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8,239,590 | 10 | 20 | 10. A method of operating a circuit, comprising: manipulating data arriving at a first data interface with a first word width into data with a second word width, wherein the first and second word widths are each multi-bit and different; transferring the manipulated data to a second data interface having the second word width; and selecting one of a plurality of different word widths for one of the first or second word widths according to a configurable structure that is field programmable. | 10. A method of operating a circuit, comprising: manipulating data arriving at a first data interface with a first word width into data with a second word width, wherein the first and second word widths are each multi-bit and different; transferring the manipulated data to a second data interface having the second word width; and selecting one of a plurality of different word widths for one of the first or second word widths according to a configurable structure that is field programmable. 20. A method according to claim 10 , comprising: wherein the circuit includes a storage portion having a plurality of independently controlled storage elements; wherein the manipulating includes dividing a first data word with the first word width from the first data interface into a plurality of second data words that each have the second word width by grouping the second data words and storing each group of the second data words in a respective one of the storage elements; maintaining a first value that is representative of the number of the second data words in each group, and maintaining a second value that is representative of the number of groups; and wherein transferring includes, as a function of the first and second values, successively enabling in a mutually exclusive manner each of the storage elements having a group of the second data words therein, each of these storage elements, when enabled, transferring the second data words therein to the second interface. | 0.680169 |
8,429,126 | 9 | 11 | 9. A method as recited in claim 1 , further comprising transmitting a message to an interested object that registered previously to be informed of changes to the first data bearing object. | 9. A method as recited in claim 1 , further comprising transmitting a message to an interested object that registered previously to be informed of changes to the first data bearing object. 11. A method as recited in claim 9 , wherein said interested object comprises a user interface manager object managing values displayed in a user interface. | 0.941132 |
7,948,400 | 10 | 12 | 10. A method for determining utility of information for an arterial flow system, comprising: with at least one processor: receiving a request to generate valuations for the flow system; obtaining a set of segments that define the flow system; determining utility values of one or more segments of the set of segments, the utility values are a function of variances of sensor data associated with the one or more segments for monitoring the flow system, selecting sensor data to provide to a remote route planning system based on the determined utility values; receiving from the remote route planning system indications of limits on an amount of sensor data to provide to the remote route planning system; and selecting sensor data to provide to the remote route planning system comprises selecting sensor data in accordance with the limits. | 10. A method for determining utility of information for an arterial flow system, comprising: with at least one processor: receiving a request to generate valuations for the flow system; obtaining a set of segments that define the flow system; determining utility values of one or more segments of the set of segments, the utility values are a function of variances of sensor data associated with the one or more segments for monitoring the flow system, selecting sensor data to provide to a remote route planning system based on the determined utility values; receiving from the remote route planning system indications of limits on an amount of sensor data to provide to the remote route planning system; and selecting sensor data to provide to the remote route planning system comprises selecting sensor data in accordance with the limits. 12. The method of claim 10 , wherein: the method further comprises: receiving the sensor data collected by a plurality of sensors; identifying correspondence between the sensor data and the set of segments; and selecting sensor data to provide to a remote route planning system based on the determined utility values comprises filtering the sensor data based at least in part upon the relative utility values of the set of segments corresponding to the sensor data. | 0.624394 |
8,595,013 | 1 | 5 | 1. A computer-implemented method for designing a speech application, the method comprising: defining common design elements of a speech application in a dialog design document; creating a design for a first step in designing the speech application using a plurality of data presentation elements; storing the design in a repository using a data repository element; generating a design for a second step in designing the speech application using a data generation element, wherein the data generation element comprises at least one element for generating at least one of a test case, an application code, a report, a view, a use case, or a call flow report; and presenting the design for the second step using the plurality of data presentation elements wherein the plurality of data presentation elements access connectors to integrate and present data stored in the repository in a plurality of application formats, the application formats comprising a portable document format, a web markup language format, a diagramming application format, and a word processing format. | 1. A computer-implemented method for designing a speech application, the method comprising: defining common design elements of a speech application in a dialog design document; creating a design for a first step in designing the speech application using a plurality of data presentation elements; storing the design in a repository using a data repository element; generating a design for a second step in designing the speech application using a data generation element, wherein the data generation element comprises at least one element for generating at least one of a test case, an application code, a report, a view, a use case, or a call flow report; and presenting the design for the second step using the plurality of data presentation elements wherein the plurality of data presentation elements access connectors to integrate and present data stored in the repository in a plurality of application formats, the application formats comprising a portable document format, a web markup language format, a diagramming application format, and a word processing format. 5. The method of claim 1 , wherein the dialog design document defines how data is shared among at least one stakeholder in designing the speech application. | 0.765766 |
9,135,239 | 3 | 4 | 3. The method of claim 1 , further comprising: traversing multiple bonds in the semantic space between the first node associated with the first term and the second node associated with the second term, wherein the semantic distance is based on respective strengths of bonds traversed between the first node and the second node. | 3. The method of claim 1 , further comprising: traversing multiple bonds in the semantic space between the first node associated with the first term and the second node associated with the second term, wherein the semantic distance is based on respective strengths of bonds traversed between the first node and the second node. 4. The method of claim 3 , wherein each bond in the semantic space has a direction of association, and wherein a first strength associated with traversing a bond in a direction opposite to its direction of association is higher than a second strength associated with traversing the bond in its direction of association. | 0.916008 |
9,591,065 | 18 | 19 | 18. The one or more non-transitory machine-readable storage media of claim 13 , wherein the functions comprise a control statement that affects a sequence of execution of the SOAP commands. | 18. The one or more non-transitory machine-readable storage media of claim 13 , wherein the functions comprise a control statement that affects a sequence of execution of the SOAP commands. 19. The one or more non-transitory machine-readable storage media of claim 18 , wherein the control statement comprises a loop. | 0.944878 |
7,689,421 | 1 | 6 | 1. In a computing environment, a system comprising, a service that includes a user interface accessible to clients via a network, a text-to-speech engine, and a data store of user-defined voice personas, a user-defined voice persona specifying one of a plurality of base voices and a plurality of voice morphing parameters associated with the base voice, the service configured to receive definitions of the voice personas from users and store the user-defined voice personas in the store of voice personas, where the users use the user interface to input new voice morphing parameters to modify the morphing parameters of the voice personas, the service configured to obtain via the network a user-provided text-to-speech input script comprised of portions of text comprised of respective voice persona identifiers, each voice persona identifier identifying one of the user-defined voice personas including a voice persona having the voice morphing parameters modified by the new voice morphing parameters inputted through the user interface, and the service converting the text-to-speech input script to a speech waveform via a text-to-speech engine based on the identified user-defined voice personas in the data store of voice personas, where portions of text in the text-to-speech script are converted to speech portions of the speech waveform using the user-defined voice personas identified by the voice persona identifiers, respectively. | 1. In a computing environment, a system comprising, a service that includes a user interface accessible to clients via a network, a text-to-speech engine, and a data store of user-defined voice personas, a user-defined voice persona specifying one of a plurality of base voices and a plurality of voice morphing parameters associated with the base voice, the service configured to receive definitions of the voice personas from users and store the user-defined voice personas in the store of voice personas, where the users use the user interface to input new voice morphing parameters to modify the morphing parameters of the voice personas, the service configured to obtain via the network a user-provided text-to-speech input script comprised of portions of text comprised of respective voice persona identifiers, each voice persona identifier identifying one of the user-defined voice personas including a voice persona having the voice morphing parameters modified by the new voice morphing parameters inputted through the user interface, and the service converting the text-to-speech input script to a speech waveform via a text-to-speech engine based on the identified user-defined voice personas in the data store of voice personas, where portions of text in the text-to-speech script are converted to speech portions of the speech waveform using the user-defined voice personas identified by the voice persona identifiers, respectively. 6. The system of claim 1 wherein service receives user-provided binary audio speech data, and the service creates and stores a personal base voice from the user-provided binary audio speech data, the personal base voice being available to be specified as a base voice for a user defined voice persona. | 0.721296 |
9,946,788 | 29 | 31 | 29. The method of claim 17 , further comprising: receiving a plurality of documents from said web browser; and parsing the plurality of documents to generate the key term feature vector of the plurality of documents. | 29. The method of claim 17 , further comprising: receiving a plurality of documents from said web browser; and parsing the plurality of documents to generate the key term feature vector of the plurality of documents. 31. The method of claim 29 , further comprising generating the key term feature vector of the plurality of documents by accessing the plurality of documents and using machine learning to extract information from the content of the plurality of documents. | 0.906755 |
10,095,735 | 8 | 9 | 8. The system of claim 1 , where the value for the input parameter comprises a wild card. | 8. The system of claim 1 , where the value for the input parameter comprises a wild card. 9. The system of claim 8 , wherein the first query comprises a set of queries based at least in part on the wild card. | 0.962563 |
8,740,620 | 1 | 2 | 1. A computer-based language immersion teaching system comprising: (a) a digital processing device that is optionally connected to a computer network, wherein said processing device comprises an operating system configured to perform executable instructions; and (b) a computer program, provided to the digital processing device, including executable instructions that create a language immersion teaching environment, the environment comprising: i. a plurality of learning activities associated with a target language; ii. a software module for providing voiceover audio in the target language; and iii. a software module for providing translation of voiceovers recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment from the target language to a specified language, the specified language selected by the mentor and different from the target language, the software module for providing translation maintaining a list comprising translation of at least 2, at least 5, or at least 10 voiceovers recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment, the list providing access to both written and voiced translation of each voiceover and text voiceover recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment, the software module for providing translation adapted for use by a human mentor to a learner of the target language. | 1. A computer-based language immersion teaching system comprising: (a) a digital processing device that is optionally connected to a computer network, wherein said processing device comprises an operating system configured to perform executable instructions; and (b) a computer program, provided to the digital processing device, including executable instructions that create a language immersion teaching environment, the environment comprising: i. a plurality of learning activities associated with a target language; ii. a software module for providing voiceover audio in the target language; and iii. a software module for providing translation of voiceovers recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment from the target language to a specified language, the specified language selected by the mentor and different from the target language, the software module for providing translation maintaining a list comprising translation of at least 2, at least 5, or at least 10 voiceovers recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment, the list providing access to both written and voiced translation of each voiceover and text voiceover recently played in the language immersion teaching environment and text recently displayed in the language immersion teaching environment, the software module for providing translation adapted for use by a human mentor to a learner of the target language. 2. The computer-based system of claim 1 , wherein access to said software module for providing translation of voiceover, text, or voiceover and text is regulated by said mentor. | 0.82085 |
7,743,057 | 1 | 3 | 1. A computer-implemented method for determining an impact on a simulation model in a modeling environment comprising a plurality of simulation models, said method including: acquiring, by a computer, performance data relating to said plurality of simulation models within a timeframe parameter and a presentation parameter, wherein said performance data includes dependency data and a simulation model score, wherein said plurality of simulation models simulate at least one of outcomes, effectiveness, penetration, utilization, or distribution of marketing strategies based upon at least one of historic, current or probability data of said marketing strategies; analyzing, by said computer, said dependency data relating to said simulation model, having a model identifier; determining, by said computer, individual variables within a first subset of said plurality of simulation models impacted by said dependency data, wherein said dependency data includes bidirectional pointers in a tree of said plurality of simulation models, said plurality of simulation models represented by nodes on said tree, and said dependency data provides interdependencies among said plurality of simulation models, wherein said variables are across said plurality of simulation models, wherein said dependency data depends upon and includes records having an identifier that is based upon said model identifier and that depend at least one of directly or indirectly from said simulation model, and wherein said dependency data relates to a transfer of information exchanged between said simulation model and at least one of said first subset of said plurality of simulation models or a second subset of said plurality of simulation models, wherein said information includes accuracy of said information, an amount of said information, a transfer rate of said information, and a processing rate of said information; analyzing, by said computer, said dependency data relating to said first subset of said plurality of simulation models; determining, by said computer, individual of said variables within said second subset of said plurality of simulation models impacted by said dependency data, wherein said second subset of said plurality of simulation models is dependent upon said first subset of said plurality of simulation models; determining, by said computer, an impact on said first subset of said plurality of simulation models, and said second subset of said plurality of simulation models in response to said analysis of said dependency data; modifying, by said computer, said simulation model score based on said dependency data to create a modified simulation model score; and at least one of: modifying said simulation model or decommissioning said simulation model based on said modified simulation model score. | 1. A computer-implemented method for determining an impact on a simulation model in a modeling environment comprising a plurality of simulation models, said method including: acquiring, by a computer, performance data relating to said plurality of simulation models within a timeframe parameter and a presentation parameter, wherein said performance data includes dependency data and a simulation model score, wherein said plurality of simulation models simulate at least one of outcomes, effectiveness, penetration, utilization, or distribution of marketing strategies based upon at least one of historic, current or probability data of said marketing strategies; analyzing, by said computer, said dependency data relating to said simulation model, having a model identifier; determining, by said computer, individual variables within a first subset of said plurality of simulation models impacted by said dependency data, wherein said dependency data includes bidirectional pointers in a tree of said plurality of simulation models, said plurality of simulation models represented by nodes on said tree, and said dependency data provides interdependencies among said plurality of simulation models, wherein said variables are across said plurality of simulation models, wherein said dependency data depends upon and includes records having an identifier that is based upon said model identifier and that depend at least one of directly or indirectly from said simulation model, and wherein said dependency data relates to a transfer of information exchanged between said simulation model and at least one of said first subset of said plurality of simulation models or a second subset of said plurality of simulation models, wherein said information includes accuracy of said information, an amount of said information, a transfer rate of said information, and a processing rate of said information; analyzing, by said computer, said dependency data relating to said first subset of said plurality of simulation models; determining, by said computer, individual of said variables within said second subset of said plurality of simulation models impacted by said dependency data, wherein said second subset of said plurality of simulation models is dependent upon said first subset of said plurality of simulation models; determining, by said computer, an impact on said first subset of said plurality of simulation models, and said second subset of said plurality of simulation models in response to said analysis of said dependency data; modifying, by said computer, said simulation model score based on said dependency data to create a modified simulation model score; and at least one of: modifying said simulation model or decommissioning said simulation model based on said modified simulation model score. 3. The method of claim 1 , wherein said modified simulation model score is displayed in at least one of: a table, a chart, and a graph. | 0.830402 |
10,078,499 | 1 | 4 | 1. A system comprising: a microprocessor; a memory coupled to the microprocessor; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about at least one keyword contained within each of the plurality of grouping blocks; and a user interface for displaying and manipulating keywords, the user interface providing a general way to display and interact with groups and hierarchies using at least a first inverted “L” shaped block, wherein the at least a first inverted “L” shaped block represents a single keyword concept. | 1. A system comprising: a microprocessor; a memory coupled to the microprocessor; a plurality of grouping blocks wherein each of the plurality of grouping blocks displays summary information about at least one keyword contained within each of the plurality of grouping blocks; and a user interface for displaying and manipulating keywords, the user interface providing a general way to display and interact with groups and hierarchies using at least a first inverted “L” shaped block, wherein the at least a first inverted “L” shaped block represents a single keyword concept. 4. The system of claim 1 further comprising at least one secondary block wherein the at least a first inverted “L” shaped block and the at least one secondary block share a hereditary relationship. | 0.899695 |
7,904,291 | 1 | 7 | 1. A communication supporting apparatus comprising: an input accepting unit that accepts a source language sentence to be translated input by a user; a paraphrase knowledge storing unit that stores paraphrase knowledge in which a source language interpretation which is an interpretation of the semantic content of the source language sentence is associated with a paraphrase interpretation having the same semantic content as the source language interpretation and a different expression form; a source language analyzing unit that analyzes the semantic content of the input source language sentence and outputs the source language interpretation; a paraphrasing unit that obtains the paraphrase interpretation associated with the output source language interpretation from the paraphrase knowledge storing unit, and paraphrases the input source language sentence in a source language paraphrase sentence based on the obtained paraphrase interpretation; and a translation unit that translates the output source language interpretation into a first target language sentence and translates the obtained paraphrase interpretation into a second target language sentence. | 1. A communication supporting apparatus comprising: an input accepting unit that accepts a source language sentence to be translated input by a user; a paraphrase knowledge storing unit that stores paraphrase knowledge in which a source language interpretation which is an interpretation of the semantic content of the source language sentence is associated with a paraphrase interpretation having the same semantic content as the source language interpretation and a different expression form; a source language analyzing unit that analyzes the semantic content of the input source language sentence and outputs the source language interpretation; a paraphrasing unit that obtains the paraphrase interpretation associated with the output source language interpretation from the paraphrase knowledge storing unit, and paraphrases the input source language sentence in a source language paraphrase sentence based on the obtained paraphrase interpretation; and a translation unit that translates the output source language interpretation into a first target language sentence and translates the obtained paraphrase interpretation into a second target language sentence. 7. The communication supporting apparatus according to claim 1 , wherein the paraphrase knowledge storing unit stores paraphrase knowledge in which a morpheme sequence which is a result of a morphological analysis of the source language sentence to be translated is associated with a paraphrase morpheme sequence having semantic content identical to the semantic content represented by the morpheme sequence and a different expression form, the source language analyzing unit outputs the morpheme sequence, which is a result of the morphological analysis of the input source language sentence as the source language interpretation, the paraphrasing unit obtains the paraphrase morpheme sequence associated with the morpheme sequence from the paraphrase knowledge storing unit, and paraphrases the input source language sentence in a source language paraphrase sentence based on the obtained paraphrase morpheme sequence, and the translation unit translates the output morpheme sequence into the first target language sentence and translates the obtained paraphrase morpheme sequence into the second target language sentence. | 0.506151 |
7,877,399 | 11 | 13 | 11. The computer hardware device of claim 1 , wherein the identifying comprises: creating, for each entry in the source leaf path table, a candidate target leaf path list of all entries in the target leaf path table having the same depth as a source leaf path table entry selected to be matched, and searching the candidate target leaf path list for leaf paths that exactly match the selected source leaf path entry. | 11. The computer hardware device of claim 1 , wherein the identifying comprises: creating, for each entry in the source leaf path table, a candidate target leaf path list of all entries in the target leaf path table having the same depth as a source leaf path table entry selected to be matched, and searching the candidate target leaf path list for leaf paths that exactly match the selected source leaf path entry. 13. The computer hardware device of claim 11 , wherein the at least one processor is further configured to perform setting a matched node indicator on all corresponding nodes of each node contained in source and target leaf paths labeled as exactly matched. | 0.895951 |
8,302,080 | 1 | 2 | 1. A method for generating test inputs for applying concolic testing in a program, the method comprising: receiving a program; performing a source-to-source transformation of the program; performing interpretation on the program based on a set of test input values; symbolically executing the program; recording a symbolic constraint for each of one or more conditional expressions encountered during execution of the program further comprising; for each variable occurrence in a Boolean control expression, creating a copy of the expression and setting all other variable occurrences in the expression to their concrete values from the execution, thereby generating a set of expressions where each expression in the set has only a single variable occurrence and each subexpression that does not depend on that variable is replaced with its concrete values; and including analyzing a string operation in the program to identify one or more possible execution paths, generating symbolic inputs representing values of variables in each of the conditional expressions as a numeric expression and a string constraint including generating constraints on string values by modeling string operations using finite state transducers (FSTs) and supplying values from the program's execution in place of intractable sub-expressions, analyzing string operations in the program using the FSTs, wherein the FSTs represent library string functions, and resolving control dependencies by recording a stack trace at a beginning of a function call, wherein functions that called the function are to be added to a set of functions to be analyzed; and generating new inputs to drive the program during a subsequent iteration based on results of solving the recorded string constraints. | 1. A method for generating test inputs for applying concolic testing in a program, the method comprising: receiving a program; performing a source-to-source transformation of the program; performing interpretation on the program based on a set of test input values; symbolically executing the program; recording a symbolic constraint for each of one or more conditional expressions encountered during execution of the program further comprising; for each variable occurrence in a Boolean control expression, creating a copy of the expression and setting all other variable occurrences in the expression to their concrete values from the execution, thereby generating a set of expressions where each expression in the set has only a single variable occurrence and each subexpression that does not depend on that variable is replaced with its concrete values; and including analyzing a string operation in the program to identify one or more possible execution paths, generating symbolic inputs representing values of variables in each of the conditional expressions as a numeric expression and a string constraint including generating constraints on string values by modeling string operations using finite state transducers (FSTs) and supplying values from the program's execution in place of intractable sub-expressions, analyzing string operations in the program using the FSTs, wherein the FSTs represent library string functions, and resolving control dependencies by recording a stack trace at a beginning of a function call, wherein functions that called the function are to be added to a set of functions to be analyzed; and generating new inputs to drive the program during a subsequent iteration based on results of solving the recorded string constraints. 2. The method defined in claim 1 wherein the test input values are dynamically generated input strings based on symbolic string constraints and concrete values gathered from executions of the program. | 0.807692 |
8,941,589 | 45 | 48 | 45. The system of claim 41 , wherein correct pose models are determined for each sensor. | 45. The system of claim 41 , wherein correct pose models are determined for each sensor. 48. The system of claim 45 , wherein a tag is tracked by a plurality of sensors at a plurality of points in time and a plurality of sets of pose models are developed for the tag, wherein each set of pose models comprises a plurality of pose models corresponding to each point in time. | 0.881469 |
8,504,362 | 13 | 18 | 13. A speech recognition method, comprising: determining a speed level of a moving object by using a noise signal at an initial time of speech recognition; if the speed level is equal to or lower than a specific level, enhancing sound quality of an input speech signal by extracting voice activity detection features robust against vehicular noise and applying to the input speech signal a Wiener filter using the extracted voice activity detection features; detecting start and end points of a signal having been subjected to the sound quality enhancement; eliminating sudden noise components occurring when the moving object moves based on a sudden noise Gaussian mixture model; and decoding a signal having been subjected to the sudden noise elimination by using a low-speed/medium-speed acoustic model database, and if the speed level is higher than the specific level, enhancing the sound quality of the input speech signal of the speech recognition by applying a Wiener filter using a Gaussian mixture model; detecting start and end points of a signal having been subjected to the sound quality enhancement; compensating distorted harmonic components of the signal having been subjected to end point detection based on a harmonic Gaussian mixture model; eliminating sudden noise components occurring when the moving object moves based on a sudden noise Gaussian mixture model; and decoding a signal having been subjected to the compensation and the sudden noise elimination by using a high-speed acoustic model database. | 13. A speech recognition method, comprising: determining a speed level of a moving object by using a noise signal at an initial time of speech recognition; if the speed level is equal to or lower than a specific level, enhancing sound quality of an input speech signal by extracting voice activity detection features robust against vehicular noise and applying to the input speech signal a Wiener filter using the extracted voice activity detection features; detecting start and end points of a signal having been subjected to the sound quality enhancement; eliminating sudden noise components occurring when the moving object moves based on a sudden noise Gaussian mixture model; and decoding a signal having been subjected to the sudden noise elimination by using a low-speed/medium-speed acoustic model database, and if the speed level is higher than the specific level, enhancing the sound quality of the input speech signal of the speech recognition by applying a Wiener filter using a Gaussian mixture model; detecting start and end points of a signal having been subjected to the sound quality enhancement; compensating distorted harmonic components of the signal having been subjected to end point detection based on a harmonic Gaussian mixture model; eliminating sudden noise components occurring when the moving object moves based on a sudden noise Gaussian mixture model; and decoding a signal having been subjected to the compensation and the sudden noise elimination by using a high-speed acoustic model database. 18. The speech recognition method of claim 13 , wherein said enhancing the sound quality if the speed level is higher than the specific level includes: estimating a de-noised power spectral density of the input speech signal; calculating a zero-mean power spectral density by using the de-noised power spectral density; calculating a first clean speech power spectral density by using a power spectral density of clean speech and the zero-mean power spectral density; calculating a second clean speech power spectral density by using the de-noised power spectral density and the first clean speech power spectral density; acquiring frequency response characteristics of the Wiener filter using the Gaussian mixture model by using the second clean speech power spectral density; and enhancing the sound quality of the input speech signal based on the frequency response characteristics. | 0.500564 |
7,765,222 | 1 | 13 | 1. A structured query language (SQL) tagging system, implemented in a data processing device associated with a database system, for tagging SQL components of a SQL query string, the system comprising: a parsing unit, of the data processing device, parsing the SQL query string into the SQL components of the SQL query string; an analysis unit, of the data processing device, analyzing the parsed SQL components of the SQL query string and determining tags to be associated with the SQL components of the parsed SQL query string, the analysis unit further applying the determined tags to the associated SQL components of the parsed SQL query string; and a string generation unit, of the data processing device, for concatenating the SQL components of the parsed SQL query string with the associated tags to generate the tagged SQL query string comprising the components of the SQL query string and the applied tags, wherein the tags are extensible markup language (XML) tags selected from a predefined group of XML tags describing components of SQL queries. | 1. A structured query language (SQL) tagging system, implemented in a data processing device associated with a database system, for tagging SQL components of a SQL query string, the system comprising: a parsing unit, of the data processing device, parsing the SQL query string into the SQL components of the SQL query string; an analysis unit, of the data processing device, analyzing the parsed SQL components of the SQL query string and determining tags to be associated with the SQL components of the parsed SQL query string, the analysis unit further applying the determined tags to the associated SQL components of the parsed SQL query string; and a string generation unit, of the data processing device, for concatenating the SQL components of the parsed SQL query string with the associated tags to generate the tagged SQL query string comprising the components of the SQL query string and the applied tags, wherein the tags are extensible markup language (XML) tags selected from a predefined group of XML tags describing components of SQL queries. 13. The system of claim 1 , wherein the data processing device is a report server associated with the database system. | 0.764 |
8,788,270 | 1 | 3 | 1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. | 1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. 3. The method according to claim 1 , wherein determining the emotion state of speaker based on the comparison comprises determining one or more emotions of the speaker based on the comparison. | 0.89128 |
9,467,437 | 1 | 4 | 1. A method for authenticating users in a secure search system for searching a plurality of secure data sources, the method comprising: receiving, using one or more processors, user identification information from a user in a secure enterprise system (SES); providing, using the one or more processors, the user identification information to a plurality of identity management systems in the SES, wherein each of the plurality of identity management systems receives the user identification information through a respective Application Program Interface (API); validating, using the one or more processors, the user against at least one identity management system in the plurality of identity management systems; crawling, using the one or more processors, at least one secure data source in the plurality of secure data sources residing on a plurality of different computer systems that is associated with the at least one identity management system; building, using the one or more processors, an index of documents from the at least one secure data source based on the crawling; receiving, using the one or more processors, a query from the user; calling back, using the one or more processors, at query time into the at least one identity management system to obtain security attribute values for the user; appending, using the one or more processors, the security attribute values for the user to the query and using the appended query to query the index of documents; and determining, using the one or more processors, one or more documents from the index of documents in the plurality of secure data sources, that are responsive to the query and accessible to the user based on the security attribute values for the user and respective security attributes of the one or more documents. | 1. A method for authenticating users in a secure search system for searching a plurality of secure data sources, the method comprising: receiving, using one or more processors, user identification information from a user in a secure enterprise system (SES); providing, using the one or more processors, the user identification information to a plurality of identity management systems in the SES, wherein each of the plurality of identity management systems receives the user identification information through a respective Application Program Interface (API); validating, using the one or more processors, the user against at least one identity management system in the plurality of identity management systems; crawling, using the one or more processors, at least one secure data source in the plurality of secure data sources residing on a plurality of different computer systems that is associated with the at least one identity management system; building, using the one or more processors, an index of documents from the at least one secure data source based on the crawling; receiving, using the one or more processors, a query from the user; calling back, using the one or more processors, at query time into the at least one identity management system to obtain security attribute values for the user; appending, using the one or more processors, the security attribute values for the user to the query and using the appended query to query the index of documents; and determining, using the one or more processors, one or more documents from the index of documents in the plurality of secure data sources, that are responsive to the query and accessible to the user based on the security attribute values for the user and respective security attributes of the one or more documents. 4. The method according to claim 1 , further comprising: receiving, using the one or more processors, user identification information from an additional user in the SES; determining that the additional user cannot be validated against the at least one identity management system; and denying the additional user access to the at least one secure data source. | 0.544529 |
10,157,609 | 15 | 16 | 15. The computer-readable storage device of claim 14 , wherein the user data is collected through at least one of: harvesting the textual data from at least one of: emails, word processing documents, or spreadsheets associated with the user employing trigrams; or receiving a user spoken text passage. | 15. The computer-readable storage device of claim 14 , wherein the user data is collected through at least one of: harvesting the textual data from at least one of: emails, word processing documents, or spreadsheets associated with the user employing trigrams; or receiving a user spoken text passage. 16. The computer-readable storage device of claim 15 , wherein the filtered data provided to the system developer includes trigrams containing words from original language models and a list of added words. | 0.933999 |
9,015,597 | 15 | 16 | 15. The non-transitory computer-readable medium of claim 12 , wherein the operations further comprise: receiving a second communication rule identifying a second type of relationship and a strength of relationship required to contact the first party via a type of communication; receiving, from the second party via the type of communication identified by the second communication rule, a second request to contact the first party; determining whether the relationship type of the social relationship between the first party and the second party meets the second type of relationship identified by the second communication rule and whether the relationship strength of the social relationship between the first party and the second party meets the strength of relationship identified by the second communication rule; and in response to determining that the relationship type of the social relationship between the first party and the second party does not meet the second type of relationship identified by the second communication rule, restricting the second party from contacting the first party via the type of communication identified by the second communication rule. | 15. The non-transitory computer-readable medium of claim 12 , wherein the operations further comprise: receiving a second communication rule identifying a second type of relationship and a strength of relationship required to contact the first party via a type of communication; receiving, from the second party via the type of communication identified by the second communication rule, a second request to contact the first party; determining whether the relationship type of the social relationship between the first party and the second party meets the second type of relationship identified by the second communication rule and whether the relationship strength of the social relationship between the first party and the second party meets the strength of relationship identified by the second communication rule; and in response to determining that the relationship type of the social relationship between the first party and the second party does not meet the second type of relationship identified by the second communication rule, restricting the second party from contacting the first party via the type of communication identified by the second communication rule. 16. The non-transitory computer-readable medium of claim 15 , wherein the type of communication identified by the second communication rule comprises a mobile communication, a text message, an instant message, or an email. | 0.954731 |
8,442,940 | 2 | 4 | 2. The method of claim 1 wherein the mapping includes sharing data describing the second ontology of the semantic network and the first ontology of the NLP system. | 2. The method of claim 1 wherein the mapping includes sharing data describing the second ontology of the semantic network and the first ontology of the NLP system. 4. The method of claim 2 wherein the second ontology of the semantic network and the first ontology of the NLP system are automatically synchronized responsive to a change in content of either the semantic network or the NLP system. | 0.933295 |
10,074,361 | 18 | 20 | 18. The method of claim 15 , wherein the calculating of the acoustic score of the first speech comprises using two acoustic scores of frames of the second speech as acoustic scores of two frames of the first speech that correspond to the two frames of the second speech and using at least one acoustic score of the frames of the second speech for an acoustic score of an adjacent frame, of the first speech, that is adjacent to the two frames of the first speech. | 18. The method of claim 15 , wherein the calculating of the acoustic score of the first speech comprises using two acoustic scores of frames of the second speech as acoustic scores of two frames of the first speech that correspond to the two frames of the second speech and using at least one acoustic score of the frames of the second speech for an acoustic score of an adjacent frame, of the first speech, that is adjacent to the two frames of the first speech. 20. The method of claim 18 , wherein the calculating of the acoustic score of the first speech comprises using, as the acoustic score of the adjacent frame, a statistical value of the acoustic scores of the two frames of the first speech or acoustic scores of the two frames of the second speech, or using a statistical value obtained by applying a weighted value to the acoustic scores of the two frames of the first speech, or to the acoustic scores of the two frames of the second speech, based on a determined temporal distance between the adjacent frame and the two frames of the first speech. | 0.751455 |
8,831,929 | 11 | 12 | 11. The system of claim 8 , wherein the operations further comprise: receiving an additional composition input after receiving the composition input, the additional composition input including one or more additional characters in the source language; determining modified candidate selections for the two or more target languages based on the composition input and the additional composition input; determining a modified language context value for each of the two or more target languages by evaluating the modified candidate selections against the language models for the two or more target languages; selecting a modified set of candidate selections based on the modified language context values, the modified set of candidate selections including at least one modified candidate selection in each of the two or more target languages; and outputting the set of modified candidate selections in a single, interleaved list of modified candidate selections arranged based on a relative likelihood that a specific modified candidate selection was intended from the composition input and the additional composition input. | 11. The system of claim 8 , wherein the operations further comprise: receiving an additional composition input after receiving the composition input, the additional composition input including one or more additional characters in the source language; determining modified candidate selections for the two or more target languages based on the composition input and the additional composition input; determining a modified language context value for each of the two or more target languages by evaluating the modified candidate selections against the language models for the two or more target languages; selecting a modified set of candidate selections based on the modified language context values, the modified set of candidate selections including at least one modified candidate selection in each of the two or more target languages; and outputting the set of modified candidate selections in a single, interleaved list of modified candidate selections arranged based on a relative likelihood that a specific modified candidate selection was intended from the composition input and the additional composition input. 12. The system of claim 11 , wherein the single, interleaved list of modified candidate selections is different than the single, interleaved list of candidate selections. | 0.966641 |
8,182,270 | 55 | 57 | 55. A computer program product as recited in claim 54 , wherein the characteristic is at least one of: (i) a learning pace of the learner; (ii) a background of the learner; (iii) a style of learning of the learner; and (iv) a learning progress of the learner. | 55. A computer program product as recited in claim 54 , wherein the characteristic is at least one of: (i) a learning pace of the learner; (ii) a background of the learner; (iii) a style of learning of the learner; and (iv) a learning progress of the learner. 57. A computer program product as recited in claim 55 , wherein the association is between available components of the educational content based on specific properties of the available components. | 0.978631 |
9,336,321 | 17 | 23 | 17. Non-transitory computer storage having stored thereon computer-executable instructions configured to execute a process on a network computing component comprising one or more computing devices, the process comprising: retrieving, from an electronic data store in communication with the network computing component, a representation of a previously accessed network resource satisfying a search request received from a client computing device, wherein the client computing device accessed the previously accessed network resource during a previous browsing session in which the client computing device also accessed one or more contextual network resources from different content servers than the previously accessed network resource, and wherein representations of the previously accessed network resource and each of the one or more contextual network resources are stored in the electronic data store; retrieving, from the electronic data store, a representation of a first contextual network resource of the one or more contextual network resources, wherein the representation of the first contextual network resource is retrieved based at least on the first contextual network resource being accessed during the same previous browsing session as the previously accessed network resource satisfying the search request; and transmit, to the client computing device, a response to the search request, the response comprising the representation of the previously accessed network resource satisfying the search request and the representation of the first contextual network resource. | 17. Non-transitory computer storage having stored thereon computer-executable instructions configured to execute a process on a network computing component comprising one or more computing devices, the process comprising: retrieving, from an electronic data store in communication with the network computing component, a representation of a previously accessed network resource satisfying a search request received from a client computing device, wherein the client computing device accessed the previously accessed network resource during a previous browsing session in which the client computing device also accessed one or more contextual network resources from different content servers than the previously accessed network resource, and wherein representations of the previously accessed network resource and each of the one or more contextual network resources are stored in the electronic data store; retrieving, from the electronic data store, a representation of a first contextual network resource of the one or more contextual network resources, wherein the representation of the first contextual network resource is retrieved based at least on the first contextual network resource being accessed during the same previous browsing session as the previously accessed network resource satisfying the search request; and transmit, to the client computing device, a response to the search request, the response comprising the representation of the previously accessed network resource satisfying the search request and the representation of the first contextual network resource. 23. The non-transitory computer storage of claim 17 , wherein the search request comprises a search term limiting the results to one of landing pages or detail pages, wherein a landing page comprises the default web page presented to a client computing device when no detail page is requested. | 0.501701 |
9,240,016 | 22 | 24 | 22. A non-transitory computer readable storage medium having instructions stored thereon that, when executed by a processor in a host organization, the instructions cause the host organization to perform operations comprising: exposing an interface to client devices operating remotely from the host organization, wherein the interface is accessible by the client devices via a public Internet; executing a predictive database at the host organization as an on-demand cloud based service for one or more subscribers; authenticating one of the client devices by verifying the client device is associated with one of the subscribers and based further on authentication credentials for the respective subscriber; processing a dataset of columns and rows to generate indices on behalf of the authenticated subscriber, the indices representing probabilistic relationships between the rows and the columns of the dataset, wherein the processing comprises: (i) processing the dataset by iteratively learning joint probability distributions over the dataset to generate the indices, (ii) periodically determining a predictive quality measure of the indices generated by the processing of the dataset, and (iii) terminating processing of the dataset when the predictive quality measure attains a specified threshold; receiving a prediction request from the authenticated subscriber via the interface; executing a query against the indices of the predictive database generated from the dataset; returning a prediction result of the query to the authenticated subscriber responsive to the prediction request; and returning a notification with the prediction result indicating processing of the stored dataset has not yet completed or returning a notification with the prediction result indicating the predictive quality measure is below the specified threshold, or returning both with the prediction result. | 22. A non-transitory computer readable storage medium having instructions stored thereon that, when executed by a processor in a host organization, the instructions cause the host organization to perform operations comprising: exposing an interface to client devices operating remotely from the host organization, wherein the interface is accessible by the client devices via a public Internet; executing a predictive database at the host organization as an on-demand cloud based service for one or more subscribers; authenticating one of the client devices by verifying the client device is associated with one of the subscribers and based further on authentication credentials for the respective subscriber; processing a dataset of columns and rows to generate indices on behalf of the authenticated subscriber, the indices representing probabilistic relationships between the rows and the columns of the dataset, wherein the processing comprises: (i) processing the dataset by iteratively learning joint probability distributions over the dataset to generate the indices, (ii) periodically determining a predictive quality measure of the indices generated by the processing of the dataset, and (iii) terminating processing of the dataset when the predictive quality measure attains a specified threshold; receiving a prediction request from the authenticated subscriber via the interface; executing a query against the indices of the predictive database generated from the dataset; returning a prediction result of the query to the authenticated subscriber responsive to the prediction request; and returning a notification with the prediction result indicating processing of the stored dataset has not yet completed or returning a notification with the prediction result indicating the predictive quality measure is below the specified threshold, or returning both with the prediction result. 24. The non-transitory computer readable storage medium of claim 22 , wherein the instructions cause the host organization to perform operations further comprising: receiving the dataset from the authenticated subscriber; wherein receiving the dataset comprises at least one of: (a) receiving the dataset as a table having the columns and rows, (b) receiving a spreadsheet document and extracting the dataset from the spreadsheet document, (c) receiving the dataset as a binary file created by a database, (d) receiving one or more queries to a database and responsively receiving the dataset by executing the one or more queries against the database and capturing a record set returned by the one or more queries as the dataset, (e) receiving a name of a table in a database and retrieving the table from the database as the dataset, (f) receiving search parameters for a specified website and responsively querying the search parameters against the specified website and capturing search results as the dataset, and (g) receiving a link and authentication credentials for a remote repository and responsively authenticating with the remote repository and retrieving the dataset via the link. | 0.513855 |
9,286,527 | 1 | 2 | 1. A computer-implemented method comprising: obtaining, for a sequence of strokes that represent a handwritten input, cut point data indicating one or more particular candidate cut points that are identified within the sequence of strokes; obtaining, for the one or more of the particular candidate cut points, feature data indicating one or more features of the particular candidate cut point; for each of the one or more particular candidate cut points, providing the feature data to a classifier that is trained to predict, based on one or more features of a candidate cut point, a likelihood of the candidate cut point being a correct cut point; for each of the one or more particular candidate cut points, receiving, from the classifier, data indicating the likelihood that the particular candidate cut point is a correct cut point; selecting a set of one or more of the particular candidate cut points whose respective likelihoods satisfy a threshold; and using the set of candidate cut points to segment the sequence of strokes. | 1. A computer-implemented method comprising: obtaining, for a sequence of strokes that represent a handwritten input, cut point data indicating one or more particular candidate cut points that are identified within the sequence of strokes; obtaining, for the one or more of the particular candidate cut points, feature data indicating one or more features of the particular candidate cut point; for each of the one or more particular candidate cut points, providing the feature data to a classifier that is trained to predict, based on one or more features of a candidate cut point, a likelihood of the candidate cut point being a correct cut point; for each of the one or more particular candidate cut points, receiving, from the classifier, data indicating the likelihood that the particular candidate cut point is a correct cut point; selecting a set of one or more of the particular candidate cut points whose respective likelihoods satisfy a threshold; and using the set of candidate cut points to segment the sequence of strokes. 2. The method of claim 1 , wherein the one or more features of the candidate cut point comprises: a coordinate of the candidate cut point; a type of cut point associated with the candidate cut point; a curvature of the handwritten input at the candidate cut point; or an input speed of the handwritten input at the candidate cut point. | 0.680952 |
9,053,101 | 15 | 16 | 15. A system for converting a first version of a database to a third version, including: a processor configured to: select a translation path from a plurality of translation paths based on either a shortest path or a first path found, each translation path proceeding from the first version of the database to the third version of the database via a second version of the database; and traverse the selected translation path comprising: convert the first version of the database to the second version of the database; and convert the second version of the database to the third version of the database, wherein the database is part of a cluster including a plurality of databases; wherein in the event that the database fails at being upgraded, another database of the cluster is available to be upgraded from the first version to the third version; wherein in the event that each database of the cluster fails to be upgraded from the first version to the third version, a determination is made that the cluster is unable to be upgraded; wherein each of the first version of the database, the third version of the database, and the second version of the database is associated with a fully migrated version of the database; wherein for each translation path, the first version of the database, the second version of the database, and the third version of the database are different from each other; and wherein for each translation path, the second version of the database is different from the second version of the database of another translation path; and a memory that is coupled with the processor, wherein the memory provides the processor with instructions. | 15. A system for converting a first version of a database to a third version, including: a processor configured to: select a translation path from a plurality of translation paths based on either a shortest path or a first path found, each translation path proceeding from the first version of the database to the third version of the database via a second version of the database; and traverse the selected translation path comprising: convert the first version of the database to the second version of the database; and convert the second version of the database to the third version of the database, wherein the database is part of a cluster including a plurality of databases; wherein in the event that the database fails at being upgraded, another database of the cluster is available to be upgraded from the first version to the third version; wherein in the event that each database of the cluster fails to be upgraded from the first version to the third version, a determination is made that the cluster is unable to be upgraded; wherein each of the first version of the database, the third version of the database, and the second version of the database is associated with a fully migrated version of the database; wherein for each translation path, the first version of the database, the second version of the database, and the third version of the database are different from each other; and wherein for each translation path, the second version of the database is different from the second version of the database of another translation path; and a memory that is coupled with the processor, wherein the memory provides the processor with instructions. 16. The system as recited in claim 15 , wherein the first version is an existing version of the database. | 0.790837 |
7,739,257 | 1 | 7 | 1. A method of retrieving documents from a database comprising the steps of: a. semantically editing a document to create at least one searchable compound word that contains information contextually relevant to the contents of the document; b. associating the at least one compound word with the document thereby to produce an enhanced document; c. storing the enhanced document in an enhanced document database; d. providing a semantic query editor that is operable to receive a query input by a searcher, and using said query editor being operable to convert the query into at least one query searchable compound words, that contains information contextually relevant to the query; e. providing a search means to search the enhanced document database, searching the enhanced document database to match the at least one query searchable compound word with compound words associated with a document and thereby locate specific documents in the database containing the at least one compound search word; and f. presenting the specific documents to the searcher, wherein there is provided a semantic rule engine that is operable to generate and store rules each of which includes at least one compound word derived from at least one of the enhanced documents, and the method comprises the further steps, prior to step (f), of semantic searching a selected enhanced document to generate at least one searchable compound word associated with the selected enhanced document, searching the rules to find at least one rule specifying the at least one searchable compound word and at least one additional compound word to generate a set of candidate rules as rules which are possibly relevant to the selected enhanced document, and processing the set of candidate rules and adding to the selected enhanced document additional compound words specified in at least one of the rules in the set of candidate rules where the respective rule is satisfied for the selected enhanced document. | 1. A method of retrieving documents from a database comprising the steps of: a. semantically editing a document to create at least one searchable compound word that contains information contextually relevant to the contents of the document; b. associating the at least one compound word with the document thereby to produce an enhanced document; c. storing the enhanced document in an enhanced document database; d. providing a semantic query editor that is operable to receive a query input by a searcher, and using said query editor being operable to convert the query into at least one query searchable compound words, that contains information contextually relevant to the query; e. providing a search means to search the enhanced document database, searching the enhanced document database to match the at least one query searchable compound word with compound words associated with a document and thereby locate specific documents in the database containing the at least one compound search word; and f. presenting the specific documents to the searcher, wherein there is provided a semantic rule engine that is operable to generate and store rules each of which includes at least one compound word derived from at least one of the enhanced documents, and the method comprises the further steps, prior to step (f), of semantic searching a selected enhanced document to generate at least one searchable compound word associated with the selected enhanced document, searching the rules to find at least one rule specifying the at least one searchable compound word and at least one additional compound word to generate a set of candidate rules as rules which are possibly relevant to the selected enhanced document, and processing the set of candidate rules and adding to the selected enhanced document additional compound words specified in at least one of the rules in the set of candidate rules where the respective rule is satisfied for the selected enhanced document. 7. The method according to claim 1 comprising the step of the semantic rule engine capturing at least some of the rules by recording edits made by rule generating users to documents stored in the database. | 0.900966 |
8,078,453 | 1 | 15 | 1. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from at least one of emotional state or emotional tone represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the at least one of emotional state or emotional tone generating with a computer an output communication pertaining to the risk posed by the person from the at least one of emotional state or emotional tone of the at least one communication. | 1. A method of computer analysis of at least one communication originated from a person, comprising: receiving with a computer the at least one communication with each communication being comprised of a group of words originated by the person; processing a text of the received group of words in each of the received at least one communication with a computer to determine risk posed by the person from at least one of emotional state or emotional tone represented by the text of the group of words in each of the at least one communication; and in response to the determined risk posed by the person from the at least one of emotional state or emotional tone generating with a computer an output communication pertaining to the risk posed by the person from the at least one of emotional state or emotional tone of the at least one communication. 15. A method in accordance with claim 1 wherein: the at least one output communication is used to alter the at least one communication. | 0.756318 |
8,854,635 | 1 | 3 | 1. A document processing device comprising: a document data acquiring part for acquiring document data; a character string extracting part for extracting character strings that correspond to at least one of a heading, a title, or a subtitle as bookmark candidate character strings from said document data acquired by said document data acquiring part; a format creating part for deriving respective features of said bookmark candidate character strings extracted by said character string extracting part, categorizing said bookmark candidate character strings having a common feature into one group, and creating a format for the group based on the common feature of the group; a display part on which said bookmark candidate character strings extracted by said character string extracting part are displayed in a list form, and on which the format corresponding to said bookmark candidate character strings created by said format creating part is displayed; and a format correcting part for receiving a correcting operation of a user given to the format displayed on said display part and correcting the format in response to the correcting operation, wherein said character string extracting part extracts the character strings again that have the common feature of the format corrected by said format correcting part from said document data as said bookmark candidate character strings. | 1. A document processing device comprising: a document data acquiring part for acquiring document data; a character string extracting part for extracting character strings that correspond to at least one of a heading, a title, or a subtitle as bookmark candidate character strings from said document data acquired by said document data acquiring part; a format creating part for deriving respective features of said bookmark candidate character strings extracted by said character string extracting part, categorizing said bookmark candidate character strings having a common feature into one group, and creating a format for the group based on the common feature of the group; a display part on which said bookmark candidate character strings extracted by said character string extracting part are displayed in a list form, and on which the format corresponding to said bookmark candidate character strings created by said format creating part is displayed; and a format correcting part for receiving a correcting operation of a user given to the format displayed on said display part and correcting the format in response to the correcting operation, wherein said character string extracting part extracts the character strings again that have the common feature of the format corrected by said format correcting part from said document data as said bookmark candidate character strings. 3. The document processing device according to claim 1 , wherein the features of each of said character strings derived by said format creating part include a positional condition indicating a range of the character string from a reference position in a document. | 0.67125 |
8,125,669 | 14 | 16 | 14. A method comprising: A processor generating a webpage that includes a canonical document object model tree; loading the webpage through a browser, wherein an action sequence performed by the browser is simulated, and states of the browser are tracked; and checking for spoofs when the loading is performed by examining graphic user interface (GUI) logic and identifying flaws in the logic that expose security damage, the action sequence and the checking for spoofs implemented using binary instrumentation tools. | 14. A method comprising: A processor generating a webpage that includes a canonical document object model tree; loading the webpage through a browser, wherein an action sequence performed by the browser is simulated, and states of the browser are tracked; and checking for spoofs when the loading is performed by examining graphic user interface (GUI) logic and identifying flaws in the logic that expose security damage, the action sequence and the checking for spoofs implemented using binary instrumentation tools. 16. The method of claim 14 further comprising repeating generating the webpage by generating another webpage. | 0.774793 |
8,566,270 | 6 | 9 | 6. A computer-implemented method of text classification based on sparse representation employing at least one hardware implemented computer processor, the method comprising: representing in a computer process an input text document as a document feature vector y; accessing in a computer process a category dictionary H of possible examples [h 1 ; h 2 ; . . . ; h n ] of the document feature vector y; and automatically classifying in a computer process the input text document based on a sparse representation text classification approach to solve for y=Hβ and enforcing a sparseness condition β to select examples from the dictionary H to describe the document feature vector y. | 6. A computer-implemented method of text classification based on sparse representation employing at least one hardware implemented computer processor, the method comprising: representing in a computer process an input text document as a document feature vector y; accessing in a computer process a category dictionary H of possible examples [h 1 ; h 2 ; . . . ; h n ] of the document feature vector y; and automatically classifying in a computer process the input text document based on a sparse representation text classification approach to solve for y=Hβ and enforcing a sparseness condition β to select examples from the dictionary H to describe the document feature vector y. 9. A method according to claim 6 , wherein the text classification approach uses a maximum l 2 classification rule that assigns the document feature vector y to a best class i* within the category dictionary H which has largest l 2 norm based on a selector δi (β)ε m to compute an 1 2 norm for β for a class i as ∥δi (β)∥ 2 . | 0.575718 |
9,966,063 | 15 | 19 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: selecting, based on a microphone type and a current location of a speaker, a user profile from a plurality of user profiles, wherein the user profile is associated with the speaker; and performing, via a processor, speech recognition on speech received from the speaker using the user profile. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: selecting, based on a microphone type and a current location of a speaker, a user profile from a plurality of user profiles, wherein the user profile is associated with the speaker; and performing, via a processor, speech recognition on speech received from the speaker using the user profile. 19. The computer-readable storage device of claim 15 , wherein the computer-readable storage device stores additional instructions stored which, when executed by the computing device, cause the computing device to perform operations further comprising modifying an aspect of the speech recognition based on a speech adaption associated with the speaker. | 0.501412 |
9,471,570 | 10 | 11 | 10. The method of claim 9 , further comprising: retrieving a fourth query suggestion from the search record; and providing the fourth query suggestion to the user, wherein the fourth query suggestion is to be presented together with the search result to the user. | 10. The method of claim 9 , further comprising: retrieving a fourth query suggestion from the search record; and providing the fourth query suggestion to the user, wherein the fourth query suggestion is to be presented together with the search result to the user. 11. The method of claim 10 , wherein the fourth query suggestion is one of the more than one query suggestion. | 0.952586 |
4,437,155 | 1 | 4 | 1. In a data processing system including a host processor for issuing addressing signals specifying data to be accessed, a mass memory, a cache store for storing segments, and a segment descriptor table for storing segment descriptors, there being a segment descriptor associated with each data segment in said cache store and including age information defining, from the most recently accessed to the least recently accessed, the relative lengths of time since each associated data segment has been accessed, the system including means for transferring to said mass memory the least recently accessed segments in said cache store in order to make room for more data segments, the improvement comprising: means connected to said host processor, said mass memory and said cache store for transferring from said mass memory to said cache store not only a data segment containing data specified by said addressing signals but not resident in said store, but also a number of additional segments; and, age modifying means for modifying said age information in said segment descriptors each time data segments are transferred from said mass memory to said cache store to produce modified age information, said modified age information indicating that the data segment containing the data specified by said addressing signals is the most recently accessed data segment, and indicating that said number of additional segments have an age intermediate the most recently accessed and the least recently accessed. | 1. In a data processing system including a host processor for issuing addressing signals specifying data to be accessed, a mass memory, a cache store for storing segments, and a segment descriptor table for storing segment descriptors, there being a segment descriptor associated with each data segment in said cache store and including age information defining, from the most recently accessed to the least recently accessed, the relative lengths of time since each associated data segment has been accessed, the system including means for transferring to said mass memory the least recently accessed segments in said cache store in order to make room for more data segments, the improvement comprising: means connected to said host processor, said mass memory and said cache store for transferring from said mass memory to said cache store not only a data segment containing data specified by said addressing signals but not resident in said store, but also a number of additional segments; and, age modifying means for modifying said age information in said segment descriptors each time data segments are transferred from said mass memory to said cache store to produce modified age information, said modified age information indicating that the data segment containing the data specified by said addressing signals is the most recently accessed data segment, and indicating that said number of additional segments have an age intermediate the most recently accessed and the least recently accessed. 4. The improvement as claimed in claim 1 wherein said data segments each comprise a plurality of data words. | 0.927322 |
7,840,442 | 1 | 13 | 1. A method comprising: gathering, by at least one processor, click information associated with a member of a search result set having a plurality of members, the search result set produced in response to a search; determining, by the at least one processor, relative responsiveness of the member, compared with the other members of the search result set, based on the click information and on a position of the member in an ordering for display of the search result set; generating, by the at least one processor, a score for association with the member that reflects the relative responsiveness of the member to the search; and using, by the at least one processor, the score to affect a response to a subsequent search. | 1. A method comprising: gathering, by at least one processor, click information associated with a member of a search result set having a plurality of members, the search result set produced in response to a search; determining, by the at least one processor, relative responsiveness of the member, compared with the other members of the search result set, based on the click information and on a position of the member in an ordering for display of the search result set; generating, by the at least one processor, a score for association with the member that reflects the relative responsiveness of the member to the search; and using, by the at least one processor, the score to affect a response to a subsequent search. 13. The method of claim 1 , wherein the click information comprises clicks of a mapped catalog click type for clicks on a product page associated with a catalog page. | 0.714777 |
6,144,938 | 1 | 13 | 1. An apparatus for a voice user interface with personality, the apparatus comprising: logic that provides a voice user interface, the voice user interface outputting first voice signals, and the voice user interface recognizing speech signals; logic that provides a personality, the logic that provides the personality interfacing with the logic that provides the voice user interface to provide the voice user interface with a verbal personality; and a recognition grammar stored in a memory, the recognition grammar comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, and the recognition grammar being selected based on the personality of the virtual assistant. | 1. An apparatus for a voice user interface with personality, the apparatus comprising: logic that provides a voice user interface, the voice user interface outputting first voice signals, and the voice user interface recognizing speech signals; logic that provides a personality, the logic that provides the personality interfacing with the logic that provides the voice user interface to provide the voice user interface with a verbal personality; and a recognition grammar stored in a memory, the recognition grammar comprising multiple phrases that a virtual assistant with a personality can recognize when spoken by a user, and the recognition grammar being selected based on the personality of the virtual assistant. 13. The apparatus as recited in claim 1 wherein the logic that provides the personality comprises selecting a prompt, the prompt comprising an appropriate temporal prompt. | 0.753602 |
8,583,448 | 6 | 10 | 6. The search engine method in claim 1 wherein: the at least one search engine enhancement service that is selected comprises providing a custom toolbar associated with said website. | 6. The search engine method in claim 1 wherein: the at least one search engine enhancement service that is selected comprises providing a custom toolbar associated with said website. 10. The method in claim 6 additionally comprising: causing, by way of said custom toolbar, display of information specific to said website. | 0.964899 |
9,508,346 | 17 | 18 | 17. An adaptive transcription system for a call center, the system comprising: an audio data source upon which a plurality of audio data files are stored, the audio data files corresponding to recorded customer service interactions between one or more customers and one or more customer service agents; a processor that receives the plurality of audio data files and applies a language model to the plurality of audio data files to produce transcriptions of each of the plurality of audio data files; and a non-transient computer readable medium communicatively connected to the processor and programmed with computer readable code that when executed by the processor causes the processor to: evaluate a quality of each of the plurality of audio data file transcriptions by assigning each transcription a score or value based on the conformity between the language model used for transcription and the audio data; select at least one best transcription from the transcriptions of each of the plurality of audio data files; calculate statistics from the selected at least one best transcription; modify the language model based upon the calculated statistics; and apply the modified language model in subsequent transcriptions. | 17. An adaptive transcription system for a call center, the system comprising: an audio data source upon which a plurality of audio data files are stored, the audio data files corresponding to recorded customer service interactions between one or more customers and one or more customer service agents; a processor that receives the plurality of audio data files and applies a language model to the plurality of audio data files to produce transcriptions of each of the plurality of audio data files; and a non-transient computer readable medium communicatively connected to the processor and programmed with computer readable code that when executed by the processor causes the processor to: evaluate a quality of each of the plurality of audio data file transcriptions by assigning each transcription a score or value based on the conformity between the language model used for transcription and the audio data; select at least one best transcription from the transcriptions of each of the plurality of audio data files; calculate statistics from the selected at least one best transcription; modify the language model based upon the calculated statistics; and apply the modified language model in subsequent transcriptions. 18. The system of claim 17 , further comprising: a large vocabulary continuous speech recognition decoder operating on the processor to create at least one work lattice from each audio file; and a minimum Bayes risk decoder operating on the processor to create at least one confusion network from each word lattice; wherein the processor evaluating the confusion network to determine a conformity between the audio data file and the at least one transcription model and calculates a transcription quality score for each of the audio files from the determined conformity. | 0.500876 |
10,095,692 | 1 | 9 | 1. A computer implemented method comprising: a) receiving by a computer comprising a processor and a memory a set of original templates and storing the set of original templates in the memory; b) accessing by a computer a set of databases comprising a large corpus of documents and searching by a search engine the set of databases based on the set of original templates; c) identifying by the search engine a set of candidate sentences from a set of documents in the corpus by using a similarity measure to determine a similarity score, wherein the similarity measure comprises extracting a first set of tokens from at least one template from the set of original templates and extracting a second set of tokens from at least one candidate sentence from the set of candidate sentences, the first set of tokens and the second set of tokens each comprising a set of token-level 1 to token-level n grams, and further comprises comparing the extracted first set of tokens with the extracted second set of tokens by determining a first value representing an intersection of the extracted first and second sets of tokens, and dividing that first value by a second value derived by applying a minimum function to the extracted first and second sets of tokens to determine the similarity score; d) automatically eliminating candidate sentences from the set of candidate sentences based upon a similarity score threshold to arrive at a reduced set of candidate sentences determined to be syntactically similar to the at least one template; and e) processing the reduced set of candidate sentences to generate a set of natural language generation templates that, when processed by a computer and combined with a set of determined words or phrases, generate natural language text. | 1. A computer implemented method comprising: a) receiving by a computer comprising a processor and a memory a set of original templates and storing the set of original templates in the memory; b) accessing by a computer a set of databases comprising a large corpus of documents and searching by a search engine the set of databases based on the set of original templates; c) identifying by the search engine a set of candidate sentences from a set of documents in the corpus by using a similarity measure to determine a similarity score, wherein the similarity measure comprises extracting a first set of tokens from at least one template from the set of original templates and extracting a second set of tokens from at least one candidate sentence from the set of candidate sentences, the first set of tokens and the second set of tokens each comprising a set of token-level 1 to token-level n grams, and further comprises comparing the extracted first set of tokens with the extracted second set of tokens by determining a first value representing an intersection of the extracted first and second sets of tokens, and dividing that first value by a second value derived by applying a minimum function to the extracted first and second sets of tokens to determine the similarity score; d) automatically eliminating candidate sentences from the set of candidate sentences based upon a similarity score threshold to arrive at a reduced set of candidate sentences determined to be syntactically similar to the at least one template; and e) processing the reduced set of candidate sentences to generate a set of natural language generation templates that, when processed by a computer and combined with a set of determined words or phrases, generate natural language text. 9. The method of claim 1 further comprising wherein the large corpus of documents is a news corpus. | 0.933108 |
7,627,827 | 8 | 12 | 8. A computer-readable storage medium having computer-executable instructions which, when executed on a computer, will cause the computer to perform a method of providing an intelligent user interface based on a context of a document, the method comprising: opening the document in a context that only facilitates reading by a user; disabling editing commands associated with the document; hiding at least one of the editing commands associated with document to indicate the context that only facilitates reading and to prevent the document from being edited in the context that only facilitates reading, wherein the at least one of the editing commands comprises a document font command; disabling typing functionality for editing the document, wherein disabling the typing functionality comprises blocking the user from typing to prevent accidental edits that will not be saved in the context that only facilitates reading and to prevent the initiation of a prompt requesting the user of the document to save the document in the context that only facilitates reading; displaying a transition button via the intelligent user interface, the transition button operative when selected to initiate transition of the document between the context that only facilitates reading and a context that facilitates editing; receiving a selection of the transition button; in response to receiving the selection, transitioning from the context that only facilitates reading to the context that facilitates editing wherein transitioning to the context that facilitates editing comprises enabling at least one of the typing functionality for editing the document or the editing commands; transitioning from the context that facilitates editing back to the context that only facilitates reading; determining whether the document is digitally signed, wherein when the document is digitally signed, displaying the transition button comprises displaying a transition button operative, when selected, to invalidate the digital signature and in response to invalidating the digital signature, automatically complete a transition of the document to the context that facilitates editing; and saving a copy of the document when the document is in the context that facilitates editing in response to receiving the selection thereby displaying a ‘Save As’ dialog, wherein the document resides on a client computer and the copy of the document is saved on another computer. | 8. A computer-readable storage medium having computer-executable instructions which, when executed on a computer, will cause the computer to perform a method of providing an intelligent user interface based on a context of a document, the method comprising: opening the document in a context that only facilitates reading by a user; disabling editing commands associated with the document; hiding at least one of the editing commands associated with document to indicate the context that only facilitates reading and to prevent the document from being edited in the context that only facilitates reading, wherein the at least one of the editing commands comprises a document font command; disabling typing functionality for editing the document, wherein disabling the typing functionality comprises blocking the user from typing to prevent accidental edits that will not be saved in the context that only facilitates reading and to prevent the initiation of a prompt requesting the user of the document to save the document in the context that only facilitates reading; displaying a transition button via the intelligent user interface, the transition button operative when selected to initiate transition of the document between the context that only facilitates reading and a context that facilitates editing; receiving a selection of the transition button; in response to receiving the selection, transitioning from the context that only facilitates reading to the context that facilitates editing wherein transitioning to the context that facilitates editing comprises enabling at least one of the typing functionality for editing the document or the editing commands; transitioning from the context that facilitates editing back to the context that only facilitates reading; determining whether the document is digitally signed, wherein when the document is digitally signed, displaying the transition button comprises displaying a transition button operative, when selected, to invalidate the digital signature and in response to invalidating the digital signature, automatically complete a transition of the document to the context that facilitates editing; and saving a copy of the document when the document is in the context that facilitates editing in response to receiving the selection thereby displaying a ‘Save As’ dialog, wherein the document resides on a client computer and the copy of the document is saved on another computer. 12. The computer-readable storage medium of claim 8 , further comprising: determining whether the document is digitally signed wherein when the document is digitally signed displaying a transition button operative, when selected, to invalidate the digital signature and transition the document to the context that facilitates editing; and invalidating the signature and save a copy of the document in response to receiving the selection. | 0.538055 |
8,006,268 | 1 | 8 | 1. A method implemented by a client device having a processor executing instructions stored in computer-readable storage media, the method comprising: receiving video signals broadcast on a multiplexed channel of a broadcast network; extracting from the received video signals a closed captioning stream of textual data; creating an active list comprising a plurality of first search terms by presenting a plurality of questions at a user interface to be answered by a viewer to develop the first search terms for creating the active list; creating a passive list comprising a plurality of second search terms by: monitoring closed captioning textual data during receipt of one or more previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, extracting words and phrases as potential search terms from the closed captioning textual data, and automatically selecting the plurality of second search terms from the potential search terms based on a recentness and a frequency of occurrence of the extracted words and phrases; searching the stream of textual data for occurrences of textual data matching one or more of the first search terms in the active list or one or more of the second search terms in the passive list, the searching comprising: storing content programming corresponding to the received video signals in a buffer; comparing, by the processor, the closed captioning stream of textual data to both the active list and the passive list; determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein the number of matches is based on a combination, over a period of time, of a number of hits with respect to the first search terms in the active list and a number of hits with respect to the second search terms in the passive list; and applying a greater weight to the first search terms in the active list than a weight applied to the second search terms in the passive list when counting the number of matches; when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and notifying the viewer when the number of matches exceeds the threshold number that content programming determined to be of interest to the viewer has been located. | 1. A method implemented by a client device having a processor executing instructions stored in computer-readable storage media, the method comprising: receiving video signals broadcast on a multiplexed channel of a broadcast network; extracting from the received video signals a closed captioning stream of textual data; creating an active list comprising a plurality of first search terms by presenting a plurality of questions at a user interface to be answered by a viewer to develop the first search terms for creating the active list; creating a passive list comprising a plurality of second search terms by: monitoring closed captioning textual data during receipt of one or more previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, extracting words and phrases as potential search terms from the closed captioning textual data, and automatically selecting the plurality of second search terms from the potential search terms based on a recentness and a frequency of occurrence of the extracted words and phrases; searching the stream of textual data for occurrences of textual data matching one or more of the first search terms in the active list or one or more of the second search terms in the passive list, the searching comprising: storing content programming corresponding to the received video signals in a buffer; comparing, by the processor, the closed captioning stream of textual data to both the active list and the passive list; determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein the number of matches is based on a combination, over a period of time, of a number of hits with respect to the first search terms in the active list and a number of hits with respect to the second search terms in the passive list; and applying a greater weight to the first search terms in the active list than a weight applied to the second search terms in the passive list when counting the number of matches; when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and notifying the viewer when the number of matches exceeds the threshold number that content programming determined to be of interest to the viewer has been located. 8. The method according to claim 1 , wherein the notifying the viewer further comprises displaying a notification message in a manner selected from the group consisting of picture in picture, split screen, video text and selective picture. | 0.862009 |
7,987,169 | 26 | 39 | 26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate. | 26. The method of claim 25 , wherein the generating of a score for a structure having an aggregate comprises calculating (a) a deviation score of the search expression, and (b) for each sub-expression of the search expression, a density and a relevance center of the sub-expression, for the aggregate, the calculating being performed using at least relevance geometry of the aggregate, one or more deviation scores of the search expression of each child of the aggregate, and a density of each sub-expression of the search expression for each child of the aggregate. 39. The method of claim 26 , wherein the aggregate corresponds to a region and children of the aggregate corresponds to sub-regions of the region, the generating of a score for a structure having the aggregate comprises calculating a relevance center of matches for the search expression for the aggregate by calculating
x =(Σ 1≦i≦n ( A i *v i *x i ))/(Σ 1≦i≦n ( A i *v i )), and (a)
y =(Σ 1≦i≦n ( A i *v i *y i ))/(Σ 1≦i≦n ( A i *V i )), (b) where n is the number of children of the aggregate, A i is the relevance size of the i-th child of the aggregate, v i is the relevance value for the search expression assigned to the i-th child of the aggregate, x is x-coordinate of the relevance center for the search expression for the aggregate, y is y-coordinate of the relevance center for the search expression for the aggregate, x i is x-coordinate of the relevance center for the search expression for the i-th child of the aggregate, and y i is y-coordinate of the relevance center for the expression for the i-th child of the aggregate. | 0.754118 |
8,121,904 | 31 | 33 | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. 33. The system of claim 31 further comprising a printer communicatively coupled to the processing system and configured to print the single composite output as a printed document. | 0.808761 |
5,543,818 | 9 | 10 | 9. A system for entering text into a computer system, including: a processor; a display device connected to the processor; and an input device connected to the processor, said input device including keys, wherein the processor is programmed with software for displaying on the display device a character selection menu including simultaneously displayed groups of character representations, each of said groups including representations of B characters, the characters within each group arranged in a pattern, highlighting a selected one of the groups in response to actuation of a first set of the keys, and selecting a character representation within the selected one of the groups in response to actuation of a one of a second set of the keys, where said second set of the keys consists of B of the keys, where B is a positive integer not less than two, and where said second set of the keys is separate from the display device and is arranged in a pattern corresponding to the pattern of the characters within each group. | 9. A system for entering text into a computer system, including: a processor; a display device connected to the processor; and an input device connected to the processor, said input device including keys, wherein the processor is programmed with software for displaying on the display device a character selection menu including simultaneously displayed groups of character representations, each of said groups including representations of B characters, the characters within each group arranged in a pattern, highlighting a selected one of the groups in response to actuation of a first set of the keys, and selecting a character representation within the selected one of the groups in response to actuation of a one of a second set of the keys, where said second set of the keys consists of B of the keys, where B is a positive integer not less than two, and where said second set of the keys is separate from the display device and is arranged in a pattern corresponding to the pattern of the characters within each group. 10. The system of claim 9, wherein the first set of the keys consists of at least one cursor movement key and the second set of the keys consists of B selection keys, and wherein the processor is programmed with software for highlighting the selected one of the groups in response to actuation of the at least one cursor movement key, and selecting said character representation within said selected one of the groups in response to actuation of one of the selection keys. | 0.501057 |
7,689,613 | 1 | 5 | 1. A method of carrying out a search of television data carried out in a television receiver device using a search engine, comprising: at a television receiver device, receiving a command from a television remote controller device that retrieves a video frame of metadata text associated with a television program; extracting selected portions of the metadata text from the video frame containing metadata text by optical character recognition (OCR) processing of the selected text from the video frame, the selected portions of the metadata text being selected based upon the receipt of navigation and selection commands from the television remote controller; loading the text extracted from the OCR processing as a search string into a browser connection to an Internet search engine; executing the search using the search engine operating on the search string; receiving search results from the search engine; and displaying the search results for viewing on a display associated with said television receiver device. | 1. A method of carrying out a search of television data carried out in a television receiver device using a search engine, comprising: at a television receiver device, receiving a command from a television remote controller device that retrieves a video frame of metadata text associated with a television program; extracting selected portions of the metadata text from the video frame containing metadata text by optical character recognition (OCR) processing of the selected text from the video frame, the selected portions of the metadata text being selected based upon the receipt of navigation and selection commands from the television remote controller; loading the text extracted from the OCR processing as a search string into a browser connection to an Internet search engine; executing the search using the search engine operating on the search string; receiving search results from the search engine; and displaying the search results for viewing on a display associated with said television receiver device. 5. The method according to claim 1 , wherein the search is carried out via a modem. | 0.906951 |
8,713,462 | 8 | 9 | 8. A system, comprising: one or more processors; a computer-readable memory containing instructions to cause the one or more processors to perform operations, including: receiving a plurality of concurrent requests to generate previews of a plurality of files, wherein the previews include pre-determined content or dynamically generated content, and wherein the plurality of files each have an associated file type; determining an order of the plurality of concurrent requests to generate the previews; determining the associated file types for the plurality of files; determining that an associated file type for a first file in the plurality of files is associated with pre-determined content; generating a preview of the first file, wherein the preview of the first file includes the predetermined content; determining that an associated file type for a second file in the plurality of files is not associated with pre-determined content; matching the file type for the second file with a plug-in, wherein the plug-in is capable of processing content in the second file; using the plug-in for the second file to process the content in the second file and to dynamically generate content for a preview of the second file, wherein dynamically generating the content includes translating the second file, using the plug-in, from a native format to a format different than the native format, wherein the generated preview of the second file includes the dynamically generated content, and wherein the previews of the first and second files are generated in accordance with the determined order of the plurality of concurrent requests; and displaying the previews of the first and second files in an overlapping manner in a preview view area. | 8. A system, comprising: one or more processors; a computer-readable memory containing instructions to cause the one or more processors to perform operations, including: receiving a plurality of concurrent requests to generate previews of a plurality of files, wherein the previews include pre-determined content or dynamically generated content, and wherein the plurality of files each have an associated file type; determining an order of the plurality of concurrent requests to generate the previews; determining the associated file types for the plurality of files; determining that an associated file type for a first file in the plurality of files is associated with pre-determined content; generating a preview of the first file, wherein the preview of the first file includes the predetermined content; determining that an associated file type for a second file in the plurality of files is not associated with pre-determined content; matching the file type for the second file with a plug-in, wherein the plug-in is capable of processing content in the second file; using the plug-in for the second file to process the content in the second file and to dynamically generate content for a preview of the second file, wherein dynamically generating the content includes translating the second file, using the plug-in, from a native format to a format different than the native format, wherein the generated preview of the second file includes the dynamically generated content, and wherein the previews of the first and second files are generated in accordance with the determined order of the plurality of concurrent requests; and displaying the previews of the first and second files in an overlapping manner in a preview view area. 9. The system of claim 8 , wherein selecting the preview of the first file causes the preview of the first file to become a focal point, and wherein selecting the preview of the second file causes the preview of the second file to become the focal point. | 0.6825 |
9,501,551 | 16 | 23 | 16. A computer-implemented method for categorizing, on behalf of a user, one or more items of a plurality of items in item categories maintained by a network-based service, the method comprising: under control of one or more computer systems: comparing item information with at least one description for a first item category in the item categories maintained by the network-based service to determine a similarity between the item information and the at least one description, wherein the at least one description is a textual description of the first item category, wherein the item information is related to a first item in the plurality of items, wherein the first item is an item offered for sale using the network-based service, and wherein the first item category is associated with at least one item in the plurality of items; automatically determining the first item category to be at least one category recommendation for the first item based on the similarity between the item information and at least one description; enabling selection of the first item category for assignment to the first item, wherein the item information is represented as an item vector according to a vector space model and a category vector according to the vector space model comprises a representation of at least a portion of the at least one description, and wherein the first item category is automatically determined to be the at least one category recommendation if a deviation of an angle between the item vector and the category vector is less than a threshold value. | 16. A computer-implemented method for categorizing, on behalf of a user, one or more items of a plurality of items in item categories maintained by a network-based service, the method comprising: under control of one or more computer systems: comparing item information with at least one description for a first item category in the item categories maintained by the network-based service to determine a similarity between the item information and the at least one description, wherein the at least one description is a textual description of the first item category, wherein the item information is related to a first item in the plurality of items, wherein the first item is an item offered for sale using the network-based service, and wherein the first item category is associated with at least one item in the plurality of items; automatically determining the first item category to be at least one category recommendation for the first item based on the similarity between the item information and at least one description; enabling selection of the first item category for assignment to the first item, wherein the item information is represented as an item vector according to a vector space model and a category vector according to the vector space model comprises a representation of at least a portion of the at least one description, and wherein the first item category is automatically determined to be the at least one category recommendation if a deviation of an angle between the item vector and the category vector is less than a threshold value. 23. The computer-implemented method of claim 16 , wherein the item information comprises at least one of an item title and an item description. | 0.865602 |
8,429,159 | 3 | 4 | 3. The method recited in claim 1 , further comprising associating metadata with the one or more objects. | 3. The method recited in claim 1 , further comprising associating metadata with the one or more objects. 4. The method recited in claim 3 , wherein the preliminary relevance is determined at least in part based on the metadata. | 0.957873 |
7,618,042 | 6 | 7 | 6. The word forming game according to claim 1 further comprising the step of challenging the existence of a word previously formed by a different player. | 6. The word forming game according to claim 1 further comprising the step of challenging the existence of a word previously formed by a different player. 7. The word forming game according to claim 6 , wherein the step of challenging the existence of a word comprises using a determination made by the word validating device. | 0.943227 |
8,626,585 | 12 | 13 | 12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by the data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements. | 12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by the data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements. 13. The system of claim 12 , wherein determining a relevance measure that represents the relevance of the landing page image to the content of the landing page comprises determining a relevance measure that measures the relevance of the content of the landing page to the landing page image. | 0.787901 |
8,572,589 | 13 | 14 | 13. The computer program product of claim 12 , wherein the translation module further comprises: an instrument interface module configured to provide interfaces between the programming language routines and the instrument for communicating with the instrument using the strings corresponding to the respective SCPI commands and queries. | 13. The computer program product of claim 12 , wherein the translation module further comprises: an instrument interface module configured to provide interfaces between the programming language routines and the instrument for communicating with the instrument using the strings corresponding to the respective SCPI commands and queries. 14. The computer program product of claim 13 , wherein the program library module stores documentation associated with respective programming language routines in association with respective programming language routines. | 0.926431 |
10,049,107 | 10 | 13 | 10. An information processing apparatus comprising: a display controller that displays, on a display device of the information processing apparatus, image information, text regions, and original text in association with each other, the text regions being obtained by extracting regions including an image of text from the image information, the original text being obtained by performing character recognition on the text included in the text regions; an operation receiver that receives an editing operation of the text regions displayed on the display device from a user; and a text region editor that edits the text regions in accordance with the content of the editing operation received on the display device of the information processing apparatus, wherein the display controller further displays on the display device merge boxes for selecting two or more of the text regions to be merged in association with the original text, and a merge button, the operation receiver receives, as part of the content of the received operation, selection of respective merge boxes for the two or more of the text regions or selection of a portion of the displayed original text, and in response to the selection of the respective merge boxes for the two or more of the text regions and in accordance with a merge instruction received by the operation receiver on the display device by operation of the merge button, the text region editor merges together the two or more of the text regions displayed on the display device as separate text regions so as to be displayed on the display device as a single text region. | 10. An information processing apparatus comprising: a display controller that displays, on a display device of the information processing apparatus, image information, text regions, and original text in association with each other, the text regions being obtained by extracting regions including an image of text from the image information, the original text being obtained by performing character recognition on the text included in the text regions; an operation receiver that receives an editing operation of the text regions displayed on the display device from a user; and a text region editor that edits the text regions in accordance with the content of the editing operation received on the display device of the information processing apparatus, wherein the display controller further displays on the display device merge boxes for selecting two or more of the text regions to be merged in association with the original text, and a merge button, the operation receiver receives, as part of the content of the received operation, selection of respective merge boxes for the two or more of the text regions or selection of a portion of the displayed original text, and in response to the selection of the respective merge boxes for the two or more of the text regions and in accordance with a merge instruction received by the operation receiver on the display device by operation of the merge button, the text region editor merges together the two or more of the text regions displayed on the display device as separate text regions so as to be displayed on the display device as a single text region. 13. The information processing apparatus according to claim 10 , further comprising: a text region extractor that generates text region information indicating (i) the original text, (ii) a coordinate, a height and a width of each of the text regions, and (iii) the image of the text included in each of the text regions. | 0.738134 |
7,680,334 | 16 | 18 | 16. The method according to claim 15 , further comprising, before the step of presenting, retrieving as the best interpretation, from a database comprising allographs, a best allograph that is associated with the best handwriting symbol pattern of the best template. | 16. The method according to claim 15 , further comprising, before the step of presenting, retrieving as the best interpretation, from a database comprising allographs, a best allograph that is associated with the best handwriting symbol pattern of the best template. 18. The method according to claim 16 , wherein the step of presenting comprises presenting the best allograph represented by a number of arcs depicting the way of hand writing symbols of the best template. | 0.931116 |
8,131,559 | 1 | 8 | 1. A method of accepting documents for publication at a server wherein shares in a first document are traded using tokens in a virtual market place, and participants in the virtual market place each own one or more tokens in the virtual market place, the method comprising: receiving from a submitting participant the first document; receiving a request from one or more purchasing participants to purchase shares in the first document, subtracting, at the server, one or more tokens from an account of the one or more purchasing participants and adding shares in the first document to the account of the one or more purchasing participants; accepting the first document for publication after a predetermined amount of shares in the first document are purchased in a predetermined period; and adding tokens to an account of at least one participant that owns shares in a second document cited in the first document. | 1. A method of accepting documents for publication at a server wherein shares in a first document are traded using tokens in a virtual market place, and participants in the virtual market place each own one or more tokens in the virtual market place, the method comprising: receiving from a submitting participant the first document; receiving a request from one or more purchasing participants to purchase shares in the first document, subtracting, at the server, one or more tokens from an account of the one or more purchasing participants and adding shares in the first document to the account of the one or more purchasing participants; accepting the first document for publication after a predetermined amount of shares in the first document are purchased in a predetermined period; and adding tokens to an account of at least one participant that owns shares in a second document cited in the first document. 8. The method according to claim 1 , wherein the method further comprises the step of adding shares in the first document to the account of the submitting participant. | 0.909924 |
8,463,043 | 1 | 2 | 1. A method comprising: under control of one or more processors configured with executable instructions: acquiring time sequential ink data for a character; conditioning the time sequential ink data to separate ink trajectories of real strokes and imaginary strokes into a plurality of ink frames, the conditioning comprising generating a plurality of contiguous time sequential frames for each imaginary stroke; extracting features from each ink frame of the conditioned ink data; and recognizing the character based on the extracted features using a character recognition model. | 1. A method comprising: under control of one or more processors configured with executable instructions: acquiring time sequential ink data for a character; conditioning the time sequential ink data to separate ink trajectories of real strokes and imaginary strokes into a plurality of ink frames, the conditioning comprising generating a plurality of contiguous time sequential frames for each imaginary stroke; extracting features from each ink frame of the conditioned ink data; and recognizing the character based on the extracted features using a character recognition model. 2. The method as recited in claim 1 , wherein the acquiring comprises collecting the time sequential ink data for the character online as a user writes the character on a recording surface using a writing implement. | 0.790448 |
9,311,528 | 32 | 34 | 32. A computer system of claim 23 wherein the first display area is used in conjunction with a gesture learning application. | 32. A computer system of claim 23 wherein the first display area is used in conjunction with a gesture learning application. 34. The computer system of claim 32 wherein the computer system comprises at least one of a handheld computer, a personal digital assistant, a media player, and a mobile telephone. | 0.924497 |
9,299,035 | 1 | 10 | 1. A method for refining a process model, comprising: mining a process model from a set of execution traces; determining whether the process model is too dense or too sparse; learning a predictive model from the execution traces to predict an outcome; modifying the predictive model with a processor, comprising: making the predictive model more specific if it is determined that the process model is too dense; and making the predictive model more general if it is determined that the process model is too sparse; and mining a refined process model from updated traces based on attributes present in the modified predictive model. | 1. A method for refining a process model, comprising: mining a process model from a set of execution traces; determining whether the process model is too dense or too sparse; learning a predictive model from the execution traces to predict an outcome; modifying the predictive model with a processor, comprising: making the predictive model more specific if it is determined that the process model is too dense; and making the predictive model more general if it is determined that the process model is too sparse; and mining a refined process model from updated traces based on attributes present in the modified predictive model. 10. The method of claim 1 , further comprising repeating said steps of determining, learning, modifying, and mining a refined process model until the step of determining determines that the process model is neither too sparse nor too dense. | 0.784946 |
8,856,099 | 29 | 34 | 29. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: analyzing contents of each of a plurality of resources to identify entities of a first entity type that are related to the resource, wherein analyzing the contents of each of the plurality of resources comprises: identifying occurrences of names of entities in the contents of the resource, and determining that each entity whose name occurs in the resource more than a threshold number of occurrences is related to the resource; annotating each of the plurality of resources in an index database with annotations identifying the entities that are related to the resource; determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with the first entity type; obtaining search results for the first search query from a search engine, the search results identifying a plurality of search result resources; identifying entities of the first entity type that are related to any of the plurality of search result resources identified by the search results; and selecting names of one or more of the identified entities of the first entity type to include in a response to the first search query. | 29. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: analyzing contents of each of a plurality of resources to identify entities of a first entity type that are related to the resource, wherein analyzing the contents of each of the plurality of resources comprises: identifying occurrences of names of entities in the contents of the resource, and determining that each entity whose name occurs in the resource more than a threshold number of occurrences is related to the resource; annotating each of the plurality of resources in an index database with annotations identifying the entities that are related to the resource; determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with the first entity type; obtaining search results for the first search query from a search engine, the search results identifying a plurality of search result resources; identifying entities of the first entity type that are related to any of the plurality of search result resources identified by the search results; and selecting names of one or more of the identified entities of the first entity type to include in a response to the first search query. 34. The system of claim 29 , the operations further comprising: for each selected entity name, obtaining search results for a search query including the selected entity name; and including one or more search results obtained for one or more of the search queries including the respective selected entity names with the obtained search results for the first search query in the response to the first search query. | 0.53288 |
9,043,301 | 7 | 11 | 7. A non-transitory computer-readable storage medium comprising instructions executable by a computer processor, the instructions comprising: instructions for receiving a query associated with a user of a social networking system; instructions for obtaining a result set comprising a plurality of objects from an object store of the social networking system that match the query, the plurality of objects including a first object having a first type and obtained based on the query using a first search algorithm, and a second object having a second type different from the first type and obtained based on the query using a second search algorithm; instructions for ordering at least a plurality of the objects of the result set based at least in part on measures of affinities of the user for the objects, an affinity of the user for an object comprising at least one from a group consisting of: a distance on a social graph between the user and the object, and a similarity between the user and the object, the social graph having nodes corresponding to objects and edges corresponding to relationships of the objects; and instructions for providing at least a portion of the result set to a client device. | 7. A non-transitory computer-readable storage medium comprising instructions executable by a computer processor, the instructions comprising: instructions for receiving a query associated with a user of a social networking system; instructions for obtaining a result set comprising a plurality of objects from an object store of the social networking system that match the query, the plurality of objects including a first object having a first type and obtained based on the query using a first search algorithm, and a second object having a second type different from the first type and obtained based on the query using a second search algorithm; instructions for ordering at least a plurality of the objects of the result set based at least in part on measures of affinities of the user for the objects, an affinity of the user for an object comprising at least one from a group consisting of: a distance on a social graph between the user and the object, and a similarity between the user and the object, the social graph having nodes corresponding to objects and edges corresponding to relationships of the objects; and instructions for providing at least a portion of the result set to a client device. 11. The non-transitory computer-readable storage medium of claim 7 , wherein the objects of the result set are grouped within the result set based at least in part on a search algorithm that produced them, the search algorithms including one or more of a second-order connections search, a history search, and a global importance search. | 0.501479 |
9,065,798 | 10 | 18 | 10. A system comprising: a processor; a computer-readable storage medium coupled to the processor, the computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: receive a request for information based on an instruction in a markup language document, wherein the request for information is responsive to a request for a web page of a third-party website that is within a domain of a third-party website that is different from a domain of a social networking system; identify a user associated with the request; determine the requested information based on social information associated with the user, wherein the requested information comprises a set of content items that relate to (1) one or more actions performed by one or more other users with whom the user has established a connection in the social networking system, and (2) at least one specified URL or domain; and send the determined requested information to a client device for rendering as content personalized for the user for display within the rendered web page. | 10. A system comprising: a processor; a computer-readable storage medium coupled to the processor, the computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: receive a request for information based on an instruction in a markup language document, wherein the request for information is responsive to a request for a web page of a third-party website that is within a domain of a third-party website that is different from a domain of a social networking system; identify a user associated with the request; determine the requested information based on social information associated with the user, wherein the requested information comprises a set of content items that relate to (1) one or more actions performed by one or more other users with whom the user has established a connection in the social networking system, and (2) at least one specified URL or domain; and send the determined requested information to a client device for rendering as content personalized for the user for display within the rendered web page. 18. The system of claim 10 , wherein the requested information includes an advertisement. | 0.862229 |
9,918,057 | 1 | 2 | 1. A method of projecting text characters onto a textured surface, the method comprising: determining, from a captured image of the textured surface, a measure of the texture on the surface for a region of the textured surface over which the text characters are to be projected; selecting, based on a function of the determined measure, a glyph set, each glyph in the glyph set having visually contrasting inner and outer portions, at least one of the inner and outer portions having a width varied according to the determined measure in each of two mutually perpendicular directions, the outer portion being sized proportionally to the inner portion according to the determined measure; and projecting the text characters onto the textured surface of the region using the selected glyph set. | 1. A method of projecting text characters onto a textured surface, the method comprising: determining, from a captured image of the textured surface, a measure of the texture on the surface for a region of the textured surface over which the text characters are to be projected; selecting, based on a function of the determined measure, a glyph set, each glyph in the glyph set having visually contrasting inner and outer portions, at least one of the inner and outer portions having a width varied according to the determined measure in each of two mutually perpendicular directions, the outer portion being sized proportionally to the inner portion according to the determined measure; and projecting the text characters onto the textured surface of the region using the selected glyph set. 2. The method according to claim 1 , wherein the function of the determined measure is a spatial frequency, the spatial frequency relating to a distribution of at least one dominant repeating pattern of the texture. | 0.502315 |
9,053,102 | 18 | 20 | 18. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to derive a context object for a non-contextual data object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of the non-contextual data object, and wherein the context object is derived by contextually searching and analyzing a document, which contains multiple instances of the non-contextual data object, to derive the context object; second program instructions to establish a minimum validity threshold for the context object, wherein the minimum validity threshold defines a probability that a set of one or more context objects accurately describes the context of the non-contextual data object; and third program instructions to expand a range of a search area of the document until the minimum validity threshold is reached; fourth program instructions to associate the non-contextual data object with the context object to define a synthetic context-based object; fifth program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; sixth program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; seventh program instructions to receive, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; eighth program instructions to return, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, fifth, sixth, seventh, and eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 18. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to derive a context object for a non-contextual data object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of the non-contextual data object, and wherein the context object is derived by contextually searching and analyzing a document, which contains multiple instances of the non-contextual data object, to derive the context object; second program instructions to establish a minimum validity threshold for the context object, wherein the minimum validity threshold defines a probability that a set of one or more context objects accurately describes the context of the non-contextual data object; and third program instructions to expand a range of a search area of the document until the minimum validity threshold is reached; fourth program instructions to associate the non-contextual data object with the context object to define a synthetic context-based object; fifth program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; sixth program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; seventh program instructions to receive, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; eighth program instructions to return, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, fifth, sixth, seventh, and eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 20. The computer system of claim 18 , further comprising: ninth program instructions to execute a map/reduce search of the document to reach the minimum validity threshold, wherein the map-reduce search sequentially performs evaluations of subsequently lower-level partitions of the document to determine finer levels of granularity to derive the context object; and tenth program instructions to utilize a progressively higher number of processors to execute the evaluations of the subsequently lower-level partitions of the document; and wherein the ninth and tenth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 0.639713 |
8,280,888 | 1 | 6 | 1. A method of creating a question title that is representative of a content of the question and optimized for a search engine, the method comprising: receiving a document in which a title optimized for a search engine is desired; identifying a maximum number of characters the search engine reads when characterizing the document, the maximum number of characters set as a maximum size; applying phrasal analysis to the document; identifying topics included in the document; computing candidate titles based on the identified topics; sorting the candidate titles based on the number of topics in each candidate title; selecting the candidate title with the largest number of topics as a candidate optimized title; selecting the candidate optimized title as a final optimized title, in response to determining that the candidate optimized title character length is less than the maximum size. | 1. A method of creating a question title that is representative of a content of the question and optimized for a search engine, the method comprising: receiving a document in which a title optimized for a search engine is desired; identifying a maximum number of characters the search engine reads when characterizing the document, the maximum number of characters set as a maximum size; applying phrasal analysis to the document; identifying topics included in the document; computing candidate titles based on the identified topics; sorting the candidate titles based on the number of topics in each candidate title; selecting the candidate title with the largest number of topics as a candidate optimized title; selecting the candidate optimized title as a final optimized title, in response to determining that the candidate optimized title character length is less than the maximum size. 6. The method of claim 1 , wherein sorting the candidate titles further comprises: sorting the candidate titles by the number of tokens contained minus the skew for each topic. | 0.773196 |
8,321,199 | 34 | 38 | 34. The method of claim 33 , wherein the first feature comprises a specified relationship with a second coding, and wherein (D) comprises determining whether the specified relationship is accurate. | 34. The method of claim 33 , wherein the first feature comprises a specified relationship with a second coding, and wherein (D) comprises determining whether the specified relationship is accurate. 38. The method of claim 34 , wherein the second coding is associated with a second code, the second code having second data, and wherein (B) comprises rendering the first data based on the second data. | 0.93615 |
8,954,349 | 21 | 27 | 21. The system of claim 19 , wherein invoking the server-administered function is triggered by the text message having a self-addressed routing direction. | 21. The system of claim 19 , wherein invoking the server-administered function is triggered by the text message having a self-addressed routing direction. 27. The system of claim 21 , wherein the network controller is configured to route the received text message to another address in the event that a determination identifies that: registration is not sought from the device used to compile the text message; or registration of the device for the service has not previously occurred; or an address header of the text message does not contain a looped routing direction. | 0.918078 |
4,677,672 | 1 | 4 | 1. A continuous speech recognition apparatus comprising: an acoustic analyzer circuit for extracting feature parameter data of an input speech in each of frame; first memory means storing a plurality of reference pattern data each including reference parameter data of N frames; a partial similarity calculating circuit for calculating a partial similarity between the feature parameter data of each frame which is supplied from said acoustic analyzer circuit and each reference parameter data which is read out from said first memory means; second memory means for sequentially storing partial similarity data from said partial similarity calculating circuit for a predetermined number of frames; an operation circuit for calculating similarities between the feature pattern data including N feature parameter data of the input speech and the reference pattern data on the basis of the N partial similarity data which correspond to each of the reference pattern data and are present in at least one subperiod, and for selecting the largest one of the calculated similarity data; third memory means for storing the largest similarity data from said operation circuit, and reference pattern indication data and subperiod indication data which respectively indicate the reference pattern and the subperiod which are associated with the largest similarity data; and a recognition circuit for detecting a plurality of series of continuous subperiods during the speech interval, calculating the sum of similarity data associated with each of said plurality of series of continuous subperiods and recognizing the input speech on the basis of a series of reference pattern indication data corresponding to a series of contiuuous subperiods with which the largest one of the sums of similarity data is associated. | 1. A continuous speech recognition apparatus comprising: an acoustic analyzer circuit for extracting feature parameter data of an input speech in each of frame; first memory means storing a plurality of reference pattern data each including reference parameter data of N frames; a partial similarity calculating circuit for calculating a partial similarity between the feature parameter data of each frame which is supplied from said acoustic analyzer circuit and each reference parameter data which is read out from said first memory means; second memory means for sequentially storing partial similarity data from said partial similarity calculating circuit for a predetermined number of frames; an operation circuit for calculating similarities between the feature pattern data including N feature parameter data of the input speech and the reference pattern data on the basis of the N partial similarity data which correspond to each of the reference pattern data and are present in at least one subperiod, and for selecting the largest one of the calculated similarity data; third memory means for storing the largest similarity data from said operation circuit, and reference pattern indication data and subperiod indication data which respectively indicate the reference pattern and the subperiod which are associated with the largest similarity data; and a recognition circuit for detecting a plurality of series of continuous subperiods during the speech interval, calculating the sum of similarity data associated with each of said plurality of series of continuous subperiods and recognizing the input speech on the basis of a series of reference pattern indication data corresponding to a series of contiuuous subperiods with which the largest one of the sums of similarity data is associated. 4. An apparatus according to claim 1, wherein said operation means includes a control circuit for setting said second memory means in a readout made in response to an output signal supplied from said partial similarity calculating circuit each time partial similarity data for one frame are all stored in said second memory means, and an operation circuit for calculating the similarity between the feature pattern data and each of the reference pattern data and generating the largest one of the similarity data, said control circuit setting said second memory means in a write-in mode after all the partial similarity data required for the similarity calculation by said operation circuit are read out from said second memory means. | 0.50068 |
9,633,457 | 1 | 2 | 1. A computer-readable non-transitory storage medium storing therein a graph generation program that causes a computer to perform a procedure comprising: producing a database of specialized vocabulary words being respectively associated with vectors, each vector is composed of first and second elements, the first element indicating an amount that a specific specialized vocabulary word suggests comparison of data, the second element indicating an amount that the specific specialized vocabulary word suggests analysis of data; extracting a plurality of specialized vocabulary words from a title of an electronic document, with reference to the database; specifying a document purpose of the electronic document, by weighting each of the vectors associated respectively with the specialized vocabulary words based on a position of the specialized vocabulary word within the title, calculating an average of the weighted vectors associated with the extracted specialized vocabulary words in the electronic document, and determining that the document purpose is comparison of data, when the first element of the calculated average overweighs the second element of the calculated average, and determining that the document purpose is analysis of data, when the second element of the calculated average overweighs the first element of the calculated average; determining a graph type, based on the document purpose; generating a graph of the determined graph type, based on data of the electronic document; and outputting a computer file of the electronic document containing the generated graph. | 1. A computer-readable non-transitory storage medium storing therein a graph generation program that causes a computer to perform a procedure comprising: producing a database of specialized vocabulary words being respectively associated with vectors, each vector is composed of first and second elements, the first element indicating an amount that a specific specialized vocabulary word suggests comparison of data, the second element indicating an amount that the specific specialized vocabulary word suggests analysis of data; extracting a plurality of specialized vocabulary words from a title of an electronic document, with reference to the database; specifying a document purpose of the electronic document, by weighting each of the vectors associated respectively with the specialized vocabulary words based on a position of the specialized vocabulary word within the title, calculating an average of the weighted vectors associated with the extracted specialized vocabulary words in the electronic document, and determining that the document purpose is comparison of data, when the first element of the calculated average overweighs the second element of the calculated average, and determining that the document purpose is analysis of data, when the second element of the calculated average overweighs the first element of the calculated average; determining a graph type, based on the document purpose; generating a graph of the determined graph type, based on data of the electronic document; and outputting a computer file of the electronic document containing the generated graph. 2. The computer-readable non-transitory storage medium according to claim 1 , wherein the procedure further comprises: extracting a character string in the electronic document which satisfies predetermined criteria; and recognizing the extracted character string as the title of the electronic document. | 0.641844 |
9,967,159 | 13 | 14 | 13. The method of claim 12 , further comprising reporting, by the cloud brokerage computing device, cost consumption data through a graphical user interface on a display device. | 13. The method of claim 12 , further comprising reporting, by the cloud brokerage computing device, cost consumption data through a graphical user interface on a display device. 14. The method of claim 13 , further comprising displaying, by the cloud brokerage computing device, an alert notification through the graphical user interface when a predetermined quota allocation threshold is exceeded, wherein the predetermined quota allocation threshold is determined from the enterprise context data. | 0.928444 |
9,241,252 | 3 | 4 | 3. The computer-implemented method of claim 2 , wherein determining, by the one or more computing devices, a semantic location of a user device based at least in part on the entity associated with the wireless network access point comprises: receiving, by the one or more computing devices, a signal indicative of a user device connection to the wireless network access point; and determining, by the one or more computing devices, the semantic location of the user device based at least in part on the entity associated with the wireless network access point. | 3. The computer-implemented method of claim 2 , wherein determining, by the one or more computing devices, a semantic location of a user device based at least in part on the entity associated with the wireless network access point comprises: receiving, by the one or more computing devices, a signal indicative of a user device connection to the wireless network access point; and determining, by the one or more computing devices, the semantic location of the user device based at least in part on the entity associated with the wireless network access point. 4. The computer-implemented method of claim 3 , wherein the connection is an authenticated connection. | 0.964924 |
7,730,059 | 8 | 9 | 8. The method of claim 7 , further comprising outputting for display a faceted search interface based on the facet hierarchy. | 8. The method of claim 7 , further comprising outputting for display a faceted search interface based on the facet hierarchy. 9. The method of claim 8 , wherein: receiving the query comprises receiving user input issuing a natural language word search through a user interface; and the faceted search interface and the multi-dimensional search interface are displayed in the user interface. | 0.88 |
8,495,483 | 1 | 2 | 1. A method comprising: selecting, by one or more processors, a plurality of documents, each document, of the plurality of documents, including a hyperlink that points to a target document; generating, by one or more processors, a web quote from each document in the plurality of documents, using selected text from the document, where, for each document in the plurality of documents, the selected text from the document is included in a paragraph in the document that includes the hyperlink, the paragraph including less than an entire content of the document; augmenting, by one or more processors, the web quote, for each document, of the plurality of documents, by incorporating text that is both located in the document and outside of the selected text, into the web quote; determining a metric of quality of each document of the plurality of documents; ranking the web quotes based on the metric of quality of each document of the plurality of documents from which the web quote is generated; selecting, by one or more processors, one of the web quotes based on the ranking of the web quotes; storing, by one or more processors and in an entry, of a plurality of entries in an index, information associating the target document with a corresponding term appearing in the target document; storing, by one or more processors and in another entry, of the plurality of entries in the index, information associating the target document with a web quote term, the web quote term appearing in the selected web quote and not appearing in the target document; receiving, by one or more processors, information identifying the target document as relevant to a search query based on the web quote term, the received information being generated based on information included in the index; and providing, by one or more processors, information regarding the target document and the selected web quote based on receiving the information identifying the target document as relevant to the search query. | 1. A method comprising: selecting, by one or more processors, a plurality of documents, each document, of the plurality of documents, including a hyperlink that points to a target document; generating, by one or more processors, a web quote from each document in the plurality of documents, using selected text from the document, where, for each document in the plurality of documents, the selected text from the document is included in a paragraph in the document that includes the hyperlink, the paragraph including less than an entire content of the document; augmenting, by one or more processors, the web quote, for each document, of the plurality of documents, by incorporating text that is both located in the document and outside of the selected text, into the web quote; determining a metric of quality of each document of the plurality of documents; ranking the web quotes based on the metric of quality of each document of the plurality of documents from which the web quote is generated; selecting, by one or more processors, one of the web quotes based on the ranking of the web quotes; storing, by one or more processors and in an entry, of a plurality of entries in an index, information associating the target document with a corresponding term appearing in the target document; storing, by one or more processors and in another entry, of the plurality of entries in the index, information associating the target document with a web quote term, the web quote term appearing in the selected web quote and not appearing in the target document; receiving, by one or more processors, information identifying the target document as relevant to a search query based on the web quote term, the received information being generated based on information included in the index; and providing, by one or more processors, information regarding the target document and the selected web quote based on receiving the information identifying the target document as relevant to the search query. 2. The method of claim 1 , where, for each document, of the plurality of documents, the selected text includes text beginning after the hyperlink and continuing to an end of the paragraph that includes the hyperlink. | 0.94108 |
5,502,774 | 1 | 16 | 1. In a message recognition system, a method of transforming a consistent message into a message recognizable by the computer, the method comprising the steps of: (A) transforming the consistent message generated by a human in at least two formats into electrical signal representations of the consistent message; (B) producing from said electrical signal representations of the consistent message a set of parameters for each said format; (C) generating a likelihood score of recognition for each said set of parameters; (D) using said sets of parameters to train a weighting coefficient for each of the at least two formats of the consistent message, wherein said step of training a weighting coefficient comprises the steps of (i) partitioning the consistent message in each said format into one or more subunits, wherein each subunit corresponds to a piece of the consistent message, (ii) grouping said subunits from each said format into a plurality of groups, wherein each group comprises one said subunit from each said format, and wherein each said subunit in one said group corresponds to the same piece of the consistent message, (iii) determining a likelihood score of recognition for each said group of subunits, (iv) determining a global score for the consistent message based on said likelihood scores of recognition, and (v) using said global score to determine said weighting coefficients, (E) generating a weighted expression based on said trained weighting coefficient and said likelihood scores of recognition; and (F) selecting a candidate message unit that maximizes said weighted expression to transform said electrical signal representations of the consistent message into a computer recognizable message. | 1. In a message recognition system, a method of transforming a consistent message into a message recognizable by the computer, the method comprising the steps of: (A) transforming the consistent message generated by a human in at least two formats into electrical signal representations of the consistent message; (B) producing from said electrical signal representations of the consistent message a set of parameters for each said format; (C) generating a likelihood score of recognition for each said set of parameters; (D) using said sets of parameters to train a weighting coefficient for each of the at least two formats of the consistent message, wherein said step of training a weighting coefficient comprises the steps of (i) partitioning the consistent message in each said format into one or more subunits, wherein each subunit corresponds to a piece of the consistent message, (ii) grouping said subunits from each said format into a plurality of groups, wherein each group comprises one said subunit from each said format, and wherein each said subunit in one said group corresponds to the same piece of the consistent message, (iii) determining a likelihood score of recognition for each said group of subunits, (iv) determining a global score for the consistent message based on said likelihood scores of recognition, and (v) using said global score to determine said weighting coefficients, (E) generating a weighted expression based on said trained weighting coefficient and said likelihood scores of recognition; and (F) selecting a candidate message unit that maximizes said weighted expression to transform said electrical signal representations of the consistent message into a computer recognizable message. 16. The method of claim 1, wherein said step (D) further comprises a step (o), before said step (i), of reordering said formats of the consistent message. | 0.828508 |
7,774,442 | 10 | 14 | 10. In a computing environment, a method comprising; using a processing unit, loading an action-style document; using the action-style document to produce an other document directed towards performing a management task, wherein using the action-style document comprises generating a constitutional document comprising at least one schema type, at least one rule and at least one action style; and processing the other document for performing the management task. | 10. In a computing environment, a method comprising; using a processing unit, loading an action-style document; using the action-style document to produce an other document directed towards performing a management task, wherein using the action-style document comprises generating a constitutional document comprising at least one schema type, at least one rule and at least one action style; and processing the other document for performing the management task. 14. The method of claim 10 wherein processing the input document comprises loading a type-function role document as the action-style document for used as a guide document by a processor. | 0.91284 |
9,406,019 | 10 | 18 | 10. A non-transitory computer storage medium encoded with computer program instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating first intermediate training records by inputting input data of a first subset of the initial training records to a first trained predictive model, the first trained predictive model generated using at least a second subset of the initial training records and a training function, each first intermediate training record having a first score; generating second intermediate training records by inputting input data of the second subset of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function and at least the first subset of the initial training records, each second intermediate training record having a second score; and generating, for the first trained predictive model and the second trained predictive model, a score normalization model using a score normalization training function, the first intermediate training records, and the second intermediate training records. | 10. A non-transitory computer storage medium encoded with computer program instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving initial training data, the initial training data comprising initial training records, each initial training record identifying input data as input and a category as output; generating first intermediate training records by inputting input data of a first subset of the initial training records to a first trained predictive model, the first trained predictive model generated using at least a second subset of the initial training records and a training function, each first intermediate training record having a first score; generating second intermediate training records by inputting input data of the second subset of the initial training records to a second trained predictive model, the second trained predictive model generated using the training function and at least the first subset of the initial training records, each second intermediate training record having a second score; and generating, for the first trained predictive model and the second trained predictive model, a score normalization model using a score normalization training function, the first intermediate training records, and the second intermediate training records. 18. The medium of claim 10 , wherein each of the intermediate training records comprises a value for each distinct category in the initial training data. | 0.895492 |
7,599,580 | 1 | 5 | 1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. | 1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. 5. The method of claim 1 , further comprising: applying voice recognition techniques to an audio clip of a person reading aloud from the distinguished rendered document to generate the captured text. | 0.865359 |
9,679,079 | 9 | 10 | 9. A system comprising: at least one server, the at least one server having a non-transient computer information storage medium storing program instructions that when executed by a computer processor effect: receiving, from a client device, a first search query and a first search result request in respect of the first search query, the first search query including at least one first query search term; sending, to the client device, first search results of a first search conducted using the first search query; causing the client device to generate a search engine result page (SERP) comprising the first search results, the SERP further comprising (i) a search field with the at least one first query search term contained therein, and (ii) a unique uniform resource locator (URL) comprising an indication of the at least one first query search term; responsive to determining that a user of the client device has deleted the at least one first query search term from the search field, and is entering a second search query comprising at least one second query search term in the search field of the SERP containing the first search results: receiving, from the client device, elements of the second search query, the elements of the second search query including (i) at least the at least one first query search term obtained from the URL of the SERP without the at least one server retrieving the at least one first query search term from stored data of the server, and (ii) the at least one second query search term; and prior to the at least one server having received a second search result request from the client device in respect of the second search query, sending, to the client device, at least one of (i) at least one search query suggestion based on, at least in part, the elements of the second search query, and (ii) second search results of a second search conducted using the at least one search query suggestion. | 9. A system comprising: at least one server, the at least one server having a non-transient computer information storage medium storing program instructions that when executed by a computer processor effect: receiving, from a client device, a first search query and a first search result request in respect of the first search query, the first search query including at least one first query search term; sending, to the client device, first search results of a first search conducted using the first search query; causing the client device to generate a search engine result page (SERP) comprising the first search results, the SERP further comprising (i) a search field with the at least one first query search term contained therein, and (ii) a unique uniform resource locator (URL) comprising an indication of the at least one first query search term; responsive to determining that a user of the client device has deleted the at least one first query search term from the search field, and is entering a second search query comprising at least one second query search term in the search field of the SERP containing the first search results: receiving, from the client device, elements of the second search query, the elements of the second search query including (i) at least the at least one first query search term obtained from the URL of the SERP without the at least one server retrieving the at least one first query search term from stored data of the server, and (ii) the at least one second query search term; and prior to the at least one server having received a second search result request from the client device in respect of the second search query, sending, to the client device, at least one of (i) at least one search query suggestion based on, at least in part, the elements of the second search query, and (ii) second search results of a second search conducted using the at least one search query suggestion. 10. A system as recited in claim 9 , wherein the at least one search query suggestion is further based on, at least in part, a search history associated with at least one second query search term included in the elements of the second search query. | 0.822095 |
9,336,207 | 9 | 11 | 9. The information handling system of claim 8 wherein the plurality of suggested translations correspond to a plurality of child class sets, and wherein the processors perform additional actions comprising: computing a child class set linguistic noise value for each of the plurality of child class sets using a corresponding child class leverage value and a child class factor value, resulting in a plurality of child class set linguistic noise values; combining the plurality of child class set linguistic noise values, resulting in a translation supply chain linguistic noise value; and utilizing the translation supply chain linguistic noise value during the performance efficiency determination of the language translation supply chain. | 9. The information handling system of claim 8 wherein the plurality of suggested translations correspond to a plurality of child class sets, and wherein the processors perform additional actions comprising: computing a child class set linguistic noise value for each of the plurality of child class sets using a corresponding child class leverage value and a child class factor value, resulting in a plurality of child class set linguistic noise values; combining the plurality of child class set linguistic noise values, resulting in a translation supply chain linguistic noise value; and utilizing the translation supply chain linguistic noise value during the performance efficiency determination of the language translation supply chain. 11. The information handling system of claim 9 wherein each of the plurality of suggested translations corresponds to one of a plurality of original segments written in a first language and one of a plurality of corresponding translation segments written in a second language, and wherein the processors perform additional actions comprising: designating a set of the plurality of original segments as a set of placebo segments, wherein the translation supply chain prevents generation of a suggested translation for each of the segments included in the set of placebo segments; computing a placebo baseline productivity value based upon the set of placebo segments that do not correspond to one of the plurality of suggested translations; selecting one of the plurality of child class sets; computing a child class match productivity value of the selected child class based upon the set of accepted translations that each correspond to the selected child class set; and computing the child class factor value of the selected child class set using the placebo baseline productivity value and the child class match productivity value. | 0.512059 |
9,602,310 | 1 | 4 | 1. A message correlation system comprising: a message manager and processor that determine whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and a keyword management module that correlates a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification. | 1. A message correlation system comprising: a message manager and processor that determine whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and a keyword management module that correlates a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification. 4. The system of claim 1 , further comprising a context correlation module that maps an identifier in the response to an identifier in the outstanding query. | 0.644796 |
9,288,039 | 1 | 14 | 1. A method for text language identification comprising: at a server, receiving an encrypted score for each of a plurality of languages from a client, the encrypted scores having been generated by homomorphic addition of encrypted frequencies of n-grams in a list of n-grams extracted from text at the client, wherein the list is not provided to the server, the encrypted frequencies of the n-grams in the list having been extracted based on encrypted resources which, for each of the plurality of languages, include an encrypted frequency for each of a set of n-grams; at the server, decrypting the encrypted scores to generate unencrypted scores; and providing information to the client based on the unencrypted scores from which the client is able to identify a language for the text, wherein at least one of the decrypting of the encrypted scores and the providing information is performed by a processor. | 1. A method for text language identification comprising: at a server, receiving an encrypted score for each of a plurality of languages from a client, the encrypted scores having been generated by homomorphic addition of encrypted frequencies of n-grams in a list of n-grams extracted from text at the client, wherein the list is not provided to the server, the encrypted frequencies of the n-grams in the list having been extracted based on encrypted resources which, for each of the plurality of languages, include an encrypted frequency for each of a set of n-grams; at the server, decrypting the encrypted scores to generate unencrypted scores; and providing information to the client based on the unencrypted scores from which the client is able to identify a language for the text, wherein at least one of the decrypting of the encrypted scores and the providing information is performed by a processor. 14. The method of claim 1 , wherein the provided information includes a position of one of the unencrypted scores. | 0.922659 |
8,126,888 | 1 | 16 | 1. A computer-implemented method for digital search with task-enhanced search results, the method comprising: generating a search query based on interaction with a user; sending the search query to a search engine for an initial search; receiving initial search results from the search engine; predicting a current task being performed by the user at the time of the initial search, the current task being an action that the user is intending to perform at the time the search query is generated, wherein the current task corresponds to the search query without being specified by the search query, wherein predicting the current task includes associating with each of a plurality of tasks a probability that the current task is a particular task from among the plurality of tasks, wherein the associating uses past event records and associated task identifiers stored in a database, the associated task identifiers identifying the plurality of tasks from which the current task is predicted, and wherein the predicted current task is the particular task having a highest probability; computing task-related information from the predicted current task; filtering and ranking the initial search results based on the computed task-related information to produce enhanced search results; and presenting the enhanced search results to the user. | 1. A computer-implemented method for digital search with task-enhanced search results, the method comprising: generating a search query based on interaction with a user; sending the search query to a search engine for an initial search; receiving initial search results from the search engine; predicting a current task being performed by the user at the time of the initial search, the current task being an action that the user is intending to perform at the time the search query is generated, wherein the current task corresponds to the search query without being specified by the search query, wherein predicting the current task includes associating with each of a plurality of tasks a probability that the current task is a particular task from among the plurality of tasks, wherein the associating uses past event records and associated task identifiers stored in a database, the associated task identifiers identifying the plurality of tasks from which the current task is predicted, and wherein the predicted current task is the particular task having a highest probability; computing task-related information from the predicted current task; filtering and ranking the initial search results based on the computed task-related information to produce enhanced search results; and presenting the enhanced search results to the user. 16. The method of claim 1 wherein predicting a current task being performed by a user includes using a task-oriented user activity system. | 0.826633 |
9,037,897 | 17 | 19 | 17. A system for cloud-driven task execution, comprising: a memory; and at least one processor coupled to the memory and operative for: determining a plurality of attributes of a task that is (i) requested by a client device and (ii) precluded from execution on a given operating system of the client device based on a policy consideration of the given operating system, wherein the plurality of attributes comprises at least one policy context attribute and multiple context attributes comprising location of a user associated with the client device, the type of client device, a data type associated with the task, a location of data associated with the task, a given operation to be performed on data associated with the task, and one or more content attributes of data associated with the task; correlating each of the plurality of attributes to at least one alternative asset in a cloud network, wherein the at least one alternative asset is comprises at least one service that can execute tasks on the given operating system; provisioning the at least one alternative asset from the cloud network to the client device to enable execution of the task on the given operating system of the client device. | 17. A system for cloud-driven task execution, comprising: a memory; and at least one processor coupled to the memory and operative for: determining a plurality of attributes of a task that is (i) requested by a client device and (ii) precluded from execution on a given operating system of the client device based on a policy consideration of the given operating system, wherein the plurality of attributes comprises at least one policy context attribute and multiple context attributes comprising location of a user associated with the client device, the type of client device, a data type associated with the task, a location of data associated with the task, a given operation to be performed on data associated with the task, and one or more content attributes of data associated with the task; correlating each of the plurality of attributes to at least one alternative asset in a cloud network, wherein the at least one alternative asset is comprises at least one service that can execute tasks on the given operating system; provisioning the at least one alternative asset from the cloud network to the client device to enable execution of the task on the given operating system of the client device. 19. The system of claim 17 , wherein the at least one processor coupled to the memory operative for identifying an alternative asset set is further operative for identifying an alternative asset set in a registry database. | 0.770661 |
8,805,887 | 1 | 6 | 1. A method, including: compiling declarative source code that includes contents of a constraint-based execution model into a post-processed definition of the declarative source code that includes a compiled transformation of the declarative source code in which a declarative format of the constraint-based execution model is preserved, wherein values in the constraint-based execution model are conformable to a plurality of types, and wherein a particular value within the constraint-based execution model is conformable with all types in which the particular value does not violate a constraint codified in a type declaration; and packaging the post-processed definition of the declarative source code as an image file, wherein the image file preserves the declarative format of the constraint-based execution model stored in an extensible storage abstraction, and wherein the image file includes at least one artifact of the compiled transformation stored in the extensible storage abstraction and metadata describing attributes of contents stored in the extensible storage abstraction, the extensible storage abstraction including a plurality of tables having a plurality of entries representing the post-processed definition. | 1. A method, including: compiling declarative source code that includes contents of a constraint-based execution model into a post-processed definition of the declarative source code that includes a compiled transformation of the declarative source code in which a declarative format of the constraint-based execution model is preserved, wherein values in the constraint-based execution model are conformable to a plurality of types, and wherein a particular value within the constraint-based execution model is conformable with all types in which the particular value does not violate a constraint codified in a type declaration; and packaging the post-processed definition of the declarative source code as an image file, wherein the image file preserves the declarative format of the constraint-based execution model stored in an extensible storage abstraction, and wherein the image file includes at least one artifact of the compiled transformation stored in the extensible storage abstraction and metadata describing attributes of contents stored in the extensible storage abstraction, the extensible storage abstraction including a plurality of tables having a plurality of entries representing the post-processed definition. 6. The method of claim 1 further comprising deploying the image file to at least one repository. | 0.809524 |
8,918,431 | 1 | 11 | 1. A computing system including at least one processor, the system comprises: a user interface to allow a user to view and input data related to sales associated with the user; an observation sub-system having a processor configured to centralize data and to identify each of a plurality of sales concepts; a conceptualization sub-system configured to generate a plurality of nodes within an ontological mapping, wherein each of the plurality of nodes corresponds to a certain one of the plurality of identified sales concepts identified by the observation sub-system, the conceptualization sub-system configured to generate new nodes within the ontological mapping responsive to a determination that a new concept exists in the system; a relationship identification sub-system configured to create relationships between at least some of the plurality of identified sales concepts, and attribute affinity weights to the relationships, wherein the affinity weight quantifies a strength of the relationship between the sales concepts using concept occurrence and co-concept occurrence, and each concept occupies a node on the ontological mapping, the relationship identification sub-system to select relationships between the nodes with the greatest affinity index and then update the ontology to with the affinity index for the selected relationships; a change refinement sub-system configured to modify at least one of the plurality of nodes, affinity weights and relationships based upon information associated with the user; and a non-transitory knowledge store configured to the information associated with the user pertaining to a sub-plurality of the plurality of identified sales concepts. | 1. A computing system including at least one processor, the system comprises: a user interface to allow a user to view and input data related to sales associated with the user; an observation sub-system having a processor configured to centralize data and to identify each of a plurality of sales concepts; a conceptualization sub-system configured to generate a plurality of nodes within an ontological mapping, wherein each of the plurality of nodes corresponds to a certain one of the plurality of identified sales concepts identified by the observation sub-system, the conceptualization sub-system configured to generate new nodes within the ontological mapping responsive to a determination that a new concept exists in the system; a relationship identification sub-system configured to create relationships between at least some of the plurality of identified sales concepts, and attribute affinity weights to the relationships, wherein the affinity weight quantifies a strength of the relationship between the sales concepts using concept occurrence and co-concept occurrence, and each concept occupies a node on the ontological mapping, the relationship identification sub-system to select relationships between the nodes with the greatest affinity index and then update the ontology to with the affinity index for the selected relationships; a change refinement sub-system configured to modify at least one of the plurality of nodes, affinity weights and relationships based upon information associated with the user; and a non-transitory knowledge store configured to the information associated with the user pertaining to a sub-plurality of the plurality of identified sales concepts. 11. The system of claim 1 , wherein the observation sub-system is configured to identify each of the plurality of sales concepts by analyzing click stream data. | 0.761194 |
6,105,021 | 11 | 12 | 11. The system as recited in claim 10 wherein inspection of the processing list is concluded according to a distance factor. | 11. The system as recited in claim 10 wherein inspection of the processing list is concluded according to a distance factor. 12. The system as recited in claim 11 wherein the distance factor is a number of servers from the original starting point from which documents can be retrieved. | 0.925651 |
10,162,893 | 1 | 10 | 1. A system for transmitting and displaying electronic media from a service provider to a subscriber comprising: a service provider computer coupled to a controller of the sub scriber via a network connection; software executing on said service provider computer to present a web page that is used to log onto the system; an electronic media library accessible by said service provider computer, said electronic media library searchable by key word; wherein, prior to initiating a search from the subscriber via the web page, the electronic media library, via the software, displays an index of key words available for searching and a number count for each of the key words, the number count indicating the number of different media content associated with each of the respective key words; wherein, when the electronic media library is searched by a user-selected key word from the index, a plurality of pre-assembled media content associated with the key word is presented, and upon receiving a user-selected one of the plurality of pre-assembled media content presented, the selected content is presented allowing the sub scriber to view the selected pre-assembled media content prior to the content being added to the electronic media collection; wherein the pre-assembled media content that is added to the electronic media collection is configured for transmission to a display; wherein a value specifying a number of discrete media for presentment as a preview at one time and, both prior to selection of any of the plurality of pre-assembled media content and prior to being added to the electronic media collection as the plurality of pre-assembled media content, is selectable by the user via the web page. | 1. A system for transmitting and displaying electronic media from a service provider to a subscriber comprising: a service provider computer coupled to a controller of the sub scriber via a network connection; software executing on said service provider computer to present a web page that is used to log onto the system; an electronic media library accessible by said service provider computer, said electronic media library searchable by key word; wherein, prior to initiating a search from the subscriber via the web page, the electronic media library, via the software, displays an index of key words available for searching and a number count for each of the key words, the number count indicating the number of different media content associated with each of the respective key words; wherein, when the electronic media library is searched by a user-selected key word from the index, a plurality of pre-assembled media content associated with the key word is presented, and upon receiving a user-selected one of the plurality of pre-assembled media content presented, the selected content is presented allowing the sub scriber to view the selected pre-assembled media content prior to the content being added to the electronic media collection; wherein the pre-assembled media content that is added to the electronic media collection is configured for transmission to a display; wherein a value specifying a number of discrete media for presentment as a preview at one time and, both prior to selection of any of the plurality of pre-assembled media content and prior to being added to the electronic media collection as the plurality of pre-assembled media content, is selectable by the user via the web page. 10. The system according to claim 1 , wherein the electronic media collection is transmitted to the subscriber. | 0.900538 |
10,108,704 | 16 | 17 | 16. A computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: accessing a search log of a search engine, the search log comprising: a plurality of queries submitted by users of the search engine; and for each query in the plurality of queries, a set of attribute values, wherein the set of attribute values comprises an indication that a user that submitted a query in the plurality of queries switched from the search engine to a different search engine and submitted the query to the different search engine; labeling each query in the plurality of queries as being a dissatisfied query based upon the indication that the user that submitted the query switched from the search engine to the different search engine and submitted the respective query to the different search engine; selecting a subset of query attribute values from the set of attribute values; computing a metric that is indicative of a correlation between user dissatisfaction with the search engine and the subset of query attribute values based at least in part upon the subset of query attribute values and the labeling of each query in the plurality of queries as being the dissatisfied query; and learning a segment-specific ranker of the search engine based upon the metric, wherein responsive to receipt of a query that has the subset of query attribute values, the segment-specific ranker is selected for ranking search results based upon the query, and further wherein the segment-specific ranker is selected from amongst a plurality of possible rankers when the query is received. | 16. A computer-readable medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: accessing a search log of a search engine, the search log comprising: a plurality of queries submitted by users of the search engine; and for each query in the plurality of queries, a set of attribute values, wherein the set of attribute values comprises an indication that a user that submitted a query in the plurality of queries switched from the search engine to a different search engine and submitted the query to the different search engine; labeling each query in the plurality of queries as being a dissatisfied query based upon the indication that the user that submitted the query switched from the search engine to the different search engine and submitted the respective query to the different search engine; selecting a subset of query attribute values from the set of attribute values; computing a metric that is indicative of a correlation between user dissatisfaction with the search engine and the subset of query attribute values based at least in part upon the subset of query attribute values and the labeling of each query in the plurality of queries as being the dissatisfied query; and learning a segment-specific ranker of the search engine based upon the metric, wherein responsive to receipt of a query that has the subset of query attribute values, the segment-specific ranker is selected for ranking search results based upon the query, and further wherein the segment-specific ranker is selected from amongst a plurality of possible rankers when the query is received. 17. The computer-readable medium of claim 16 , wherein the metric is computed as a function of a probability of the subset of query attribute values occurring in a dissatisfied query divided by a product of: a probability of the subset of query attribute values occurring in any query; and a probability of any query being a dissatisfied query. | 0.509972 |
8,904,474 | 1 | 5 | 1. A computing device comprising: one or more processors; one or more computer-readable hardware storage memories comprising computer readable instructions which, when executed by the one or more processors, implement: a security module configured to enable secure information transfer between a web content scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. | 1. A computing device comprising: one or more processors; one or more computer-readable hardware storage memories comprising computer readable instructions which, when executed by the one or more processors, implement: a security module configured to enable secure information transfer between a web content scripting engine and layout engine, the security module comprising: a module configured to enable restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; a module configured to enable at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object; and a module configured to enable at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 5. The system of claim 1 , the security module further comprising: a module configured to enable bypassing security checks based, at least in part, on a determination of the information transfer occurring in a same domain. | 0.715385 |
9,116,977 | 9 | 14 | 9. An apparatus comprises: one or more processors; and computer storage media having stored thereon computer-executable components that are executable by the one or more processors, the one or more computer-executable components comprising: an obtaining unit that obtains a category click rate of a query and a category click rate of published information; a calculation unit that calculates a similarity degree between the category click rate of the query and the category click rate of the published information; and a transmission unit that transmits the published information as a successful matching result if the calculated similarity degree is above a first threshold; wherein the obtaining unit comprises: a first segmenting module that segments the query to obtain one or more words; a first obtaining module that obtains a category click rate of the one or more words after the segment from historical statistics information of category click rates, the category click rate of the one or more words after the segment being a category click rate of a string formed by the one or more words after the segment for a corresponding category; a revising module that determines a word in the one or more words after the segment as a present word; if a difference between a category click rate of a string formed by the one or more words after the segment except for the present word and a category click rate of another string formed by the one or more words after the segment reaches a second threshold, determining the present word as a core word; or if a difference between a category click rate of a string formed by the one or more words after the segment except for the present word and a category click rate of another string formed by the one or more words after the segment does not reach the second threshold, determining the present word as a non-core word; and a second obtaining module that obtains a category click rate of a string formed by the one or more core words for the corresponding category as the category click rate of the query. | 9. An apparatus comprises: one or more processors; and computer storage media having stored thereon computer-executable components that are executable by the one or more processors, the one or more computer-executable components comprising: an obtaining unit that obtains a category click rate of a query and a category click rate of published information; a calculation unit that calculates a similarity degree between the category click rate of the query and the category click rate of the published information; and a transmission unit that transmits the published information as a successful matching result if the calculated similarity degree is above a first threshold; wherein the obtaining unit comprises: a first segmenting module that segments the query to obtain one or more words; a first obtaining module that obtains a category click rate of the one or more words after the segment from historical statistics information of category click rates, the category click rate of the one or more words after the segment being a category click rate of a string formed by the one or more words after the segment for a corresponding category; a revising module that determines a word in the one or more words after the segment as a present word; if a difference between a category click rate of a string formed by the one or more words after the segment except for the present word and a category click rate of another string formed by the one or more words after the segment reaches a second threshold, determining the present word as a core word; or if a difference between a category click rate of a string formed by the one or more words after the segment except for the present word and a category click rate of another string formed by the one or more words after the segment does not reach the second threshold, determining the present word as a non-core word; and a second obtaining module that obtains a category click rate of a string formed by the one or more core words for the corresponding category as the category click rate of the query. 14. The apparatus as recited in claim 9 , wherein the published information comprises product information. | 0.898273 |
7,912,186 | 5 | 6 | 5. The system of claim 4 , wherein the unified messaging system includes: a component that receives from a first device a message of a first format; and a unified messaging component that analyzes the message and converts the message to a second format that corresponds to a target device that conveys the message in accordance with a user instruction, the user instruction being transmitted via the currently selected user interface. | 5. The system of claim 4 , wherein the unified messaging system includes: a component that receives from a first device a message of a first format; and a unified messaging component that analyzes the message and converts the message to a second format that corresponds to a target device that conveys the message in accordance with a user instruction, the user instruction being transmitted via the currently selected user interface. 6. The system of claim 5 , wherein the received message is text based. | 0.97952 |
10,025,564 | 8 | 10 | 8. A computer program product for generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: identifying a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying detail of the first context constraint on the IDE; and receiving changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object. | 8. A computer program product for generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: identifying a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying detail of the first context constraint on the IDE; and receiving changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object. 10. The computer program product of claim 8 , wherein the first zoom-input is caused by a user hovering a cursor over the first object. | 0.945565 |
9,870,655 | 1 | 9 | 1. An apparatus for processing a plurality of logging policies, the logging policies defining data logging specifications for selectively collecting vehicle data according to purpose of using the vehicle data, the apparatus comprising: a logging policy input device configured to receive the plurality of logging policies for vehicle data, the plurality of logging policies being determined depending upon car models; a logging policy storage configured to store the logging policies received by the logging policy input unit; and a processor including: a logging policy analyzer configured to parse the logging policies stored in the logging policy storage and extract variables from the parsed logging policies; a rule maker configured to make a logging policy applying rule based on the variables extracted by the logging policy analyzer; and a logging policy processor configured to read and process the corresponding logging policy which is stored in the logging policy storage depending on the logging policy applying rule made by the rule maker in order to prevent a collision situation between the plurality of logging policies, when the plurality of logging policies are applied to one vehicle under multiple users and multiple service environment, wherein the logging policy input device includes: a memory configured to temporarily store the received logging policy; a filter configured to authenticate the logging policies stored in the memory and perform a primary integrity check and a redundancy check; and an ID tagger configured to tag IDs to the logging policies normally passing through the filter, and wherein, when an application period of a logging policy having a high priority arrives while a logging policy having a low priority is applied, the logging policy processor pauses applying the logging policy having the low priority and applies the logging policy having the high priority. | 1. An apparatus for processing a plurality of logging policies, the logging policies defining data logging specifications for selectively collecting vehicle data according to purpose of using the vehicle data, the apparatus comprising: a logging policy input device configured to receive the plurality of logging policies for vehicle data, the plurality of logging policies being determined depending upon car models; a logging policy storage configured to store the logging policies received by the logging policy input unit; and a processor including: a logging policy analyzer configured to parse the logging policies stored in the logging policy storage and extract variables from the parsed logging policies; a rule maker configured to make a logging policy applying rule based on the variables extracted by the logging policy analyzer; and a logging policy processor configured to read and process the corresponding logging policy which is stored in the logging policy storage depending on the logging policy applying rule made by the rule maker in order to prevent a collision situation between the plurality of logging policies, when the plurality of logging policies are applied to one vehicle under multiple users and multiple service environment, wherein the logging policy input device includes: a memory configured to temporarily store the received logging policy; a filter configured to authenticate the logging policies stored in the memory and perform a primary integrity check and a redundancy check; and an ID tagger configured to tag IDs to the logging policies normally passing through the filter, and wherein, when an application period of a logging policy having a high priority arrives while a logging policy having a low priority is applied, the logging policy processor pauses applying the logging policy having the low priority and applies the logging policy having the high priority. 9. The apparatus according to claim 1 , wherein the logging policy analyzer includes: a contents checker configured to perform a contents check to verify a result of the primary integrity check performed by the filter; and a grammar checker configured to perform a grammar check to detect a structural error of a policy file in a script form. | 0.501458 |
8,825,405 | 13 | 16 | 13. The apparatus of claim 12 , wherein the at least one processor is further operative with the set of instructions to: determine whether the first road intersects the second road; and generate a portion of the routing graph that includes the first and second route links when the first and second roads intersect, the first and second route links being connected within the routing graph by a node. | 13. The apparatus of claim 12 , wherein the at least one processor is further operative with the set of instructions to: determine whether the first road intersects the second road; and generate a portion of the routing graph that includes the first and second route links when the first and second roads intersect, the first and second route links being connected within the routing graph by a node. 16. The apparatus of claim 13 , wherein the at least one processor is further operative with the set of instructions to: obtain connectivity information associated with the first and second route links; and determine whether the first and second roads in sect based on the obtained connectivity information. | 0.851834 |
9,244,985 | 14 | 15 | 14. The method of claim 13 , wherein the search results are filtered based on an action that a member of the social networking service that corresponds to the display area has taken with respect to content associated with the search results, or an association that the member has with the content. | 14. The method of claim 13 , wherein the search results are filtered based on an action that a member of the social networking service that corresponds to the display area has taken with respect to content associated with the search results, or an association that the member has with the content. 15. The method of claim 14 , wherein the content is filtered to include only content authored by the member; and wherein the filtered search results that are displayed comprise only snippets of content that is authored by the member. | 0.925985 |
9,400,958 | 6 | 7 | 6. A non-transitory computer-readable storage medium having stored thereon instructions that cause one or more processors to display information, the instructions comprising: instructions that cause the one or more processors to identify, based at least in part on data stored in a data store, a policy violation; instructions that cause the one or more processors to identify a plurality of semantic objects that cause the policy violation, the identified plurality of semantic objects including semantic objects of different semantic object types, the identified plurality of semantic objects representing data related to a business policy in an organization; instructions that cause the one or more processors to compute a probability of occurrence of the policy violation in each semantic object of the identified plurality of semantic objects, the probability of occurrence of the policy violation comprising data that represents a relationship between a first state of a first semantic object of the identified plurality of semantic objects and a second state of a second semantic object of the identified plurality of semantic objects; instructions that cause the one or more processors to generate a first graphical representation of the identified plurality of semantic objects based on the probability of occurrence of the policy violation; instructions that cause the one or more processors to cause display of the first graphical representation of the identified plurality of semantic objects that cause the policy violation in an arrangement indicative of the relationship between at least the first semantic object and the second semantic object of the identified plurality of semantic objects; instructions that cause the one or more processors to identify a semantic object as an origin of the policy violation in the plurality of semantic objects in the first graphical representation, the semantic object comprising a set of one or more workflows; instructions that cause the one or more processors to identify at least one workflow from the set of one or more workflows related to the semantic object that cause the policy violation; instructions that cause the one or more processors to cause a display of the identified one or more workflows related to the policy violation in a display interface of the first graphical representation; and instructions that cause the one or more processors to cause the identified one or more workflows to be processed in accordance with an order of the arrangement of the identified plurality of semantic objects. | 6. A non-transitory computer-readable storage medium having stored thereon instructions that cause one or more processors to display information, the instructions comprising: instructions that cause the one or more processors to identify, based at least in part on data stored in a data store, a policy violation; instructions that cause the one or more processors to identify a plurality of semantic objects that cause the policy violation, the identified plurality of semantic objects including semantic objects of different semantic object types, the identified plurality of semantic objects representing data related to a business policy in an organization; instructions that cause the one or more processors to compute a probability of occurrence of the policy violation in each semantic object of the identified plurality of semantic objects, the probability of occurrence of the policy violation comprising data that represents a relationship between a first state of a first semantic object of the identified plurality of semantic objects and a second state of a second semantic object of the identified plurality of semantic objects; instructions that cause the one or more processors to generate a first graphical representation of the identified plurality of semantic objects based on the probability of occurrence of the policy violation; instructions that cause the one or more processors to cause display of the first graphical representation of the identified plurality of semantic objects that cause the policy violation in an arrangement indicative of the relationship between at least the first semantic object and the second semantic object of the identified plurality of semantic objects; instructions that cause the one or more processors to identify a semantic object as an origin of the policy violation in the plurality of semantic objects in the first graphical representation, the semantic object comprising a set of one or more workflows; instructions that cause the one or more processors to identify at least one workflow from the set of one or more workflows related to the semantic object that cause the policy violation; instructions that cause the one or more processors to cause a display of the identified one or more workflows related to the policy violation in a display interface of the first graphical representation; and instructions that cause the one or more processors to cause the identified one or more workflows to be processed in accordance with an order of the arrangement of the identified plurality of semantic objects. 7. The computer-readable storage medium of claim 6 , wherein the arrangement includes a graph comprising a plurality of nodes and one or more edges connecting at least a subset of the nodes, each of the plurality of nodes corresponding to at least one of the identified plurality of semantic objects, and the subset of the nodes including nodes corresponding to different semantic object types. | 0.501266 |
8,103,501 | 1 | 3 | 1. In a computerized network system, a method for generation and authentication of a signed document over the network comprising the steps of: (a) providing to a service through an interactive interface provided by software executing from a digital storage medium associated with an Internet-connected server on the network providing the service, personal user data specific to a new system registrant, including textual or graphical digital data or images; (b) storing the user data provided in step (a) in a digital storage medium or memory associated with the server; (c) generating and providing to the new registrant unique enrollment session identifier and additional data required for continuing registration, said identifier and additional data displayable on a terminal data device connected to the system network and accessible by the registrant; (d) providing to the server via a telecommunications device initial voice samples of new registrant, said samples recorded, analyzed and stored along with personal data provided in step (a) in memory or other digital storage associated with the server; (e) assigning to the registered user a unique authentication certificate and storing said certificate in memory or other digital storage associated with the server; (f) uploading through a user data terminal device a new document to be certified and authenticated; (g) providing to the server via a telecommunications device current voice samples of new registrant, said samples recorded, analyzed and stored along with personal data provided in step (a) in memory or other digital storage associated with the server; (h) comparing in a voice comparison unit associated with the server current voice samples provided in step (g) with initial voice samples provided in step (d), and if matched, providing a corresponding output signal to a certification unit associated with the server, said signal generating a current authentication certificate; and (i) attaching the authentication certificate of step (h) to the document of step (f) wherein the document becomes a signed and authenticated document downloadable to the user's data terminal device, and verifiable by another querying user; wherein in practice of the method separate system channels are utilized for generation and authentication of the signed document, and document data is transmitted via a channel other than that for transmitting voice data, and generation and authentication of the signed document is accomplished by a single end user registered to the system wherein the single user is the signer of the document. | 1. In a computerized network system, a method for generation and authentication of a signed document over the network comprising the steps of: (a) providing to a service through an interactive interface provided by software executing from a digital storage medium associated with an Internet-connected server on the network providing the service, personal user data specific to a new system registrant, including textual or graphical digital data or images; (b) storing the user data provided in step (a) in a digital storage medium or memory associated with the server; (c) generating and providing to the new registrant unique enrollment session identifier and additional data required for continuing registration, said identifier and additional data displayable on a terminal data device connected to the system network and accessible by the registrant; (d) providing to the server via a telecommunications device initial voice samples of new registrant, said samples recorded, analyzed and stored along with personal data provided in step (a) in memory or other digital storage associated with the server; (e) assigning to the registered user a unique authentication certificate and storing said certificate in memory or other digital storage associated with the server; (f) uploading through a user data terminal device a new document to be certified and authenticated; (g) providing to the server via a telecommunications device current voice samples of new registrant, said samples recorded, analyzed and stored along with personal data provided in step (a) in memory or other digital storage associated with the server; (h) comparing in a voice comparison unit associated with the server current voice samples provided in step (g) with initial voice samples provided in step (d), and if matched, providing a corresponding output signal to a certification unit associated with the server, said signal generating a current authentication certificate; and (i) attaching the authentication certificate of step (h) to the document of step (f) wherein the document becomes a signed and authenticated document downloadable to the user's data terminal device, and verifiable by another querying user; wherein in practice of the method separate system channels are utilized for generation and authentication of the signed document, and document data is transmitted via a channel other than that for transmitting voice data, and generation and authentication of the signed document is accomplished by a single end user registered to the system wherein the single user is the signer of the document. 3. The method of claim 1 wherein in step (i) text, image or other data representing the signer is attached on the document in combination with the authentication certificate, the certificate generated as a result of signer voice analysis performed in timely fashion with the generation of the document. | 0.50165 |
7,584,458 | 1 | 9 | 1. In a computer system comprising a computer, a method of annotating computer program code stored on a computer-readable medium, the method comprising: inserting, by the computer, one or more in-line code annotations at one or more annotation targets in source code; wherein the one or more in-line code annotations comprise at least one annotation on a first pointer to a buffer, wherein the at least one annotation comprises a property that indicates a characteristic of the buffer, wherein the property that indicates the characteristic of the buffer takes a size argument, and wherein the size argument comprises a location of a second pointer associated with the buffer; and wherein the at least one annotation on the first pointer is placed in an argument list to a function call that uses the first pointer as a parameter. | 1. In a computer system comprising a computer, a method of annotating computer program code stored on a computer-readable medium, the method comprising: inserting, by the computer, one or more in-line code annotations at one or more annotation targets in source code; wherein the one or more in-line code annotations comprise at least one annotation on a first pointer to a buffer, wherein the at least one annotation comprises a property that indicates a characteristic of the buffer, wherein the property that indicates the characteristic of the buffer takes a size argument, and wherein the size argument comprises a location of a second pointer associated with the buffer; and wherein the at least one annotation on the first pointer is placed in an argument list to a function call that uses the first pointer as a parameter. 9. The method of claim 1 wherein the second pointer associated with the buffer is an internal pointer for the buffer. | 0.891466 |
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