in a plurality of documents, determine a document-specific number of occurrences of the particular word in a particular document of the plurality of documents, determine a weight of meaningfulness for the particular word based on a relationship between the document-specific number of occurrences and an expected value of the document-specific number of occurrences determined using the total number of occurrences, wherein weight of meaningfulness for the particular word is determined according to: weight of meaningfulness = K ! m ! ( K - m ) ! · 1 N m - 1 , where: K is the total number of occurrences of the particular word, m is the document-specific number of occurrences, and N is a total number of documents, and selectively add the particular word to a set of keywords for the particular document based on the weight of meaningfulness determined for the particular word. 6. The computing device of claim 1 , wherein: each of the plurality of documents is a B-word block of a single document, and the processor is configured to: set a total number of documents used to determine the weight of meaningfulness to [L/B], where L is a total number of words in the single document. | 0.681342 |
9,280,534 | 18 | 19 | 18. A system, comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: determine that a textual term is not associated with a known meaning, wherein the textual term is related to one or more users of a social-networking system, the user being associated with a user node in a social graph of the social-networking system, the social graph comprising: a plurality of nodes, the plurality of nodes comprising user nodes and concept nodes, wherein each user node corresponds to a user of the social-networking system; and a plurality of edges, wherein one or more edges connect two nodes, the one or more edges representing a relationship between the two nodes; determine that the textual term should be added to a social glossary; add the textual term to the social glossary; add to the social graph a new element representing the textual term, wherein the new element comprises: a new concept node, wherein the textual term is a noun, a new edge, wherein the textual term is a verb, or a new attribute for the user node, wherein the textual term is an adjective; and provide information related to one or more textual terms in the social glossary. | 18. A system, comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: determine that a textual term is not associated with a known meaning, wherein the textual term is related to one or more users of a social-networking system, the user being associated with a user node in a social graph of the social-networking system, the social graph comprising: a plurality of nodes, the plurality of nodes comprising user nodes and concept nodes, wherein each user node corresponds to a user of the social-networking system; and a plurality of edges, wherein one or more edges connect two nodes, the one or more edges representing a relationship between the two nodes; determine that the textual term should be added to a social glossary; add the textual term to the social glossary; add to the social graph a new element representing the textual term, wherein the new element comprises: a new concept node, wherein the textual term is a noun, a new edge, wherein the textual term is a verb, or a new attribute for the user node, wherein the textual term is an adjective; and provide information related to one or more textual terms in the social glossary. 19. The system of claim 18 , wherein the processors are further operable to: discover new textual terms by mining information, wherein the information was received from one or more users of the social-networking system, was generated for one or more users of the social-networking system, is marked as being associated with one or more users of the social-networking system, or includes an identifier for each of one or more users of the social-networking system. | 0.545187 |
9,471,851 | 6 | 7 | 6. The method of claim 1 , further comprising performing confidence checking on at least some of the semantic scores to influence an inference of the gender of the user. | 6. The method of claim 1 , further comprising performing confidence checking on at least some of the semantic scores to influence an inference of the gender of the user. 7. The method of claim 6 , wherein the confidence checking is performed separately by a first confidence check on the at least some of the semantic scores relating to the visual content and by a second confidence check on the at least some of the semantic scores relating to the textual content, and the inference of the gender of the user is influenced differently based on an agreement or a non-agreement between the first and the second confidence checks. | 0.5 |
6,092,037 | 1 | 3 | 1. A computer system comprising: a processor; a storage coupled to the processor, the storage being capable of storing an executable code; and an executable code for translating messages in a database from a first language to a second language, the executable code including: a display routine which displays messages in the first language for translation; an interactive input routine which inputs a message in the second language corresponding to a translated message in the first language; and a database build routine which builds a second language database from a plurality of input messages in the second language, the second language database being separate from a first language database, the database build routine including: a macro which substitutes for a text string, the macro for inclusion into a source code; and a message collection and source update utility which scans the source code, locates the macro in the source code, derives a key relating to the text string and updates the second database with the text string and key. | 1. A computer system comprising: a processor; a storage coupled to the processor, the storage being capable of storing an executable code; and an executable code for translating messages in a database from a first language to a second language, the executable code including: a display routine which displays messages in the first language for translation; an interactive input routine which inputs a message in the second language corresponding to a translated message in the first language; and a database build routine which builds a second language database from a plurality of input messages in the second language, the second language database being separate from a first language database, the database build routine including: a macro which substitutes for a text string, the macro for inclusion into a source code; and a message collection and source update utility which scans the source code, locates the macro in the source code, derives a key relating to the text string and updates the second database with the text string and key. 3. A computer system according to claim 1 wherein the message collection and source update utility further includes: a utility for verifying the format of the key and message with respect to a source code type. | 0.796512 |
8,676,565 | 1 | 4 | 1. A method implemented by one or more computer processors, the method comprising: computationally matching one or more of a plurality of utterances into a respective one of a plurality of predefined topics through comparison with one or more corresponding semantic graph patterns: and for at least one said utterance that was not matched to the semantic graph patterns, computationally generating a semantic graph pattern that described information common to the at least one said utterance. | 1. A method implemented by one or more computer processors, the method comprising: computationally matching one or more of a plurality of utterances into a respective one of a plurality of predefined topics through comparison with one or more corresponding semantic graph patterns: and for at least one said utterance that was not matched to the semantic graph patterns, computationally generating a semantic graph pattern that described information common to the at least one said utterance. 4. A method as described in claim 1 , wherein the matching and the generating are performed automatically and without user intervention by the one or more modules. | 0.5 |
8,687,792 | 1 | 14 | 1. A method for dialog management within a call handling system, comprising: initiating, by a computer executing machine readable instructions stored on a non-transitory computer readable medium, a dialog between a contact and an operator; monitoring, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, dialog attributes including generating a dialog attribute score for each dialog attribute; presenting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, an instantaneous value of at least one of the dialog attributes on an operator display; and effecting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, a dialog rule in response to the dialog attribute scores; wherein the monitoring includes, identifying computational resources required to calculate each of the dialog attribute scores; generating dialog attribute scores hierarchically beginning with the dialog attribute score requiring a least amount of computational resources; and stopping generation of the dialog attribute scores once the combined dialog attribute score exceeds a predetermined threshold. | 1. A method for dialog management within a call handling system, comprising: initiating, by a computer executing machine readable instructions stored on a non-transitory computer readable medium, a dialog between a contact and an operator; monitoring, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, dialog attributes including generating a dialog attribute score for each dialog attribute; presenting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, an instantaneous value of at least one of the dialog attributes on an operator display; and effecting, by the computer executing machine readable instructions stored on the non-transitory computer readable medium, a dialog rule in response to the dialog attribute scores; wherein the monitoring includes, identifying computational resources required to calculate each of the dialog attribute scores; generating dialog attribute scores hierarchically beginning with the dialog attribute score requiring a least amount of computational resources; and stopping generation of the dialog attribute scores once the combined dialog attribute score exceeds a predetermined threshold. 14. The method of claim 1 , wherein effecting includes: presenting an advisory message to the operator on the display. | 0.797945 |
9,818,401 | 19 | 22 | 19. The method of claim 18 , wherein said adaptation object comprises an adaptation grammar. | 19. The method of claim 18 , wherein said adaptation object comprises an adaptation grammar. 22. The method of claim 19 , wherein said adaptation grammar is composed of a linearly connected series of grammar sections, comprising a prefix section, a target section and a suffix section, of which: said prefix section comprises a linearly connected series of zero or more grammar pathways, each said pathway labeled with a sequence of zero or more grammar labels, said linearly connected series of labeled pathways as a whole defining a linear sequence of zero or more grammar labels corresponding to a portion of the nominal primary transcription starting with and including a first nominal transcribed word therein and proceeding up to but not including a first nominal transcribed word of said target span, in order; said target section comprises a structure and content appropriate to said putative type of proper name entity; and said suffix section comprises a linearly connected series of zero or more grammar pathways, each said pathway labeled with a sequence of zero or more grammar labels, said linearly connected series of labeled pathways as a whole defining a linear sequence of zero or more grammar labels corresponding to a portion of the nominal primary transcription starting after and not including a last nominal transcribed word of said target span and ending with and including a last nominal transcribed word therein, in order. | 0.5 |
7,970,601 | 1 | 2 | 1. A method of creating a requirement description for testing an embedded system, comprising: storing a vocabulary of natural-language, selectable text segments in a data processing system, each of said text segments being combinable only with a deterministically selected subset of said text segments to form at least one natural-language sentence including a condition and a response to a condition, and storing a requirements metamodel in the data processing system, each text segment being linked to an instance in the requirements metamodel such that when a text segment is selected a machine readable description of the text segment is created and such that said condition is assigned a value placeable at an input of the embedded system and the response to the condition is assigned a value placeable at an output of the embedded system. | 1. A method of creating a requirement description for testing an embedded system, comprising: storing a vocabulary of natural-language, selectable text segments in a data processing system, each of said text segments being combinable only with a deterministically selected subset of said text segments to form at least one natural-language sentence including a condition and a response to a condition, and storing a requirements metamodel in the data processing system, each text segment being linked to an instance in the requirements metamodel such that when a text segment is selected a machine readable description of the text segment is created and such that said condition is assigned a value placeable at an input of the embedded system and the response to the condition is assigned a value placeable at an output of the embedded system. 2. The method according to claim 1 , further comprising assigning the text segments to classes of a stored requirement metamodel. | 0.905286 |
9,053,079 | 1 | 8 | 1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records. | 1. An apparatus, comprising: a processor circuit; and an application program operative on the processor circuit to manage a collaborative document having a presentation surface with multiple constructs, the application program comprising: a document render component operative to render a first document instance of the collaborative document; a document share component operative to receive a document update list comprising a set of change records for a second document instance of the collaborative document, each change record comprising information for a modification made to a construct of the second document instance, determine whether a time stamp of a change record for the first document instance of the collaborative document and a time stamp of a change record for the second document instance of the collaborative document are both within a synchronization interval when the change records have matching constructs, annotate the change records as conflict records, and modify properties of one or more constructs for the first document instance based on the change records to form a merged document instance of the collaborative document; and an undo manager component operative to manage a local undo stack for the first document instance, the local undo stack comprising a set of undo records each storing information to undo a modification made to a construct of the first document instance, compare the set of undo records and the set of change records, and determine whether to preserve one or more of the undo records of the local undo stack after formation of the merged document instance based on one or more of the change records. 8. The apparatus of claim 1 , the document share component operative to receive a document update list comprising a set of change records for the first document instance of the collaborative document. | 0.684543 |
9,008,425 | 1 | 6 | 1. A method of detection of numbered captions in a document comprising: receiving a document comprising a sequence of document pages; identifying illustrations on pages of the document; for each identified illustration, identifying associated text; generating an imitation page for each of the identified illustrations, each of the imitation pages comprising only a single illustration and its associated text; for a sequence of the imitation pages, with a processor, identifying a sequence of terms, each term comprising a text fragment of the associate text of a respective one of the imitation pages, the terms of the sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence; and construing the terms of the identified sequence of terms as each being at least a part of a numbered caption for a respective illustration in the document. | 1. A method of detection of numbered captions in a document comprising: receiving a document comprising a sequence of document pages; identifying illustrations on pages of the document; for each identified illustration, identifying associated text; generating an imitation page for each of the identified illustrations, each of the imitation pages comprising only a single illustration and its associated text; for a sequence of the imitation pages, with a processor, identifying a sequence of terms, each term comprising a text fragment of the associate text of a respective one of the imitation pages, the terms of the sequence complying with at least one predefined numbering scheme which defines a form and an incremental state of the terms in a sequence; and construing the terms of the identified sequence of terms as each being at least a part of a numbered caption for a respective illustration in the document. 6. The method of claim 1 , wherein the imitation pages in the sequence of the imitation pages are ordered in a same order as the identified illustrations in the document. | 0.894541 |
8,036,877 | 8 | 9 | 8. A method according to claim 5 , wherein said database further includes an importance value in correspondence with each association of a potential additional token sequence with a target token sequence, and wherein said step of comparing tokens in said user input to said target token sequences includes a step of calculating a confidence value of a given association in said database between a potential additional token sequence and a target token sequence, said confidence value being dependent upon both the importance value of the given association and a correlation between said tokens in said user input and the target token sequence of the given association. | 8. A method according to claim 5 , wherein said database further includes an importance value in correspondence with each association of a potential additional token sequence with a target token sequence, and wherein said step of comparing tokens in said user input to said target token sequences includes a step of calculating a confidence value of a given association in said database between a potential additional token sequence and a target token sequence, said confidence value being dependent upon both the importance value of the given association and a correlation between said tokens in said user input and the target token sequence of the given association. 9. A method according to claim 8 , wherein said step of selecting comprises the step of comparing said confidence value to a predetermined minimum acceptable confidence value. | 0.716828 |
8,533,206 | 9 | 16 | 9. A system comprising: one or more computers; a computer program including instructions, stored on a non-transitory computer-readable storage medium, that when executed by the one or more computers, cause the one or more computers to performs operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. | 9. A system comprising: one or more computers; a computer program including instructions, stored on a non-transitory computer-readable storage medium, that when executed by the one or more computers, cause the one or more computers to performs operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. 16. The system of claim 9 , wherein each new set of one or more URL patterns is distinct from a previously identified set of one or more URL patterns. | 0.829157 |
7,603,355 | 1 | 4 | 1. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. | 1. A computer-implemented method for controlling access to a portion of a document, the document comprising a plurality of portions, the method performed by at least one processor, the method comprising: receiving a request to access the document portion; identifying a variable accessibility rule associated with the requested document portion; evaluating the rule based on data describing past accesses of other ones of the plurality of document portions; determining whether to provide access to the requested document portion responsive to the evaluation of the rule; and responding to the request based on the determination. 4. The method of claim 1 , wherein the rule indicates that access to the requested document portion is denied responsive to the data describing past accesses indicating that access was provided to one or more other document portions more frequently than access was provided to the requested document portion. | 0.598958 |
6,061,602 | 1 | 3 | 1. A computer apparatus for interactively developing a graphical control application software program for use in controlling an automation apparatus, the computer apparatus comprising: means for storing an application development program including a first program representing a first set of flow sequences, each flow sequence including at least one transition and at least one step; means for storing a plurality of controls for use in the automation apparatus, the plurality of controls each being an object obeying a standard which defines characteristics of the object as having one of a plurality of methods, one of plurality of properties, and one of a plurality of events; each step in each flow sequence redefined as an object; a display; means for receiving user commands to select from the first program one of the first set of flow sequences, and for selecting one of the objects, the receiving means controlling the display to display a structure wherein the graphical representation of the selected one of the first set of flow sequences is a step in the structure and the selected object structure having at least one transition and at least one event; and means for linking the first program with the possible controls to directly form an automation program in response to user commands. | 1. A computer apparatus for interactively developing a graphical control application software program for use in controlling an automation apparatus, the computer apparatus comprising: means for storing an application development program including a first program representing a first set of flow sequences, each flow sequence including at least one transition and at least one step; means for storing a plurality of controls for use in the automation apparatus, the plurality of controls each being an object obeying a standard which defines characteristics of the object as having one of a plurality of methods, one of plurality of properties, and one of a plurality of events; each step in each flow sequence redefined as an object; a display; means for receiving user commands to select from the first program one of the first set of flow sequences, and for selecting one of the objects, the receiving means controlling the display to display a structure wherein the graphical representation of the selected one of the first set of flow sequences is a step in the structure and the selected object structure having at least one transition and at least one event; and means for linking the first program with the possible controls to directly form an automation program in response to user commands. 3. The apparatus of claim 1 wherein the control is instantiated when linked with a selected one of the flow sequences on the display. | 0.743243 |
9,292,505 | 6 | 9 | 6. A machine-implemented method for providing a graphical user interface (GUI) for a research system, the method comprising: providing a selectable list of user objectives for a recurring search that identifies documents, from a particular recurring time period, classified as relevant to a set of categories by the research system, wherein a selected user objective comprises a purpose for which the user plans to use the identified documents; providing a categories display area for displaying a set of recommended categories to include in the recurring search based on the selected user objective and an initial set of categories, wherein the set of recommended categories comprises a subset of pre-selected categories most related to the initial set of categories and further categories for selection by the user; after a set of additional categories for the recurring search are selected by the user, providing a filters display area for displaying a set of recommended filters for removing specific types of documents from the recurring search that are otherwise relevant to the selected categories for the recurring search, wherein a first set of selected additional categories results in displaying a first set of recommended filters and a second set of selected additional categories results in displaying a second, different set of recommended filters; and providing a plurality of selectable user interface controls for modifying delivery parameters for the recurring search, wherein a set of the plurality of selectable user interface controls are automatically pre-selected for the user based on an analysis of a plurality of user profile information and user behavior information, wherein email is pre-selected as a medium through which reports are delivered to the user if the user does not log-in to the research system on a recurring basis over a specified time period. | 6. A machine-implemented method for providing a graphical user interface (GUI) for a research system, the method comprising: providing a selectable list of user objectives for a recurring search that identifies documents, from a particular recurring time period, classified as relevant to a set of categories by the research system, wherein a selected user objective comprises a purpose for which the user plans to use the identified documents; providing a categories display area for displaying a set of recommended categories to include in the recurring search based on the selected user objective and an initial set of categories, wherein the set of recommended categories comprises a subset of pre-selected categories most related to the initial set of categories and further categories for selection by the user; after a set of additional categories for the recurring search are selected by the user, providing a filters display area for displaying a set of recommended filters for removing specific types of documents from the recurring search that are otherwise relevant to the selected categories for the recurring search, wherein a first set of selected additional categories results in displaying a first set of recommended filters and a second set of selected additional categories results in displaying a second, different set of recommended filters; and providing a plurality of selectable user interface controls for modifying delivery parameters for the recurring search, wherein a set of the plurality of selectable user interface controls are automatically pre-selected for the user based on an analysis of a plurality of user profile information and user behavior information, wherein email is pre-selected as a medium through which reports are delivered to the user if the user does not log-in to the research system on a recurring basis over a specified time period. 9. The method of claim 6 , wherein the plurality of selectable user interface controls for modifying delivery parameters comprises controls for specifying a format of reports generated by the recurring search, a frequency of delivering the reports to the user, and a medium through which the reports are delivered to the user. | 0.5 |
7,509,303 | 57 | 58 | 57. The method of claim 56 , further comprising inputting said mapping information in said medium. | 57. The method of claim 56 , further comprising inputting said mapping information in said medium. 58. The method of claim 57 , wherein said inputting is performed through a user interface displayed in a screen. | 0.656442 |
8,762,469 | 24 | 25 | 24. The method of claim 20 , wherein the contextual information includes information from one or more sensors on the portable electronic device. | 24. The method of claim 20 , wherein the contextual information includes information from one or more sensors on the portable electronic device. 25. The method of claim 24 , wherein the one or more sensors include a location sensor. | 0.521978 |
8,332,530 | 19 | 24 | 19. An apparatus for navigating a video program segmented into a plurality of segments and having a spoken dialog, comprising: one or more computer processors; and a computer-readable storage medium comprising instructions for controlling the one or more computer processors to be operable for: generating a full textual transcript of the spoken dialog, the full textual transcript comprising a plurality of portions wherein each portion is associated with a segment of the video program; synchronizing each portion of the full textual transcript with the associated segment of the video program; accepting a command to select the video program from a client computer; and transmitting user interface data including the full textual transcript to the client computer for presentation in a user interface, the user interface comprising a concurrently presented video program player playing the video program, a window configured to include portions of the full textual transcript, and a histogram having a plurality of features, each feature representing at least one of the segments of the video program and indicating a popularity of the represented at least one of the segments of the video program; accepting a selection for a portion of the full textual transcript included in the window of the user interface; determining the associated segment for the portion of the full textual transcript based on the synchronizing; and dynamically navigating to the segment of the video program associated with the selected portion of the full textual transcript in the video program player in response to the accepted selection. | 19. An apparatus for navigating a video program segmented into a plurality of segments and having a spoken dialog, comprising: one or more computer processors; and a computer-readable storage medium comprising instructions for controlling the one or more computer processors to be operable for: generating a full textual transcript of the spoken dialog, the full textual transcript comprising a plurality of portions wherein each portion is associated with a segment of the video program; synchronizing each portion of the full textual transcript with the associated segment of the video program; accepting a command to select the video program from a client computer; and transmitting user interface data including the full textual transcript to the client computer for presentation in a user interface, the user interface comprising a concurrently presented video program player playing the video program, a window configured to include portions of the full textual transcript, and a histogram having a plurality of features, each feature representing at least one of the segments of the video program and indicating a popularity of the represented at least one of the segments of the video program; accepting a selection for a portion of the full textual transcript included in the window of the user interface; determining the associated segment for the portion of the full textual transcript based on the synchronizing; and dynamically navigating to the segment of the video program associated with the selected portion of the full textual transcript in the video program player in response to the accepted selection. 24. The apparatus of claim 19 , further operable for generating the histogram from a combined first set of video program segments streamed to a first client computer and a second set of video program segments streamed to a second computer. | 0.787367 |
7,689,418 | 1 | 9 | 1. A system for verifying user identity comprising: a conversational system that receives multi-modal inputs from a user interacting with the conversational system during a user session and transforms the received multi-modal inputs into formal commands executable by a program of instructions executable by a processor; and a behavior verifier coupled to the conversational system to extract features from the multi-modal inputs and formal commands, wherein the extracted features include a combination of input modalities representative of the user's current interaction behavior for performing a task during the user session, and wherein the behavior verifier compares the combination of input modalities representative of the user's current interaction behavior for performing the task to a behavior model representative of the user's past interaction behavior comprising a known combination of input modalities for performing the task used by the user during one or more previous user sessions to determine the identity of the user. | 1. A system for verifying user identity comprising: a conversational system that receives multi-modal inputs from a user interacting with the conversational system during a user session and transforms the received multi-modal inputs into formal commands executable by a program of instructions executable by a processor; and a behavior verifier coupled to the conversational system to extract features from the multi-modal inputs and formal commands, wherein the extracted features include a combination of input modalities representative of the user's current interaction behavior for performing a task during the user session, and wherein the behavior verifier compares the combination of input modalities representative of the user's current interaction behavior for performing the task to a behavior model representative of the user's past interaction behavior comprising a known combination of input modalities for performing the task used by the user during one or more previous user sessions to determine the identity of the user. 9. The system as recited in claim 1 , wherein the behavior model includes a plurality of models representative of different interaction behaviors comprising combinations of input modalities of the user. | 0.678344 |
9,454,962 | 3 | 4 | 3. The method of claim 2 , wherein performing a dependency parse comprises: identifying a top level predicate; and excluding at least one auxiliary word in the text phrase. | 3. The method of claim 2 , wherein performing a dependency parse comprises: identifying a top level predicate; and excluding at least one auxiliary word in the text phrase. 4. The method of claim 3 , wherein the at least one auxiliary word comprises a dependent of the top level predicate. | 0.63522 |
8,626,627 | 12 | 22 | 12. An article of manufacture comprising: a computer-readable medium having instructions stored thereon, which when executed by a processor on the computer, cause the computer to perform a method of disseminating online promotion campaigns, the instructions comprising: instructions for accessing and harvesting profile information of users of a social media platform; instructions for receiving interest in an online promotion from a participant through an entry point; instructions for harvesting identification information from a social media profile of the participant; instructions for generating a personalized promotion for the participant containing at least some of the participant's identification information including securing the personalized promotion by providing a means for verifying integrity of the personalized promotion at a time for redemption wherein the means includes a verifiable portion of the participant's identification information obtained by the accessing; and instructions for distributing the personalized promotion to the participant, wherein the identification information on the personalized promotion provides a higher level of security and authenticity than promotions that do not contain such identification information. | 12. An article of manufacture comprising: a computer-readable medium having instructions stored thereon, which when executed by a processor on the computer, cause the computer to perform a method of disseminating online promotion campaigns, the instructions comprising: instructions for accessing and harvesting profile information of users of a social media platform; instructions for receiving interest in an online promotion from a participant through an entry point; instructions for harvesting identification information from a social media profile of the participant; instructions for generating a personalized promotion for the participant containing at least some of the participant's identification information including securing the personalized promotion by providing a means for verifying integrity of the personalized promotion at a time for redemption wherein the means includes a verifiable portion of the participant's identification information obtained by the accessing; and instructions for distributing the personalized promotion to the participant, wherein the identification information on the personalized promotion provides a higher level of security and authenticity than promotions that do not contain such identification information. 22. The article of manufacture of claim 12 , further comprising instructions for directing the participant to download a promotion application to the participant's social network profile. | 0.739554 |
8,051,061 | 7 | 8 | 7. The method as recited in claim 1 , wherein the identifying the query in target language from the query log further comprises: identifying one or more queries in target language whose cross-lingual query similarity score with the input query meets or exceeds a threshold. | 7. The method as recited in claim 1 , wherein the identifying the query in target language from the query log further comprises: identifying one or more queries in target language whose cross-lingual query similarity score with the input query meets or exceeds a threshold. 8. The method as recited in claim 7 , wherein the threshold is learned using a development data set by fitting a monolingual query suggestion output. | 0.5 |
9,378,740 | 4 | 6 | 4. The system of claim 1 , wherein the first intent definition further includes a slot definition identifying a data type, and wherein the one or more physical computer processors are further programmed by the executable instructions to: obtain a user identifier for the client device; obtain an example text value of the data type for the slot definition based on the user identifier; and generate the second text using the example text value in the slot. | 4. The system of claim 1 , wherein the first intent definition further includes a slot definition identifying a data type, and wherein the one or more physical computer processors are further programmed by the executable instructions to: obtain a user identifier for the client device; obtain an example text value of the data type for the slot definition based on the user identifier; and generate the second text using the example text value in the slot. 6. The system of claim 4 , wherein obtaining the example text value of the data type comprises obtaining the example text value from a content library for the identified user. | 0.5 |
7,908,325 | 18 | 19 | 18. A device, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions configured to: execute a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application; wherein the first collaboration framework is configured to: intercept, via an operating system event handling mechanism executing on the device, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, send a message including the user input event to each of one or more other collaboration frameworks each executing on one of a respective one or more other devices that are each executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other device; wherein the message includes information usable by each of the one or more other collaboration frameworks to deliver the user input event, via an operating system event handling mechanism executing on the respective other device, to the respective other instance of the application executing on the respective other device as if the user input event originated locally from the respective other user interface displayed by the respective other application on the respective other device; and wherein the delivered user input event causes each of the respective other application instances to apply the modification to the respective instance of the graphical user interface. | 18. A device, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions configured to: execute a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application; wherein the first collaboration framework is configured to: intercept, via an operating system event handling mechanism executing on the device, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, send a message including the user input event to each of one or more other collaboration frameworks each executing on one of a respective one or more other devices that are each executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other device; wherein the message includes information usable by each of the one or more other collaboration frameworks to deliver the user input event, via an operating system event handling mechanism executing on the respective other device, to the respective other instance of the application executing on the respective other device as if the user input event originated locally from the respective other user interface displayed by the respective other application on the respective other device; and wherein the delivered user input event causes each of the respective other application instances to apply the modification to the respective instance of the graphical user interface. 19. The device of claim 18 , wherein as part of said intercepting the first collaboration framework is configured to monitor an event queue of the operating system event handling mechanism for the input event. | 0.732737 |
8,731,954 | 1 | 8 | 1. A method performed by a computer of evaluating coded medical documents, the method comprising: receiving, by a computer, audit parameters comprising an expected coder error level, and receiving an empirically established expected auditor error level of an auditor based on an assessment of the auditor; selecting, by the computer, a sample batch of coded medical documents for auditing by the auditor, the sample batch of coded medical documents selected from a universe of coded medical documents stored on one or more storage devices, the selection based at least in part on the received audit parameters; receiving, by the computer, audited medical documents corresponding to the selected sample batch of coded medical documents, wherein the audited medical documents include corrections by the auditor; calculating, by the computer, a medical document score for each of the audited medical documents based on medical document corrections received from the auditor and applying weighted factors, wherein the weighted factors comprise predefined weights assigned to diagnosis and procedure codes in each of the audited medical documents; calculating, by the computer, a sample score for the audited medical documents based on a function of the calculated medical document scores; designating, by the computer, at least one of an upper control limit and a lower control limit based on the expected auditor error level; and comparing, by the computer, the sample score against the at least one of the upper and lower control limits to determine an acceptability of the sample score. | 1. A method performed by a computer of evaluating coded medical documents, the method comprising: receiving, by a computer, audit parameters comprising an expected coder error level, and receiving an empirically established expected auditor error level of an auditor based on an assessment of the auditor; selecting, by the computer, a sample batch of coded medical documents for auditing by the auditor, the sample batch of coded medical documents selected from a universe of coded medical documents stored on one or more storage devices, the selection based at least in part on the received audit parameters; receiving, by the computer, audited medical documents corresponding to the selected sample batch of coded medical documents, wherein the audited medical documents include corrections by the auditor; calculating, by the computer, a medical document score for each of the audited medical documents based on medical document corrections received from the auditor and applying weighted factors, wherein the weighted factors comprise predefined weights assigned to diagnosis and procedure codes in each of the audited medical documents; calculating, by the computer, a sample score for the audited medical documents based on a function of the calculated medical document scores; designating, by the computer, at least one of an upper control limit and a lower control limit based on the expected auditor error level; and comparing, by the computer, the sample score against the at least one of the upper and lower control limits to determine an acceptability of the sample score. 8. The method of claim 1 , wherein calculating the sample score for the audited medical documents based on a function of the calculated medical document scores comprises obtaining a summation of the calculated medical document scores. | 0.5 |
10,013,492 | 8 | 9 | 8. The computer-implemented method of claim 1 , further comprising weighting the response based in part on a characteristic of the user profile associated with the user device. | 8. The computer-implemented method of claim 1 , further comprising weighting the response based in part on a characteristic of the user profile associated with the user device. 9. The computer-implemented method of claim 8 , further comprising: identifying, from the user profile, previous responses to other customized questionnaires, and wherein the characteristic is based at least in part on the previous responses. | 0.5 |
9,620,104 | 17 | 18 | 17. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing: receiving a first speech input including at least one word; determining a first phonetic representation of the at least one word, the first phonetic representation comprising a first set of phonemes selected from a speech recognition phonetic alphabet; mapping the first set of phonemes to a second set of phonemes to generate a second phonetic representation, the second set of phonemes selected from a speech synthesis phonetic alphabet that is different from the speech recognition phonetic alphabet, wherein the speech recognition phonetic alphabet and the speech synthesis phonetic alphabet are phonetic alphabets of a same language; and storing the second phonetic representation in association with a text string corresponding to the at least one word. | 17. An electronic device, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for performing: receiving a first speech input including at least one word; determining a first phonetic representation of the at least one word, the first phonetic representation comprising a first set of phonemes selected from a speech recognition phonetic alphabet; mapping the first set of phonemes to a second set of phonemes to generate a second phonetic representation, the second set of phonemes selected from a speech synthesis phonetic alphabet that is different from the speech recognition phonetic alphabet, wherein the speech recognition phonetic alphabet and the speech synthesis phonetic alphabet are phonetic alphabets of a same language; and storing the second phonetic representation in association with a text string corresponding to the at least one word. 18. The device of claim 17 , further comprising instructions for performing, prior to receiving the first speech input, providing the text string. | 0.578035 |
8,522,130 | 17 | 25 | 17. A non-transitory computer-readable storage medium storing executable computer program instructions for creating notes associated with a document, the computer program instructions comprising instructions for: accessing the document, the document associated with a table of contents listing a plurality of headers extracted from the document and defining a structure of a plurality of sections of the document, wherein each header corresponds to a section of the document defined by the table of contents and comprises a textual description of the section, and wherein the document is configured to be rendered by an eReader browser application; sending for display to a user, a note window within a user interface of the eReader browser application; receiving a user input to generate a note in connection with the note window, the user input indicating a location within the document; linking the note window to a section of the document based on the user input, the linked section of the document including the indicated location and corresponding to one of the headers; adding the note to a note region in a note object, the note region associated with the linked section of the document; and accessing the note using the header corresponding to the linked section of the document. | 17. A non-transitory computer-readable storage medium storing executable computer program instructions for creating notes associated with a document, the computer program instructions comprising instructions for: accessing the document, the document associated with a table of contents listing a plurality of headers extracted from the document and defining a structure of a plurality of sections of the document, wherein each header corresponds to a section of the document defined by the table of contents and comprises a textual description of the section, and wherein the document is configured to be rendered by an eReader browser application; sending for display to a user, a note window within a user interface of the eReader browser application; receiving a user input to generate a note in connection with the note window, the user input indicating a location within the document; linking the note window to a section of the document based on the user input, the linked section of the document including the indicated location and corresponding to one of the headers; adding the note to a note region in a note object, the note region associated with the linked section of the document; and accessing the note using the header corresponding to the linked section of the document. 25. The non-transitory computer-readable storage medium of claim 17 , wherein the user input specifies multimedia content to be inserted into the note; and wherein adding the note to the note region comprises embedding a multimedia player into the note region. | 0.749518 |
8,280,882 | 1 | 6 | 1. A computer-implemented method for an author-centric search, comprising: initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality of documented communications has at least one author to which the respective documented communication is attributed; utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; determining a score for an author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by the author; prompting a user to enter a search string; parsing the search string into one or more words; populating at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; populating at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and displaying search results based at least in part upon a ranked listing of one or more author scores, wherein the weighted value for the author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the author, a prestige of the documented communication, and a number of authors for the documented communication. | 1. A computer-implemented method for an author-centric search, comprising: initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality of documented communications has at least one author to which the respective documented communication is attributed; utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; determining a score for an author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by the author; prompting a user to enter a search string; parsing the search string into one or more words; populating at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; populating at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and displaying search results based at least in part upon a ranked listing of one or more author scores, wherein the weighted value for the author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the author, a prestige of the documented communication, and a number of authors for the documented communication. 6. The method of claim 1 , determining the score further comprises executing a mathematical function that utilizes the aggregate for each author and the communications weight to arrive at the score. | 0.634686 |
7,668,805 | 1 | 8 | 1. A method for sharing information between SQL queries, in a relational database management system (RDBMS), the method comprising: maintaining a user-defined named memory variable and an associated value in an allocated portion of a memory coupled to the RDBMS, said named memory variable facilitating the transfer of the associated value between two or more separate queries, said named memory variable defined in response to a SQL statement received from a client application coupled to the RDBMS and said named memory variable comprising a variable name, a data type, and variable attributes, the variable attributes set by a user and defining one of a private named memory variable and a public named memory variable, said private named memory variable having a unique value for each database session and said public named memory variable having a common value for a plurality of database sessions and shared by a plurality of client applications communicating within the plurality of database sessions; accessing the associated value for the named memory variable in response to a first query referencing the named memory variable; sending a result for the first query, the result based on the associated value; accessing the associated value for the named memory variable in response to a second query referencing the named memory variable; and sending a result for the second query, the result based on the associated value. | 1. A method for sharing information between SQL queries, in a relational database management system (RDBMS), the method comprising: maintaining a user-defined named memory variable and an associated value in an allocated portion of a memory coupled to the RDBMS, said named memory variable facilitating the transfer of the associated value between two or more separate queries, said named memory variable defined in response to a SQL statement received from a client application coupled to the RDBMS and said named memory variable comprising a variable name, a data type, and variable attributes, the variable attributes set by a user and defining one of a private named memory variable and a public named memory variable, said private named memory variable having a unique value for each database session and said public named memory variable having a common value for a plurality of database sessions and shared by a plurality of client applications communicating within the plurality of database sessions; accessing the associated value for the named memory variable in response to a first query referencing the named memory variable; sending a result for the first query, the result based on the associated value; accessing the associated value for the named memory variable in response to a second query referencing the named memory variable; and sending a result for the second query, the result based on the associated value. 8. The method according to claim 1 , further comprising accessing predetermined information for a predefined named memory variable in response to a query referencing the predefined named memory variable; and sending a result for the query, the result based on the associated value. | 0.505282 |
7,689,927 | 51 | 53 | 51. A computer-readable medium including computer-executable instructions for performing a method for managing a view-size of an electronic document and useful for displaying information on a display device, the method comprising: providing a user interface window; displaying at least a portion of the electronic document in the user interface window; storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the stored boundary information in the viewable document section is adjusted based on a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system enables a user only to change the displayed portion to include information that is indicated by the stored boundary information in the viewable document section; providing the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window. | 51. A computer-readable medium including computer-executable instructions for performing a method for managing a view-size of an electronic document and useful for displaying information on a display device, the method comprising: providing a user interface window; displaying at least a portion of the electronic document in the user interface window; storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the stored boundary information in the viewable document section is adjusted based on a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system enables a user only to change the displayed portion to include information that is indicated by the stored boundary information in the viewable document section; providing the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window. 53. A computer-readable medium according to claim 51 , wherein, in the method, responsive to the user interface window being enlarged, the viewable document section also changes to include information indicative of any new portion of the electronic document displayed in the user interface window that was not previously displayed in the user interface window. | 0.5 |
8,060,507 | 12 | 15 | 12. An article of manufacture comprising a computer-readable storage device storing computer-readable instructions which, when executed, cause one or more processing devices to perform the following: access information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing; generate at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generate at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generate document word vectors for at least some of the documents that were selected by the user for viewing; perform, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish, using at least one processor, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; rank the predetermined categories based on the document rank order; send the ranked categories to an ad server; and receive advertisements associated with the ranked categories from the ad server in a selected context. | 12. An article of manufacture comprising a computer-readable storage device storing computer-readable instructions which, when executed, cause one or more processing devices to perform the following: access information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing; generate at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generate at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generate document word vectors for at least some of the documents that were selected by the user for viewing; perform, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish, using at least one processor, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; rank the predetermined categories based on the document rank order; send the ranked categories to an ad server; and receive advertisements associated with the ranked categories from the ad server in a selected context. 15. The manufacture of claim 12 , wherein the instructions further comprise instructions that cause the one or more processing devices to: apply an expectation maximization algorithm to the documents in the document set that were not selected by the user for viewing to generate negative labels for certain ones of the non-selected documents, and positive labels for the rest of the non-selected documents; and wherein, to generate at least one negative word vector, the instructions include instructions that cause the one or more processing devices to generate at least one negative word vector using words contained in at least a segment of the documents for which the expectation maximization algorithm generates negative labels. | 0.5 |
7,885,904 | 1 | 12 | 1. A user-interface method of selecting and presenting a subset of content items of a first dataspace in which at least one content item of the subset is selected at least in part based on content preferences of the user learned from the user selecting content of a second dataspace, the method comprising: providing access to a first collection of content items of a first dataspace, each content item of the first collection having at least one associated descriptive term to describe the content item; providing access to a second collection of content items of a second dataspace, each content item of the second collection having at least one associated descriptive term to describe the content item; receiving selection actions of content items of the second collection from the user; a computer system determining a user preference signature by analyzing the descriptive terms of the selected content items of the second collection to learn the content preferences of the user for the content of the second dataspace; determining a relationship between the content items of the first dataspace and the content items of the second dataspace, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first dataspace; and subsequent to learning the content preferences of the user, selecting and presenting to the user at least one content item of the first dataspace based on the learned content preferences of the user determined to be relevant to the content items of the first dataspace. | 1. A user-interface method of selecting and presenting a subset of content items of a first dataspace in which at least one content item of the subset is selected at least in part based on content preferences of the user learned from the user selecting content of a second dataspace, the method comprising: providing access to a first collection of content items of a first dataspace, each content item of the first collection having at least one associated descriptive term to describe the content item; providing access to a second collection of content items of a second dataspace, each content item of the second collection having at least one associated descriptive term to describe the content item; receiving selection actions of content items of the second collection from the user; a computer system determining a user preference signature by analyzing the descriptive terms of the selected content items of the second collection to learn the content preferences of the user for the content of the second dataspace; determining a relationship between the content items of the first dataspace and the content items of the second dataspace, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first dataspace; and subsequent to learning the content preferences of the user, selecting and presenting to the user at least one content item of the first dataspace based on the learned content preferences of the user determined to be relevant to the content items of the first dataspace. 12. The method of claim 1 , wherein the selection actions are entered by the user on at least one of a telephone, a PDA, and a mobile computing device. | 0.927958 |
8,938,450 | 1 | 5 | 1. A method for microcontent natural language processing comprising: receiving a plurality of microcontent messages from a social networking server, the plurality of microcontent messages including a microcontent message; breaking up the microcontent message into one or more text tokens by using a tokenizer module that is configured to process micro-syntax and punctuation in the microcontent message; performing a part-of-speech (POS) tagging process on the text tokens to identify a linguistic category for each of the text tokens, wherein the POS tagging process for a respective text token is performed using an error-driven transformation-based tagger and based on a definition and a context of the respective text token; performing a topic extraction on the microcontent message to extract topic metadata for the microcontent message based on the identified linguistic category for each of the text tokens, wherein the extraction is performed without looking up a pre-specified topic in a dictionary of known entities; associating a topic metadata to the microcontent message based on the extracted topic; identifying type metadata from the microcontent message based on an ontology of predetermined microcontent types by applying a database of annotation rules to the text tokens of the microcontent message; associating the identified type metadata to the microcontent message; analyzing co-occurrence of all available metadatas in the plurality of microcontent messages; producing a list of trending topics for the all available metadatas based on results from the analyzing; and compiling a trend database by tracking how the list of trending topics changes over time. | 1. A method for microcontent natural language processing comprising: receiving a plurality of microcontent messages from a social networking server, the plurality of microcontent messages including a microcontent message; breaking up the microcontent message into one or more text tokens by using a tokenizer module that is configured to process micro-syntax and punctuation in the microcontent message; performing a part-of-speech (POS) tagging process on the text tokens to identify a linguistic category for each of the text tokens, wherein the POS tagging process for a respective text token is performed using an error-driven transformation-based tagger and based on a definition and a context of the respective text token; performing a topic extraction on the microcontent message to extract topic metadata for the microcontent message based on the identified linguistic category for each of the text tokens, wherein the extraction is performed without looking up a pre-specified topic in a dictionary of known entities; associating a topic metadata to the microcontent message based on the extracted topic; identifying type metadata from the microcontent message based on an ontology of predetermined microcontent types by applying a database of annotation rules to the text tokens of the microcontent message; associating the identified type metadata to the microcontent message; analyzing co-occurrence of all available metadatas in the plurality of microcontent messages; producing a list of trending topics for the all available metadatas based on results from the analyzing; and compiling a trend database by tracking how the list of trending topics changes over time. 5. The method of claim 1 , wherein the step of identifying type metadata of the microcontent message includes: compiling a matching index including a set of expressions based on the ontology of predetermined microcontent types or the database of annotation rules; and matching the expressions of the matching index with the microcontent message. | 0.5 |
7,596,568 | 7 | 11 | 7. A computer implemented method for resolving ambiguity in a natural language request, the method comprising: in response to receiving a natural language request and at least one input at a computer system, parsing a grammatical structure of the at least one input to identify a token not present in the at least one input, wherein the token includes a word that is statistically associated with documents that have grammatical structures similar to the at least one input; adding the token to the at least one input thereby generating a modified at least one input; generating a plurality of ranked interpretations representing a list of probable intent comprising a set of fragments of data types structurally compatible to data types in the modified at least one input, wherein a fragment of the set of compatible fragments is generated by analyzing a grammatical structure of the request at a linguistic level; and performing an action in response to at least one of the plurality of ranked interpretations; connecting to a plurality of search providers and receives a collection of search results from at least one of the plurality of search providers and displaying results according to a specified expansion policy, in relevance order, as blocks of results from search providers, merged results from multiple search providers in relevance order and eliminate duplicate results. | 7. A computer implemented method for resolving ambiguity in a natural language request, the method comprising: in response to receiving a natural language request and at least one input at a computer system, parsing a grammatical structure of the at least one input to identify a token not present in the at least one input, wherein the token includes a word that is statistically associated with documents that have grammatical structures similar to the at least one input; adding the token to the at least one input thereby generating a modified at least one input; generating a plurality of ranked interpretations representing a list of probable intent comprising a set of fragments of data types structurally compatible to data types in the modified at least one input, wherein a fragment of the set of compatible fragments is generated by analyzing a grammatical structure of the request at a linguistic level; and performing an action in response to at least one of the plurality of ranked interpretations; connecting to a plurality of search providers and receives a collection of search results from at least one of the plurality of search providers and displaying results according to a specified expansion policy, in relevance order, as blocks of results from search providers, merged results from multiple search providers in relevance order and eliminate duplicate results. 11. The method of claim 7 , wherein the at least one input comprises a bias. | 0.931159 |
6,144,958 | 16 | 17 | 16. In a computer system that implements a search engine that is accessible to users over a computer network, a method of processing a search query that includes at least one misspelled search term, the method comprising the computer-implemented steps of: (a) receiving the search query from a user over the computer network, the search query comprising a plurality of search terms and being directed to an informational database to be searched; (b) identifying within the search query a non-matching search term which does not produce a match within the informational database, and at least one matching search term which produces a match within the informational database; (c) using search term correlation data to identify a plurality of additional terms that are deemed to be related to the at least one matching search term, the search term correlation data based at least on historical query submissions; and (d) comparing the additional terms identified in step (c) to the non-matching term to identify an additional term that is a candidate correctly-spelled replacement for the non-matching term. | 16. In a computer system that implements a search engine that is accessible to users over a computer network, a method of processing a search query that includes at least one misspelled search term, the method comprising the computer-implemented steps of: (a) receiving the search query from a user over the computer network, the search query comprising a plurality of search terms and being directed to an informational database to be searched; (b) identifying within the search query a non-matching search term which does not produce a match within the informational database, and at least one matching search term which produces a match within the informational database; (c) using search term correlation data to identify a plurality of additional terms that are deemed to be related to the at least one matching search term, the search term correlation data based at least on historical query submissions; and (d) comparing the additional terms identified in step (c) to the non-matching term to identify an additional term that is a candidate correctly-spelled replacement for the non-matching term. 17. The method of claim 16, wherein the search term correlation data is based at least on frequencies with which search terms have previously occurred within the same query. | 0.800691 |
7,823,117 | 1 | 9 | 1. A processor-implemented method for implementing a high-level programming language program in hardware and software components, comprising: compiling the high-level programming language program into a target language program that includes a plurality of functional elements; profiling execution of the target language program and storing profile data that specifies respective execution counts of the functional elements; selecting a subset of the functional elements for implementation in programmable resources of a programmable device based on the profile data and availability of the programmable resources to implement functions of the subset of functional elements; generating a bitstream that implements a first sub-circuit that performs functions of the subset of functional elements; wherein the generating the bitstream includes generating bits that implement a first soft processor and a second soft processor on the programmable device, wherein the first soft processor in executing a first part of the target language program provides input data to the first sub-circuit, and the second soft processor executing a second part of the target language program receives output data from the first sub-circuit; removing the subset of functional elements from the target language program; configuring the programmable device with the bitstream; and after the removing step, providing the target language program for execution by a processor. | 1. A processor-implemented method for implementing a high-level programming language program in hardware and software components, comprising: compiling the high-level programming language program into a target language program that includes a plurality of functional elements; profiling execution of the target language program and storing profile data that specifies respective execution counts of the functional elements; selecting a subset of the functional elements for implementation in programmable resources of a programmable device based on the profile data and availability of the programmable resources to implement functions of the subset of functional elements; generating a bitstream that implements a first sub-circuit that performs functions of the subset of functional elements; wherein the generating the bitstream includes generating bits that implement a first soft processor and a second soft processor on the programmable device, wherein the first soft processor in executing a first part of the target language program provides input data to the first sub-circuit, and the second soft processor executing a second part of the target language program receives output data from the first sub-circuit; removing the subset of functional elements from the target language program; configuring the programmable device with the bitstream; and after the removing step, providing the target language program for execution by a processor. 9. The method of claim 1 , further comprising for each functional element, generating in the configuration bitstream configuration bits that implement an input FIFO buffer and an output FIFO buffer for input and output of data to and from the functional element. | 0.854283 |
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