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8,291,237 | 6 | 7 | 6. The method of claim 1 , further comprising writing the encrypted electronic document to gamma slots in the buffer chosen randomly, wherein gamma is an integer parameter chosen to produce an acceptable probability of data loss, and said probability is exponentially small as a function of gamma. | 6. The method of claim 1 , further comprising writing the encrypted electronic document to gamma slots in the buffer chosen randomly, wherein gamma is an integer parameter chosen to produce an acceptable probability of data loss, and said probability is exponentially small as a function of gamma. 7. The method of claim 6 , wherein the electronic document has associated therewith a collision detection string, and wherein each time the encrypted electronic document is written to one of the plurality of slots in the buffer, the encryption variable is written to the same slot and the collision detection string is written to the same slot. | 0.5 |
9,129,226 | 29 | 31 | 29. The method of claim 1 wherein the human feedback includes structured feedback directly useable by the computer system. | 29. The method of claim 1 wherein the human feedback includes structured feedback directly useable by the computer system. 31. The method of claim 29 wherein the structured feedback comprises sentences constructed from a limited group of words. | 0.516 |
9,237,255 | 8 | 9 | 8. A system for processing a document, the system comprising: one or more processors operable to: determine one or more text regions and one or more image regions in a scanned document; determine a font size associated with each of said one or more text regions; modify a first resolution of each of said one or more text regions, based on respective font size associated with each of said one or more text regions to generate one or more modified text regions; modify a second resolution of each of said one or more image regions, based on at least a third resolution provided by a user, to generate one or more modified image regions; and generate a multiresolution document based on said one or more modified image regions and said one or more text regions. | 8. A system for processing a document, the system comprising: one or more processors operable to: determine one or more text regions and one or more image regions in a scanned document; determine a font size associated with each of said one or more text regions; modify a first resolution of each of said one or more text regions, based on respective font size associated with each of said one or more text regions to generate one or more modified text regions; modify a second resolution of each of said one or more image regions, based on at least a third resolution provided by a user, to generate one or more modified image regions; and generate a multiresolution document based on said one or more modified image regions and said one or more text regions. 9. The system of claim 8 , wherein said document corresponds to a printed document. | 0.845149 |
9,003,318 | 5 | 7 | 5. A system for declarative specification, the system comprising: a memory, the memory stores executable instructions; and a microprocessor, the microprocessor is configured to execute the executable instructions to: a receiving unit configured to receive from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, and the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; alter a declarative specification for controlling the game character in the computer game as a function of the first grouping, wherein the first grouping is a logical implication in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and the game character does not perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; and and during the computer game, in response to the declarative specification, allow the game character to perform the respective action identified by the icon of the first action predicate when the first data indication is positive and not allow the game character to perform the respective action identified by the icon of the first action predicate when the first data indication is negative; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. | 5. A system for declarative specification, the system comprising: a memory, the memory stores executable instructions; and a microprocessor, the microprocessor is configured to execute the executable instructions to: a receiving unit configured to receive from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, and the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; alter a declarative specification for controlling the game character in the computer game as a function of the first grouping, wherein the first grouping is a logical implication in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and the game character does not perform the respective action identified by the icon of the first action predicate when the first data indication predicate is negative; and and during the computer game, in response to the declarative specification, allow the game character to perform the respective action identified by the icon of the first action predicate when the first data indication is positive and not allow the game character to perform the respective action identified by the icon of the first action predicate when the first data indication is negative; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. 7. The system of claim 5 , wherein the first data indication predicate and/or first action predicate is at least one of a sub-parameterized predicate or a hierarchical predicate. | 0.65098 |
9,600,897 | 1 | 3 | 1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets. | 1. A system to perform hierarchical video segmentation, comprising: a processor coupled to a camera; wherein the processor executes: defining voxels over a spatio-temporal video; grouping into segments contiguous voxels that display similar characteristics including similar appearance or motion; determining a trajectory-based feature that complements color and optical flow cues, wherein trajectory cues are probabilistic histograms combinable in a graph-based framework; and applying a max-margin cue combination that learns a supervised distance metric for region dissimilarity that combines color, flow and trajectory features; generating a max-margin distance metric for video segmentation that combines a plurality of feature channels; determining feature representation φ(S) for a segment S as a stacked up histograms from all the individual cues; learning feature weighting as a linear combination w T |φ(S i )−φ(S j ), where an optimal weight w* is determined by solving an optimization problem of the form: min w , ξ ij 1 2 w T w + λ N + ∑ i , j ξ ij + + λ N - ∑ i , j ξ ij - s . t . y ij w T ϕ ( s i ) - ϕ ( s j ) ≤ 2 y ij - 1 + ξ ij , ∀ i , j w ± 0 , ξ ij ≥ 0 , where ξ ij denote slack variables and λ is a soft margin trade-off parameter, N + and N − are the number of pairs of segments that have the same or different ground truth label and ξ ij + , ξ ij − are slack variables with respective membership in those positive or negative sets. 3. The system of claim 1 , comprising generating histogram-based features in a graph-based hierarchical segmentation. | 0.844415 |
9,594,837 | 1 | 2 | 1. A method of presenting search results returned responsive to executing a query, comprising: determining, by employing a query classifier, whether the query is intrinsically diverse or not intrinsically diverse, wherein the query is intrinsically diverse when included in an intrinsically diverse session, wherein the intrinsically diverse session is directed towards a task, and wherein queries included in the intrinsically diverse session are directed towards respective subtasks of the task; receiving the search results retrieved by a search engine responsive to executing the query, wherein related queries correspond to the search results; evaluating an objective function to compute an optimized value in response to the query being determined to be intrinsically diverse, wherein: the objective function is based on relevance of differing search results to the query, the differing search results returned responsive to the related queries; and the objective function is based on redundancy between the related queries; and controlling presentation of the search results on a display screen according to the optimized value when the query is determined to be intrinsically diverse. | 1. A method of presenting search results returned responsive to executing a query, comprising: determining, by employing a query classifier, whether the query is intrinsically diverse or not intrinsically diverse, wherein the query is intrinsically diverse when included in an intrinsically diverse session, wherein the intrinsically diverse session is directed towards a task, and wherein queries included in the intrinsically diverse session are directed towards respective subtasks of the task; receiving the search results retrieved by a search engine responsive to executing the query, wherein related queries correspond to the search results; evaluating an objective function to compute an optimized value in response to the query being determined to be intrinsically diverse, wherein: the objective function is based on relevance of differing search results to the query, the differing search results returned responsive to the related queries; and the objective function is based on redundancy between the related queries; and controlling presentation of the search results on a display screen according to the optimized value when the query is determined to be intrinsically diverse. 2. The method of claim 1 , wherein the objective function is further based on relevance of the search results to one or more of the related queries. | 0.927522 |
8,392,188 | 18 | 43 | 18. A method of task classification using a phonotactic model built for domain independent speech recognition, comprising: recognizing phones from a user's input communication using a current phonotactic model stored in a database; detecting morphemes from the recognized phones; creating, via a processor, a new phonotactic model using the detected morpheme, the creating the new phonotactic model comprising transforming a prior probability distribution associated with a first domain to a prior probability distribution associated with a second domain; replacing the current phonotactic model with the new phonotactic model in the database; and making a task-type classification decision based on the detected morphemes from the user's input communication. | 18. A method of task classification using a phonotactic model built for domain independent speech recognition, comprising: recognizing phones from a user's input communication using a current phonotactic model stored in a database; detecting morphemes from the recognized phones; creating, via a processor, a new phonotactic model using the detected morpheme, the creating the new phonotactic model comprising transforming a prior probability distribution associated with a first domain to a prior probability distribution associated with a second domain; replacing the current phonotactic model with the new phonotactic model in the database; and making a task-type classification decision based on the detected morphemes from the user's input communication. 43. The method of claim 18 , wherein creating a new phonotactic model using the detected morphemes further comprises: mapping phone sequence statistics into word statistics; and transforming a word probability vector of the prior probability distribution of the first domain using the mapped word statistics. | 0.5 |
9,965,569 | 10 | 11 | 10. A computer-implemented method for reducing user error when constructing a search query, comprising: receiving, by a computing device, a search query without launching a web search for the search query; obtaining, by the computing device, autosuggest candidates having the search query as a common prefix wherein the autosuggest candidates are based, at least in part, on received user preference information corresponding to the search query; generating, by the computing device, truncated autosuggest candidates by removing the search query from the autosuggest candidates; and providing the truncated autosuggest candidates for display. | 10. A computer-implemented method for reducing user error when constructing a search query, comprising: receiving, by a computing device, a search query without launching a web search for the search query; obtaining, by the computing device, autosuggest candidates having the search query as a common prefix wherein the autosuggest candidates are based, at least in part, on received user preference information corresponding to the search query; generating, by the computing device, truncated autosuggest candidates by removing the search query from the autosuggest candidates; and providing the truncated autosuggest candidates for display. 11. The computer-implemented method of claim 10 , wherein the search query is received and presented in a search box of a user interface. | 0.659204 |
7,873,183 | 1 | 2 | 1. A watermark embedding method for embedding a secret message sequence in a document, said method comprising: obtaining layout information of said document; extracting a digest of said document by using a Hash function; calculating by a computer processor embedded positions where said secret message sequence is embedded in said document, wherein said calculating the embedded positions is performed by means of a Hash digest of said document and a finite state machine driven by a public key encrypted algorithm, wherein said calculating the embedded positions further comprises calculating an initial state based on the extracted document digest and said secret message sequence, calculating a state sequence based on the initial state and a public key, and calculating the embedded position sequence based on the state sequence; and dispersedly hiding said secret message sequence in each of said calculated embedded positions by altering the layout of said document. | 1. A watermark embedding method for embedding a secret message sequence in a document, said method comprising: obtaining layout information of said document; extracting a digest of said document by using a Hash function; calculating by a computer processor embedded positions where said secret message sequence is embedded in said document, wherein said calculating the embedded positions is performed by means of a Hash digest of said document and a finite state machine driven by a public key encrypted algorithm, wherein said calculating the embedded positions further comprises calculating an initial state based on the extracted document digest and said secret message sequence, calculating a state sequence based on the initial state and a public key, and calculating the embedded position sequence based on the state sequence; and dispersedly hiding said secret message sequence in each of said calculated embedded positions by altering the layout of said document. 2. The watermark embedding method according to claim 1 , wherein said obtaining the layout information further comprises dividing said document into a plurality of segments. | 0.708754 |
9,916,303 | 17 | 19 | 17. A computer program product providing an answer to a question containing at least one time-sensitive word or at least one time-sensitive phrase using natural language processing (NLP), the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions executable by a processor, the program instructions comprising: program instructions to create and maintaining an online T-Word Dictionary, wherein creating and maintaining the online T-Word Dictionary comprises: program instructions to determine a relationship between a plurality of T-Words and a plurality of corresponding values, wherein the plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; program instructions to mapping the plurality of T-Words to the plurality of corresponding values based on the determine relationship; and program instructions to store the mapped plurality of T-Words to the plurality of corresponding values in the online T-Word Dictionary; program instructions to receive the input question, wherein the input question is entered by a user via a graphical user interface associated with a first computer; program instructions to perform natural language processing (NLP) analysis on the input question to extract a required value phrase; program instructions to form at least one mathematical equation based on the extracted required value phrase, wherein forming the at least one mathematical equation comprises: program instructions to identify the at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein a value associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase varies according to a particular point in time, and wherein the identifying comprises communicating online with a second computer to access the online T-Word Dictionary; and program instructions to resolve the identified at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein the resolving comprises communicating online with the second computer to access the online T-Word Dictionary and recursively mapping a plurality of variables associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase to at least one formula contained in the T-Word Dictionary; program instructions to determine the answer to the input question in natural language based on the solved at least one mathematical equation; and program instructions to narrate the answer to the input question in natural language based on the solved at least one mathematical equation. | 17. A computer program product providing an answer to a question containing at least one time-sensitive word or at least one time-sensitive phrase using natural language processing (NLP), the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions executable by a processor, the program instructions comprising: program instructions to create and maintaining an online T-Word Dictionary, wherein creating and maintaining the online T-Word Dictionary comprises: program instructions to determine a relationship between a plurality of T-Words and a plurality of corresponding values, wherein the plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; program instructions to mapping the plurality of T-Words to the plurality of corresponding values based on the determine relationship; and program instructions to store the mapped plurality of T-Words to the plurality of corresponding values in the online T-Word Dictionary; program instructions to receive the input question, wherein the input question is entered by a user via a graphical user interface associated with a first computer; program instructions to perform natural language processing (NLP) analysis on the input question to extract a required value phrase; program instructions to form at least one mathematical equation based on the extracted required value phrase, wherein forming the at least one mathematical equation comprises: program instructions to identify the at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein a value associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase varies according to a particular point in time, and wherein the identifying comprises communicating online with a second computer to access the online T-Word Dictionary; and program instructions to resolve the identified at least one time-sensitive word or the at least one time-sensitive phrase contained in the received input question, wherein the resolving comprises communicating online with the second computer to access the online T-Word Dictionary and recursively mapping a plurality of variables associated with the identified at least one time-sensitive word or the at least one time-sensitive phrase to at least one formula contained in the T-Word Dictionary; program instructions to determine the answer to the input question in natural language based on the solved at least one mathematical equation; and program instructions to narrate the answer to the input question in natural language based on the solved at least one mathematical equation. 19. The computer program product of claim 17 , wherein identifying the at least one time-sensitive word or the at least one time-sensitive phrase comprises the use of a T-Word Dictionary. | 0.621457 |
5,548,749 | 6 | 7 | 6. The method of claim 4, wherein the one or more properties defined by the simple value profiles, group profiles and object link profiles include a minimum cardinality property that defines a minimum number of data entries that are stored in the relational database for the corresponding attribute and a maximum cardinality property that defines a maximum number of data entries that are stored in the relational database for a corresponding attribute, wherein the step of translating the semantic objects and their associated attributes in the semantic object model into a relational database schema, further comprises the steps of: analyzing each attribute associated with a semantic object to determine if it is a simple value attribute and if so: reading the maximum cardinality property of the simple value attribute; automatically creating an additional column in the relational database table created for the semantic object with which the simple value attribute is associated, the additional column storing a data entry for the simple value attribute if the maximum cardinality is less than or equal to one; and otherwise automatically creating a separate relational database table for the attribute, the separate relational database table having at least two columns to store multiple data entries for the simple value attribute and one or more foreign keys that link an entry in the separate relational data base table to an entry in the relational database table created for the semantic object with which the multivalued, simple value attribute is associated. | 6. The method of claim 4, wherein the one or more properties defined by the simple value profiles, group profiles and object link profiles include a minimum cardinality property that defines a minimum number of data entries that are stored in the relational database for the corresponding attribute and a maximum cardinality property that defines a maximum number of data entries that are stored in the relational database for a corresponding attribute, wherein the step of translating the semantic objects and their associated attributes in the semantic object model into a relational database schema, further comprises the steps of: analyzing each attribute associated with a semantic object to determine if it is a simple value attribute and if so: reading the maximum cardinality property of the simple value attribute; automatically creating an additional column in the relational database table created for the semantic object with which the simple value attribute is associated, the additional column storing a data entry for the simple value attribute if the maximum cardinality is less than or equal to one; and otherwise automatically creating a separate relational database table for the attribute, the separate relational database table having at least two columns to store multiple data entries for the simple value attribute and one or more foreign keys that link an entry in the separate relational data base table to an entry in the relational database table created for the semantic object with which the multivalued, simple value attribute is associated. 7. The method of claim 6, wherein the step of translating the semantic objects and their included attributes in the semantic object model into a relational database schema, further comprises the steps of: analyzing each attribute associated with a semantic object to determine if the attribute is a group attribute and if so: reading the maximum cardinality property of the group attribute to determine if the group attribute is not multivalued, and if so: automatically creating an additional column in the relational database table created for the semantic object with which the group attribute is associated to store data entries for each simple value attribute that is included in the list of member attributes if the maximum cardinality of the group attribute is less than or equal to one. | 0.5 |
7,991,613 | 14 | 19 | 14. A system for analyzing audio components of communications comprising: an audio analyzer operative to: receive information corresponding to an audio component of a communication session from a recorder; generate text from the information at a speech recognition engine executing on a computing device; and integrate the text with additional information provided by the recorder corresponding to the communication session, the additional information being integrated in a textual format, wherein the text with the additional information forms a textual representation of the audio component; and the text with the additional information includes a first representation of a party to the communication session and a second representation of a characteristic of the audio component associated with the information of the communication session, wherein the first representation comprises a first letter to indicate audio communication by a first party of the communication session, and wherein the second representation comprises a lower case representation of the letter indicates a first volume level and an upper case representation of the letter indicates a second volume level. | 14. A system for analyzing audio components of communications comprising: an audio analyzer operative to: receive information corresponding to an audio component of a communication session from a recorder; generate text from the information at a speech recognition engine executing on a computing device; and integrate the text with additional information provided by the recorder corresponding to the communication session, the additional information being integrated in a textual format, wherein the text with the additional information forms a textual representation of the audio component; and the text with the additional information includes a first representation of a party to the communication session and a second representation of a characteristic of the audio component associated with the information of the communication session, wherein the first representation comprises a first letter to indicate audio communication by a first party of the communication session, and wherein the second representation comprises a lower case representation of the letter indicates a first volume level and an upper case representation of the letter indicates a second volume level. 19. The system of claim 14 , further comprising a recorder operative to record the audio component such that the information corresponding to the audio component is accessible to the audio analyzer. | 0.642599 |
9,454,348 | 2 | 5 | 2. The method of claim 1 , wherein, a syntax of the data interchange protocol modeling language comprises a JavaScript Object Notation syntax. | 2. The method of claim 1 , wherein, a syntax of the data interchange protocol modeling language comprises a JavaScript Object Notation syntax. 5. The method of claim 2 , wherein specifying features further comprises: defining a minimum cardinality in the data models specifying a minimum number of occurrences of at least one property that are required in the data interchange protocol document. | 0.720621 |
4,707,801 | 1 | 3 | 1. A word processing system comprising: interactive display terminal means for receiving data representative of alphanumeric characters and data representative of graphics, and for displaying alphanumeric characters and graphic information; means for integrating said alphanumeric character data and said graphic data from said terminal means into a data stream; a character generator, connected to the data stream and responsive to the alphanumeric character data, for generating said alphanumeric characters for display on said terminal means from said data representative of alphanumeric characters from said data stream; means, connected to the data stream and responsive to the graphic data, for converting said data representative of graphics from said data stream into graphic characters and for providing said graphic characters to said character generator to display said characters on said terminal means; means, connected to the data stream and responsive to the alphanumeric character data and the graphic data, for selectively applying the data in said data stream representative of said alphanumeric characters to a printing means, and for selectively applying the data in said data stream representative of said graphics to an illustrating means; said printing means, responsive to the selectively applying means, for printing said alphanumeric characters on a document from said data representative of alphanumeric characters; and said illustrating means, responsive to the selectively applying means, for producing graphic information on said document from said data representative of said graphics in a format different from said graphic characters or said alphanumeric characters. | 1. A word processing system comprising: interactive display terminal means for receiving data representative of alphanumeric characters and data representative of graphics, and for displaying alphanumeric characters and graphic information; means for integrating said alphanumeric character data and said graphic data from said terminal means into a data stream; a character generator, connected to the data stream and responsive to the alphanumeric character data, for generating said alphanumeric characters for display on said terminal means from said data representative of alphanumeric characters from said data stream; means, connected to the data stream and responsive to the graphic data, for converting said data representative of graphics from said data stream into graphic characters and for providing said graphic characters to said character generator to display said characters on said terminal means; means, connected to the data stream and responsive to the alphanumeric character data and the graphic data, for selectively applying the data in said data stream representative of said alphanumeric characters to a printing means, and for selectively applying the data in said data stream representative of said graphics to an illustrating means; said printing means, responsive to the selectively applying means, for printing said alphanumeric characters on a document from said data representative of alphanumeric characters; and said illustrating means, responsive to the selectively applying means, for producing graphic information on said document from said data representative of said graphics in a format different from said graphic characters or said alphanumeric characters. 3. A word processing system according to claim 1 wherein said means for selectively applying data separates the data representative of alphanumeric characters from said data representative of graphic information for application to the printing means and illustrating means respectively and said printing means prints only said alphanumeric characters on said document and said illustrating means produces only said graphic information on said document. | 0.5 |
9,704,487 | 7 | 10 | 7. A vehicle comprising: a speech recognition module configured to recognize a speech uttered by a user; a communication unit configured to receive a result of processing for speech recognition acquired by at least one user terminal; and a controller configured to: compare a result of processing for speech recognition acquired by the speech recognition module to the result of processing for speech recognition acquired by the at least one user terminal, and to control a device in the vehicle based on the comparison; and when the controller determines a speech waveform of the speech uttered from the user is different from a speech waveform acquired by the at least one user terminal and determines a number of the result of processing for speech recognition acquired by the speech recognition module is one, control the device in the vehicle based on the result of processing for speech recognition acquired by the speech recognition module. | 7. A vehicle comprising: a speech recognition module configured to recognize a speech uttered by a user; a communication unit configured to receive a result of processing for speech recognition acquired by at least one user terminal; and a controller configured to: compare a result of processing for speech recognition acquired by the speech recognition module to the result of processing for speech recognition acquired by the at least one user terminal, and to control a device in the vehicle based on the comparison; and when the controller determines a speech waveform of the speech uttered from the user is different from a speech waveform acquired by the at least one user terminal and determines a number of the result of processing for speech recognition acquired by the speech recognition module is one, control the device in the vehicle based on the result of processing for speech recognition acquired by the speech recognition module. 10. The vehicle according to claim 7 , wherein when the controller determines that a speech waveform of the speech uttered from the user is different from a speech waveform acquired by the at least one user terminal, that the number of the result of speech recognition acquired by the speech input module is one, and that the acquired result of speech recognition is identical to the result of speech recognition acquired by the at least one user terminal, the controller is configured to request the user to input a speech again. | 0.5 |
10,121,071 | 1 | 12 | 1. A document verification system comprising digital data processors programmed to provide: an interface configured to receive electronic document runs at a presentment stage from document generation systems in excess of 500,000 documents; a normalisation component configured to transfer each document to an instance in a mark-up language taxonomy with one instance per document; a verification engine configured to perform per-document checking by checking each document instance including semantic checking using granular semantic rules within groups of items of document data, wherein the verification engine is configured to store document instances in a relational database and to set a state including a rejected state, and to remove document instances if errors are detected; a rule server configured to maintain current data item contents of each group and to maintain verification rules for execution for said semantic checking within each group; and a feedback component arranged to provide per-document error feedback arising from operation of the verification engine, wherein the feedback component is arranged to provide feedback without affecting operation of a system which generates the documents. | 1. A document verification system comprising digital data processors programmed to provide: an interface configured to receive electronic document runs at a presentment stage from document generation systems in excess of 500,000 documents; a normalisation component configured to transfer each document to an instance in a mark-up language taxonomy with one instance per document; a verification engine configured to perform per-document checking by checking each document instance including semantic checking using granular semantic rules within groups of items of document data, wherein the verification engine is configured to store document instances in a relational database and to set a state including a rejected state, and to remove document instances if errors are detected; a rule server configured to maintain current data item contents of each group and to maintain verification rules for execution for said semantic checking within each group; and a feedback component arranged to provide per-document error feedback arising from operation of the verification engine, wherein the feedback component is arranged to provide feedback without affecting operation of a system which generates the documents. 12. A document verification system as claimed in claim 1 , wherein the interface is configured to re-receive rejected document instances in a feedback loop only upon re-feeding the document through a modification stage and back into the document interface before normalisation. | 0.818717 |
8,380,840 | 1 | 2 | 1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. | 1. A method comprising: receiving, by a Session Initiation Protocol (SIP) server, first call event information, associated with a first call event, from a first module, the first call event information from the first module being processed by the first module using a first type of proprietary application; receiving, by the SIP server, second call event information, associated with a second call event, from a second module, the second call event information from the second module being processed by the second module using a second type of proprietary application, the second type of proprietary application being different from the first type of proprietary application; converting, by the SIP server, the first call event information from a first format associated with the first type of proprietary application into a first Extensible Markup Language (XML) document to generate a first call event record for the first call event information; converting, by the SIP server, the second call event information from a second format associated with the second type of proprietary application into a second XML document to generate a second call event record for the second call event information; creating, by the SIP server, an XML call event file based on the first XML document and the second XML document, creating the XML call event file including: generating a first section that includes data identifying relationships associated with one or more tags included in the XML call event file, generating a second section that includes data identifying the SIP server, generating third section that identifies a type of a first message associated with the first call event and a type of a second message associated with the second call event record, and generating a fourth section that includes information associated with a processing of the first message and information associated with a processing of the second message; and monitoring, by the SIP server, network traffic associated with the SIP server based on the XML call event file using a third type of proprietary application that is different than the first type of proprietary application and the second type of proprietary application. 2. The method of claim 1 , where the SIP server comprises a SIP proxy server. | 0.946897 |
9,430,141 | 6 | 12 | 6. A method comprising: under control of one or more computer systems configured with executable instructions, receiving a first stroke associated with a touch input; determining, based on the first stroke, a predetermined type of annotation associated with the touch input; determining the predetermined type of annotation is a free form annotation; associating the free form annotation with a word of content presented on a display of a device; receiving a additional strokes associated with the touch input; associating the free form annotation with the word based at least in part on a location of the word within the content; and rendering the content to be presented on the display, the rendering including rendering the content presented on the display around the annotation to cause the annotation to appear adjacent to the word and at least partially surrounded by the content. | 6. A method comprising: under control of one or more computer systems configured with executable instructions, receiving a first stroke associated with a touch input; determining, based on the first stroke, a predetermined type of annotation associated with the touch input; determining the predetermined type of annotation is a free form annotation; associating the free form annotation with a word of content presented on a display of a device; receiving a additional strokes associated with the touch input; associating the free form annotation with the word based at least in part on a location of the word within the content; and rendering the content to be presented on the display, the rendering including rendering the content presented on the display around the annotation to cause the annotation to appear adjacent to the word and at least partially surrounded by the content. 12. The method of claim 6 , further comprising: receiving a second touch input; determining the second touch input is an circle input based at least in part on an analysis of a first stoke associated with the second touch input; associating the first stroke of the second touch input with a portion of the content based at least in part on a position of the first stroke of the second touch input with respect to the content presented on the display; and replacing the first stroke of the second touch input with a processed circle. | 0.529204 |
7,702,692 | 1 | 2 | 1. A computer-executed method for preventing unauthorized access to database resources, the method comprising: receiving, at a computer, a section of programming language code to execute on a computer system, wherein the programming language code is annotated with a pragma that defines a set of database objects that the programming language code has permission to access, wherein the pragma is run-time interpreted or compilation-directed; analyzing the pragma to determine the set of database objects; creating a sandbox which includes the set of database objects defined by the pragma; executing the programming language code within the boundaries of the sandbox; determining if the programming language code is attempting to access a table database object outside the boundaries of the sandbox; and if so, generating an exception. | 1. A computer-executed method for preventing unauthorized access to database resources, the method comprising: receiving, at a computer, a section of programming language code to execute on a computer system, wherein the programming language code is annotated with a pragma that defines a set of database objects that the programming language code has permission to access, wherein the pragma is run-time interpreted or compilation-directed; analyzing the pragma to determine the set of database objects; creating a sandbox which includes the set of database objects defined by the pragma; executing the programming language code within the boundaries of the sandbox; determining if the programming language code is attempting to access a table database object outside the boundaries of the sandbox; and if so, generating an exception. 2. The method of claim 1 , wherein processing the programming language code involves interpreting the programming language code at run-time. | 0.763514 |
9,626,628 | 10 | 11 | 10. An apparatus, comprising: one or more network interfaces that communicate with a network; a processor coupled to the one or more network interfaces and configured to execute a process; and a memory configured to store program instructions which contain the process executable by the processor, the process comprising: communicating an expert discovery request into a network to discover one or more experts; receiving, from the one or more experts, one or more expert discovery responses; building, based on the one or more expert discovery responses, a dynamic multicast tree of experts to create a communication infrastructure for the LM to interact with multiple experts for supervised learning; determining that the LM does not have a way of categorizing a certain set of data received at the node; in response to determining that the LM cannot categorize the certain set of data, triggering an on-the-fly tunnel connection to at least one of the one or more experts in the multicast tree of experts; sending an expert request message over the on-the-fly tunnel connection, the expert request message requesting input by the at least one expert to categorize the certain set of data for the LM; receiving one or more expert input responses; and categorizing, by the LM, the certain set of data based on the one or more expert input responses. | 10. An apparatus, comprising: one or more network interfaces that communicate with a network; a processor coupled to the one or more network interfaces and configured to execute a process; and a memory configured to store program instructions which contain the process executable by the processor, the process comprising: communicating an expert discovery request into a network to discover one or more experts; receiving, from the one or more experts, one or more expert discovery responses; building, based on the one or more expert discovery responses, a dynamic multicast tree of experts to create a communication infrastructure for the LM to interact with multiple experts for supervised learning; determining that the LM does not have a way of categorizing a certain set of data received at the node; in response to determining that the LM cannot categorize the certain set of data, triggering an on-the-fly tunnel connection to at least one of the one or more experts in the multicast tree of experts; sending an expert request message over the on-the-fly tunnel connection, the expert request message requesting input by the at least one expert to categorize the certain set of data for the LM; receiving one or more expert input responses; and categorizing, by the LM, the certain set of data based on the one or more expert input responses. 11. The apparatus according to claim 10 , wherein the process further comprises: including in the expert request message an indication of a particular expert from which the LM is requesting information. | 0.779956 |
8,352,509 | 15 | 20 | 15. A computer program product for creating a multi-format data object, the computer program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for implementing a method, the method comprising: creating a multi-format data object, the multi-format data object comprising: a text format markup language (ML) document in a text format section of the multi-format data object; a parsed binary format ML document in a binary format section of the multi-format data object, wherein the parsed binary format ML document provides a parsed format of the text format ML document to an ML consumer; and a pointer in a metadata section of the multi-format data object, wherein the pointer provides access to at least one of the text format section and the binary format section. | 15. A computer program product for creating a multi-format data object, the computer program product comprising: a storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for implementing a method, the method comprising: creating a multi-format data object, the multi-format data object comprising: a text format markup language (ML) document in a text format section of the multi-format data object; a parsed binary format ML document in a binary format section of the multi-format data object, wherein the parsed binary format ML document provides a parsed format of the text format ML document to an ML consumer; and a pointer in a metadata section of the multi-format data object, wherein the pointer provides access to at least one of the text format section and the binary format section. 20. The computer program product of claim 15 wherein the parsed binary format ML document is generated via an ML parser and written to the binary format section in response to an update of the text format ML document in the text format section. | 0.5 |
4,697,242 | 19 | 20 | 19. An adaptive computing system comprising, in combination, a message memory for storing a plurality of messages, each message being represented by a sequence of binary digits; a classifier memory for storing a plurality of classifiers, each such classifier consisting of: a condition part identifying selected messages which are to be read from the message memory and processed into result messages, an action part which specifies the functional relationship between said selected messages and said result messages, and a strength value; and processing means for translating messages in said message store in accordance with each of said classifiers, said processing means including means for increasing the strength value of any classifier which creates a result message which is itself specified by the condition part of a second classifier and translated into a further result message which is placed in said message store. | 19. An adaptive computing system comprising, in combination, a message memory for storing a plurality of messages, each message being represented by a sequence of binary digits; a classifier memory for storing a plurality of classifiers, each such classifier consisting of: a condition part identifying selected messages which are to be read from the message memory and processed into result messages, an action part which specifies the functional relationship between said selected messages and said result messages, and a strength value; and processing means for translating messages in said message store in accordance with each of said classifiers, said processing means including means for increasing the strength value of any classifier which creates a result message which is itself specified by the condition part of a second classifier and translated into a further result message which is placed in said message store. 20. An adaptive computing system as set forth in claim 19 wherein said processing means further includes means for forming a bid value associated with every result message based at least in part on the strength value of the classifier which created said result message, and means included in said processing means for translating only those result messages having high associated bid values relative to the bid values of other result messages. | 0.521598 |
8,336,078 | 13 | 19 | 13. A system for managing role-based access in a multi-customer computing environment, the system comprising: one or more servers configured to: receive a request from an actor to take action within the multi-customer computing environment; determine a role from one or more roles for the actor based on an identification of the actor, wherein each role is assigned a plurality of context parameters, each role is used by a plurality of customers, and the role that is determined can have a first policy element for the actor and a second policy element for a different actor, the first policy element and the second policy element are not the same; receive one value for each of the one or more context parameters assigned to the role based on the identification of the actor; determine a role scope for the role based on the one value of each of the one or more context parameters assigned to the actor; determine an actor-role scope value based on the role scope and the one value of each of the one or more context parameters assigned to the role; determine a policy type based on the request from the actor and the actor's role and the one or more context parameters assigned to actor; populate policy elements of the policy type to form a policy instance with one or more values from the one or more context parameters assigned to the role; and provide to the actor an access permission for the first policy element or the second policy element so the actor can take action within the multi-customer computing environment based on the policy instance. | 13. A system for managing role-based access in a multi-customer computing environment, the system comprising: one or more servers configured to: receive a request from an actor to take action within the multi-customer computing environment; determine a role from one or more roles for the actor based on an identification of the actor, wherein each role is assigned a plurality of context parameters, each role is used by a plurality of customers, and the role that is determined can have a first policy element for the actor and a second policy element for a different actor, the first policy element and the second policy element are not the same; receive one value for each of the one or more context parameters assigned to the role based on the identification of the actor; determine a role scope for the role based on the one value of each of the one or more context parameters assigned to the actor; determine an actor-role scope value based on the role scope and the one value of each of the one or more context parameters assigned to the role; determine a policy type based on the request from the actor and the actor's role and the one or more context parameters assigned to actor; populate policy elements of the policy type to form a policy instance with one or more values from the one or more context parameters assigned to the role; and provide to the actor an access permission for the first policy element or the second policy element so the actor can take action within the multi-customer computing environment based on the policy instance. 19. The system of claim 13 , wherein the policy type includes an access control policy element, a data view/presentation policy element, a function performance/update operation policy element, or any combination thereof. | 0.5 |
10,074,097 | 1 | 4 | 1. A computer-implemented method comprising: receiving a plurality of business categories, wherein each of the business categories is associated with (i) at least one category profile and (ii) a set of electronic messages, wherein the set of electronic messages are maintained in a storage device; receiving business information for an unclassified business, wherein the business information comprises at least information describing power consumption of the unclassified business and a zoning restriction classification associated with a location at which the unclassified business operates; comparing the business information to one or more of the category profiles to determine if the unclassified business corresponds with at least one of the plurality of business categories based at least in part on the power consumption of the unclassified business, wherein for a first business category of the plurality of business categories, the comparing comprises: (i) determining a degree of similarity value describing a degree to which the business information matches information contained within the one or more of the category profiles associated with the first business category; and (ii) determining that the unclassified business corresponds with the first business category when the degree of similarity value exceeds a predetermined threshold; in response to determining that the unclassified business corresponds with the first business category, associating the unclassified business with the first business category, wherein a first subset of the set of electronic messages are maintained in the storage device in association with the first business category; and controlling transmission of the set of electronic messages based on associations between businesses and the business categories, comprising: (i) selecting the first subset of the set of electronic messages from the storage device for transmission to remote devices associated with the unclassified business based on the unclassified business being associated with the first business category; and (ii) sending the first subset of the set of electronic messages to the remote devices associated with the unclassified business. | 1. A computer-implemented method comprising: receiving a plurality of business categories, wherein each of the business categories is associated with (i) at least one category profile and (ii) a set of electronic messages, wherein the set of electronic messages are maintained in a storage device; receiving business information for an unclassified business, wherein the business information comprises at least information describing power consumption of the unclassified business and a zoning restriction classification associated with a location at which the unclassified business operates; comparing the business information to one or more of the category profiles to determine if the unclassified business corresponds with at least one of the plurality of business categories based at least in part on the power consumption of the unclassified business, wherein for a first business category of the plurality of business categories, the comparing comprises: (i) determining a degree of similarity value describing a degree to which the business information matches information contained within the one or more of the category profiles associated with the first business category; and (ii) determining that the unclassified business corresponds with the first business category when the degree of similarity value exceeds a predetermined threshold; in response to determining that the unclassified business corresponds with the first business category, associating the unclassified business with the first business category, wherein a first subset of the set of electronic messages are maintained in the storage device in association with the first business category; and controlling transmission of the set of electronic messages based on associations between businesses and the business categories, comprising: (i) selecting the first subset of the set of electronic messages from the storage device for transmission to remote devices associated with the unclassified business based on the unclassified business being associated with the first business category; and (ii) sending the first subset of the set of electronic messages to the remote devices associated with the unclassified business. 4. The computer-implemented method of claim 1 , wherein the information describing power consumption comprises information describing a power usage pattern associated with the unclassified business. | 0.738095 |
9,420,422 | 1 | 5 | 1. A mobile media communications system, comprising: a host network server executable on one or more processors coupled to a memory and a network, and configured to receive a search request having one or more of a source identifier and a query, and to generate a location from the source identifier and to shallow-parse the query into extracted entities; the host network server further configured to (a) search with the extracted entities, predetermined category domains, each domain including at least items, services, and locations, (b) generate a one-to-many category array for each extracted entity that associates one or more categories of the predetermined category domains to each extracted entity, and (c) generate, with the location and extracted entities and associated category arrays, a conflated query array that includes the extracted entities, the category array, and a query confidence probability for each category array element; and the host network server further configured to search a network site repository with the location and conflated query array, and to retrieve one or more network site keys within a proximity of the location, and to generate an associated relevancy probability calculated as a function of the number of retrieved one or more network site keys having associated categories that match those of the category arrays of the conflated query. | 1. A mobile media communications system, comprising: a host network server executable on one or more processors coupled to a memory and a network, and configured to receive a search request having one or more of a source identifier and a query, and to generate a location from the source identifier and to shallow-parse the query into extracted entities; the host network server further configured to (a) search with the extracted entities, predetermined category domains, each domain including at least items, services, and locations, (b) generate a one-to-many category array for each extracted entity that associates one or more categories of the predetermined category domains to each extracted entity, and (c) generate, with the location and extracted entities and associated category arrays, a conflated query array that includes the extracted entities, the category array, and a query confidence probability for each category array element; and the host network server further configured to search a network site repository with the location and conflated query array, and to retrieve one or more network site keys within a proximity of the location, and to generate an associated relevancy probability calculated as a function of the number of retrieved one or more network site keys having associated categories that match those of the category arrays of the conflated query. 5. The mobile media communications system of claim 1 , further comprising: the host network server further configured to generate the location from the source identifier that may include one or more of a geolocation, a source IP address, a media access control device address, and other data. | 0.505085 |
9,984,069 | 11 | 14 | 11. A terminal, comprising an input apparatus and a display, wherein the input apparatus causes a processor to execute program codes stored in a non-transitory computer readable storage medium to perform functions, which configures the input apparatus to: receive an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the terminal; receive an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receive an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the terminal, wherein the second phrase or the second sentence follows after the first punctuation; detect a first location of a cursor on the display of the terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identify one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; use the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, query for a first next text or a first next phrase from a word library in a memory of the terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; output on the display of the terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detect a second location of the cursor on the display of the terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, wherein the second location of the cursor is positioned after the first punctuation; identify one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; use the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, and query for a second next text or a second next phrase from the word library in the memory of the terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and output on the display of the terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. | 11. A terminal, comprising an input apparatus and a display, wherein the input apparatus causes a processor to execute program codes stored in a non-transitory computer readable storage medium to perform functions, which configures the input apparatus to: receive an input of a plurality of words as a first phrase or a first sentence through key entries for displaying on the terminal; receive an input of a first punctuation, wherein the first punctuation follows after the first phrase or the first sentence; receive an input of a plurality of words as a second phrase or a second sentence through key entries for displaying on the terminal, wherein the second phrase or the second sentence follows after the first punctuation; detect a first location of a cursor on the display of the terminal, wherein the first location of the cursor is positioned after an end of the second phrase or the second sentence; identify one or more words within only the second phrase or the second sentence which is located between the first punctuation and the first location of the cursor; use the identified one or more words within only the second phrase or the second sentence as a first previous text or a first previous phrase, query for a first next text or a first next phrase from a word library in a memory of the terminal, wherein the first next text or the first next phrase is associated in context with the first previous text or the first previous phrase; output on the display of the terminal, the associated first next text or first next phrase which appends after the end of the second phrase or the second sentence; detect a second location of the cursor on the display of the terminal after the associated first next text or first next phrase is outputted, wherein the second location of the cursor is positioned before the first location of the cursor, wherein the second location of the cursor is positioned after the first punctuation; identify one or more words within only a third phrase or a third sentence which is located between the first punctuation and the second location of the cursor; use the identified one or more words within only the third phrase or the third sentence as a second previous text or a second previous phrase, and query for a second next text or a second next phrase from the word library in the memory of the terminal, wherein the second next text or the second next phrase is associated in context with the second previous text or the second previous phrase; and output on the display of the terminal, the associated second next text or second next phrase which appends after the end of the third phrase or the third sentence. 14. The terminal according to claim 11 , wherein in querying for the second next text or the second next phrase from the word library in the memory of the terminal, the input apparatus is configured to: query from the word library for all expressions and sentences comprising the second previous text or the second previous phrase, and use an expression or a sentence that exists in the found expressions and sentences but does not exist in the second previous text or the second previous phrase as the second next text or the second next phrase. | 0.580645 |
8,744,135 | 3 | 5 | 3. The computer readable medium of claim 2 further comprising a step of: attaching the multiple citation data structure to one of the plurality of formatted documents, wherein, when a portion of text is copied from the one of the plurality of formatted documents, corresponding multiple internal citations are included with the copied portion. | 3. The computer readable medium of claim 2 further comprising a step of: attaching the multiple citation data structure to one of the plurality of formatted documents, wherein, when a portion of text is copied from the one of the plurality of formatted documents, corresponding multiple internal citations are included with the copied portion. 5. The computer readable medium of claim 3 wherein the attaching step yields a searchable annotated formatted document. | 0.709756 |
9,177,016 | 12 | 15 | 12. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to: generate, at a social networking system, a structured query based on information received from a user, the structured query including a focal search object and a connected search object; store the structured query in association with the user; perform a first search on a social graph maintained by the social networking system to find one or more first objects on the social graph matching the structured query; update a list of links associated with the structured query to include links to the first objects; after a time interval, perform a second search on the social graph to find one or more second objects on the social graph matching the structured query, the second objects not included in the first objects; and update the list of links associated with the structured query to include links to the second objects. | 12. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to: generate, at a social networking system, a structured query based on information received from a user, the structured query including a focal search object and a connected search object; store the structured query in association with the user; perform a first search on a social graph maintained by the social networking system to find one or more first objects on the social graph matching the structured query; update a list of links associated with the structured query to include links to the first objects; after a time interval, perform a second search on the social graph to find one or more second objects on the social graph matching the structured query, the second objects not included in the first objects; and update the list of links associated with the structured query to include links to the second objects. 15. The non-transitory computer readable storage medium of claim 12 , wherein the instructions when executed by the computing device further cause the computing device to: present the first objects to the user after updating the list of links to include links to the first objects; and present the second objects to the user after updating the list of links to include links to the second objects. | 0.512285 |
8,892,992 | 1 | 5 | 1. A non-transitory machine readable medium storing a program which when executed by at least one processor defines structure for a document comprising a plurality of primitive elements, the program comprising sets of instructions for: defining an indirectly sorted first array that stores sorted indices of a second array of difference values, wherein the difference values indicate differences between sorted attribute values of different primitive elements, the primitive elements being defined in terms of the attribute values; using the indirectly sorted first array to generate a plurality of different partition sets at different distance scales for the plurality of primitive elements; from the plurality of partition sets, selecting an optimal partition set based on a set of optimization measures; and grouping the plurality of primitive elements using the optimal partition set in order to associate a subset of the primitive elements as a structured element in the document. | 1. A non-transitory machine readable medium storing a program which when executed by at least one processor defines structure for a document comprising a plurality of primitive elements, the program comprising sets of instructions for: defining an indirectly sorted first array that stores sorted indices of a second array of difference values, wherein the difference values indicate differences between sorted attribute values of different primitive elements, the primitive elements being defined in terms of the attribute values; using the indirectly sorted first array to generate a plurality of different partition sets at different distance scales for the plurality of primitive elements; from the plurality of partition sets, selecting an optimal partition set based on a set of optimization measures; and grouping the plurality of primitive elements using the optimal partition set in order to associate a subset of the primitive elements as a structured element in the document. 5. The non-transitory machine readable medium of claim 1 , wherein each different partition set divides the plurality of primitive elements into different subsets of primitive elements. | 0.681034 |
9,424,248 | 1 | 3 | 1. A method of monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising the steps of: performing a simple check on the text transcript for existence of a potential frustration precondition, the simple check includes checking a set of at least one table including a list of text-based signals to identify in the text transcript a text-based signal on the list of text-based signals; on condition that the potential frustration precondition is found, performing a first text analytics analysis on the text transcript to determine whether potential frustration is evidenced by the text transcript; and responsive to potential frustration being evidenced by the text transcript, taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a second text analytics analysis on the text transcript; wherein: the responsive action is designed to alleviate an occurrence of potential frustration for the second chat participant; the set of at least one table includes a user-specific table that is customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific table being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant; and the performing-a-simple-check step and the performing-a-first-text-analytics-analysis steps are performed by the computer system running under software control. | 1. A method of monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising the steps of: performing a simple check on the text transcript for existence of a potential frustration precondition, the simple check includes checking a set of at least one table including a list of text-based signals to identify in the text transcript a text-based signal on the list of text-based signals; on condition that the potential frustration precondition is found, performing a first text analytics analysis on the text transcript to determine whether potential frustration is evidenced by the text transcript; and responsive to potential frustration being evidenced by the text transcript, taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a second text analytics analysis on the text transcript; wherein: the responsive action is designed to alleviate an occurrence of potential frustration for the second chat participant; the set of at least one table includes a user-specific table that is customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific table being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant; and the performing-a-simple-check step and the performing-a-first-text-analytics-analysis steps are performed by the computer system running under software control. 3. The method of claim 1 wherein the simple check further includes checking for a threshold amount of repetition of the text-based signal in the text transcript, with the threshold amount of repetition being a frustration precondition. | 0.729263 |
7,590,936 | 12 | 13 | 12. A computer-implemented method for identifying one or more tagged data items proximate to a result of a search of an electronic document, comprising the steps of: completing the search of the electronic document; locating each result of the search within the electronic document; determining if one or more of the tagged data items are present in the electronic document within a distance from each search result using a proximity rule, wherein the distance comprises a location of the one or more tagged data items relative to each search result; identifying applicable tagged data items by determining whether the each of the tagged data items present in the electronic document should be associated with the one or more search results using grammatical semantic intelligence, the grammatical semantic intelligence comprising a rule that tagged data items that satisfy the proximity rule, with respect to the one or more search results, represent facts about search terms used in generating the search of the electronic document only when the search terms are proper nouns; displaying on a user interface at least a portion of the electronic document using the tagged data items; and removing a tag from a displayed item associated with the one or more search results by specifying in the user interface that the item should not be categorized, wherein the user interface comprises an on-object-user interface which receives a pointing action from a computer pointing device for pointing at the displayed item, the pointing action causing the generation of a menu for removing the tag in the on-object user interface. | 12. A computer-implemented method for identifying one or more tagged data items proximate to a result of a search of an electronic document, comprising the steps of: completing the search of the electronic document; locating each result of the search within the electronic document; determining if one or more of the tagged data items are present in the electronic document within a distance from each search result using a proximity rule, wherein the distance comprises a location of the one or more tagged data items relative to each search result; identifying applicable tagged data items by determining whether the each of the tagged data items present in the electronic document should be associated with the one or more search results using grammatical semantic intelligence, the grammatical semantic intelligence comprising a rule that tagged data items that satisfy the proximity rule, with respect to the one or more search results, represent facts about search terms used in generating the search of the electronic document only when the search terms are proper nouns; displaying on a user interface at least a portion of the electronic document using the tagged data items; and removing a tag from a displayed item associated with the one or more search results by specifying in the user interface that the item should not be categorized, wherein the user interface comprises an on-object-user interface which receives a pointing action from a computer pointing device for pointing at the displayed item, the pointing action causing the generation of a menu for removing the tag in the on-object user interface. 13. The method of claim 12 wherein the distance from each search result comprises the distance between a first paragraph mark and a second paragraph mark, wherein one or more of the search results are located between the first paragraph mark and the second paragraph mark. | 0.5 |
7,801,917 | 8 | 9 | 8. A data processing system comprising a processor; and a memory coupled with the processor for storing instructions which, when executed by the processor, cause the processing system to perform a process that includes intercepting, by a computer, an electronic document while the electronic document is being transmitted on a network by an entity, automatically identifying content within the electronic document as being potentially descriptive of an information focus of the entity, wherein the identifying the content comprises assigning a figure of merit to the content, and wherein the assigning the figure of merit to the content comprises determining a frequency with which the content occurs in collection of information associated with the entity, automatically prompting the entity to provide an authorization regarding the identified content in response to the content being automatically identified as potentially descriptive of an information focus of the entity, the authorization indicating whether the identified content is to be included in at least a particular portion of a profile of the entity, including the content within said at least a particular portion of the profile only if the entity provides the authorization, wherein the profile comprises a first portion and a second portion, wherein the first portion is a private portion of the profile and the second portion is a public portion of the profile, and wherein said including the identified content within said at least a particular portion of the profile only if the entity provides the authorization comprises including the identified content within the public portion of the profile. | 8. A data processing system comprising a processor; and a memory coupled with the processor for storing instructions which, when executed by the processor, cause the processing system to perform a process that includes intercepting, by a computer, an electronic document while the electronic document is being transmitted on a network by an entity, automatically identifying content within the electronic document as being potentially descriptive of an information focus of the entity, wherein the identifying the content comprises assigning a figure of merit to the content, and wherein the assigning the figure of merit to the content comprises determining a frequency with which the content occurs in collection of information associated with the entity, automatically prompting the entity to provide an authorization regarding the identified content in response to the content being automatically identified as potentially descriptive of an information focus of the entity, the authorization indicating whether the identified content is to be included in at least a particular portion of a profile of the entity, including the content within said at least a particular portion of the profile only if the entity provides the authorization, wherein the profile comprises a first portion and a second portion, wherein the first portion is a private portion of the profile and the second portion is a public portion of the profile, and wherein said including the identified content within said at least a particular portion of the profile only if the entity provides the authorization comprises including the identified content within the public portion of the profile. 9. The data processing system of claim 8 wherein the processor further indicates the content to the entity for authorization. | 0.601911 |
8,727,780 | 16 | 23 | 16. A method of creating and using a matrix for a mathematical research system, the method comprising: accessing a plurality of documents; analyzing each of the plurality of documents to identify any mathematical concepts expressed in each document, wherein the mathematical concepts are extracted from one or more algorithmic, linguistic, geometric, and graphic mathematical exercise representations; for each document including one or more mathematical concepts, tagging the documents with a corresponding one or more mathematical concept tags; creating two or more concept line items (CLI)s from the one or more mathematical concepts, wherein a CLI is a textual expression of a mathematical concept; defining interrelationships between the two or more CLIs, wherein each defined interrelationship includes one or more of a prerequisite to another CLI, a dependency on another CLI, or a lack of relationship to another CLI; assigning each defined interrelationship a relationship code; generating, by a computer processor, a matrix including the two or more CLIs and the relationship codes, wherein the relationship codes identify the defined interrelationships between the two or more CLIs, wherein the matrix includes one or more prerequisite and dependency interrelationships; storing the two or more CLIs and the generated mapping in one or more databases; creating an index relating each CLI to the corresponding documents; providing a search interface through which a user searches the database to identify documents related to one or more CLIs; and generating an educational curriculum from a search result, wherein the search interface accepts a search term provided by the user, and wherein the search interface accepts all of the following forms of search terms: text-based phrases, mathematical expressions expressed in documents, interrelationships, and concept ranges. | 16. A method of creating and using a matrix for a mathematical research system, the method comprising: accessing a plurality of documents; analyzing each of the plurality of documents to identify any mathematical concepts expressed in each document, wherein the mathematical concepts are extracted from one or more algorithmic, linguistic, geometric, and graphic mathematical exercise representations; for each document including one or more mathematical concepts, tagging the documents with a corresponding one or more mathematical concept tags; creating two or more concept line items (CLI)s from the one or more mathematical concepts, wherein a CLI is a textual expression of a mathematical concept; defining interrelationships between the two or more CLIs, wherein each defined interrelationship includes one or more of a prerequisite to another CLI, a dependency on another CLI, or a lack of relationship to another CLI; assigning each defined interrelationship a relationship code; generating, by a computer processor, a matrix including the two or more CLIs and the relationship codes, wherein the relationship codes identify the defined interrelationships between the two or more CLIs, wherein the matrix includes one or more prerequisite and dependency interrelationships; storing the two or more CLIs and the generated mapping in one or more databases; creating an index relating each CLI to the corresponding documents; providing a search interface through which a user searches the database to identify documents related to one or more CLIs; and generating an educational curriculum from a search result, wherein the search interface accepts a search term provided by the user, and wherein the search interface accepts all of the following forms of search terms: text-based phrases, mathematical expressions expressed in documents, interrelationships, and concept ranges. 23. The method of claim 16 wherein said matrix is an edge weight matrix and wherein said defined relationships are assigned weights. | 0.79375 |
7,613,731 | 76 | 77 | 76. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that generate a cognitively parsed file. | 76. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that generate a cognitively parsed file. 77. The computer system for presenting an electronic document of claim 76 wherein the computer program product further comprises program instructions that determine a number of characters in each cognitive cluster and assign a character count value to each cognitive cluster. | 0.556452 |
7,747,980 | 7 | 8 | 7. The method of claim 1 , wherein the software application package format includes: a signature portion; a keywords portion; a parts portion; a part table portion; and a trailer portion containing the offset of the part table from the beginning of the package file. | 7. The method of claim 1 , wherein the software application package format includes: a signature portion; a keywords portion; a parts portion; a part table portion; and a trailer portion containing the offset of the part table from the beginning of the package file. 8. The method of claim 7 , wherein the parts portion further comprises: a renditions table having renditions table records that includes: (i) information about linear segments within the main data part and a main code part needed by the rendition that is referenced by a part ID in that record, and (ii) the starting code image address to begin execution for that rendition. | 0.578829 |
9,570,065 | 13 | 14 | 13. The system of claim 12 , wherein the calculating is performed based at least in part on a transformation from a second group of speech segments having the second speaking style to a first group of speech segments having the desired speaking style, wherein the second group of speech segments comprises the second speech segment, wherein the first and second groups of speech segments are associated with a same phonetic context. | 13. The system of claim 12 , wherein the calculating is performed based at least in part on a transformation from a second group of speech segments having the second speaking style to a first group of speech segments having the desired speaking style, wherein the second group of speech segments comprises the second speech segment, wherein the first and second groups of speech segments are associated with a same phonetic context. 14. The system of claim 13 , wherein the first group of speech segments is represented by a first statistical model and the second group of speech segments is represented by a second statistical model, and wherein calculating the value comprises: using the transformation to transform the second statistical model to obtain a transformed statistical model; and calculating the value as a distance between the transformed second statistical model and the first statistical model. | 0.5 |
9,043,198 | 1 | 5 | 1. A method comprising: receiving a text item, the text item including one or more terms; determining a plurality of text strings, each text string including a matching portion and one or more suffixes, wherein the matching portion matches the text item, and the one or more suffixes are located after the matching portion; ranking the one or more suffixes based on a credibility score of each suffix and a frequency score of each suffix, the credibility score of a suffix indicating an estimated credibility of a source of the text string including the suffix, the frequency score of a suffix indicating an estimated frequency of appearance of the suffix, wherein the frequency score of the suffix is calculated based at least in part on a function measuring partial overlaps between at least a portion of the suffix and one or more other suffixes; and providing a group of the one or more suffixes that includes a highest ranking suffix for display as a suggestion for completing a sentence starting from the text item. | 1. A method comprising: receiving a text item, the text item including one or more terms; determining a plurality of text strings, each text string including a matching portion and one or more suffixes, wherein the matching portion matches the text item, and the one or more suffixes are located after the matching portion; ranking the one or more suffixes based on a credibility score of each suffix and a frequency score of each suffix, the credibility score of a suffix indicating an estimated credibility of a source of the text string including the suffix, the frequency score of a suffix indicating an estimated frequency of appearance of the suffix, wherein the frequency score of the suffix is calculated based at least in part on a function measuring partial overlaps between at least a portion of the suffix and one or more other suffixes; and providing a group of the one or more suffixes that includes a highest ranking suffix for display as a suggestion for completing a sentence starting from the text item. 5. The method of claim 1 , wherein each suffix comprises one or more words. | 0.807692 |
8,161,112 | 23 | 24 | 23. An apparatus for delivering dynamic media content to collaborators, the apparatus comprising: a dynamic media server coupled for data communications with a client coupled for data communication with a context server coupled for data communications with an action engine; wherein the dynamic media server comprises a module of automated computing machinery that provides collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; the client comprises a module of automated computing machinery that acquires from an environmental sensor data representing the client's environmental condition and stores the data representing the client's environmental condition in the context server in a data structure comprising a dynamic client context for the client; the context server comprises a module of automated computing machinery that detects an event in dependence upon the dynamic client context; and the action engine comprises a module of automated computing machinery that identifies one or more collaborators in dependence upon the dynamic client context and the event, selects from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators and transmits the selected structural element to the collaborator. | 23. An apparatus for delivering dynamic media content to collaborators, the apparatus comprising: a dynamic media server coupled for data communications with a client coupled for data communication with a context server coupled for data communications with an action engine; wherein the dynamic media server comprises a module of automated computing machinery that provides collaborative event media content, wherein the collaborative event media content further comprises a grammar and a structured document, said structured document comprising a plurality of classified structural elements; the client comprises a module of automated computing machinery that acquires from an environmental sensor data representing the client's environmental condition and stores the data representing the client's environmental condition in the context server in a data structure comprising a dynamic client context for the client; the context server comprises a module of automated computing machinery that detects an event in dependence upon the dynamic client context; and the action engine comprises a module of automated computing machinery that identifies one or more collaborators in dependence upon the dynamic client context and the event, selects from the structured document a classified structural element from among the plurality of classified structural elements based upon an event type and a collaborator classification associated with a collaborator among the one or more collaborators and transmits the selected structural element to the collaborator. 24. The apparatus of claim 23 wherein the dynamic client context includes network addresses for environmental sensors for the client and wherein the client polls the environmental sensors to acquire data representing the client's environmental condition. | 0.817003 |
7,912,854 | 1 | 4 | 1. A computer-implemented method of mining address data to locate a preferred address for each of a plurality of parcels, comprising: maintaining a package-level detail database of active shipment records, each active shipment record comprising an active tracking number, an active ship-to address, and an active delivery pattern code; maintaining an electronic archive of delivery records, each delivery record comprising a past tracking number, a past ship-to address, a past delivery pattern code, and a stop identifier; receiving address indicia data associated with a current parcel; assigning a mining key to said current parcel, said mining key comprising a parcel tracking number and a current delivery pattern code related to said address indicia; comparing said mining key to said package-level detail database and said archive by having one or more computer components execute logic for: (a) retrieving from said archive those select delivery records having a past delivery pattern code that matches said current delivery pattern code, each of said select delivery records having a select past ship-to address; (b) retrieving from said package-level detail database those select active shipment records having an active ship-to address that matches any said select past ship-to address in said select delivery records; building a set of mined data comprising said select delivery records and said select active shipment records; prioritizing said set of mined data in order of the records most closely associated with said mining key, such that a preferred address related to said mining key occurs first, by having said one or more computer components execute logic for: (a) replacing one or more sequence values in a plurality of ship-to address records stored in said set of mined data with a representative symbol; (b) clustering together those said ship-to address records having the same stop identifier; and (c) clustering together those said ship-to address records having the same delivery pattern code; and assigning said preferred address to said current parcel for delivery. | 1. A computer-implemented method of mining address data to locate a preferred address for each of a plurality of parcels, comprising: maintaining a package-level detail database of active shipment records, each active shipment record comprising an active tracking number, an active ship-to address, and an active delivery pattern code; maintaining an electronic archive of delivery records, each delivery record comprising a past tracking number, a past ship-to address, a past delivery pattern code, and a stop identifier; receiving address indicia data associated with a current parcel; assigning a mining key to said current parcel, said mining key comprising a parcel tracking number and a current delivery pattern code related to said address indicia; comparing said mining key to said package-level detail database and said archive by having one or more computer components execute logic for: (a) retrieving from said archive those select delivery records having a past delivery pattern code that matches said current delivery pattern code, each of said select delivery records having a select past ship-to address; (b) retrieving from said package-level detail database those select active shipment records having an active ship-to address that matches any said select past ship-to address in said select delivery records; building a set of mined data comprising said select delivery records and said select active shipment records; prioritizing said set of mined data in order of the records most closely associated with said mining key, such that a preferred address related to said mining key occurs first, by having said one or more computer components execute logic for: (a) replacing one or more sequence values in a plurality of ship-to address records stored in said set of mined data with a representative symbol; (b) clustering together those said ship-to address records having the same stop identifier; and (c) clustering together those said ship-to address records having the same delivery pattern code; and assigning said preferred address to said current parcel for delivery. 4. The method of claim 1 , wherein said step of assigning said preferred address to said current parcel for delivery comprises: presenting said set of mined data to an electronic address database administrator; and receiving a selection of said preferred address by said administrator. | 0.816129 |
9,959,324 | 1 | 5 | 1. A method to search for at least one relationship pattern in a plurality of runtime artifacts, the method comprising: detecting at least one data manipulation statement in the plurality of artifacts; extracting at least one relationship clause from the detected at least one data manipulation statement; parsing the extracted at least one relationship clause; generating at least one normalized syntax tree based on the parsed at least one relationship clause; and performing a classification and a snippet discovery on the generated at least one normalized syntax tree. | 1. A method to search for at least one relationship pattern in a plurality of runtime artifacts, the method comprising: detecting at least one data manipulation statement in the plurality of artifacts; extracting at least one relationship clause from the detected at least one data manipulation statement; parsing the extracted at least one relationship clause; generating at least one normalized syntax tree based on the parsed at least one relationship clause; and performing a classification and a snippet discovery on the generated at least one normalized syntax tree. 5. The method of claim 1 , wherein the plurality of runtime artifacts is associated with a data source comprising at least one of an ETL, a database view, a database SQL procedure, a batch file, a plurality of reporting tool metadata, a metadata server, a program, and a script. | 0.5 |
8,533,621 | 1 | 14 | 1. A method of using a graphical display for communication based on character recognition between a sender and a receiver, wherein said graphical display is configured from a set of characters associated with a predetermined language and said graphical display enables expeditious discovery of said sender-selected character by said receiver, said graphical display comprising: a plurality of distinct quadrants, wherein said plurality of distinct quadrants each having an array of coordinate locations, wherein each said coordinate location possesses a location value based on the effort required to reach each said coordinate location when said receiver utilizes a top-left based scanning routine, and each said coordinate location is populated with a unique character selected from said set of characters, wherein each said unique character possesses a character value substantially derived from a set of character guidelines, wherein said guidelines provides a character ranking system primarily directed to enable early character detection and selection, said character ranking system includes assigning a higher rank to said unique characters having a greater use frequency within said predetermined language, and said coordinate locations with a higher ranked said location value are substantially populated with a corresponding said unique characters having higher ranked said character values, wherein said higher ranked said coordinate locations are substantially populated with the higher ranked said unique characters, said method comprising the steps of: (a) having a communication that can be conveyed using a written language that a sender or receiver wishes to communicate, wherein the communication is comprised of words constructed from a plurality of characters; said communication commences with the identification of a first letter corresponding to a first word; (b) positioning the graphical display such that the display is visible to both the sender and the receiver; (c) initiating a sequential scan of quadrants located on the graphical display, using a top-left based scanning routine performed by the receiver; (d) observing the sender for a selection motion, thereby communicating to the receiver the particular quadrant containing the first letter of the first word of the communication of step(a); (e) initiating sequential scan of characters contained within the selected quadrant in step(d), using a top-left based scanning routine performed by the receiver; (f) observing the sender for a selection motion, thereby communicating to the receiver the first character of the first word of step(a); and noting the selected first character; (g) repeating steps (c) through (f) wherein each subsequent cycle provides additional characters, thereby enabling the completion of words that shape the foundation of the communication of step(a). | 1. A method of using a graphical display for communication based on character recognition between a sender and a receiver, wherein said graphical display is configured from a set of characters associated with a predetermined language and said graphical display enables expeditious discovery of said sender-selected character by said receiver, said graphical display comprising: a plurality of distinct quadrants, wherein said plurality of distinct quadrants each having an array of coordinate locations, wherein each said coordinate location possesses a location value based on the effort required to reach each said coordinate location when said receiver utilizes a top-left based scanning routine, and each said coordinate location is populated with a unique character selected from said set of characters, wherein each said unique character possesses a character value substantially derived from a set of character guidelines, wherein said guidelines provides a character ranking system primarily directed to enable early character detection and selection, said character ranking system includes assigning a higher rank to said unique characters having a greater use frequency within said predetermined language, and said coordinate locations with a higher ranked said location value are substantially populated with a corresponding said unique characters having higher ranked said character values, wherein said higher ranked said coordinate locations are substantially populated with the higher ranked said unique characters, said method comprising the steps of: (a) having a communication that can be conveyed using a written language that a sender or receiver wishes to communicate, wherein the communication is comprised of words constructed from a plurality of characters; said communication commences with the identification of a first letter corresponding to a first word; (b) positioning the graphical display such that the display is visible to both the sender and the receiver; (c) initiating a sequential scan of quadrants located on the graphical display, using a top-left based scanning routine performed by the receiver; (d) observing the sender for a selection motion, thereby communicating to the receiver the particular quadrant containing the first letter of the first word of the communication of step(a); (e) initiating sequential scan of characters contained within the selected quadrant in step(d), using a top-left based scanning routine performed by the receiver; (f) observing the sender for a selection motion, thereby communicating to the receiver the first character of the first word of step(a); and noting the selected first character; (g) repeating steps (c) through (f) wherein each subsequent cycle provides additional characters, thereby enabling the completion of words that shape the foundation of the communication of step(a). 14. The method of claim 1 , wherein each distinct quadrant further includes a quadrant background and a quadrant perimeter; and at least one said distinct quadrant further includes a border disposed about at least a portion of its said perimeter, wherein said border possesses a contrasting appearance for substantially differentiating each said distinct quadrant from each other, whereby a clear, visible distinction among each said quadrant helps remove ambiguity as to which quadrant is being referred to during use. | 0.5 |
8,751,230 | 1 | 6 | 1. A method for automatically generating a vocabulary entry from input acoustic data, said method comprising: performing, by a computer processor, a vocabulary entry type-specific acoustic phonetic transcription of the input acoustic data and a classification of vocabulary entry types based on phonetic structure, wherein the classification of vocabulary entries is carried out in accordance with a number of predetermined types; performing, by the computer processor, a vocabulary entry type-specific phoneme-to-grapheme conversion, to derive the respective vocabulary entries comprising a pair of the phonetic transcription of the input acoustic data and its grapheme form; and providing a select one of the vocabulary entries to a database for use in a speech processing application; wherein the classification of vocabulary entries is carried out together with the vocabulary entry type-specific acoustic phonetic transcription in a combined step. | 1. A method for automatically generating a vocabulary entry from input acoustic data, said method comprising: performing, by a computer processor, a vocabulary entry type-specific acoustic phonetic transcription of the input acoustic data and a classification of vocabulary entry types based on phonetic structure, wherein the classification of vocabulary entries is carried out in accordance with a number of predetermined types; performing, by the computer processor, a vocabulary entry type-specific phoneme-to-grapheme conversion, to derive the respective vocabulary entries comprising a pair of the phonetic transcription of the input acoustic data and its grapheme form; and providing a select one of the vocabulary entries to a database for use in a speech processing application; wherein the classification of vocabulary entries is carried out together with the vocabulary entry type-specific acoustic phonetic transcription in a combined step. 6. The method according to claim 1 , wherein the vocabulary entries are classified according to four types, namely vocabulary entries fitting to a given language morphology; vocabulary entries fitting to morphology of at least one other supported language; vocabulary entries which do not fit to any supported language morphology but are normally pronounced; and vocabulary entries which do not fit to any supported language morphology and are pronounced by spelling. | 0.5 |
9,014,362 | 17 | 18 | 17. A method according to claim 15 , wherein the response comprises one or more of reply text messages and reply speech utterances. | 17. A method according to claim 15 , wherein the response comprises one or more of reply text messages and reply speech utterances. 18. A method according to claim 17 , further comprising: converting the text messages of the agent to synthesized speech utterances before providing the response to the caller. | 0.5 |
9,064,005 | 10 | 15 | 10. A processor implemented system, comprising: a first module executing on a processor and configured to, for at least one search term received from a user, automatically determine additional search terms related to the at least one search term at least in part by performing a probability calculation determining a relevance of the additional search terms to the at least one search term using a Simple Bayes probability model developed from analysis of at least one known document, wherein the analysis involves generating a plurality of overlapping vectors corresponding to a plurality of windows centered on a plurality of respective words of the at least one known document by counting a number of occurrences of the plurality of respective words within each window, wherein each respective word on which a window is centered is excluded from a vector generated corresponding to the window; and a second module configured to provide at least one of the additional search terms to the user. | 10. A processor implemented system, comprising: a first module executing on a processor and configured to, for at least one search term received from a user, automatically determine additional search terms related to the at least one search term at least in part by performing a probability calculation determining a relevance of the additional search terms to the at least one search term using a Simple Bayes probability model developed from analysis of at least one known document, wherein the analysis involves generating a plurality of overlapping vectors corresponding to a plurality of windows centered on a plurality of respective words of the at least one known document by counting a number of occurrences of the plurality of respective words within each window, wherein each respective word on which a window is centered is excluded from a vector generated corresponding to the window; and a second module configured to provide at least one of the additional search terms to the user. 15. The processor implemented system of claim 10 , wherein the plurality of windows comprises a respective window centered on each word of the at least one known document. | 0.5 |
7,523,036 | 24 | 32 | 24. A text-to-speech synthesis apparatus comprising: a memory for storing phoneme data of a plurality of speaker voices; a selecting section for selecting any one of said plurality of speaker voices; a search section for searching said memory for the phoneme data of the speaker voices selected by said selecting section; a text-to-speech synthesis processing section for linking said phoneme data of said speaker voices retrieved by said search section to convert script data into a synthetic speech; a storage section for accumulating said synthetic speech converted from said script data on the basis of the phoneme data of said plurality of speaker voices; and a reproducing section for retrieving said synthetic speech of said speaker voices selected by said selecting section and reproducing said synthetic speech, wherein said text-to-speech synthesis processing means can convert said script into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data. | 24. A text-to-speech synthesis apparatus comprising: a memory for storing phoneme data of a plurality of speaker voices; a selecting section for selecting any one of said plurality of speaker voices; a search section for searching said memory for the phoneme data of the speaker voices selected by said selecting section; a text-to-speech synthesis processing section for linking said phoneme data of said speaker voices retrieved by said search section to convert script data into a synthetic speech; a storage section for accumulating said synthetic speech converted from said script data on the basis of the phoneme data of said plurality of speaker voices; and a reproducing section for retrieving said synthetic speech of said speaker voices selected by said selecting section and reproducing said synthetic speech, wherein said text-to-speech synthesis processing means can convert said script into a synthetic speech including at least said two speaker voices including said speaker voice corresponding to said speaker voice identification data. 32. The text-to-speech synthesis apparatus according to claim 24 , further comprising a communication section for receiving said script data via a network. | 0.830786 |
9,196,002 | 7 | 8 | 7. A method, including comprising: accessing, by a context module including at least one processor, data identifying a context in relation to a category of merchant offerings in a network-based marketplace, the context being associated with a user of the network; processing information from a plurality of other users of the network regarding the category of merchant offerings to determine attributes relevant to the context; receiving input from the user including a selection of at least one of the attributes; and generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute and according to one of one or more ratings associated with buyers or sellers of products or services included in the result data. | 7. A method, including comprising: accessing, by a context module including at least one processor, data identifying a context in relation to a category of merchant offerings in a network-based marketplace, the context being associated with a user of the network; processing information from a plurality of other users of the network regarding the category of merchant offerings to determine attributes relevant to the context; receiving input from the user including a selection of at least one of the attributes; and generating result data by retrieving data associated with the context and filtering the retrieved data according to the at least one selected attribute and according to one of one or more ratings associated with buyers or sellers of products or services included in the result data. 8. The method of claim 7 wherein the result data includes at least one from a group consisting of: a review list, a recommendation list, research from other users, research from the user, a seller list, and a buyer list. | 0.5 |
9,910,924 | 1 | 4 | 1. A method of searching online social profiles of real-world entities on an online social network, the method including: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities. | 1. A method of searching online social profiles of real-world entities on an online social network, the method including: specifying one or more core entity attributes as a first search attribute set for use in searching an online social network; electronically receiving, responsive to searching the online social network based on the first search attribute set, entity reflections that include supplemental entity attributes for real-world entities; and using a combination of the core entity attributes and one or more supplemental entity attributes to electronically receive more entity reflections that include meta entity attributes for the real-world entities. 4. The method of claim 1 , wherein at least some of the supplemental entity attributes are narrower than the first search attribute set. | 0.708155 |
9,106,979 | 1 | 3 | 1. A method for associating a second media content item with a first media content item, wherein the first media content item comprises a first audio/video content and the second media content item comprises a second audio/video content, the method comprising: receiving, by a recommender system, a first map of a first delimited segment of the first media content item, the first map comprising a first sentiment-state keyword associated with the first segment and a first temporal delimitation of the first segment; receiving, by the recommender system, a second map of a second delimited segment of the second media content item, the second map comprising a second sentiment-state keyword associated with the second segment and a second temporal delimitation of the second segment; comparing, by the recommender system, the first and second maps; and if a result of the comparison is a favorable result for a temporal extent associated with the first and second temporal delimitations, then associating, by the recommender system, the second media content item with the first media content item. | 1. A method for associating a second media content item with a first media content item, wherein the first media content item comprises a first audio/video content and the second media content item comprises a second audio/video content, the method comprising: receiving, by a recommender system, a first map of a first delimited segment of the first media content item, the first map comprising a first sentiment-state keyword associated with the first segment and a first temporal delimitation of the first segment; receiving, by the recommender system, a second map of a second delimited segment of the second media content item, the second map comprising a second sentiment-state keyword associated with the second segment and a second temporal delimitation of the second segment; comparing, by the recommender system, the first and second maps; and if a result of the comparison is a favorable result for a temporal extent associated with the first and second temporal delimitations, then associating, by the recommender system, the second media content item with the first media content item. 3. The method of claim 1 wherein the recommender system is selected from the group consisting of: a set-top box, a personal communications device, a mobile telephone, a personal digital assistant, a personal computer, a tablet computer, a gaming console, a head-end server, a server, and a plurality of servers. | 0.739531 |
7,917,363 | 1 | 10 | 1. A process for estimating the speech recognition accuracy of a dialog system, including steps executed by a computer system comprising: generating a grammar from a plurality of example phrases; determining respective probabilities for correctly identifying words of an input phrase with corresponding words of said grammar; and generating a probability for correctly recognizing said input phrase by multiplying said respective probabilities. | 1. A process for estimating the speech recognition accuracy of a dialog system, including steps executed by a computer system comprising: generating a grammar from a plurality of example phrases; determining respective probabilities for correctly identifying words of an input phrase with corresponding words of said grammar; and generating a probability for correctly recognizing said input phrase by multiplying said respective probabilities. 10. A process as claimed in claim 1 , including generating an estimate for the speech recognition accuracy of said dialog system from the probabilities for correctly recognizing each of a plurality of input phrases. | 0.677177 |
9,110,950 | 18 | 20 | 18. A computer program product to determine individuals having target skills, the computer program product comprising: a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to: receive, by an application and from a requesting entity, a request to identify individuals having a target skill specified in the request, wherein the application includes a first layer representing a body of knowledge in a data store, wherein the request comprises a query composed according to a query language not supported by the first layer; reformulate the query into a different query language supported by the first layer; identify, by accessing the data store using the reformulated query: (i) a first individual having the specified skill and (ii) a first characterization of a skill level of the first individual in the specified skill, wherein the first characterization is stored in the data store and is determined based on input from a plurality of individuals; and upon determining that a count of the plurality of individuals is less than a predefined count of individuals characterizing the skill level of the first individual, confirm the skill level of the first individual by requesting at least a second individual to provide a second characterization of the skill level of the first individual in the specified skill, wherein the second individual is not included in the plurality of individuals. | 18. A computer program product to determine individuals having target skills, the computer program product comprising: a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to: receive, by an application and from a requesting entity, a request to identify individuals having a target skill specified in the request, wherein the application includes a first layer representing a body of knowledge in a data store, wherein the request comprises a query composed according to a query language not supported by the first layer; reformulate the query into a different query language supported by the first layer; identify, by accessing the data store using the reformulated query: (i) a first individual having the specified skill and (ii) a first characterization of a skill level of the first individual in the specified skill, wherein the first characterization is stored in the data store and is determined based on input from a plurality of individuals; and upon determining that a count of the plurality of individuals is less than a predefined count of individuals characterizing the skill level of the first individual, confirm the skill level of the first individual by requesting at least a second individual to provide a second characterization of the skill level of the first individual in the specified skill, wherein the second individual is not included in the plurality of individuals. 20. The computer program product of claim 18 , wherein the query is reformulated by a semantic software component including an Artificial Intelligence (AI) engine, into a reformulated query having a predetermined syntax. | 0.844633 |
9,081,919 | 9 | 13 | 9. The method of claim 1 , wherein the knowledge database stores information related to process sensitivity, design information including type of hotspots and width, location of pattern in mask, pattern type or identification, and mask simulation information. | 9. The method of claim 1 , wherein the knowledge database stores information related to process sensitivity, design information including type of hotspots and width, location of pattern in mask, pattern type or identification, and mask simulation information. 13. The method of claim 9 , wherein the knowledge database further stores information comprising pattern matching results and layout profiled results, wherein the pattern matching results comprise marginal or critical patterns which are detected from each design, and wherein the layout profiled results comprise one or more design feature of manufacturing interest. | 0.5 |
10,146,995 | 12 | 18 | 12. An information processing device comprising: a communicator configured to communicate with a printer; a controller; and storage storing a program; the controller reading the program from the storage and executing steps including: receiving print information from the printer, the print information being text data written as text; deconstructing the text data and generating multiple words; acquiring keyword information identifying a keyword, and relation information identifying a relationship between the keyword information and a word to detect; and detecting from the multiple words, based on the keyword information and the relation information, the word to detect. | 12. An information processing device comprising: a communicator configured to communicate with a printer; a controller; and storage storing a program; the controller reading the program from the storage and executing steps including: receiving print information from the printer, the print information being text data written as text; deconstructing the text data and generating multiple words; acquiring keyword information identifying a keyword, and relation information identifying a relationship between the keyword information and a word to detect; and detecting from the multiple words, based on the keyword information and the relation information, the word to detect. 18. The information processing device described in claim 12 , wherein: the information processing device and the printer are in a server-client relationship. | 0.908615 |
9,690,847 | 7 | 8 | 7. The computer-implemented method of claim 6 further comprising for all matching content items located, conducting an auction to determine which matching content item to use when providing the matching content item. | 7. The computer-implemented method of claim 6 further comprising for all matching content items located, conducting an auction to determine which matching content item to use when providing the matching content item. 8. The computer-implemented method of claim 7 further comprising summing scores for all keywords associated with a content item in the inventory, comparing the sum to a first threshold, and not qualifying a content item for inclusion in the auction when the first threshold is not met. | 0.5 |
9,047,070 | 12 | 13 | 12. The computer program product of claim 1 , wherein the custom object relates to a component of a user interface. | 12. The computer program product of claim 1 , wherein the custom object relates to a component of a user interface. 13. The computer program product of claim 12 , wherein the at least one aspect of the application implements the component of the user interface. | 0.5 |
6,029,043 | 17 | 22 | 17. A computer-aided group-learning method for more than one user to work on a subject, the method comprising the steps of: setting a duration of time for users to communicate among themselves to allow them to work on materials on the subject; starting a dialogue session for users to communicate in an area related to the subject; stopping the dialogue session approximately at or before the end of the duration of time; and monitoring at least one user's input during the dialogue session so as to have the monitored input available for analysis; wherein based on the analysis, the method further comprises the step of guiding at least one user back to the subject in the dialogue session when one or more users have been distracted from the subject for a duration of time; such that the dialogue session provides an interactive environment to help the users learn. | 17. A computer-aided group-learning method for more than one user to work on a subject, the method comprising the steps of: setting a duration of time for users to communicate among themselves to allow them to work on materials on the subject; starting a dialogue session for users to communicate in an area related to the subject; stopping the dialogue session approximately at or before the end of the duration of time; and monitoring at least one user's input during the dialogue session so as to have the monitored input available for analysis; wherein based on the analysis, the method further comprises the step of guiding at least one user back to the subject in the dialogue session when one or more users have been distracted from the subject for a duration of time; such that the dialogue session provides an interactive environment to help the users learn. 22. A computer-aided group-learning system as recited in claim 17 further comprising the step of restricting one user from communicating with any other users. | 0.700758 |
10,043,088 | 19 | 20 | 19. A method for image quality scoring of an image from a medical scanner, the method comprising: generating, by the medical scanner, the image representing a patient, the image having a level of artifacts due to the generating by the medical scanner; determining, by a machine, a probability map of artifacts as a function of location for the image with a deep generative machine-learnt model; assigning, by the machine, a quality score for the image with application of the probability map to a discriminative machine-learnt classifier, the probability map comprising a first input vector and features of the image comprising a second input vector; and transmitting the quality score for the image of the patient. | 19. A method for image quality scoring of an image from a medical scanner, the method comprising: generating, by the medical scanner, the image representing a patient, the image having a level of artifacts due to the generating by the medical scanner; determining, by a machine, a probability map of artifacts as a function of location for the image with a deep generative machine-learnt model; assigning, by the machine, a quality score for the image with application of the probability map to a discriminative machine-learnt classifier, the probability map comprising a first input vector and features of the image comprising a second input vector; and transmitting the quality score for the image of the patient. 20. The method of claim 19 wherein the discriminative machine-learnt classifier comprises a deep learnt classifier, the second input vector learned training images and the first input vector learned from training probability maps. | 0.5 |
8,032,860 | 1 | 21 | 1. A method for editing a source code file, comprising: modifying the source code file using a language-independent source code editor, wherein the language-independent source code editor does not include a language-specific lexical analyzer or parser; sending a change notification to an extensible multi-language compiler framework identifying a changed file, changed text, and type of change, wherein the editor communicates to the compiler framework using language-independent metadata, and wherein the compiler framework provides a stream of token nodes, supports mixing and nesting of languages within a source file, and provides the editor with information about the source file, comprising signatures of classes defined by the source file, errors found in the source file, stacks of nested languages at any point in the source file, and information exposed by any language; retokenizing the source code file and updating token and node information; enqueueing a task for the extensible multi-language compiler framework to complete compilation in a background thread; repainting a screen giving immediate feedback to a user; and emptying enqueued tasks and completing remaining steps in the background thread; wherein the extensible multi-language compiler framework has error correction in code-generation, permitting the user to run code even if there is an error in the code; wherein a thread pool allows compilation of multiple files to be performed in parallel; wherein a type cache contains signatures for classes. | 1. A method for editing a source code file, comprising: modifying the source code file using a language-independent source code editor, wherein the language-independent source code editor does not include a language-specific lexical analyzer or parser; sending a change notification to an extensible multi-language compiler framework identifying a changed file, changed text, and type of change, wherein the editor communicates to the compiler framework using language-independent metadata, and wherein the compiler framework provides a stream of token nodes, supports mixing and nesting of languages within a source file, and provides the editor with information about the source file, comprising signatures of classes defined by the source file, errors found in the source file, stacks of nested languages at any point in the source file, and information exposed by any language; retokenizing the source code file and updating token and node information; enqueueing a task for the extensible multi-language compiler framework to complete compilation in a background thread; repainting a screen giving immediate feedback to a user; and emptying enqueued tasks and completing remaining steps in the background thread; wherein the extensible multi-language compiler framework has error correction in code-generation, permitting the user to run code even if there is an error in the code; wherein a thread pool allows compilation of multiple files to be performed in parallel; wherein a type cache contains signatures for classes. 21. The method of claim 1 , wherein a file compiler is used to perform compilation of a single source file. | 0.886892 |
9,413,780 | 3 | 4 | 3. The method of claim 1 comprising: determining a vulnerability score for the candidate security vulnerability of the particular network under test that is received from the particular researcher, wherein the vulnerability score indicates a relative importance of the candidate security vulnerability; mapping the vulnerability score to a particular award that is within a range of a minimum award value and a maximum award value that are associated in the taxonomy with an identifier of the candidate security vulnerability; based upon the mapping, determining and providing the particular award. | 3. The method of claim 1 comprising: determining a vulnerability score for the candidate security vulnerability of the particular network under test that is received from the particular researcher, wherein the vulnerability score indicates a relative importance of the candidate security vulnerability; mapping the vulnerability score to a particular award that is within a range of a minimum award value and a maximum award value that are associated in the taxonomy with an identifier of the candidate security vulnerability; based upon the mapping, determining and providing the particular award. 4. The method of claim 3 wherein the particular award is a fee. | 0.646067 |
8,559,695 | 1 | 7 | 1. A method of using a U.S. currency processing device in a find mode to detect one or more find bills, a U.S. currency bill having been designated as a find bill in response to a selectable find bill element having been selected, the method comprising: receiving an input to cause the currency processing device to operate in a find mode; receiving U.S. currency bills in an input receptacle of the currency processing device; transporting the U.S. currency bills along a transport path in a serial fashion from the input receptacle, past an image scanner, to one or more output receptacles; imaging each of the U.S. currency bills with the image scanner to produce image data, the image data associated with each U.S. currency bill being reproducible as a visually readable image of at least a portion of a respective U.S. currency bill; extracting a serial number from the image data for each of the transported U.S. currency bills; denominating each of the transported U.S. currency bills; determining whether each of the transported U.S. currency bills is a find bill, a find bill having a serial number and a denomination stored in a find bill queue; and detecting one or more find bills. | 1. A method of using a U.S. currency processing device in a find mode to detect one or more find bills, a U.S. currency bill having been designated as a find bill in response to a selectable find bill element having been selected, the method comprising: receiving an input to cause the currency processing device to operate in a find mode; receiving U.S. currency bills in an input receptacle of the currency processing device; transporting the U.S. currency bills along a transport path in a serial fashion from the input receptacle, past an image scanner, to one or more output receptacles; imaging each of the U.S. currency bills with the image scanner to produce image data, the image data associated with each U.S. currency bill being reproducible as a visually readable image of at least a portion of a respective U.S. currency bill; extracting a serial number from the image data for each of the transported U.S. currency bills; denominating each of the transported U.S. currency bills; determining whether each of the transported U.S. currency bills is a find bill, a find bill having a serial number and a denomination stored in a find bill queue; and detecting one or more find bills. 7. The method of claim 1 , wherein each U.S. currency bill has a wide edge, and wherein the act of transporting comprises transporting each U.S. currency bill in a wide-edge leading manner. | 0.6625 |
8,356,036 | 1 | 8 | 1. A computer system comprising: a processor; and memory coupled to the processor and having stored therein instructions that, if executed by the computer system, cause the computer system to perform operations comprising: providing, in a database, a plurality of entity table types relevant to a domain type, wherein each entity table type includes a respective entity table name field and at least one respective data item field; populating the respective entity table name fields and the respective data item fields by automatically: extracting a plurality of data items from a plurality of data sources; determining respective confidence values for the extracted data items based on a plurality of pre-determined confidence values, wherein the pre-determined confidence values, wherein a respective predetermined confidence value is provided for each respective entity table name and each respective data item according to which data source of the plurality of data sources provided the respective entity table name and the respective data item; and integrating the extracted data items into respective entity table name fields and data item fields based on the respective confidence values for the extracted data items; determining relationship types between at least some data items of the plurality of data items that are integrated into a plurality of tables in the database, wherein the relationship types are based on respective data sources from which the data items have been extracted, the relationship types including at least two of the following: a first relationship type, a second relationship type, a third relationship type, and a fourth relationship type, wherein: the first relationship type is between first and second data items extracted from a first structured data source, the second relationship type is between data items extracted from different structured data sources, wherein the second relationship type is based on a plurality of respective first relationship types, the third relationship type is between a data item extracted from a second structured data source, and an entity table including, as entity table data items, attributes about a first unstructured data source, and wherein the data item extracted from the second structured data source is mentioned in the first unstructured data source, and the fourth relationship type is between two data items that: have been integrated from different structured data sources, and are both mentioned in a second unstructured data source; and storing the relationship types in a computer system memory. | 1. A computer system comprising: a processor; and memory coupled to the processor and having stored therein instructions that, if executed by the computer system, cause the computer system to perform operations comprising: providing, in a database, a plurality of entity table types relevant to a domain type, wherein each entity table type includes a respective entity table name field and at least one respective data item field; populating the respective entity table name fields and the respective data item fields by automatically: extracting a plurality of data items from a plurality of data sources; determining respective confidence values for the extracted data items based on a plurality of pre-determined confidence values, wherein the pre-determined confidence values, wherein a respective predetermined confidence value is provided for each respective entity table name and each respective data item according to which data source of the plurality of data sources provided the respective entity table name and the respective data item; and integrating the extracted data items into respective entity table name fields and data item fields based on the respective confidence values for the extracted data items; determining relationship types between at least some data items of the plurality of data items that are integrated into a plurality of tables in the database, wherein the relationship types are based on respective data sources from which the data items have been extracted, the relationship types including at least two of the following: a first relationship type, a second relationship type, a third relationship type, and a fourth relationship type, wherein: the first relationship type is between first and second data items extracted from a first structured data source, the second relationship type is between data items extracted from different structured data sources, wherein the second relationship type is based on a plurality of respective first relationship types, the third relationship type is between a data item extracted from a second structured data source, and an entity table including, as entity table data items, attributes about a first unstructured data source, and wherein the data item extracted from the second structured data source is mentioned in the first unstructured data source, and the fourth relationship type is between two data items that: have been integrated from different structured data sources, and are both mentioned in a second unstructured data source; and storing the relationship types in a computer system memory. 8. The computer system of claim 1 wherein the operations further comprise: determining a synonym for a first extracted data item; and integrating the first extracted data item into the database based on the synonym, wherein the synonym is integrated into the database. | 0.904011 |
8,849,034 | 25 | 27 | 25. An article comprising: a non-transitory computer-readable medium having instructions that, when executed by a computing platform, result in execution of a method comprising: drawing one or more strokes of a desired shape using a stylus on a touch screen, wherein one of the drawn one or more strokes is a head-line stroke and is a last drawn stroke of the desired shape; inputting an associated data of the drawn one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a trigger stroke in the drawn one or more strokes of the desired shape that can be used to trigger shape recognition based as a function of the computed stroke recognition characteristics of each of the drawn one or more strokes, wherein the trigger stroke is the head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering shape recognition for the desired shape by the handwriting recognition engine upon determining the trigger stroke. | 25. An article comprising: a non-transitory computer-readable medium having instructions that, when executed by a computing platform, result in execution of a method comprising: drawing one or more strokes of a desired shape using a stylus on a touch screen, wherein one of the drawn one or more strokes is a head-line stroke and is a last drawn stroke of the desired shape; inputting an associated data of the drawn one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a trigger stroke in the drawn one or more strokes of the desired shape that can be used to trigger shape recognition based as a function of the computed stroke recognition characteristics of each of the drawn one or more strokes, wherein the trigger stroke is the head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering shape recognition for the desired shape by the handwriting recognition engine upon determining the trigger stroke. 27. The article of claim 25 , wherein, in outputting the candidate shape, the output is selected from the group comprising transmitting, printing, and displaying. | 0.573684 |
9,460,056 | 1 | 7 | 1. A method performed by a first computing device for determining a layout of a structural document, the method comprising: receiving a plurality of images from a second computing device; determining a design associated with a structural document, the structural document comprising one or more facets, each facet representing one or more exterior surfaces of the structural document; determining a number of facets associated with the structural document based on the determined design; determining an image area associated with the structural document based on the received plurality of images and the number of facets; determining an image aspect ratio associated with each of the plurality of received images; determining a layout associated with the structural document based on the determined image area by: determining one or more areas of each facet in the number of facets; for each area of each facet in the number of facets: determining an area aspect ratio associated with each of the one or more areas; assigning a received image to the area, and determining a fit ratio comprising a ratio of the determined aspect ratio associated with the area and the determined aspect ratio associated with the image assigned to the area; evaluating the layout by: for each facet in the number of facets, determining an average fit ratio of aspect ratios associated with the facet, and determining whether the average fit ratio of aspect ratios exceeds a threshold value; when the average fit ratio of aspect ratios exceeds a threshold value for one or more of the facets in the number of facets, determining a new layout associated with the structural document and evaluating the new layout; and when the average fit ratio of aspect ratios for all facets associated with the evaluated layout does not exceed the threshold value, causing a graphical representation of the structural document to be displayed at the second computing device, wherein each received image is displayed on its assigned area on the graphical representation. | 1. A method performed by a first computing device for determining a layout of a structural document, the method comprising: receiving a plurality of images from a second computing device; determining a design associated with a structural document, the structural document comprising one or more facets, each facet representing one or more exterior surfaces of the structural document; determining a number of facets associated with the structural document based on the determined design; determining an image area associated with the structural document based on the received plurality of images and the number of facets; determining an image aspect ratio associated with each of the plurality of received images; determining a layout associated with the structural document based on the determined image area by: determining one or more areas of each facet in the number of facets; for each area of each facet in the number of facets: determining an area aspect ratio associated with each of the one or more areas; assigning a received image to the area, and determining a fit ratio comprising a ratio of the determined aspect ratio associated with the area and the determined aspect ratio associated with the image assigned to the area; evaluating the layout by: for each facet in the number of facets, determining an average fit ratio of aspect ratios associated with the facet, and determining whether the average fit ratio of aspect ratios exceeds a threshold value; when the average fit ratio of aspect ratios exceeds a threshold value for one or more of the facets in the number of facets, determining a new layout associated with the structural document and evaluating the new layout; and when the average fit ratio of aspect ratios for all facets associated with the evaluated layout does not exceed the threshold value, causing a graphical representation of the structural document to be displayed at the second computing device, wherein each received image is displayed on its assigned area on the graphical representation. 7. The method of claim 1 , further comprising: receiving one or more changes to the displayed graphical representation of the structural document from a user of the second computing device; determining a new design associated with the structural document that incorporates the one or more changes; determining an updated number of facets associated with the structural document based on the new design; determining an updated image area associated with the structural document based on the received plurality of images and the updated number of facets; determining an updated layout associated with the structural document based on the determined image area; and evaluating the updated layout by: for each facet in the updated number of facets, determining an average fit ratio of aspect ratios associated with the facet, and determining whether the average fit ratio of aspect ratios exceeds a threshold value. | 0.5 |
7,739,658 | 45 | 70 | 45. A method of responding to a request message sent from a remote user device for web page information by generating web page code capable of being interpreted by a browser within the remote user device for displaying one or more web pages and for outputting a response message comprising the web page code, the method comprising: extracting from the request message information determining a device type identifier identifying the remote user device which sent the request message as being one of a set of possible remote user device types having different capabilities of processing and displaying web page code; operating a code generating engine to generate the web page code; storing the web page information in a first memory means as a content document comprising a set of instructions authored in a script language for generating the web page code; and storing device dependent information for each of the set of different remote user device types in a second memory means; wherein the code generating engine interprets the instructions with reference to selected device dependent information corresponding to the device type identifier of the remote user device which sent the request message, the code generating engine thereby generating the web page code in a form in which the web page code is tailored to the capabilities of the remote user device for processing and displaying web page code; wherein the content document comprises at least one component name identifying a respective data component, and wherein the method comprises accessing a data structure in which at least one data component exists as a set of data objects defining multiple versions of the data component where the data objects have different data properties suited to the different capabilities of processing and displaying web page code of the different remote user devices, and further comprising selecting a data object from the set of data objects identified by a component name for inclusion in the web page code on the basis of the device type identifier; wherein the selecting step comprises looking up a predetermined selection of data object using a component policy table in a case where selection of the version of data component for the remote user device is predetermined by an author of the content document, and wherein the selecting step further comprises determining technical attributes of the remote user device and selecting the data object by comparing the technical attributes with data properties of each data object in a case where no version of the data component for the remote user device has been predetermined by the author of the content document, wherein the technical attributes of the remote user device are defined in a device policy table. | 45. A method of responding to a request message sent from a remote user device for web page information by generating web page code capable of being interpreted by a browser within the remote user device for displaying one or more web pages and for outputting a response message comprising the web page code, the method comprising: extracting from the request message information determining a device type identifier identifying the remote user device which sent the request message as being one of a set of possible remote user device types having different capabilities of processing and displaying web page code; operating a code generating engine to generate the web page code; storing the web page information in a first memory means as a content document comprising a set of instructions authored in a script language for generating the web page code; and storing device dependent information for each of the set of different remote user device types in a second memory means; wherein the code generating engine interprets the instructions with reference to selected device dependent information corresponding to the device type identifier of the remote user device which sent the request message, the code generating engine thereby generating the web page code in a form in which the web page code is tailored to the capabilities of the remote user device for processing and displaying web page code; wherein the content document comprises at least one component name identifying a respective data component, and wherein the method comprises accessing a data structure in which at least one data component exists as a set of data objects defining multiple versions of the data component where the data objects have different data properties suited to the different capabilities of processing and displaying web page code of the different remote user devices, and further comprising selecting a data object from the set of data objects identified by a component name for inclusion in the web page code on the basis of the device type identifier; wherein the selecting step comprises looking up a predetermined selection of data object using a component policy table in a case where selection of the version of data component for the remote user device is predetermined by an author of the content document, and wherein the selecting step further comprises determining technical attributes of the remote user device and selecting the data object by comparing the technical attributes with data properties of each data object in a case where no version of the data component for the remote user device has been predetermined by the author of the content document, wherein the technical attributes of the remote user device are defined in a device policy table. 70. A method as claimed in claim 45 , comprising storing the portions of code in a buffer memory for subsequent transmission to the user device. | 0.864151 |
8,965,145 | 1 | 3 | 1. A dispatcher apparatus having: one or more processors; a segmenter stored on a memory and executable by the one or more processors, the segmenter for receiving an image query including an image and segmenting the image into one or more content-type specific queries; a distributor stored on the memory and executable by the one or more processors, the distributor coupled to the segmenter for submitting the one or more content-type specific queries to one or more coupled corresponding content-type index tables for recognition; and an integrator stored on the memory and executable by the one or more processors, the integrator for receiving recognition results from the one or more corresponding content-type index tables, integrating the recognition results into an integrated result based on a level of agreement between the recognition results and transmitting the integrated result. | 1. A dispatcher apparatus having: one or more processors; a segmenter stored on a memory and executable by the one or more processors, the segmenter for receiving an image query including an image and segmenting the image into one or more content-type specific queries; a distributor stored on the memory and executable by the one or more processors, the distributor coupled to the segmenter for submitting the one or more content-type specific queries to one or more coupled corresponding content-type index tables for recognition; and an integrator stored on the memory and executable by the one or more processors, the integrator for receiving recognition results from the one or more corresponding content-type index tables, integrating the recognition results into an integrated result based on a level of agreement between the recognition results and transmitting the integrated result. 3. The dispatcher apparatus of claim 1 , wherein information regarding the one or more content-types is received with the image query. | 0.826873 |
9,767,144 | 10 | 13 | 10. A system, comprising: a general purpose computing device; and a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to: receive a database comprising a plurality of items; for each item, automatically mine a plurality of websites to retrieve a plurality of instances of unstructured user entered textual descriptions corresponding to each item; for each item, extract a plurality of candidate attribute values from the corresponding user entered textual descriptions; rank the candidate attribute values according to how selection of each candidate attribute value will reduce a size of a search result set; wherein ranking the candidate attribute values further comprises computing a degree of discrimination for each of a plurality of attribute values, the degree of discrimination for each attribute value corresponding to the number of items that would be excluded from the search result set when the search result set is limited to items having the corresponding attribute value; for each item, generate a reduced set of candidate attribute values by applying a classifier to filter out one or more ranked candidate attribute values that are unlikely to reduce the size of the search result set by determining, for each candidate attribute value, whether an answer to a question formulated from each candidate attribute value is likely to reduce the size of the search result set; in response to a search query, return a query result set comprising a subset of items from the database; apply a top ranked one of the reduced set of candidate attribute values corresponding to the items of the query result set to automatically formulate and present a question relating to the top ranked candidate attribute value such that any response to that question will reduce a size of the query result set returned in response to the search query; and wherein the presented question is a request for a value of an attribute. | 10. A system, comprising: a general purpose computing device; and a computer program comprising program modules executable by the computing device, wherein the computing device is directed by the program modules of the computer program to: receive a database comprising a plurality of items; for each item, automatically mine a plurality of websites to retrieve a plurality of instances of unstructured user entered textual descriptions corresponding to each item; for each item, extract a plurality of candidate attribute values from the corresponding user entered textual descriptions; rank the candidate attribute values according to how selection of each candidate attribute value will reduce a size of a search result set; wherein ranking the candidate attribute values further comprises computing a degree of discrimination for each of a plurality of attribute values, the degree of discrimination for each attribute value corresponding to the number of items that would be excluded from the search result set when the search result set is limited to items having the corresponding attribute value; for each item, generate a reduced set of candidate attribute values by applying a classifier to filter out one or more ranked candidate attribute values that are unlikely to reduce the size of the search result set by determining, for each candidate attribute value, whether an answer to a question formulated from each candidate attribute value is likely to reduce the size of the search result set; in response to a search query, return a query result set comprising a subset of items from the database; apply a top ranked one of the reduced set of candidate attribute values corresponding to the items of the query result set to automatically formulate and present a question relating to the top ranked candidate attribute value such that any response to that question will reduce a size of the query result set returned in response to the search query; and wherein the presented question is a request for a value of an attribute. 13. The system of claim 10 , further comprising applying the classifier to determine whether each of the candidate attribute values is answerable if used to formulate the presented question. | 0.597458 |
9,002,956 | 1 | 5 | 1. A method for sending messages with loudness points to self regulate transmission of messages, the method comprising: receiving a message from a first user having a predefined number of available loudness points; receiving one or more loudness points associated with the message; determining the available loudness points for the first user; determining whether the available loudness points exceed or equal the one or more loudness points associated with the message; responsive to the available loudness points being less than the one or more loudness points associated with the message, scheduling to automatically send the message at a future time when the first user accumulates the one or more loudness points associated with the message; responsive to the available loudness points for the first user being greater than the one or more loudness points associated with the message, sending the message, the message remaining unsent when unassociated with the one or more loudness points; receiving a reply message from a second user, the second user having a predefined number of available loudness points; receiving one or more loudness points associated with the reply message; and modifying the one or more loudness points associated with the message by the one or more loudness points associated with the reply message. | 1. A method for sending messages with loudness points to self regulate transmission of messages, the method comprising: receiving a message from a first user having a predefined number of available loudness points; receiving one or more loudness points associated with the message; determining the available loudness points for the first user; determining whether the available loudness points exceed or equal the one or more loudness points associated with the message; responsive to the available loudness points being less than the one or more loudness points associated with the message, scheduling to automatically send the message at a future time when the first user accumulates the one or more loudness points associated with the message; responsive to the available loudness points for the first user being greater than the one or more loudness points associated with the message, sending the message, the message remaining unsent when unassociated with the one or more loudness points; receiving a reply message from a second user, the second user having a predefined number of available loudness points; receiving one or more loudness points associated with the reply message; and modifying the one or more loudness points associated with the message by the one or more loudness points associated with the reply message. 5. The method of claim 1 , further comprising determining an audience for delivery of the message. | 0.87037 |
9,818,141 | 1 | 2 | 1. A method for pricing data according to provenance-based use in a query, the method comprising: identifying, by a processor, a set of data cubes, the set of data cubes being identified to participate in answering the query; removing, responsive to a participation of a data cube in the query being subject to a restriction, the data cube from the set of data cubes as disqualified from participating in the query; selecting a first subset of qualified data cubes remaining in the set of data cubes, the first subset of qualified data cubes being selected based on a selected first set of provenance attributes; executing the query on the first subset of qualified data cubes from the set of data cubes to form a result set; computing, by the processor, a first confidence value of the result set, wherein the first confidence value is computed using the first set of provenance attributes associated with the first data cube, the first data cube being included in the first subset of qualified data cubes; producing, by using the processor, a preview of the confidence value without providing in the preview the result set, the preview further including a set of available provenance attributes; changing, using the set of available provenance attributes, the first set of provenance attributes to a second set of provenance attributes; and modifying, by using the processor, responsive to the confidence value in the preview being unacceptable, the query, such that a different data cube participates in the modified query to produce an expected confidence value, the different data cube being selected according to the second set of provenance attributes. | 1. A method for pricing data according to provenance-based use in a query, the method comprising: identifying, by a processor, a set of data cubes, the set of data cubes being identified to participate in answering the query; removing, responsive to a participation of a data cube in the query being subject to a restriction, the data cube from the set of data cubes as disqualified from participating in the query; selecting a first subset of qualified data cubes remaining in the set of data cubes, the first subset of qualified data cubes being selected based on a selected first set of provenance attributes; executing the query on the first subset of qualified data cubes from the set of data cubes to form a result set; computing, by the processor, a first confidence value of the result set, wherein the first confidence value is computed using the first set of provenance attributes associated with the first data cube, the first data cube being included in the first subset of qualified data cubes; producing, by using the processor, a preview of the confidence value without providing in the preview the result set, the preview further including a set of available provenance attributes; changing, using the set of available provenance attributes, the first set of provenance attributes to a second set of provenance attributes; and modifying, by using the processor, responsive to the confidence value in the preview being unacceptable, the query, such that a different data cube participates in the modified query to produce an expected confidence value, the different data cube being selected according to the second set of provenance attributes. 2. The method of claim 1 , further comprising: receiving an input, wherein the input changes a selection of a provenance attribute in the first set of provenance attributes, forming a revised first set of provenance attributes; and changing, responsive to the input, the first data cube such that a portion of the first data cube participates in the set of data cubes, forming a revised set of data cubes. | 0.5 |
4,600,997 | 24 | 25 | 24. A control circuit according to claim 1 wherein said means for storing is a modular storage unit including means for selectively disconnecting from said control circuit, said storage unit retaining said elevation signals after said unit is disconnected from said control circuit. | 24. A control circuit according to claim 1 wherein said means for storing is a modular storage unit including means for selectively disconnecting from said control circuit, said storage unit retaining said elevation signals after said unit is disconnected from said control circuit. 25. A control circuit according to claim 24 wherein said modular storage unit includes a random access memory unit for storing said elevation signal and a power supply unit connected to said random access memory. | 0.5 |
8,145,579 | 11 | 12 | 11. A computer program product for estimating a labor cost to reconcile semantic conflicts between data schema terms used in different data sources, the computer program product comprising: a computer readable storage media; first program instructions to estimate a labor cost for mapping, to shared ontology terms, respective pairs of the data schema terms having semantic conflicts with each other, the first program instructions estimating the labor cost based on at least five of the following: (a) a number of the data sources that contain the data schema terms having the semantic conflicts, (b) an approximate number of the data schema terms in each of the data sources, (c) an approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) an approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) an approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) an approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) an approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms; and second program instructions to initiate display on a monitor the estimated labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other; and wherein the first and second program instructions are stored on the computer readable storage media. | 11. A computer program product for estimating a labor cost to reconcile semantic conflicts between data schema terms used in different data sources, the computer program product comprising: a computer readable storage media; first program instructions to estimate a labor cost for mapping, to shared ontology terms, respective pairs of the data schema terms having semantic conflicts with each other, the first program instructions estimating the labor cost based on at least five of the following: (a) a number of the data sources that contain the data schema terms having the semantic conflicts, (b) an approximate number of the data schema terms in each of the data sources, (c) an approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) an approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) an approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) an approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) an approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms; and second program instructions to initiate display on a monitor the estimated labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other; and wherein the first and second program instructions are stored on the computer readable storage media. 12. The computer program product of claim 11 wherein the first program instructions estimate the labor cost for the mapping, to the shared ontology terms, the data schema terms having semantic conflicts with each other, based on at least six of the following: (a) the number of the data sources that contain the data schema terms having the semantic conflicts, (b) the approximate number of the data schema terms in each of the data sources, (c) the approximate labor cost for implementing the shared ontology terms for each of the data sources, (d) the approximate labor cost to manually map to the shared ontology terms a percent of the data schema terms in each of the data sources, (e) the approximate labor cost to validate a percent of the mappings from the data schema terms to the shared ontology terms, (f) the approximate labor cost to perform functional computation for a percent of the mappings from the data schema terms to the shared ontology terms, and (g) the approximate labor cost to perform structural heterogeneity semantic mapping between a percent of the data schema terms and the shared ontology terms. | 0.5 |
8,838,457 | 25 | 26 | 25. The method of claim 15 wherein the at least one application includes a music application and the subject includes a media file. | 25. The method of claim 15 wherein the at least one application includes a music application and the subject includes a media file. 26. The method of claim 25 wherein the subject includes a name of content in the media file. | 0.5 |
6,094,671 | 39 | 43 | 39. The media distribution network system of claim 3 wherein the transmission system includes a one-way link adapted to transmit the envelope from the producer station to one or more remote receiving stations. | 39. The media distribution network system of claim 3 wherein the transmission system includes a one-way link adapted to transmit the envelope from the producer station to one or more remote receiving stations. 43. A media distribution network system as claimed in claim 39 wherein: (i) the receiving station includes a telecommunications link to the producer station or another content site; and (ii) the mark-up language document further comprises a tag for requesting a further mark-up language document or media file over the telecommunications link. | 0.600233 |
9,424,257 | 6 | 10 | 6. The method of claim 1 further comprising defining a SCHEMA statement that defines a plurality of fields within said record, one of said defined fields comprising an offset defining a location in said record, a field name, and a field length. | 6. The method of claim 1 further comprising defining a SCHEMA statement that defines a plurality of fields within said record, one of said defined fields comprising an offset defining a location in said record, a field name, and a field length. 10. The method of claim 6 further comprising instructions that cause a portion of one of said fields specified in said SCHEMA to be extracted from said record. | 0.612195 |
4,506,326 | 1 | 10 | 1. A method for operating a computing apparatus to translate into a linear query a graphic language query expressed as one or more elements, including example elements and implied operand predicates, appearing in rows and columms of an example table including one or more source and target tables and, optionally, in condition blocks, comprising the steps of: generating row names into a row name table having one entry for each row in a source table; for each data field within each row named in said row name table which contains an example element definition or implied operand predicate, generating and loading into a column data table an entry specifying the row name, column name, and data; and generating into a conditions table an entry containing a basic predicate for each column data table entry containing an implied operand predicate or an example element having an implied condition; thereby establishing in said row name table, column data table, and conditions table a data structure for synthesizing into a linear query a graphic language query specified as a target point query, or a combined print query, or an insert query, or an update query, or a delete query. | 1. A method for operating a computing apparatus to translate into a linear query a graphic language query expressed as one or more elements, including example elements and implied operand predicates, appearing in rows and columms of an example table including one or more source and target tables and, optionally, in condition blocks, comprising the steps of: generating row names into a row name table having one entry for each row in a source table; for each data field within each row named in said row name table which contains an example element definition or implied operand predicate, generating and loading into a column data table an entry specifying the row name, column name, and data; and generating into a conditions table an entry containing a basic predicate for each column data table entry containing an implied operand predicate or an example element having an implied condition; thereby establishing in said row name table, column data table, and conditions table a data structure for synthesizing into a linear query a graphic language query specified as a target point query, or a combined print query, or an insert query, or an update query, or a delete query. 10. The method of claim 1, comprising the further step, responsive to said graphic language query being a delete query expressed as a delete command appearing in a source table, of synthesizing a linear delete query. | 0.653846 |
7,636,855 | 1 | 37 | 1. A user authentication system, comprising: a dialogue manager, executed on a processor of the user authentication system, adapted to prompt a user with multiple pass-phrases and requests the user to select a proper subset from the prompted multiple pass-phrase during authentication; wherein the prompted multiple pass-phrases are formed by selecting one or more pass-phrases from a set of pass-phrases satisfying a rule associated with the user and selecting one or more pass-phrases that do not satisfy the rule associated with user, wherein the rule associated with the user is determined prior to authentication and is not suggested to the user during authentication; a selection recognizer, executed on the processor of the user authentication system, adapted to recognize user selection of a proper subset of the prompted multiple pass-phrases; a user input adapted to capture a user biometric from the user selection; a biometric matching module, executed on the processor of the user authentication system, adapted to perform a biometric match between the user biometric and at least one biometric model associated with a potential user identity, wherein said user identity analysis module is adapted to analyze the potential user identity based on the biometric match between the user biometric and the at least one biometric model; and a user identity analysis module, executed on the processor of the user authentication system, adapted to analyze at least one potential user identity based on whether the pass-phrases in the proper subset of user selection each satisfy the rule associated with the user, wherein said dialogue manager is adapted to recursively prompt the user with new sets of multiple, selectable pass-phrases randomly assembled from a pass-phrase corpus over multiple dialogue turns, and said user identity analysis module is adapted to combine selection results and biometric match results from each dialogue turn to yield dialogue turn results and combine the dialogue turn results from each dialogue turn to form a cumulative result and authorize the user when the cumulative result exceeds a threshold. | 1. A user authentication system, comprising: a dialogue manager, executed on a processor of the user authentication system, adapted to prompt a user with multiple pass-phrases and requests the user to select a proper subset from the prompted multiple pass-phrase during authentication; wherein the prompted multiple pass-phrases are formed by selecting one or more pass-phrases from a set of pass-phrases satisfying a rule associated with the user and selecting one or more pass-phrases that do not satisfy the rule associated with user, wherein the rule associated with the user is determined prior to authentication and is not suggested to the user during authentication; a selection recognizer, executed on the processor of the user authentication system, adapted to recognize user selection of a proper subset of the prompted multiple pass-phrases; a user input adapted to capture a user biometric from the user selection; a biometric matching module, executed on the processor of the user authentication system, adapted to perform a biometric match between the user biometric and at least one biometric model associated with a potential user identity, wherein said user identity analysis module is adapted to analyze the potential user identity based on the biometric match between the user biometric and the at least one biometric model; and a user identity analysis module, executed on the processor of the user authentication system, adapted to analyze at least one potential user identity based on whether the pass-phrases in the proper subset of user selection each satisfy the rule associated with the user, wherein said dialogue manager is adapted to recursively prompt the user with new sets of multiple, selectable pass-phrases randomly assembled from a pass-phrase corpus over multiple dialogue turns, and said user identity analysis module is adapted to combine selection results and biometric match results from each dialogue turn to yield dialogue turn results and combine the dialogue turn results from each dialogue turn to form a cumulative result and authorize the user when the cumulative result exceeds a threshold. 37. The system of claim 1 , wherein the pass-phrase selection criteria are predefined by sub-classes of a pass-phrase corpus that is entirely predefined and pre-classified before the enrollment of the user. | 0.757075 |
9,189,707 | 7 | 8 | 7. The method of claim 1 , wherein said sensors that are associated with said location data comprise at least one of an environmental sensor, an object sensor, and a social sensor. | 7. The method of claim 1 , wherein said sensors that are associated with said location data comprise at least one of an environmental sensor, an object sensor, and a social sensor. 8. The method of claim 7 , wherein said sensor data obtained from said environmental sensor comprises at least one of weather data, temperature data, pressure data, humidity data, wind data, precipitation data, and data from at least one of a chemical sensor, an allergen sensor, a noise sensor, and a light sensor. | 0.5 |
7,593,060 | 1 | 4 | 1. A text subtitle decoder for decoding text subtitle streams recorded on a recording medium, comprising: a text subtitle processor configured to parse the text subtitle stream into text data to be displayed in the subtitle region, region style information indicating a region style to be applied to an overall region including the text data, and inline style information indicating at least one font related style to be applied to the text data, the parsed text data and inline style information being transferred to a different area of the text subtitle decoder than the parsed region style information; a text renderer configured to receive the text data and the inline style information; and a controller configured to input the region style information into the text renderer, wherein the text renderer is controlled by the controller, and converts the text data into bitmap data using the region style information and the inline style information. | 1. A text subtitle decoder for decoding text subtitle streams recorded on a recording medium, comprising: a text subtitle processor configured to parse the text subtitle stream into text data to be displayed in the subtitle region, region style information indicating a region style to be applied to an overall region including the text data, and inline style information indicating at least one font related style to be applied to the text data, the parsed text data and inline style information being transferred to a different area of the text subtitle decoder than the parsed region style information; a text renderer configured to receive the text data and the inline style information; and a controller configured to input the region style information into the text renderer, wherein the text renderer is controlled by the controller, and converts the text data into bitmap data using the region style information and the inline style information. 4. The text subtitle decoder of claim 1 , wherein the text subtitle processor is configured to parse the text subtitle stream into region style information specifying a region style of the text subtitle region, the region style being specified by at least one of a region position, a region size, a region background color, a text position, a text flow, a text alignment, a line space, a font identification, a font style, a font size, and a font color defined in the region style information. | 0.5 |
8,402,032 | 20 | 36 | 20. A computer-implemented method, comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair. | 20. A computer-implemented method, comprising: receiving texts from each of a plurality of text sources, wherein each text source provides a text; deriving a plurality of name-context pairs from the texts, wherein each name-context pair comprises an entity name included in the text from a text source and a context term included in the text from the text source, wherein each entity name is one or more terms used to refer to a respective entity and each context term is a term that appears in text associated with the entity name; calculating a context consistency measure for each distinct name-context pair, wherein the context consistency measure for a particular name-context pair is an estimate of a probability that, if the entity name of the particular name-context pair appears in text, the context term of the particular name-context pair will also appear in the text; and storing context-entity name data, wherein the context-entity name data is searchable data that represents one or more of the distinct name-context pairs and the context consistency measure for each of the one or more name-context pair. 36. The method of claim 20 , wherein each entity name has one or more parts and the context-entity name data further associates one or more of the entity names with one or more related name parts for one or more parts of the entity name. | 0.533465 |
7,822,729 | 11 | 16 | 11. A computer-readable medium on which is stored a Structured Query Language (SQL) swap alias command, wherein the SQL swap alias command is a single SQL statement that comprises a list of multiple different objects whose aliases are to be swapped and which, when compiled and executed, causes a global alias name swap for multiple objects in a database management system; wherein the SQL swap alias command, when compiled and issued as a compiled SQL swap alias command to an SQL interface for the database management system, performs the steps of: in response to determining that an issuer of the SQL swap alias command is authorized to issue the SQL swap alias command, determining if a particular alias name, for one of the multiple objects, is locked to prevent changing the particular alias name to point to a different underlying table/view; in response to determining that the particular alias name is locked, determining if the issuer of the swap alias command has an authority to force the alias name swap of the particular alias name; in response to determining that the issuer has the authority to force the alias name swap of the particular alias name: swapping alias names for all objects using the particular alias name in the database management system; and concurrently swapping multiple alias names of all non-locked alias names for the multiple objects in the database management system, wherein said swapping is performed as a global alias swap; when the issuer does not have the authority to force the alias name swap of the particular alias name: issuing an error message if the SQL swap alias command fails because the issuer is not authorized to force the alias name swap; and swapping only the alias names of each of multiple other objects whose alias names are non-locked or for which the issuer has authority to force the alias name swap, wherein said swapping is performed as a global alias swap via execution of the compiled SQL swap alias command generated from the single SQL swap alias command. | 11. A computer-readable medium on which is stored a Structured Query Language (SQL) swap alias command, wherein the SQL swap alias command is a single SQL statement that comprises a list of multiple different objects whose aliases are to be swapped and which, when compiled and executed, causes a global alias name swap for multiple objects in a database management system; wherein the SQL swap alias command, when compiled and issued as a compiled SQL swap alias command to an SQL interface for the database management system, performs the steps of: in response to determining that an issuer of the SQL swap alias command is authorized to issue the SQL swap alias command, determining if a particular alias name, for one of the multiple objects, is locked to prevent changing the particular alias name to point to a different underlying table/view; in response to determining that the particular alias name is locked, determining if the issuer of the swap alias command has an authority to force the alias name swap of the particular alias name; in response to determining that the issuer has the authority to force the alias name swap of the particular alias name: swapping alias names for all objects using the particular alias name in the database management system; and concurrently swapping multiple alias names of all non-locked alias names for the multiple objects in the database management system, wherein said swapping is performed as a global alias swap; when the issuer does not have the authority to force the alias name swap of the particular alias name: issuing an error message if the SQL swap alias command fails because the issuer is not authorized to force the alias name swap; and swapping only the alias names of each of multiple other objects whose alias names are non-locked or for which the issuer has authority to force the alias name swap, wherein said swapping is performed as a global alias swap via execution of the compiled SQL swap alias command generated from the single SQL swap alias command. 16. The computer-readable medium of claim 11 , wherein the computer executable instructions are capable of being provided by a service provider to a customer on an on-demand. | 0.815678 |
8,666,730 | 2 | 4 | 2. The method according to claim 1 , further comprising: applying parts-of-speech tags to the text documents and user question to generate tagged text documents and user question; parsing the tagged text documents and user question to generate parsed and tagged text documents and user question; and semantically analyzing the parsed and tagged text documents and user question to generate semantically analyzed, parsed, and tagged text documents and user question. | 2. The method according to claim 1 , further comprising: applying parts-of-speech tags to the text documents and user question to generate tagged text documents and user question; parsing the tagged text documents and user question to generate parsed and tagged text documents and user question; and semantically analyzing the parsed and tagged text documents and user question to generate semantically analyzed, parsed, and tagged text documents and user question. 4. The method according to claim 2 , wherein the semantic analysis comprises: recognizing one or more facts in the form of one or more expanded Subject-Action-Object (eSAO) sets in the text documents and user question, wherein each eSAO set has one or more eSAO components; and recognizing rules in the text documents and user question that reflect regularities of the outside world/knowledge domain in the form of Cause-Effect relations in the eSAO sets, wherein each of the Cause-Effect relations comprises a Cause eSAO and an Effect eSAO. | 0.690857 |
7,805,428 | 13 | 21 | 13. A method for search engine optimization, comprising: using log files for key-wordless rank checking by a first smart tool; using log files for hyperlink analysis by a second smart tool; identifying web authorities for competitive analysis by a third smart tool; providing live relevancy metrics in on-page optimization editor by a fourth smart tool; authorization code to prevent usage of a software license in more than one computer by a fifth smart tool ; extracting incoming links for a user website and querying search engines directly; processing website log files to identify every internal page on the user website, and external pages that are linking to each internal page; presenting the website log files in a referrer log files; and identifying link rich pages and link poor pages from extracted hyperlink information where the link poor pages are less likely to be included in search engines index than the link rich pages. | 13. A method for search engine optimization, comprising: using log files for key-wordless rank checking by a first smart tool; using log files for hyperlink analysis by a second smart tool; identifying web authorities for competitive analysis by a third smart tool; providing live relevancy metrics in on-page optimization editor by a fourth smart tool; authorization code to prevent usage of a software license in more than one computer by a fifth smart tool ; extracting incoming links for a user website and querying search engines directly; processing website log files to identify every internal page on the user website, and external pages that are linking to each internal page; presenting the website log files in a referrer log files; and identifying link rich pages and link poor pages from extracted hyperlink information where the link poor pages are less likely to be included in search engines index than the link rich pages. 21. The method for search engine optimization of claim 13 , further comprising: analysis of the log files based on a date range; providing a file filter to match specific log files; discovering keywords, search engines, and number of visits related to a website page for a specific URL that matches the log files. | 0.828399 |
8,578,481 | 13 | 14 | 13. The non-transitory computer readable medium of claim 8 , the operation further comprises: when the alternate domain name is not resolved, generating, by the processor, one or more another alternate domain names from the suspected domain name and submitting the one or more another alternate domain names to the domain server for resolution. | 13. The non-transitory computer readable medium of claim 8 , the operation further comprises: when the alternate domain name is not resolved, generating, by the processor, one or more another alternate domain names from the suspected domain name and submitting the one or more another alternate domain names to the domain server for resolution. 14. The non-transitory computer readable medium of claim 13 , the operation further comprises: when the alternate domain name and the one or more another alternate domain names are not resolved, monitoring, by the processor, for another suspected domain name. | 0.5 |
8,438,469 | 1 | 4 | 1. A method of embedding evaluations in a document, comprising: at a client device having one or more processors and memory storing programs executed by the one or more processors: receiving a document including an authoring tool from a remote server system and displaying the document and the authoring tool to a user, wherein the document is written in a markup language; in response to user actions, modifying the document using the authoring tool by performing at least the following two operations: embedding an identifier tag in the document in response to a first user action, wherein the identifier tag includes a review from the user and an identifier associated with an entity, distinct from the document, that is a subject of the review; and embedding a rating tag in the document in response to a second user action, wherein the rating tag includes a rating value from the user, the rating value corresponding to a user-selected rating of the entity that is the subject of the review; and transmitting the document including the embedded identifier tag and the embedded rating tag from the client device to the remote server system; submitting a search query to the remote server system; and receiving from the remote server system an ordered list of search results including a search result corresponding to the document, wherein the search result's position in the ordered list is determined at least in part by a ranking value of the document that is determined in accordance with the review in the identifier tag and the rating value in the rating tag. | 1. A method of embedding evaluations in a document, comprising: at a client device having one or more processors and memory storing programs executed by the one or more processors: receiving a document including an authoring tool from a remote server system and displaying the document and the authoring tool to a user, wherein the document is written in a markup language; in response to user actions, modifying the document using the authoring tool by performing at least the following two operations: embedding an identifier tag in the document in response to a first user action, wherein the identifier tag includes a review from the user and an identifier associated with an entity, distinct from the document, that is a subject of the review; and embedding a rating tag in the document in response to a second user action, wherein the rating tag includes a rating value from the user, the rating value corresponding to a user-selected rating of the entity that is the subject of the review; and transmitting the document including the embedded identifier tag and the embedded rating tag from the client device to the remote server system; submitting a search query to the remote server system; and receiving from the remote server system an ordered list of search results including a search result corresponding to the document, wherein the search result's position in the ordered list is determined at least in part by a ranking value of the document that is determined in accordance with the review in the identifier tag and the rating value in the rating tag. 4. The method of claim 1 , wherein the rating value is selected from a set of pre-determined rating values. | 0.822848 |
10,129,367 | 9 | 10 | 9. A method comprising: receiving user information about a target user of an online system, the user information describing interactions performed by the target user on the online system; receiving third party information from a third party outside of the online system, the third party information describing an item associated with the third party that the target user is interested in acquiring from the third party; retrieving a plurality of trained machine learning models each associated with a population of users of the online system, each trained machine learning model configured to determine a likelihood that a user matching the corresponding population of users will perform a transaction associated with a particular item; receiving item information indicating a change in a status of the item; selecting a trained machine learning model of the plurality of trained machine learning models based at least in part on the user information; determining, using the selected trained machine learning model, the user information, the third party information, and the item information, a likelihood that the target user will perform a transaction associated with the item; sending, in response to the likelihood that the target user will perform the transaction associated with the item exceeding a threshold value, a content item associated with the item for display on a client device of the target user. | 9. A method comprising: receiving user information about a target user of an online system, the user information describing interactions performed by the target user on the online system; receiving third party information from a third party outside of the online system, the third party information describing an item associated with the third party that the target user is interested in acquiring from the third party; retrieving a plurality of trained machine learning models each associated with a population of users of the online system, each trained machine learning model configured to determine a likelihood that a user matching the corresponding population of users will perform a transaction associated with a particular item; receiving item information indicating a change in a status of the item; selecting a trained machine learning model of the plurality of trained machine learning models based at least in part on the user information; determining, using the selected trained machine learning model, the user information, the third party information, and the item information, a likelihood that the target user will perform a transaction associated with the item; sending, in response to the likelihood that the target user will perform the transaction associated with the item exceeding a threshold value, a content item associated with the item for display on a client device of the target user. 10. The method of claim 9 , wherein the population of users is categorized based on demographic data or geographical location data of the population of users. | 0.812352 |
8,599,318 | 6 | 7 | 6. The method of claim 5 further comprising: determining the first and second clip lines based upon a number of histogram points of the first histogram to be redistributed. | 6. The method of claim 5 further comprising: determining the first and second clip lines based upon a number of histogram points of the first histogram to be redistributed. 7. The method of claim 6 , wherein the number of histogram points to be redistributed is based upon a predefined percentage of the total number of points of the histogram. | 0.703125 |
9,990,420 | 12 | 16 | 12. A non-transitory computer readable storage medium storing machine executable instructions that upon execution by a processor cause a computer system to: receive user interaction selecting a first screen element, the first screen element being part of a plurality of screen elements that are displayed by an application, wherein the plurality of screen elements correspond to different contextual information; extract text and contextual information from the first screen element, wherein the contextual information extracted from the first screen element includes operating system data indicating a type of screen element from which the text is extracted; identify a plurality of strings of different text data types from the extracted text using a series of analyses; determine a plurality of search types for the extracted text based on the contextual information of the first screen element and the series of analyses, wherein the determined search types are selected from a plurality of different search types that are mapped to respective contextual information of the different contextual information corresponding to the plurality of screen elements; automatically append the determined search types to respective strings from the plurality of strings; automatically generate a relevant search string by logically combining the determined search types and the respective strings; and search a database with the relevant search string. | 12. A non-transitory computer readable storage medium storing machine executable instructions that upon execution by a processor cause a computer system to: receive user interaction selecting a first screen element, the first screen element being part of a plurality of screen elements that are displayed by an application, wherein the plurality of screen elements correspond to different contextual information; extract text and contextual information from the first screen element, wherein the contextual information extracted from the first screen element includes operating system data indicating a type of screen element from which the text is extracted; identify a plurality of strings of different text data types from the extracted text using a series of analyses; determine a plurality of search types for the extracted text based on the contextual information of the first screen element and the series of analyses, wherein the determined search types are selected from a plurality of different search types that are mapped to respective contextual information of the different contextual information corresponding to the plurality of screen elements; automatically append the determined search types to respective strings from the plurality of strings; automatically generate a relevant search string by logically combining the determined search types and the respective strings; and search a database with the relevant search string. 16. The non-transitory computer readable storage medium of claim 12 , wherein machine executable instructions for extracting the contextual information from the first screen element cause the computer system to: include within the contextual information extracted from the first screen element, a part of the first screen element that receives the user interaction. | 0.693792 |
9,128,732 | 15 | 16 | 15. The medium of claim 11 , wherein the selection is based on heuristic indicators including a proportion of amount of un-trusted code vs amount of trusted code in an already emitted portion of the code stream, and wherein the proportion is dynamically tracked during emission of the code stream. | 15. The medium of claim 11 , wherein the selection is based on heuristic indicators including a proportion of amount of un-trusted code vs amount of trusted code in an already emitted portion of the code stream, and wherein the proportion is dynamically tracked during emission of the code stream. 16. The medium of claim 15 , wherein the heuristic indicators are associated with environmental settings to allow adjustment between effectiveness of the protection and efficiency of execution of the code stream. | 0.5 |
9,767,255 | 14 | 15 | 14. The medical system of claim 13 , wherein the steps further comprise: generating a list of popular data entries; saving the list of popular data entries in an electronic memory storage; and selecting at least a subset of the list of popular data entries to be displayed as the plurality of predefined suggestions. | 14. The medical system of claim 13 , wherein the steps further comprise: generating a list of popular data entries; saving the list of popular data entries in an electronic memory storage; and selecting at least a subset of the list of popular data entries to be displayed as the plurality of predefined suggestions. 15. The medical system of claim 14 , wherein the generating the list of popular data entries comprises defining the popular data entries in response to feedback from the healthcare professional. | 0.692063 |
8,175,911 | 16 | 20 | 16. A method for inferring and visualizing correlations of different business aspects for business transformation, comprising: providing a computer-implemented module operable to load into memory a plurality of business models, said plurality of business models including at least business component model, business process model, value drivers and metrics model, application model, organization model, and solutions model, the plurality of business models structured using a model topology, the model topology representing data schema for connecting said plurality of business models; providing a computer-implemented user-interface module operable to configure one or more qualitative relationships between one or more entities in said business models, the user-interface module further operable to configure one or more quantitative properties of said one or more entities in said business models based on said configured one or more qualitative relationships; providing a computer-implemented inference engine, executing on a processor, operable to infer one or more qualitative correlations from the said qualitative relationships among said one or more entities in said business models, the inference engine utilizing one or more logical rules; providing a computer-implemented module operable to determine quantitative correlations from said quantitative properties of said one or more entities, utilizing statistics, data mining, mathematical models, simulations, or optimizations, or combinations thereof, said quantitative correlations including distance, intensity determined from a formula that incorporates values of said one or more entities that are correlated, and direction representing forward or backward inferring, said quantitative correlations including coefficient measure between the elements of said entities in said business models, said coefficient measure providing pattern of relationship between the elements of said entities in said business models; and providing a computer-implemented visualization module operable to generate visualization of said qualitative correlations and quantitative correlations. | 16. A method for inferring and visualizing correlations of different business aspects for business transformation, comprising: providing a computer-implemented module operable to load into memory a plurality of business models, said plurality of business models including at least business component model, business process model, value drivers and metrics model, application model, organization model, and solutions model, the plurality of business models structured using a model topology, the model topology representing data schema for connecting said plurality of business models; providing a computer-implemented user-interface module operable to configure one or more qualitative relationships between one or more entities in said business models, the user-interface module further operable to configure one or more quantitative properties of said one or more entities in said business models based on said configured one or more qualitative relationships; providing a computer-implemented inference engine, executing on a processor, operable to infer one or more qualitative correlations from the said qualitative relationships among said one or more entities in said business models, the inference engine utilizing one or more logical rules; providing a computer-implemented module operable to determine quantitative correlations from said quantitative properties of said one or more entities, utilizing statistics, data mining, mathematical models, simulations, or optimizations, or combinations thereof, said quantitative correlations including distance, intensity determined from a formula that incorporates values of said one or more entities that are correlated, and direction representing forward or backward inferring, said quantitative correlations including coefficient measure between the elements of said entities in said business models, said coefficient measure providing pattern of relationship between the elements of said entities in said business models; and providing a computer-implemented visualization module operable to generate visualization of said qualitative correlations and quantitative correlations. 20. The method of claim 16 , wherein the logical rules include transitivity, ontology, or semantics or combinations thereof. | 0.737288 |
9,672,618 | 1 | 4 | 1. A system for Dyslexia management, comprising: a hardware, a network, a database, a server and a processor for implementing the Dyslexia management system; the processor or the server further comprising: a test module that is multilingual, to be presented to an user as consisting of tests to detect their reading, writing, drawing, spelling and listening skills in a language of the user's choice; an intelligent dyslexia analytic module to analyze a result of the test module using several equations for a group, community and an individual wherein the several equations are Equations 1-4 in sequence, wherein Equation 1 is: x=a+by+cy 2 , where a, b, and c are as follows: a = Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 Σ y 3 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 b = N Σ x Σ y 2 Σ y Σ xy Σ y 3 Σ y 2 Σ xy 2 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 c = N Σ y Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 Equation 2 is: κ=x 2 (1+x 1 2 ) 3/2 where x 1 =dx/dy & x 2 =d 2 x/dy 2 Wherein equation 3: x=a+by y=mx+c form, we get y(x/b)−(a/b), so the slope of the line=1/b, where a, b are defined as follows: a = Σ x Σ y Σ xy Σ y 2 N Σ y Σ y Σ y 2 b = N Σ x Σ y Σ xy N Σ y Σ y Σ y 2 And, Equation 4
Sl=M (i,j) +max(( M (i+1,j) +M (i+2,j) ),( M (i+1,j) +M (i+2,j+1) ))
Sr=M (i,j) +max(( M (i,j+1) +M (i,j+2) ),( M (i,j+1) +M (i+1,j+2) ))
Sd=M (i,j) +( M (i+1,j+1) +max( M (i+1,j+2) ,( M (i+2,j+2) ,M (i+2,j+1) ), Where, Sl denotes a shift down, Sr denotes a Shift right, Sd denotes a Shift diagonally; and an analysis module to present an analyzed result for a medical professional to detect and manage Dyslexia in the user. | 1. A system for Dyslexia management, comprising: a hardware, a network, a database, a server and a processor for implementing the Dyslexia management system; the processor or the server further comprising: a test module that is multilingual, to be presented to an user as consisting of tests to detect their reading, writing, drawing, spelling and listening skills in a language of the user's choice; an intelligent dyslexia analytic module to analyze a result of the test module using several equations for a group, community and an individual wherein the several equations are Equations 1-4 in sequence, wherein Equation 1 is: x=a+by+cy 2 , where a, b, and c are as follows: a = Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 Σ y 3 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 b = N Σ x Σ y 2 Σ y Σ xy Σ y 3 Σ y 2 Σ xy 2 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 c = N Σ y Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 Equation 2 is: κ=x 2 (1+x 1 2 ) 3/2 where x 1 =dx/dy & x 2 =d 2 x/dy 2 Wherein equation 3: x=a+by y=mx+c form, we get y(x/b)−(a/b), so the slope of the line=1/b, where a, b are defined as follows: a = Σ x Σ y Σ xy Σ y 2 N Σ y Σ y Σ y 2 b = N Σ x Σ y Σ xy N Σ y Σ y Σ y 2 And, Equation 4
Sl=M (i,j) +max(( M (i+1,j) +M (i+2,j) ),( M (i+1,j) +M (i+2,j+1) ))
Sr=M (i,j) +max(( M (i,j+1) +M (i,j+2) ),( M (i,j+1) +M (i+1,j+2) ))
Sd=M (i,j) +( M (i+1,j+1) +max( M (i+1,j+2) ,( M (i+2,j+2) ,M (i+2,j+1) ), Where, Sl denotes a shift down, Sr denotes a Shift right, Sd denotes a Shift diagonally; and an analysis module to present an analyzed result for a medical professional to detect and manage Dyslexia in the user. 4. The system of claim 1 , wherein the test module is incremental in complexity, context-aware content, time duration, cognitive challenges and school curriculum dependent. | 0.530055 |
9,740,922 | 81 | 82 | 81. The system of claim 79 , wherein the plurality of sensors measure in real-time display device poses using information of the at least one tag. | 81. The system of claim 79 , wherein the plurality of sensors measure in real-time display device poses using information of the at least one tag. 82. The system of claim 81 , wherein the tracking component automatically adapts to changes in the display device poses. | 0.5 |
6,056,551 | 7 | 13 | 7. An apparatus for use in improving reading speed with comprehension comprising: a computer system having a means for data storage, a means for data computation and presentation formatting, and a means for data display; the data display means providing an animated designated word display area and a plurality of animated, input device controllable, operational indicia; the data computation and presentation formatting means being enabled for presenting a textual matter data file selected from the data storage means, on the data display means as a series of textual portions in timed sequence with each of the textual portions being replaced by a next said textual portion in turn; a set of selectable burst buttons on the video monitor screen enabled for displaying a preset number of words or sentences before stopping such that users can burst back to re-read a previous set of words, repeat to reread the last set of words, or go forward with a new set of words; a set of selectable search buttons on the video monitor screen enabled for selecting one of the search buttons to find a specific word within the textural matter, selecting another of the search buttons to find a set of words within the textural matter, and selecting a still further one of the search buttons to find a sentence within the textural matter; and an operational indicia enabled for searching the textual matter data file forward or backward and for displaying the data file accordingly by dragging the operational indicia with a pointing device. | 7. An apparatus for use in improving reading speed with comprehension comprising: a computer system having a means for data storage, a means for data computation and presentation formatting, and a means for data display; the data display means providing an animated designated word display area and a plurality of animated, input device controllable, operational indicia; the data computation and presentation formatting means being enabled for presenting a textual matter data file selected from the data storage means, on the data display means as a series of textual portions in timed sequence with each of the textual portions being replaced by a next said textual portion in turn; a set of selectable burst buttons on the video monitor screen enabled for displaying a preset number of words or sentences before stopping such that users can burst back to re-read a previous set of words, repeat to reread the last set of words, or go forward with a new set of words; a set of selectable search buttons on the video monitor screen enabled for selecting one of the search buttons to find a specific word within the textural matter, selecting another of the search buttons to find a set of words within the textural matter, and selecting a still further one of the search buttons to find a sentence within the textural matter; and an operational indicia enabled for searching the textual matter data file forward or backward and for displaying the data file accordingly by dragging the operational indicia with a pointing device. 13. The apparatus of claim 7 wherein the input device controllable, operational indicia further comprises a scroll indicia enabled for searching the textual matter data file forward or backward and for displaying the data file accordingly. | 0.72338 |
9,223,868 | 1 | 2 | 1. A method performed by a system of one or more computers, the method comprising: comparing, by the system, a first scoring algorithm for scoring electronic documents responsive to search queries with a second scoring algorithm for scoring the electronic documents responsive to search queries, wherein the comparing includes: obtaining a first profile that characterizes historical interaction, by a first plurality of users, with electronic documents in first result sets of electronic documents, the electronic documents in each first result set scored by a search engine in accordance with the first scoring algorithm and ranked by the search engine in each first result set in accordance with said scoring, obtaining a second profile that characterizes historical interaction, by a second plurality of users, with electronic documents in second result sets of electronic documents, the electronic documents in each second result set scored by the search engine in accordance with the second scoring algorithm and ranked by the search engine in each second result set in accordance with said scoring, determining that one or more metrics of the user interaction characterized in the first profile collectively indicate a higher level of user satisfaction with the first result sets of electronic documents than a level of user satisfaction with the second result sets indicated by the one or more metrics of the user interaction characterized in the second profile, and in response to the determination, outputting an indication that the first scoring algorithm is better than the second scoring algorithm, wherein the one or more metrics of the user interaction characterized in the first profile comprise a total number of respective selections of one or more electronic documents from each of the first result sets of electronic documents, wherein the one or more metrics of the user interaction characterized in the second profile comprise a total number of respective selections of one or more electronic documents from each of the second result sets of electronic documents, and wherein the higher level of user satisfaction is indicated by a lower total number of respective selections of the one or more electronic documents from each of the first result sets of electronic documents than the total number of respective selections of the one or more electronic documents from each of the second result sets of electronic documents. | 1. A method performed by a system of one or more computers, the method comprising: comparing, by the system, a first scoring algorithm for scoring electronic documents responsive to search queries with a second scoring algorithm for scoring the electronic documents responsive to search queries, wherein the comparing includes: obtaining a first profile that characterizes historical interaction, by a first plurality of users, with electronic documents in first result sets of electronic documents, the electronic documents in each first result set scored by a search engine in accordance with the first scoring algorithm and ranked by the search engine in each first result set in accordance with said scoring, obtaining a second profile that characterizes historical interaction, by a second plurality of users, with electronic documents in second result sets of electronic documents, the electronic documents in each second result set scored by the search engine in accordance with the second scoring algorithm and ranked by the search engine in each second result set in accordance with said scoring, determining that one or more metrics of the user interaction characterized in the first profile collectively indicate a higher level of user satisfaction with the first result sets of electronic documents than a level of user satisfaction with the second result sets indicated by the one or more metrics of the user interaction characterized in the second profile, and in response to the determination, outputting an indication that the first scoring algorithm is better than the second scoring algorithm, wherein the one or more metrics of the user interaction characterized in the first profile comprise a total number of respective selections of one or more electronic documents from each of the first result sets of electronic documents, wherein the one or more metrics of the user interaction characterized in the second profile comprise a total number of respective selections of one or more electronic documents from each of the second result sets of electronic documents, and wherein the higher level of user satisfaction is indicated by a lower total number of respective selections of the one or more electronic documents from each of the first result sets of electronic documents than the total number of respective selections of the one or more electronic documents from each of the second result sets of electronic documents. 2. The method of claim 1 , wherein: the one or more metrics of the user interaction further comprise a number of refinements of the search queries; and the higher level of user satisfaction is further indicated by a lower number of refinements by the first plurality of users or the second plurality of users. | 0.807357 |
8,527,508 | 13 | 17 | 13. A non-transitory storage medium storing an input assistance program, the input assistance program causing the computer to execute: referring to stored plurality of input candidates for an input item, and historical values that indicate an input history of information of each of the plurality of input candidates for the input item; determining a first display order of the plurality of input candidates based on the historical values to change the first display order of the plurality of input candidates for the input item into a second display order by replacing a first input candidate from among the plurality of input candidates for the input item in a first range from a top percentile priority with a second input candidate in a second range from another percentile priority that is outside of the first range in the top percentile priority; and outputting the plurality of input candidates for the input item to a display according to the second display order. | 13. A non-transitory storage medium storing an input assistance program, the input assistance program causing the computer to execute: referring to stored plurality of input candidates for an input item, and historical values that indicate an input history of information of each of the plurality of input candidates for the input item; determining a first display order of the plurality of input candidates based on the historical values to change the first display order of the plurality of input candidates for the input item into a second display order by replacing a first input candidate from among the plurality of input candidates for the input item in a first range from a top percentile priority with a second input candidate in a second range from another percentile priority that is outside of the first range in the top percentile priority; and outputting the plurality of input candidates for the input item to a display according to the second display order. 17. The non-transitory storage medium storing the input assistance program according to claim 13 further causing the computer to execute: referring to stored number of times a user selects an input candidate having a specified priority in a display order; and notifying a number of times an input candidate having the specified priority is selected is equal to or more than a threshold. | 0.5 |
9,026,701 | 27 | 30 | 27. The computer system of claim 26 , wherein the instructions further comprise: directing instructions to direct the second request to the first device. | 27. The computer system of claim 26 , wherein the instructions further comprise: directing instructions to direct the second request to the first device. 30. The computer system of claim 27 , wherein the instructions further comprise: sending instructions for sending a response to the first request. | 0.560241 |
8,762,857 | 13 | 14 | 13. The portable dataport of claim 1 , wherein the portable dataport wirelessly synchronizes to a remote, host server to provide the ability to load real-time documents onto the portable dataport. | 13. The portable dataport of claim 1 , wherein the portable dataport wirelessly synchronizes to a remote, host server to provide the ability to load real-time documents onto the portable dataport. 14. The portable dataport of claim 13 , wherein the wireless synchronization is used to access and store up-to-date secondary project elements, and wherein the secondary project elements are selected from the group consisting of users, contacts, security access, software and developmental tools. | 0.5 |
8,285,196 | 1 | 6 | 1. An electronic device comprising: a communication circuitry; at least one non-volatile memory having stored therein one or both of firmware and software; a demographic profile reference stored in the at least one non-volatile memory; at least one processor operably coupled to the non-volatile memory, wherein the at least one processor, during operation, at least: employs the communication circuitry to communicate with a distribution server that supports delivery of a questionnaire to the electronic device and processes responses from the electronic device; receives a questionnaire from the distribution server and displays it to a user; receives the user's input and gathers a response; and communicates the response to the distribution server along with the demographic profile reference. | 1. An electronic device comprising: a communication circuitry; at least one non-volatile memory having stored therein one or both of firmware and software; a demographic profile reference stored in the at least one non-volatile memory; at least one processor operably coupled to the non-volatile memory, wherein the at least one processor, during operation, at least: employs the communication circuitry to communicate with a distribution server that supports delivery of a questionnaire to the electronic device and processes responses from the electronic device; receives a questionnaire from the distribution server and displays it to a user; receives the user's input and gathers a response; and communicates the response to the distribution server along with the demographic profile reference. 6. The electronic device of claim 1 , wherein the questionnaire comprises criteria tags inserted by the distribution server wherein the criteria tags determine the criteria for analysis by the distribution server, an age based analysis, a priority based analysis and a satisfaction level analysis. | 0.552711 |
8,099,313 | 39 | 42 | 39. The system of claim 32 , wherein a task description includes a sequence of actions scripts that the controller uses to orchestrate the device actions. | 39. The system of claim 32 , wherein a task description includes a sequence of actions scripts that the controller uses to orchestrate the device actions. 42. The system of claim 39 , wherein device grounding information specifies interactions and parameter settings to determine the control of a device. | 0.664414 |
7,987,195 | 14 | 16 | 14. A computer program product tangibly embodied on a computer-readable storage medium and including executable code that, when executed, is configured to cause a data processing apparatus to: provide location factors for first phrases in a collection of phrases, each location factor for a first phrase being associated with a likelihood that a second phrase of a search query is associated with a location when the first phrase and the second phrase are used in the search query; receive a search query, the received search query including a first phrase from the collection of phrases and a second phrase; determine that the second phrase does not correspond to a location that can be identified by the second phrase alone, by: determining a name score indicating a popularity of the second phrase for the location; obtaining a signature for the location, wherein the signature includes a set of combinations of location specifiers, wherein each combination of location specifiers refers to the location; determining a signature score that indicates a popularity of the signature for the location; and determining that the location cannot be identified by the second phrase alone based on the name score and the signature score for the location; and determine whether the second phrase of the received search query refers to a location based, at least in part, on the location factor for the first phrase of the search query. | 14. A computer program product tangibly embodied on a computer-readable storage medium and including executable code that, when executed, is configured to cause a data processing apparatus to: provide location factors for first phrases in a collection of phrases, each location factor for a first phrase being associated with a likelihood that a second phrase of a search query is associated with a location when the first phrase and the second phrase are used in the search query; receive a search query, the received search query including a first phrase from the collection of phrases and a second phrase; determine that the second phrase does not correspond to a location that can be identified by the second phrase alone, by: determining a name score indicating a popularity of the second phrase for the location; obtaining a signature for the location, wherein the signature includes a set of combinations of location specifiers, wherein each combination of location specifiers refers to the location; determining a signature score that indicates a popularity of the signature for the location; and determining that the location cannot be identified by the second phrase alone based on the name score and the signature score for the location; and determine whether the second phrase of the received search query refers to a location based, at least in part, on the location factor for the first phrase of the search query. 16. The computer program product of claim 14 , wherein determining a location factor for the first phrase based on the responses to the search results includes: determining how often responses to a search result associated with a known location are received relative to how often responses to a search result not associated with a known location are received. | 0.613978 |
8,700,389 | 1 | 3 | 1. A computer-implemented method comprising: receiving, on a computer system, an input from a user, the input comprising one or more linguistic inputs; parsing the one or more linguistic inputs on the computer system; mapping, on the computer system, the one or more linguistic inputs to a formal representation used by a model, wherein the formal representation comprises actors, activities, and objects, wherein the one or more linguistic inputs are mapped to a first actor, a first activity, and a first object; storing information in a datastore on the computer system, the information corresponding to a plurality of software resources, wherein the plurality of software resources have associated annotations, the annotations comprising first elements of the formal representation used by the model; applying, on the computer system, the formal representation of the linguistic inputs against the model, wherein the model specifies relationships between elements of the formal representation and defines process information; and accessing software resources on the computer system based on the formal representation of the linguistic inputs, the relationships and process information in said model, and the annotations. | 1. A computer-implemented method comprising: receiving, on a computer system, an input from a user, the input comprising one or more linguistic inputs; parsing the one or more linguistic inputs on the computer system; mapping, on the computer system, the one or more linguistic inputs to a formal representation used by a model, wherein the formal representation comprises actors, activities, and objects, wherein the one or more linguistic inputs are mapped to a first actor, a first activity, and a first object; storing information in a datastore on the computer system, the information corresponding to a plurality of software resources, wherein the plurality of software resources have associated annotations, the annotations comprising first elements of the formal representation used by the model; applying, on the computer system, the formal representation of the linguistic inputs against the model, wherein the model specifies relationships between elements of the formal representation and defines process information; and accessing software resources on the computer system based on the formal representation of the linguistic inputs, the relationships and process information in said model, and the annotations. 3. The method of claim 1 further comprising determining that the one or more linguistic inputs do not include at least one of the first actor, the first activity, or the first object, the method further comprising invoking a resolution dialog to obtain first actor, first activity, or first object not included in said one or more linguistic inputs. | 0.524523 |
9,449,288 | 10 | 14 | 10. A system comprising: a processor; and memory storing instructions configured to instruct the processor to: receive, from a client device operated by a user, a travel request; identify travel options according to the travel request; rank each travel option in the identified travel options, the ranking based on travel attributes of each travel option and user preferences; train a bucket configuration module to determine a bucket algorithm and a bucket context for grouping travel options, one or more of the bucket algorithm and the bucket context based on input from domain experts, input from semantic analysts, analytics data, user preferences, company policies, and past transaction analysis; classify, from the bucket algorithm and the bucket context, the ranked travel options into predefined buckets the instructions configured to instruct the processor to classify further comprises instructions to define the buckets, the instructions to define the buckets further comprise instructions that are personalized for the user; filter the ranked travel options in the predefined buckets; communicate, to a client device for display, the filtered classified ranked travel options in the corresponding predefined buckets, the filtered classified ranked travel options in the corresponding predefined buckets displayed at the client device in an order associated with the user, the order enabling the user to determine a tradeoff between one bucket and another bucket; receive, from the client device, interactions from the user with one or more of the displayed predefined buckets, the interactions comprising a voting of the travel options in the bucket; and in response to receiving the interactions from the user with the one or more of the displayed predefined buckets, use, by the bucket configuration module, the interactions in the bucket algorithm for future classifying. | 10. A system comprising: a processor; and memory storing instructions configured to instruct the processor to: receive, from a client device operated by a user, a travel request; identify travel options according to the travel request; rank each travel option in the identified travel options, the ranking based on travel attributes of each travel option and user preferences; train a bucket configuration module to determine a bucket algorithm and a bucket context for grouping travel options, one or more of the bucket algorithm and the bucket context based on input from domain experts, input from semantic analysts, analytics data, user preferences, company policies, and past transaction analysis; classify, from the bucket algorithm and the bucket context, the ranked travel options into predefined buckets the instructions configured to instruct the processor to classify further comprises instructions to define the buckets, the instructions to define the buckets further comprise instructions that are personalized for the user; filter the ranked travel options in the predefined buckets; communicate, to a client device for display, the filtered classified ranked travel options in the corresponding predefined buckets, the filtered classified ranked travel options in the corresponding predefined buckets displayed at the client device in an order associated with the user, the order enabling the user to determine a tradeoff between one bucket and another bucket; receive, from the client device, interactions from the user with one or more of the displayed predefined buckets, the interactions comprising a voting of the travel options in the bucket; and in response to receiving the interactions from the user with the one or more of the displayed predefined buckets, use, by the bucket configuration module, the interactions in the bucket algorithm for future classifying. 14. The system of claim 10 , further comprising instructions to classify a first bucket, the instructions based on a model function of the first bucket. | 0.631068 |
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