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9,418,111 | 1 | 7 | 1. A method comprising: receiving, by one or more computers, input specifying, explicitly or implicitly, (i) an aggregation function agg having an input type and an output type, a relation s that has a domain and a range, wherein s represents one or more entities to be aggregated over, and a relation t that is a relation from the range of s to the input type of the aggregation function agg, and (ii) a recursive relation definition, wherein an aggregation construct agg* is within a recursive term of the recursive relation definition; and evaluating, by the one or more computers, the recursive relation definition, including evaluating the aggregation construct agg* to calculate a relation between the domain of s and the output type of the aggregation function agg according to
agg*( s,t )={( m ,agg( n ))|β d :( m,d )Ξ΅ s,nΡΠ{|t ( y )| yΞ΅s ( m )|}}. | 1. A method comprising: receiving, by one or more computers, input specifying, explicitly or implicitly, (i) an aggregation function agg having an input type and an output type, a relation s that has a domain and a range, wherein s represents one or more entities to be aggregated over, and a relation t that is a relation from the range of s to the input type of the aggregation function agg, and (ii) a recursive relation definition, wherein an aggregation construct agg* is within a recursive term of the recursive relation definition; and evaluating, by the one or more computers, the recursive relation definition, including evaluating the aggregation construct agg* to calculate a relation between the domain of s and the output type of the aggregation function agg according to
agg*( s,t )={( m ,agg( n ))|β d :( m,d )Ξ΅ s,nΡΠ{|t ( y )| yΞ΅s ( m )|}}. 7. The method of claim 1 , wherein the aggregation function agg has multiple input types, and the relation t is a relation from the range of s to the multiple input types of the aggregation function agg. | 0.558696 |
7,890,964 | 1 | 9 | 1. A method for providing data to a groupware client application (GCA) of an office productivity suite of applications, comprising: receiving at an enterprise server a query from the GCA for enterprise-level data, the query generated within a context of the GCA for the enterprise-level data, the context being a local working environment of the GCA, wherein the GCA being a collaborative application having an associated groupware server that provides services to collaborative applications, the GCA including native functionality to access the associated groupware server but not to access the enterprise server, wherein an extension to the GCA enables the GCA to interact directly with the enterprise server, bypassing the groupware server to access enterprise-level data while leaving unaffected access to other data by the GCA through the groupware server, and wherein the enterprise-level data is associated with execution of a workflow from within the context of the GCA; determining at the enterprise server the context of the GCA in which the query was generated, including identifying a workflow associated with the query; selecting enterprise data based at least in part on the determined context; and providing, in response to the query, the selected data within the context of the GCA through the extension to the GCA, including integrating the selected data into a user interface of the GCA to enable interaction with the selected data through the GCA via the extension that provides functionality in the GCA to interact with enterprise-level data associated with the workflow from the context of the GCA without having to change from the context of the GCA to another application to access the enterprise-level data. | 1. A method for providing data to a groupware client application (GCA) of an office productivity suite of applications, comprising: receiving at an enterprise server a query from the GCA for enterprise-level data, the query generated within a context of the GCA for the enterprise-level data, the context being a local working environment of the GCA, wherein the GCA being a collaborative application having an associated groupware server that provides services to collaborative applications, the GCA including native functionality to access the associated groupware server but not to access the enterprise server, wherein an extension to the GCA enables the GCA to interact directly with the enterprise server, bypassing the groupware server to access enterprise-level data while leaving unaffected access to other data by the GCA through the groupware server, and wherein the enterprise-level data is associated with execution of a workflow from within the context of the GCA; determining at the enterprise server the context of the GCA in which the query was generated, including identifying a workflow associated with the query; selecting enterprise data based at least in part on the determined context; and providing, in response to the query, the selected data within the context of the GCA through the extension to the GCA, including integrating the selected data into a user interface of the GCA to enable interaction with the selected data through the GCA via the extension that provides functionality in the GCA to interact with enterprise-level data associated with the workflow from the context of the GCA without having to change from the context of the GCA to another application to access the enterprise-level data. 9. The method of claim 1 , wherein providing the selected data to the GCA comprises: populating a task pane of the GCA with the selected data. | 0.792398 |
7,765,574 | 6 | 7 | 6. A method as in claim 1 wherein the expected event cues are taken from at least one of: a text information stream, an image information stream, or an audio information stream. | 6. A method as in claim 1 wherein the expected event cues are taken from at least one of: a text information stream, an image information stream, or an audio information stream. 7. A method as in claim 6 wherein the expected event cues taken from the text information stream include at least one of: token phrases for the class of multimedia presentations, closed captioned punctuation cues, closed captioned word cues, or named entities. | 0.667519 |
9,070,357 | 1 | 3 | 1. A method comprising: indexing, by a computer comprising hardware and software executing on the hardware, a plurality of health conditions of a human against a plurality of different health-related speech characteristics; identifying, by the computer, a speech segment of a speaker; analyzing, by the computer, the speech segment to determine a presence or absence of any of the health-related speech characteristics; upon determining a presence of one of the health-related speech characteristics, determining, by the computer, a corresponding one of the health conditions consistent with the indexing; and generating, by the computer, an alert indicating that the speaker has a statistically significant likelihood of having the determined health condition based on results of the analyzing, wherein the speech segment is received from mobile computing device of the speaker, wherein the alert triggers an advertisement specific to the determined health condition to be sent over a network for presentation on the mobile communication device. | 1. A method comprising: indexing, by a computer comprising hardware and software executing on the hardware, a plurality of health conditions of a human against a plurality of different health-related speech characteristics; identifying, by the computer, a speech segment of a speaker; analyzing, by the computer, the speech segment to determine a presence or absence of any of the health-related speech characteristics; upon determining a presence of one of the health-related speech characteristics, determining, by the computer, a corresponding one of the health conditions consistent with the indexing; and generating, by the computer, an alert indicating that the speaker has a statistically significant likelihood of having the determined health condition based on results of the analyzing, wherein the speech segment is received from mobile computing device of the speaker, wherein the alert triggers an advertisement specific to the determined health condition to be sent over a network for presentation on the mobile communication device. 3. The method of claim 1 , further comprising: storing a plurality of audio segments for the speaker while the speaker is in an initial state of health, said audio segments being part of a speech history specific to the speaker, wherein the determining of the presence of the health-related speech characteristics is based on deviations between the health-related speech characteristics in the speech segment and the audio segments of the speech history. | 0.718711 |
8,375,312 | 12 | 20 | 12. A medium bearing instructions to enable one or more machines to perform operations, the operations comprising: displaying one or more poster frames in a user interface, wherein a poster frame corresponds to an item of digital content; in response to receiving an input, displaying a plurality of first level classification panes adjacent to a poster frame corresponding to an item of digital content, wherein each of the first level classification panes is associated with a corresponding keyword; detecting a selection and positioning of the poster frame at an at least partially common location with a classification pane of the plurality of first level classification panes; and in response to the detecting, associating the item of digital content to which the selected poster frame corresponds with a keyword associated with the first level classification pane on which the selected poster frame that corresponds to the item of digital content is positioned. | 12. A medium bearing instructions to enable one or more machines to perform operations, the operations comprising: displaying one or more poster frames in a user interface, wherein a poster frame corresponds to an item of digital content; in response to receiving an input, displaying a plurality of first level classification panes adjacent to a poster frame corresponding to an item of digital content, wherein each of the first level classification panes is associated with a corresponding keyword; detecting a selection and positioning of the poster frame at an at least partially common location with a classification pane of the plurality of first level classification panes; and in response to the detecting, associating the item of digital content to which the selected poster frame corresponds with a keyword associated with the first level classification pane on which the selected poster frame that corresponds to the item of digital content is positioned. 20. The medium of claim 12 wherein associating the keyword with the item comprises including the keyword in metadata associated with the item. | 0.925498 |
8,239,185 | 4 | 5 | 4. The apparatus of claim 1 , further comprising: g) a data collection device adapted to collecting data in digital form and transmitting the data across a digital network; and h) data server logic associated with the interviewer digital electronic system adapted to receiving the data from the data collection device across the digital network and causing the data to be saved in data server digital storage. | 4. The apparatus of claim 1 , further comprising: g) a data collection device adapted to collecting data in digital form and transmitting the data across a digital network; and h) data server logic associated with the interviewer digital electronic system adapted to receiving the data from the data collection device across the digital network and causing the data to be saved in data server digital storage. 5. The apparatus of claim 4 , wherein the headset system includes the data server logic and the data server digital storage. | 0.5 |
8,682,677 | 2 | 3 | 2. The method of claim 1 , wherein the linear evaluation comprises estimating a weight for each feature in the features. | 2. The method of claim 1 , wherein the linear evaluation comprises estimating a weight for each feature in the features. 3. The method of claim 2 , wherein the weight of each feature indicates how much each feature contributes to the policy. | 0.5 |
8,347,381 | 1 | 5 | 1. A computer-implemented method for detecting a malicious social networking profile, the method comprising: detecting, by a computer system, access of a social networking profile on a social networking website; selecting, by the computer system, based on a type of the social networking profile, at least one fingerprint from a plurality of fingerprints, each of the plurality of fingerprints specifying characteristics for evaluating one or more types of social networking profiles, the selected fingerprint comprising a legitimate fingerprint that specifies characteristics of legitimate social networking profiles of the type; evaluating, by the computer system, whether the social networking profile includes characteristics specified by the selected fingerprint; determining, by the computer system, whether the social networking profile is suspicious based on the evaluation; responsive to a determination that the social networking profile is suspicious, identifying, by the computer system, a malicious fingerprint, the malicious fingerprint specifying characteristics of malicious social networking profiles; evaluating, by the computer system, whether the social networking profile includes the characteristics specified by the malicious fingerprint; determining, by the computer system, whether the social networking profile is malicious based on the evaluation of whether the social networking profile includes the characteristics specified by the malicious fingerprint; and responsive to determining that the social networking profile is malicious, reporting, by the computer system, the social networking profile as being malicious. | 1. A computer-implemented method for detecting a malicious social networking profile, the method comprising: detecting, by a computer system, access of a social networking profile on a social networking website; selecting, by the computer system, based on a type of the social networking profile, at least one fingerprint from a plurality of fingerprints, each of the plurality of fingerprints specifying characteristics for evaluating one or more types of social networking profiles, the selected fingerprint comprising a legitimate fingerprint that specifies characteristics of legitimate social networking profiles of the type; evaluating, by the computer system, whether the social networking profile includes characteristics specified by the selected fingerprint; determining, by the computer system, whether the social networking profile is suspicious based on the evaluation; responsive to a determination that the social networking profile is suspicious, identifying, by the computer system, a malicious fingerprint, the malicious fingerprint specifying characteristics of malicious social networking profiles; evaluating, by the computer system, whether the social networking profile includes the characteristics specified by the malicious fingerprint; determining, by the computer system, whether the social networking profile is malicious based on the evaluation of whether the social networking profile includes the characteristics specified by the malicious fingerprint; and responsive to determining that the social networking profile is malicious, reporting, by the computer system, the social networking profile as being malicious. 5. The method of claim 1 , further comprising: responsive to a determination that the social networking profile is malicious, preventing a browser from being redirected to a domain different than the domain of the social networking website. | 0.762376 |
7,730,395 | 3 | 10 | 3. The method of claim 1 further comprising the step of: storing said one or more virtual tags with said one or more transformation rules as a respective one or more virtual tag objects in a virtual tag repository; and retrieving said one or more stored virtual tag objects from said virtual repository when subsequently accessing said electronic document, said stored one or more transformation rules being used to generate said virtual page. | 3. The method of claim 1 further comprising the step of: storing said one or more virtual tags with said one or more transformation rules as a respective one or more virtual tag objects in a virtual tag repository; and retrieving said one or more stored virtual tag objects from said virtual repository when subsequently accessing said electronic document, said stored one or more transformation rules being used to generate said virtual page. 10. The method of claim 3 wherein said virtual tag object is formatted as an extensible markup language (XML) view. | 0.931548 |
8,508,489 | 13 | 14 | 13. The method of claim 6 wherein said text is a representation of the converted handwritten input when the percentage accuracy of recognition is over a threshold. | 13. The method of claim 6 wherein said text is a representation of the converted handwritten input when the percentage accuracy of recognition is over a threshold. 14. The method of claim 13 wherein said percentage accuracy threshold is 90%. | 0.5 |
10,042,622 | 13 | 17 | 13. A computer program product operable on a computer system for generating ease of use interfaces for legacy system management facilities (SMF), comprising a non-transitory computer storage medium readable by the computer system having a processor and a memory configured to store computer executable instructions for execution by the processor of the computer system for performing a method comprising: retrieving an SMF record from an SMF data source through an SMF data interface from a file, over a network or via a real-time API, wherein the SMF record comprises a data control section (DSECT) with code comments for storing a mapping of the SMF record defining data structure of the SMF record with one or more fields; converting the mapping of the SMF record into an intermediate format representing the mapping of the SMF record and corresponding information extracted from the code comments among the one or more fields of the SMF record; generating at least one application programming interface (API) in a different computer language using the intermediate format; and accessing the SMF record using the API generated, wherein the converting comprises: building a set of matching keywords from the code comments including wildcard matching; weighting different matching keywords; and matching the mapping of the SMF record to the intermediate format with one or more corresponding fields by combining the matching keywords, weighting, descriptions and a location of the one or more fields. | 13. A computer program product operable on a computer system for generating ease of use interfaces for legacy system management facilities (SMF), comprising a non-transitory computer storage medium readable by the computer system having a processor and a memory configured to store computer executable instructions for execution by the processor of the computer system for performing a method comprising: retrieving an SMF record from an SMF data source through an SMF data interface from a file, over a network or via a real-time API, wherein the SMF record comprises a data control section (DSECT) with code comments for storing a mapping of the SMF record defining data structure of the SMF record with one or more fields; converting the mapping of the SMF record into an intermediate format representing the mapping of the SMF record and corresponding information extracted from the code comments among the one or more fields of the SMF record; generating at least one application programming interface (API) in a different computer language using the intermediate format; and accessing the SMF record using the API generated, wherein the converting comprises: building a set of matching keywords from the code comments including wildcard matching; weighting different matching keywords; and matching the mapping of the SMF record to the intermediate format with one or more corresponding fields by combining the matching keywords, weighting, descriptions and a location of the one or more fields. 17. The computer program product of claim 13 , wherein the accessing the SMF record comprises: retrieving data from the SMF record using the API generated; processing the data retrieved from the SMF record using the different computer language; and storing the data processed back to the SMF record. | 0.578873 |
7,668,849 | 11 | 12 | 11. A computer implemented system for processing data associated with an e-mail, the system comprising: (a) a data processing unit; (b) programming, executable by said data processing unit, for providing a plurality of data processing modules, said data processing modules comprising: an e-mail capture and parsing engine for intercepting, copying, and processing e-mails transmitted from a gateway to an email server, said processing comprising dividing a copy of an email into sections including at least a header section and a body section, and dividing the header section into sections comprising one or more of sender email address, sender name, recipient email address, recipient name, summary of email contents, date the email was sent, or time the email was sent; an email reload engine for loading data associated with archived or stored emails; a web crawler engine for Internet crawling and capturing Internet web pages; a document gathering engine for capturing data from external sources comprising one or more of an application data warehouse, application server, or file system; one or more data staging areas configured for temporary storage of data associated with said email capture and parsing engine, said web crawler engine, and said document gathering engine; a text extraction and parsing engine for receiving data from the data staging areas, extracting structured data from unstructured data, and correlating extracted structured data and associated unstructured data and a to define a link between said structured data and said associated unstructured data; a data holding area configured for temporary storage of said structured and said unstructured data from said text extraction and parsing engine; a data loading engine for loading and storing into a database management system said structured data and said unstructured data from said data holding area based on said link; an email account management engine for bypassing said text extraction and parsing engine and directly copying structured data from said email server to said database management system; (c) wherein said plurality of data processing modules are configured for carrying out operations comprising: receiving unstructured data and structured data from a plurality of sources comprising an unstructured data source and a structured data source, the unstructured data being associated with the structured data, wherein the unstructured data source and the structured data source are each associated with at least an email, the email including a parsing the header into at least a sending email address, a receiving email address, a date and time of transmission associated with the email, and a carbon copy email address; evaluating the email using an email capture and parsing engine, wherein the email capture and parsing engine is configured to generate a summary of content associated with the email, the sending email address, the receiving email address, the date and the time of transmission associated with the email, the carbon copy email address, and a summary used to classify the email; correlating the unstructured data and the structured data to establish a link between the unstructured data and the structured data, wherein the link integrates the unstructured data and the structured data; and storing the unstructured data and the structured data in a data structure based on the link, wherein the unstructured data is stored in an unstructured portion of the data structure and wherein the structured data is stored in a structured portion of the data structure. | 11. A computer implemented system for processing data associated with an e-mail, the system comprising: (a) a data processing unit; (b) programming, executable by said data processing unit, for providing a plurality of data processing modules, said data processing modules comprising: an e-mail capture and parsing engine for intercepting, copying, and processing e-mails transmitted from a gateway to an email server, said processing comprising dividing a copy of an email into sections including at least a header section and a body section, and dividing the header section into sections comprising one or more of sender email address, sender name, recipient email address, recipient name, summary of email contents, date the email was sent, or time the email was sent; an email reload engine for loading data associated with archived or stored emails; a web crawler engine for Internet crawling and capturing Internet web pages; a document gathering engine for capturing data from external sources comprising one or more of an application data warehouse, application server, or file system; one or more data staging areas configured for temporary storage of data associated with said email capture and parsing engine, said web crawler engine, and said document gathering engine; a text extraction and parsing engine for receiving data from the data staging areas, extracting structured data from unstructured data, and correlating extracted structured data and associated unstructured data and a to define a link between said structured data and said associated unstructured data; a data holding area configured for temporary storage of said structured and said unstructured data from said text extraction and parsing engine; a data loading engine for loading and storing into a database management system said structured data and said unstructured data from said data holding area based on said link; an email account management engine for bypassing said text extraction and parsing engine and directly copying structured data from said email server to said database management system; (c) wherein said plurality of data processing modules are configured for carrying out operations comprising: receiving unstructured data and structured data from a plurality of sources comprising an unstructured data source and a structured data source, the unstructured data being associated with the structured data, wherein the unstructured data source and the structured data source are each associated with at least an email, the email including a parsing the header into at least a sending email address, a receiving email address, a date and time of transmission associated with the email, and a carbon copy email address; evaluating the email using an email capture and parsing engine, wherein the email capture and parsing engine is configured to generate a summary of content associated with the email, the sending email address, the receiving email address, the date and the time of transmission associated with the email, the carbon copy email address, and a summary used to classify the email; correlating the unstructured data and the structured data to establish a link between the unstructured data and the structured data, wherein the link integrates the unstructured data and the structured data; and storing the unstructured data and the structured data in a data structure based on the link, wherein the unstructured data is stored in an unstructured portion of the data structure and wherein the structured data is stored in a structured portion of the data structure. 12. The system of claim 11 , wherein the storing the unstructured data and the structured data further comprises enabling access of the unstructured data and the structured data from the data structure. | 0.553097 |
7,925,986 | 1 | 7 | 1. A user-interface system for entering an alphanumeric string, the system comprising: presentation logic for displaying on a presentation device an alphabet arranged into a row of letters, the presentation logic including logic to display a string field for presenting an alphanumeric string of characters selected by a user; indication logic, cooperative with the presentation logic, for presenting visual cues grouping a series of letters of the row into a cluster of letters to aid in the navigation of the row and the selection of a desired cluster; navigation logic, cooperative with the indication logic, for receiving user actions from an input device to move the visual cues along the row of letters to change the letters grouped into the cluster from a first subset of letters to a second subset of letters, the visual cues moving along the row of letters in variable offsets based on a rate of input of the user actions, wherein the visual cues move by a single offset for each user action in response to user actions entered at or slower than a predetermined rate, and wherein the visual cues move by more than a single offset for each user action and the first subset of letters and the second subset of letters are contiguous in response to user actions entered faster than the predetermined rate; and selection logic for receiving user actions from the input device to select the cluster of letters to cause at least one of the letters of the selected cluster to be displayed in the string field. | 1. A user-interface system for entering an alphanumeric string, the system comprising: presentation logic for displaying on a presentation device an alphabet arranged into a row of letters, the presentation logic including logic to display a string field for presenting an alphanumeric string of characters selected by a user; indication logic, cooperative with the presentation logic, for presenting visual cues grouping a series of letters of the row into a cluster of letters to aid in the navigation of the row and the selection of a desired cluster; navigation logic, cooperative with the indication logic, for receiving user actions from an input device to move the visual cues along the row of letters to change the letters grouped into the cluster from a first subset of letters to a second subset of letters, the visual cues moving along the row of letters in variable offsets based on a rate of input of the user actions, wherein the visual cues move by a single offset for each user action in response to user actions entered at or slower than a predetermined rate, and wherein the visual cues move by more than a single offset for each user action and the first subset of letters and the second subset of letters are contiguous in response to user actions entered faster than the predetermined rate; and selection logic for receiving user actions from the input device to select the cluster of letters to cause at least one of the letters of the selected cluster to be displayed in the string field. 7. The system of claim 1 , wherein the presentation device and the input device are included in the same device. | 0.820513 |
7,668,802 | 1 | 9 | 1. A method of enforcing application-layer policies to application layer formatted documents, each policy defining a rule and an action, comprising: distinctly storing simple policies and complex policies applicable to the application layer formatted documents in a simple policies data structure, wherein said simple policies data structure stores XPath queries that do not use wildcard β*β and descendent β//β expressions, and, respectively, a complex policies data structure, wherein said complex policies data structure stores XPath queries that use wildcard β*β and descendent β//β expressions; parsing a document received as streaming application layer data in a hierarchical structure, for enabling evaluation of an object in the document, wherein the document is an Extensible Markup Language (XML) document and the object is a result of evaluation of an XPath expression; simultaneously querying the simple and complex policies data structures to identify all policies corresponding to the object; discontinuing the query for the object in the simple and complex policies data structures once all of the simple and complex policies that match the object are identified; and executing the actions defined by the simple and complex policies corresponding to the object. | 1. A method of enforcing application-layer policies to application layer formatted documents, each policy defining a rule and an action, comprising: distinctly storing simple policies and complex policies applicable to the application layer formatted documents in a simple policies data structure, wherein said simple policies data structure stores XPath queries that do not use wildcard β*β and descendent β//β expressions, and, respectively, a complex policies data structure, wherein said complex policies data structure stores XPath queries that use wildcard β*β and descendent β//β expressions; parsing a document received as streaming application layer data in a hierarchical structure, for enabling evaluation of an object in the document, wherein the document is an Extensible Markup Language (XML) document and the object is a result of evaluation of an XPath expression; simultaneously querying the simple and complex policies data structures to identify all policies corresponding to the object; discontinuing the query for the object in the simple and complex policies data structures once all of the simple and complex policies that match the object are identified; and executing the actions defined by the simple and complex policies corresponding to the object. 9. The method of claim 1 , wherein the simultaneously querying terminates once a policy matching the XML document is found in either the simple policies data structure or the complex policies data structure. | 0.743812 |
8,560,531 | 1 | 7 | 1. A method for providing proximate dataset recommendations comprising: creating of a plurality of metadata records that correspond to a plurality of datasets representing scientific data by a scientific dataset search tool, wherein said plurality of metadata records conform to a standardized structural definition, wherein values for data elements of a metadata record are contained within a corresponding dataset; identifying at least one metadata record from the plurality of metadata records having a value that is proximate to one or more user-entered search parameters, wherein one of the search parameters is a temporal parameter, wherein proximity is determined with respect to a range represented by the corresponding user-entered search parameters; calculating a proximity score for each identified metadata record, wherein said proximity score expresses a relevance of the corresponding dataset to the user-entered search parameters, wherein calculating the proximity score comprises calculating a temporal proximity score, wherein calculating the temporal proximity score further comprises: determining a temporal distance, d Tdist , from a central point of the user-entered temporal search parameter for the dataset using the following formula or a variation or derivative thereof: d Tdist = { 0 d Tmin β₯ Q Tmin , d Tmax β€ Q Tmax ( ο d Rmax ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin β₯ Q Tmin , d Tmax > Q Tmax ( ο d Rmin ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin < Q Tmin , d Tmax β€ Q Tmax ( ο d Rmax ο - 1 ) 2 + ( ο d Rmax ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin < Q Tmin , d Tmax > Q Tmax ( ο d Rmin + d Rmax ο / 2 ) - 1 d Tmin > Q Tmin β’ β’ or β’ β’ d Tmax < Q Tmax , wherein Q Tmin and Q Tmax represent the minimum and maximum bounds of the temporal search parameter range, d Tmin and d Tmax represent the minimum and maximum time values of the dataset, and d Rmin and d Rmax represent the distance of d Tmin and d Tmax from the central point of the range; and using the proximity score to filter or order metadata records to create a listing of dataset results. | 1. A method for providing proximate dataset recommendations comprising: creating of a plurality of metadata records that correspond to a plurality of datasets representing scientific data by a scientific dataset search tool, wherein said plurality of metadata records conform to a standardized structural definition, wherein values for data elements of a metadata record are contained within a corresponding dataset; identifying at least one metadata record from the plurality of metadata records having a value that is proximate to one or more user-entered search parameters, wherein one of the search parameters is a temporal parameter, wherein proximity is determined with respect to a range represented by the corresponding user-entered search parameters; calculating a proximity score for each identified metadata record, wherein said proximity score expresses a relevance of the corresponding dataset to the user-entered search parameters, wherein calculating the proximity score comprises calculating a temporal proximity score, wherein calculating the temporal proximity score further comprises: determining a temporal distance, d Tdist , from a central point of the user-entered temporal search parameter for the dataset using the following formula or a variation or derivative thereof: d Tdist = { 0 d Tmin β₯ Q Tmin , d Tmax β€ Q Tmax ( ο d Rmax ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin β₯ Q Tmin , d Tmax > Q Tmax ( ο d Rmin ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin < Q Tmin , d Tmax β€ Q Tmax ( ο d Rmax ο - 1 ) 2 + ( ο d Rmax ο - 1 ) 2 2 β’ ο d Rmax - d Rmin ο d Tmin < Q Tmin , d Tmax > Q Tmax ( ο d Rmin + d Rmax ο / 2 ) - 1 d Tmin > Q Tmin β’ β’ or β’ β’ d Tmax < Q Tmax , wherein Q Tmin and Q Tmax represent the minimum and maximum bounds of the temporal search parameter range, d Tmin and d Tmax represent the minimum and maximum time values of the dataset, and d Rmin and d Rmax represent the distance of d Tmin and d Tmax from the central point of the range; and using the proximity score to filter or order metadata records to create a listing of dataset results. 7. The method of claim 1 , further comprising: converting the determined d Tdist to the temporal proximity score, d Ts , using
d Ts =s ( d Tdist ), wherein s is a scaling function that translates d Tdist into a value within a scale defined for the proximity score. | 0.798179 |
8,887,111 | 13 | 19 | 13. A computing device selected from the group consisting of a desktop computer, a laptop computer, a tablet computer, a smartphone, an application server computer, a virtual computing host computer, and a file server computer, for synthesizing a first description of a circuit into a second description of the circuit, comprising: a memory and a processor that are respectively configured to store and execute instructions, including instructions organized into: an analyzer to: receive the first description of the circuit, the circuit including at least a first circuit portion and a second circuit portion, the first description describing a first hierarchical structure for the first circuit portion, the second circuit portion, and components of the first circuit portion and the second circuit portion; and determine a first component that is described in the first description as being part of the first circuit portion and that has a commonality with a second component described in the first description as being part of the second circuit portion; a circuit portion synthesizer to: synthesize a shared circuit portion as a replacement for the determined first and second components; and synthesize a plurality of accessing circuit portions; and a circuit synthesizer to synthesize the second description of the circuit, the second description describing: a second hierarchical structure for the first circuit portion, the second circuit portion, and the components thereof, the second hierarchical structure being different than the first hierarchical structure; the shared circuit portion; the first circuit portion with an interface to the shared circuit portion instead of an individual description of the first component; and the second circuit portion with an interface to the shared circuit portion instead of an individual description of the second component; whereby the computing device synthesizes the first description of the circuit into the second description of the circuit. | 13. A computing device selected from the group consisting of a desktop computer, a laptop computer, a tablet computer, a smartphone, an application server computer, a virtual computing host computer, and a file server computer, for synthesizing a first description of a circuit into a second description of the circuit, comprising: a memory and a processor that are respectively configured to store and execute instructions, including instructions organized into: an analyzer to: receive the first description of the circuit, the circuit including at least a first circuit portion and a second circuit portion, the first description describing a first hierarchical structure for the first circuit portion, the second circuit portion, and components of the first circuit portion and the second circuit portion; and determine a first component that is described in the first description as being part of the first circuit portion and that has a commonality with a second component described in the first description as being part of the second circuit portion; a circuit portion synthesizer to: synthesize a shared circuit portion as a replacement for the determined first and second components; and synthesize a plurality of accessing circuit portions; and a circuit synthesizer to synthesize the second description of the circuit, the second description describing: a second hierarchical structure for the first circuit portion, the second circuit portion, and the components thereof, the second hierarchical structure being different than the first hierarchical structure; the shared circuit portion; the first circuit portion with an interface to the shared circuit portion instead of an individual description of the first component; and the second circuit portion with an interface to the shared circuit portion instead of an individual description of the second component; whereby the computing device synthesizes the first description of the circuit into the second description of the circuit. 19. The computing device of claim 13 , wherein: the shared circuit portion, first circuit portion, and second circuit portion are represented in the second hierarchical structure at a same hierarchical level. | 0.693215 |
8,392,445 | 45 | 46 | 45. The system of claim 37 , wherein each first parent query is a high quality parent query for the particular child query, and each second parent query for a particular candidate sibling query is a high quality parent query for the particular sibling query. | 45. The system of claim 37 , wherein each first parent query is a high quality parent query for the particular child query, and each second parent query for a particular candidate sibling query is a high quality parent query for the particular sibling query. 46. The system of claim 45 , wherein a high quality parent query has a high inverse document frequency in a corpus of documents. | 0.5 |
9,720,974 | 3 | 4 | 3. The computer-implemented method of claim 1 , further comprising identifying one or more search terms in the query issued by the user, based at least in part on the first action. | 3. The computer-implemented method of claim 1 , further comprising identifying one or more search terms in the query issued by the user, based at least in part on the first action. 4. The computer-implemented method of claim 3 , wherein determining the fingerprint for the query further comprises comparing the fingerprint information of a plurality of queries in the query classification database to the one or more search terms identified in the query. | 0.5 |
8,930,342 | 1 | 15 | 1. A computer-implemented process for enabling multidimensional search capabilities, comprising: using one or more computing devices that are in communication with each other via a computer network to perform the following process actions: receiving an original user query; accessing a structured data repository to extract structured data that is available for the original user query, the extracted structured data representing attributes of the original user query; and providing the extracted structured data in the form of a hierarchical menu for use in generating a revised user query. | 1. A computer-implemented process for enabling multidimensional search capabilities, comprising: using one or more computing devices that are in communication with each other via a computer network to perform the following process actions: receiving an original user query; accessing a structured data repository to extract structured data that is available for the original user query, the extracted structured data representing attributes of the original user query; and providing the extracted structured data in the form of a hierarchical menu for use in generating a revised user query. 15. The process of claim 1 , wherein the structured data repository is constructed by crawling one or more prescribed websites. | 0.910689 |
9,727,637 | 8 | 9 | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input question for which an answer is sought; extract features of the input question based on a natural language processing of the input question; execute a first search of a corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; execute a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generate query results from the subset of passages from which a set of candidate answers for the input question are identified. | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input question for which an answer is sought; extract features of the input question based on a natural language processing of the input question; execute a first search of a corpus of documents based on a first subset of the extracted features of the input question and an initial evaluation of a utility of the first subset of extracted features to generate a subset of documents matching the first subset of extracted features, wherein the utility of the first subset of extracted features identifies a degree to which each feature of the first subset of extracted features of the input question discriminates between documents in the corpus of documents that are sources of candidate answers to the input question; execute a second search of a set of passages extracted from the subset of documents based on a second subset of the extracted features of the input question and a reevaluation of the utility of the second subset of extracted features thereby forming a subset of passages, wherein the utility of the second subset of extracted features identifies a degree to which each feature of the second subset of extracted features of the input question discriminates between passages in the set of passages that are sources of candidate answers to the input question; and generate query results from the subset of passages from which a set of candidate answers for the input question are identified. 9. The computer program product of claim 8 , wherein the set of passages extracted from the subset of documents is less than all of the passages included in the subset of documents. | 0.880764 |
8,112,401 | 18 | 26 | 18. The method of claim 17 further comprising the steps of reviewing the introduced document, identifying and storing section headers and associating the selected data point with the text under the appropriate section header in the Conversion Database. | 18. The method of claim 17 further comprising the steps of reviewing the introduced document, identifying and storing section headers and associating the selected data point with the text under the appropriate section header in the Conversion Database. 26. The method of claim 18 wherein the steps of identifying and storing the section headers comprise the steps of: (uu) identifying paragraphs shorter than a given length; and (vv) marking each such identified stand-alone paragraph as a section header. | 0.536765 |
9,438,419 | 1 | 9 | 1. One or more tangible non-transitory computer-readable media having computer-executable instructions for performing a method of running a software program on a computing device, the computing device operating under an operating system, the method including issuing instructions from the software program for a computer processor to generate a probabilistic password cracking system for cracking a targeted password for a secured user account associated with a user, the instructions comprising: receiving a plurality of known password strings, said plurality of known password strings formed of at least one category selected from the group consisting of alpha strings, digits, and special characters; deriving one or more base structures from said plurality of known password strings, whereby one base structure may include more than one password string from said plurality of known password strings; automatically incorporating a keyboard pattern into said one or more base structures, said keyboard pattern contained within at least one password string of said plurality of known password strings, said keyboard pattern being a sequence of contiguous characters starting from a particular key without regards to actual characters typed but uses a physical sequence shape of the actual characters; automatically assigning a set of probability values to each base structure of said one or more base structures based on a probability value of each alpha string, each digit, each special character, or each keyboard pattern in said each base structure; creating a probabilistic context free grammar based on said set of probability values assigned to said each base structure; receiving one or more input dictionaries containing a plurality of sequences of alpha characters; generating password guess strings in decreasing estimated probability via said probabilistic context-free grammar by utilizing said plurality of sequences of alpha characters; accessing a login interface to the secured user account; and applying said password guess strings from said computer processor sequentially to said login interface, whereby authentication of the user can be achieved. | 1. One or more tangible non-transitory computer-readable media having computer-executable instructions for performing a method of running a software program on a computing device, the computing device operating under an operating system, the method including issuing instructions from the software program for a computer processor to generate a probabilistic password cracking system for cracking a targeted password for a secured user account associated with a user, the instructions comprising: receiving a plurality of known password strings, said plurality of known password strings formed of at least one category selected from the group consisting of alpha strings, digits, and special characters; deriving one or more base structures from said plurality of known password strings, whereby one base structure may include more than one password string from said plurality of known password strings; automatically incorporating a keyboard pattern into said one or more base structures, said keyboard pattern contained within at least one password string of said plurality of known password strings, said keyboard pattern being a sequence of contiguous characters starting from a particular key without regards to actual characters typed but uses a physical sequence shape of the actual characters; automatically assigning a set of probability values to each base structure of said one or more base structures based on a probability value of each alpha string, each digit, each special character, or each keyboard pattern in said each base structure; creating a probabilistic context free grammar based on said set of probability values assigned to said each base structure; receiving one or more input dictionaries containing a plurality of sequences of alpha characters; generating password guess strings in decreasing estimated probability via said probabilistic context-free grammar by utilizing said plurality of sequences of alpha characters; accessing a login interface to the secured user account; and applying said password guess strings from said computer processor sequentially to said login interface, whereby authentication of the user can be achieved. 9. One or more tangible non-transitory computer-readable media as in claim 1 , further comprising: optimizing a primary dictionary of said one or more input dictionaries based on size and content of said primary dictionary; and assigning an additional probability value to said primary dictionary, wherein an effectiveness of said primary dictionary is measured by coverage and precision of said primary dictionary cracking said targeted password. | 0.5 |
7,680,782 | 11 | 13 | 11. A data processing system comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes a set of instructions for a XQuery code generator that is operable for automatically generating a query to test a query processing engine that processes queries received by the query processing engine; and a processing unit connected to the bus system, wherein the processing unit executes the set of instructions to describe data and occurrence using a sequence type, match the data and the occurrence from the sequence type to a sequence type pattern, automatically generate sentences in XQuery language using the sequence type pattern, test an ability of the query processing engine to interpret queries using the sentences that are automatically generated, define a grammar wherein the grammar uses the sequence type pattern to drive sentence generation by producing a plurality of tokens in the grammar automatically, wherein the plurality of tokens is consistent with the sequence type pattern, translate the plurality of tokens into a syntactically valid query in a target language automatically, and define the sequence type pattern wherein the sequence type pattern abstracts a class of query. | 11. A data processing system comprising: a bus system; a communications system connected to the bus system; a memory connected to the bus system, wherein the memory includes a set of instructions for a XQuery code generator that is operable for automatically generating a query to test a query processing engine that processes queries received by the query processing engine; and a processing unit connected to the bus system, wherein the processing unit executes the set of instructions to describe data and occurrence using a sequence type, match the data and the occurrence from the sequence type to a sequence type pattern, automatically generate sentences in XQuery language using the sequence type pattern, test an ability of the query processing engine to interpret queries using the sentences that are automatically generated, define a grammar wherein the grammar uses the sequence type pattern to drive sentence generation by producing a plurality of tokens in the grammar automatically, wherein the plurality of tokens is consistent with the sequence type pattern, translate the plurality of tokens into a syntactically valid query in a target language automatically, and define the sequence type pattern wherein the sequence type pattern abstracts a class of query. 13. The data processing system of claim 11 , wherein the set of instructions receives a goal and builds a syntax tree, wherein the syntax tree is processed to generate the sentences. | 0.5 |
7,584,092 | 9 | 10 | 9. A computer-implemented method for applying a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to derive the paraphrase alternation pattern from a set of parallel texts, wherein deriving the paraphrase alteration pattern from a set of parallel texts comprises deriving from a set of bilingual texts; creating a series of different application alternatives that each represent a different application of the paraphrase alternation pattern to the input string; and applying the series of different application alternatives to a language model to determine a probable sequence of words. | 9. A computer-implemented method for applying a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to derive the paraphrase alternation pattern from a set of parallel texts, wherein deriving the paraphrase alteration pattern from a set of parallel texts comprises deriving from a set of bilingual texts; creating a series of different application alternatives that each represent a different application of the paraphrase alternation pattern to the input string; and applying the series of different application alternatives to a language model to determine a probable sequence of words. 10. The method of claim 9 , wherein deriving the paraphrase alternation pattern from a set of parallel texts comprises deriving from a set of parallel, word-aligned texts. | 0.5 |
7,542,029 | 1 | 5 | 1. An apparatus comprising: an output display device on which two or more choices for selection are graphically presented; an input device which detects one or more input actions performed by a user to position, move, and activate or de-activate a control point on said display; and a processor coupled to the input device, and the output device, the processor comprising: a first component for displaying a graphical presentation of said two or more choices within a defined, bounded region on said display; a second component for defining one or more distinct segments of the boundary of said bounded region; a third component for uniquely associating each of one or more of said defined segments with a distinct one of said graphically presented choices; a fourth component for detecting an activation of said control point within said bounded region; a fifth component for detecting a subsequent movement of said activated control point such that said activated control point exits said bounded region; a sixth component for identifying one of said distinct boundary segments through which said activated control point is moved in exiting said bounded region; and a sixth component for determining one of said graphically presented choices based on said identified boundary segment. | 1. An apparatus comprising: an output display device on which two or more choices for selection are graphically presented; an input device which detects one or more input actions performed by a user to position, move, and activate or de-activate a control point on said display; and a processor coupled to the input device, and the output device, the processor comprising: a first component for displaying a graphical presentation of said two or more choices within a defined, bounded region on said display; a second component for defining one or more distinct segments of the boundary of said bounded region; a third component for uniquely associating each of one or more of said defined segments with a distinct one of said graphically presented choices; a fourth component for detecting an activation of said control point within said bounded region; a fifth component for detecting a subsequent movement of said activated control point such that said activated control point exits said bounded region; a sixth component for identifying one of said distinct boundary segments through which said activated control point is moved in exiting said bounded region; and a sixth component for determining one of said graphically presented choices based on said identified boundary segment. 5. The apparatus of claim 1 , wherein the relation between the lengths of two or more of said defined boundary segments is related to the relation between determined probabilities that a user will select each of said graphically presented choices uniquely associated with each of said two or more defined boundary segments. | 0.653433 |
9,418,143 | 9 | 10 | 9. The method of claim 2 , wherein the query context includes event information and the language model rules include event language model rules having an adjustment factor for adjusting a probability value of the base language model. | 9. The method of claim 2 , wherein the query context includes event information and the language model rules include event language model rules having an adjustment factor for adjusting a probability value of the base language model. 10. The method of claim 9 , wherein the event information includes one or more of time of day and weather information. | 0.5 |
8,161,066 | 25 | 28 | 25. The method of claim 2 , wherein the semantic object is created in a process of matching offers and requests, an offer represented by an offer object and a request represented by a request object, and wherein the offer object and the request object are semantic objects that include metadata defining particulars of the offer and the request. | 25. The method of claim 2 , wherein the semantic object is created in a process of matching offers and requests, an offer represented by an offer object and a request represented by a request object, and wherein the offer object and the request object are semantic objects that include metadata defining particulars of the offer and the request. 28. The method of claim 25 , further comprising, computing a similarity measure between the offer object and the request object based on the comparison between the offer object metadata and the request object metadata or the comparison between the offer object meta-tag and the request object meta-tag. | 0.5 |
8,036,877 | 13 | 14 | 13. A method according to claim 1 , wherein said step of attempting a natural language interpretation produces an interpretation of a token in said first user input, wherein additional potential input entries in said database each associate a target token sequence with at least one potential additional token sequence, said database also including a respective importance value for each of said associations, and wherein said step of identifying additional potential input comprises the steps of: comparing to said target token sequences, tokens in at least one of said user input and said interpretation; and selecting a set of at least one of said additional potential input entries in response to said step of comparing and in dependence upon said importance values. | 13. A method according to claim 1 , wherein said step of attempting a natural language interpretation produces an interpretation of a token in said first user input, wherein additional potential input entries in said database each associate a target token sequence with at least one potential additional token sequence, said database also including a respective importance value for each of said associations, and wherein said step of identifying additional potential input comprises the steps of: comparing to said target token sequences, tokens in at least one of said user input and said interpretation; and selecting a set of at least one of said additional potential input entries in response to said step of comparing and in dependence upon said importance values. 14. A method according to claim 13 , wherein said step of selecting a set of at least one of said additional potential input entries comprises the steps of: for each particular one of said associations, calculating a confidence score given by the degree to which said target token sequences of the particular association match the tokens in said at least one of said user input and said interpretation, scaled by the importance value of the particular association; and selecting the additional potential input entries from only those of said associations having a confidence score exceeding a predetermined minimum acceptable confidence score. | 0.622653 |
9,032,298 | 22 | 29 | 22. A Web-based method for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said method comprising: receiving over a network a plurality of video and music clips from a plurality of content provider users; storing the plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; indexing the database and media content storage devices that store the libraries of uploaded video and music clips; providing a plurality of producer users with interactive Web formatting screens, said Web formatting screens capable of allowing said producer users to select among said uploaded video and music clips; providing said plurality of producer users with an online mixer module, said mixer module capable of editing, mixing together, and playing said selected uploaded video and music clips, to thereby create video advertisement templates each comprising a static component and at least one placeholder, wherein said mixer module is further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is further capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file and encoding and formatting video advertisements in particular formats. | 22. A Web-based method for accessing development components, which include an online video clip library and an online music clip library, and enabling online production of custom-integrated media products, said method comprising: receiving over a network a plurality of video and music clips from a plurality of content provider users; storing the plurality of video and music clips provided by said plurality of content provider users in a database and media content storage devices as libraries; indexing the database and media content storage devices that store the libraries of uploaded video and music clips; providing a plurality of producer users with interactive Web formatting screens, said Web formatting screens capable of allowing said producer users to select among said uploaded video and music clips; providing said plurality of producer users with an online mixer module, said mixer module capable of editing, mixing together, and playing said selected uploaded video and music clips, to thereby create video advertisement templates each comprising a static component and at least one placeholder, wherein said mixer module is further capable of allowing advertiser users to customize said video advertisement templates by uploading a list, such that advertiser users are able to automatically self-produce a set of different customized video advertisements based on an advertisement template, in which the at least one placeholder for each customized video advertisement contains a different item from the list, wherein said mixer module is further capable of arranging said video advertisement templates and customized video advertisements as respective XML files on a server, said XML files being accessible by a plurality of users using respective browser applications, such that upon updating an XML file representing a video advertisement template or a customized video advertisement, the updated video advertisement template or customized video advertisement is made accessible to users accessing the updated XML file and encoding and formatting video advertisements in particular formats. 29. The method of claim 22 , wherein said mixer module is further capable of taking various sources of media content and integrating them in the video template. | 0.738562 |
7,797,309 | 2 | 3 | 2. The system of claim 1 , wherein the data field includes a first subfield, and a type of data contained in a first subfield of said data field is determined from a feature of the first subfield. | 2. The system of claim 1 , wherein the data field includes a first subfield, and a type of data contained in a first subfield of said data field is determined from a feature of the first subfield. 3. The system of claim 2 , wherein the feature of said first subfield is that the first subfield is all numeric characters. | 0.547794 |
10,133,733 | 1 | 3 | 1. A computer implemented method for driving a graphical autonomous avatar, comprising: receiving, by a processor, an electronic communication including dialogue of at least one language source; generating, by the processor, a parsed data structure for the dialog, wherein the parsed data structure includes segmented portions derived from discrete logical subsections of the dialogue and parsed portions derived from linking a grammatical mood identified in the dialog; generating, by the processor, a pragmatics report based on a pragmatics analysis of the parsed data structure; generating, by the processor, automated responses for the autonomous avatar based on the pragmatics report and a unique personality of the graphical autonomous avatar, the unique personality delineated by an intellectual attribute and an emotional attribute, wherein the intellectual attribute includes a backstory, a history, and a memory, and wherein the emotional attribute includes a prescribed emotional disposition and at least one reaction and/or response procedure; and wherein the processor utilizes a translation matrix to analyze, mine, and generate responses based on the electronic communication corresponding to any of a variety of languages. | 1. A computer implemented method for driving a graphical autonomous avatar, comprising: receiving, by a processor, an electronic communication including dialogue of at least one language source; generating, by the processor, a parsed data structure for the dialog, wherein the parsed data structure includes segmented portions derived from discrete logical subsections of the dialogue and parsed portions derived from linking a grammatical mood identified in the dialog; generating, by the processor, a pragmatics report based on a pragmatics analysis of the parsed data structure; generating, by the processor, automated responses for the autonomous avatar based on the pragmatics report and a unique personality of the graphical autonomous avatar, the unique personality delineated by an intellectual attribute and an emotional attribute, wherein the intellectual attribute includes a backstory, a history, and a memory, and wherein the emotional attribute includes a prescribed emotional disposition and at least one reaction and/or response procedure; and wherein the processor utilizes a translation matrix to analyze, mine, and generate responses based on the electronic communication corresponding to any of a variety of languages. 3. The computer implemented method, as recited in claim 1 , further comprising segmenting the dialog by at least one of performing particle representation, converting characters and splitting dialog. | 0.738845 |
8,620,911 | 1 | 2 | 1. A document registry system ( 10 ), comprising: a registry database ( 20 ), including: a specific task sub-database ( 22 ), including: pre-existing fields configured to store specific task-related document data received from one or more of a plurality of sources (S 1 , S 2 , S 3 , S 4 or from a source other than the plurality of sources (NS 1 , NS 2 ); and de novo fields configured to be generated as a result of a general task query and configured to store specific task-related document data received from the source other than the plurality of sources (NS 1 , NS 2 ); an analytics-supporting general task sub-database ( 24 ), including: pre-existing fields configured to store general task-related document data received from one or more of the plurality of sources (S 1 , S 2 , S 3 , S 4 ) or at least a second source other than the plurality of sources (NS 1 , NS 2 ): and de novo fields configured to be generated as a result of a general task query and configured to store general task-related document data received from the source or the second source other than the plurality of sources (NS 1 NS 2 ); and a query mapping engine ( 26 ) configured to receive a request entry, map the request entry into a query, and actively collect data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the source or the it least a second source other than the plurality of sources (NS 1 , NS 2 ). | 1. A document registry system ( 10 ), comprising: a registry database ( 20 ), including: a specific task sub-database ( 22 ), including: pre-existing fields configured to store specific task-related document data received from one or more of a plurality of sources (S 1 , S 2 , S 3 , S 4 or from a source other than the plurality of sources (NS 1 , NS 2 ); and de novo fields configured to be generated as a result of a general task query and configured to store specific task-related document data received from the source other than the plurality of sources (NS 1 , NS 2 ); an analytics-supporting general task sub-database ( 24 ), including: pre-existing fields configured to store general task-related document data received from one or more of the plurality of sources (S 1 , S 2 , S 3 , S 4 ) or at least a second source other than the plurality of sources (NS 1 , NS 2 ): and de novo fields configured to be generated as a result of a general task query and configured to store general task-related document data received from the source or the second source other than the plurality of sources (NS 1 NS 2 ); and a query mapping engine ( 26 ) configured to receive a request entry, map the request entry into a query, and actively collect data based upon the query from the specific task sub-database ( 22 ) or the analytics-supporting general task sub-database ( 24 ), and from the source or the it least a second source other than the plurality of sources (NS 1 , NS 2 ). 2. The document registry system ( 10 ) as defined in claim 1 , further comprising an anonymity or obfuscation engine ( 30 ) in operative communication with the registry database ( 20 ), the anonymity or obfuscation engine ( 30 ) configured to anonymize or obfuscate the collected data. | 0.663915 |
5,530,775 | 18 | 22 | 18. The method of claim 17, wherein the recognition enhancement of a particular pixel image I.sub.j with respect to a particular pixel version s.sub.i involves maximizing the minimum recognition margin between the primary comparison C* and the maximum secondary comparison C** which form the selected pair of identified comparisons C* and C** for the pixel version s.sub.i, in the general relationship: EQU maximize M=min[C*-max(C**)] where M is the recognition margin between C* and C**, C* is the primary comparison for the template T* which is the closest template in the library to the particular pixel version s.sub.i, and C** is the secondary comparison for the template T** which is the second closest template in the library to the pixel version s.sub.i. | 18. The method of claim 17, wherein the recognition enhancement of a particular pixel image I.sub.j with respect to a particular pixel version s.sub.i involves maximizing the minimum recognition margin between the primary comparison C* and the maximum secondary comparison C** which form the selected pair of identified comparisons C* and C** for the pixel version s.sub.i, in the general relationship: EQU maximize M=min[C*-max(C**)] where M is the recognition margin between C* and C**, C* is the primary comparison for the template T* which is the closest template in the library to the particular pixel version s.sub.i, and C** is the secondary comparison for the template T** which is the second closest template in the library to the pixel version s.sub.i. 22. The method of claim 18, wherein only the next closest pixel image I** is weighted causing the next closest pixel image I** to become the next closest pixel template T**. | 0.686594 |
7,849,076 | 1 | 4 | 1. A method for learning ranking functions to determine the ranking of one or more content items that are responsive to a query, the method comprising: generating one or more training sets comprising one or more content item-query pairs; determining one or more contradicting pairs in a given training set; formulating an optimization function to minimize the number of contradicting pairs in the training set using a functional iterative method that comprises applying an isotonic regression function within each query and using the output to determine regression targets for each content item-query pair in a next iteration; modifying the optimization function by incorporating a grade difference between one or more content items corresponding to the query in the training set; applying the optimization function to each query in the training set; determining a ranking function based on an application of regression trees on the one or more queries of the training set minimized by the optimization function; and storing the ranking function for application to content item-query pairs not contained in the one or more training sets. | 1. A method for learning ranking functions to determine the ranking of one or more content items that are responsive to a query, the method comprising: generating one or more training sets comprising one or more content item-query pairs; determining one or more contradicting pairs in a given training set; formulating an optimization function to minimize the number of contradicting pairs in the training set using a functional iterative method that comprises applying an isotonic regression function within each query and using the output to determine regression targets for each content item-query pair in a next iteration; modifying the optimization function by incorporating a grade difference between one or more content items corresponding to the query in the training set; applying the optimization function to each query in the training set; determining a ranking function based on an application of regression trees on the one or more queries of the training set minimized by the optimization function; and storing the ranking function for application to content item-query pairs not contained in the one or more training sets. 4. The method of claim 1 , wherein generating one or more training sets comprising one or more content item-query pairs further comprises extracting query independent features for the one or more content item-query pairs. | 0.545267 |
9,699,490 | 15 | 21 | 15. Non-transitory physical computer storage comprising computer-executable instructions stored thereon that, when executed by a hardware processor, are configured to perform operations comprising: accessing, from an electronic data store, contextual information associated with a browse session for a user, wherein the contextual information includes one or more attributes indicative of a user browsing context for the browse session; determining the user browsing context with respect to items available from the electronic catalog based at least in part on the contextual information; generating a candidate list of candidate video content recommendation items for the user such that the candidate list includes (i) one or more items from a watch list associated with the user and (ii) one or more additional items not in the watch list, the watch list indicative of one or more items added to the watch list and when the one or more items were added to the watch list; determining, based at least in part on an amount of time elapsed between (i) when a given item is added to the watch list and (ii) when the given item is watched, a time interval by which to reorder the list of candidate video content recommendation items; reordering the candidate list based at least in part on the determined time interval and the one or more time periods at which the one or more items in the watch list were added to the watch list; and providing one or more video content item recommendations from the reordered candidate list to the consumer computing device. | 15. Non-transitory physical computer storage comprising computer-executable instructions stored thereon that, when executed by a hardware processor, are configured to perform operations comprising: accessing, from an electronic data store, contextual information associated with a browse session for a user, wherein the contextual information includes one or more attributes indicative of a user browsing context for the browse session; determining the user browsing context with respect to items available from the electronic catalog based at least in part on the contextual information; generating a candidate list of candidate video content recommendation items for the user such that the candidate list includes (i) one or more items from a watch list associated with the user and (ii) one or more additional items not in the watch list, the watch list indicative of one or more items added to the watch list and when the one or more items were added to the watch list; determining, based at least in part on an amount of time elapsed between (i) when a given item is added to the watch list and (ii) when the given item is watched, a time interval by which to reorder the list of candidate video content recommendation items; reordering the candidate list based at least in part on the determined time interval and the one or more time periods at which the one or more items in the watch list were added to the watch list; and providing one or more video content item recommendations from the reordered candidate list to the consumer computing device. 21. The non-transitory physical computer storage of claim 15 , wherein the time interval is determined based on an average elapsed time across a plurality of users other than the user between (1) a respective user in the plurality of users adding a specific item in the candidate list associated with the user to the respective user's watch list and (2) the respective user actually watching the specific item. | 0.5 |
8,434,000 | 1 | 2 | 1. A method for saving only a pertinent portion of a dynamically generated web page, comprising: placing a start tag at a first location in an HTML document; placing an end tag in a second location in the HTML document; and placing an execution tag into the HTML document prior to the start tag, wherein: execution of a script is begun at the execution tag, without saving text rendered between the execution tag and the start tag, text between the start tag and the end tag is rendered and output to a temporary buffer, the script continues executing after encountering the end tag, without saving text rendered after the end tag, the text between the start tag and the end tag is written to a file from the temporary buffer such that the file comprises the pertinent portion of the dynamically generated web page including a confirmation of a transaction, the start tag includes an attribute to name the file, a response stream sent to an end user comprises data generated by the execution of the script, the data comprises the text rendered between the execution tag and the start tag, the text rendered after the end tag, and the text between the start tag and the end tag, and the text between the start tag and the end tag is written to the response stream from the temporary buffer such that the text between the start tag and the end tag is rendered to the end user from the temporary buffer and does not come directly from the execution of the script. | 1. A method for saving only a pertinent portion of a dynamically generated web page, comprising: placing a start tag at a first location in an HTML document; placing an end tag in a second location in the HTML document; and placing an execution tag into the HTML document prior to the start tag, wherein: execution of a script is begun at the execution tag, without saving text rendered between the execution tag and the start tag, text between the start tag and the end tag is rendered and output to a temporary buffer, the script continues executing after encountering the end tag, without saving text rendered after the end tag, the text between the start tag and the end tag is written to a file from the temporary buffer such that the file comprises the pertinent portion of the dynamically generated web page including a confirmation of a transaction, the start tag includes an attribute to name the file, a response stream sent to an end user comprises data generated by the execution of the script, the data comprises the text rendered between the execution tag and the start tag, the text rendered after the end tag, and the text between the start tag and the end tag, and the text between the start tag and the end tag is written to the response stream from the temporary buffer such that the text between the start tag and the end tag is rendered to the end user from the temporary buffer and does not come directly from the execution of the script. 2. The method of claim 1 , wherein the start tag and the end tag are server scripting technology tags. | 0.679245 |
9,990,417 | 1 | 2 | 1. A method, comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the user interface represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective subset; the user interface includes a user-selectable input by which the first Boolean query is changed, at least in part, without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. | 1. A method, comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the user interface represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective subset; the user interface includes a user-selectable input by which the first Boolean query is changed, at least in part, without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. 2. The method of claim 1 , wherein: the data set includes one or more corpora of unstructured text documents, the one or more corpora including more than 50,000 natural language text documents; causing the computing device to display the user interface comprises: receiving the first Boolean query from the user computing device; recursively decomposing the first Boolean query to form an abstract syntax tree representation of the first Boolean query; accessing a plurality of previously formed indices based on terms parsed from the first Boolean query to identify documents including the terms; determining the subsets based on a semantic analysis of the one or more corpora; determining respective statistics of the subsets; determining dimensions in display space of the user interface based on the respective statistics; sending instructions to render the user interface over a network from a computational linguistics system to a browser executing on the computing device, wherein the user interface is presented within the browser and is formed, at least in part, by invoking WebGL commands to enlist a graphical processing unit of the computing device in rendering at least part of the user interface; the user interface includes means for depicting a space-filling layout; causing the computing device to display the result of the second Boolean query comprises: sending instructions to the computing device to update the user interface by inserting or removing components of a document object model of the user interface in memory. | 0.5 |
7,743,047 | 12 | 15 | 12. A computer-implemented method for modifying a search experience, the method comprising: obtaining a collection of data that is a record of user-initiated commands initiated while conducting a search engine-facilitated searching process; determining a measure of interaction variance based on a pattern reflected within the collection of data, the pattern being indicative of a sequence of events indicated in the record, and wherein the measure of interaction variance is a measure based on a comparison of the pattern to at least one other pattern reflected within the collection of data, and wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigation indicated in the record of user-initiated commends; and customizing, based at least in part on the measure of interaction variance, the user's experience with a search process. | 12. A computer-implemented method for modifying a search experience, the method comprising: obtaining a collection of data that is a record of user-initiated commands initiated while conducting a search engine-facilitated searching process; determining a measure of interaction variance based on a pattern reflected within the collection of data, the pattern being indicative of a sequence of events indicated in the record, and wherein the measure of interaction variance is a measure based on a comparison of the pattern to at least one other pattern reflected within the collection of data, and wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigation indicated in the record of user-initiated commends; and customizing, based at least in part on the measure of interaction variance, the user's experience with a search process. 15. The method of claim 12 , wherein customizing comprises providing a customized search result interface. | 0.713514 |
7,594,270 | 8 | 12 | 8. The method according to claim 1 , wherein the step of determining an attack validation value further comprises: determining a class rating value; determining a vulnerability to attack value for said host; and utilizing said class rating value and said vulnerability to attack value to calculate said attack validation value. | 8. The method according to claim 1 , wherein the step of determining an attack validation value further comprises: determining a class rating value; determining a vulnerability to attack value for said host; and utilizing said class rating value and said vulnerability to attack value to calculate said attack validation value. 12. The method according to claim 8 , further comprising: applying a first weight factor to said class rating value; and applying a second weight factor to vulnerability to attack value for said host. | 0.820789 |
7,496,854 | 34 | 35 | 34. The computer system of claim 31 , wherein the operation performed is entering additional data into a database. | 34. The computer system of claim 31 , wherein the operation performed is entering additional data into a database. 35. The computer system of claim 34 , wherein the additional data is entered by a user. | 0.5 |
7,689,559 | 4 | 10 | 4. The method of claim 1 , wherein the following operations are performed on at least two documents in the index-word document list, in order of decreasing word similarity: for each of said at least two documents, setting one of said at least two documents as a first document D; choosing a second document D 2 to be the highest-lying document on the index-word document list which (i) has not been chosen before, and (ii) lies lower on the index-word document list than first document D; checking, for each second document D 2 lying lower on the index-word document list than first document D, whether the similarity S(D,D 2 ) has been previously calculated; for each second document D 2 for which S(D,D 2 ) has not been previously calculated, calculating a similarity S(D,D 2 ) of first document D to second document D 2 ; and enforcing a similarity threshold Ο SIM by stopping said step of choosing second documents, and by stopping said step of calculating S(D,D 2 ) for any further second document D 2 , when a similarity between document D and some second document D 2 is less than the similarity threshold. | 4. The method of claim 1 , wherein the following operations are performed on at least two documents in the index-word document list, in order of decreasing word similarity: for each of said at least two documents, setting one of said at least two documents as a first document D; choosing a second document D 2 to be the highest-lying document on the index-word document list which (i) has not been chosen before, and (ii) lies lower on the index-word document list than first document D; checking, for each second document D 2 lying lower on the index-word document list than first document D, whether the similarity S(D,D 2 ) has been previously calculated; for each second document D 2 for which S(D,D 2 ) has not been previously calculated, calculating a similarity S(D,D 2 ) of first document D to second document D 2 ; and enforcing a similarity threshold Ο SIM by stopping said step of choosing second documents, and by stopping said step of calculating S(D,D 2 ) for any further second document D 2 , when a similarity between document D and some second document D 2 is less than the similarity threshold. 10. The method of claim 4 , wherein said step of enforcing a similarity threshold Ο SIM , comprises predetermining the similarity threshold Ο SIM , said step of predetermining including one of: setting the predetermined similarity threshold Ο SIM equal to zero; and setting the predetermined similarity threshold Ο SIM equal to a value greater than zero. | 0.5 |
8,290,822 | 21 | 23 | 21. A computer-implemented system for efficiently displaying selectable attribute values for a product based on a provided criterion, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of the product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values selectable by the user. | 21. A computer-implemented system for efficiently displaying selectable attribute values for a product based on a provided criterion, comprising: at least one memory storage device storing: a set of product records that identify products potentially selectable by a user, wherein the product records comprise product attributes that represent one or more features of the product, wherein the product attributes comprise one or more attribute values; and one or more product configuration rules used to define permissible or impermissible product configurations and attributes of the products; at least one processor programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure and prepare a customized set of product records for transmission to the user, wherein the customized set of product records contains product attribute values selectable by the user. 23. The computer-implemented system of claim 21 , wherein the attribute BDD structure comprises: a non-offering attribute node representative of a product attribute value that is not selectable by the user based on evaluating the at least one product configuration rule. | 0.882711 |
7,831,951 | 32 | 33 | 32. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform the method, comprising: optimizing a description of the functionality and timing of a digital system, wherein the description comprises a plurality of tasks, wherein optimizing includes separately performing design-time intra-task scheduling for at least two of the tasks to generate a plurality of intra-task schedules for each of the tasks, wherein the plurality of intra-task schedules are a subset of all possible intra-task schedules, and wherein the subset defines partly task trade-off optimization information. | 32. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform the method, comprising: optimizing a description of the functionality and timing of a digital system, wherein the description comprises a plurality of tasks, wherein optimizing includes separately performing design-time intra-task scheduling for at least two of the tasks to generate a plurality of intra-task schedules for each of the tasks, wherein the plurality of intra-task schedules are a subset of all possible intra-task schedules, and wherein the subset defines partly task trade-off optimization information. 33. The program storage device of claim 32 , wherein optimizing a description comprises optimizing a task concurrency description. | 0.775862 |
7,694,226 | 19 | 20 | 19. The system of claim 13 , wherein said processor is further adapted to determine the narrative content of the designated set of content data files by way of input made at a user input system. | 19. The system of claim 13 , wherein said processor is further adapted to determine the narrative content of the designated set of content data files by way of input made at a user input system. 20. The system of claim 19 , wherein the processor is further adapted to determine nodes of the narrative content of the content data files, to further determine additional inference queries that are produced by calculating the relative significance of content data files to the nodes of the narrative content, said to combine these additional inference queries reiteratively and recursively with said inference queries to form combined inference queries and wherein said processor is adapted to search for context data files using the combined inference queries. | 0.5 |
8,204,838 | 1 | 10 | 1. A computer-implemented method of clustering items, each item having at least one associated feature, the method comprising: storing a data structure in memory the data structure holding a plurality of clusters; for each item, one or more associated features; for each cluster, at least one cluster membership parameter related to a prior probability distribution representing belief about whether any one of the items is a member of that cluster; for each cluster and feature combination, at least one feature parameter related to a prior probability distribution representing belief about whether any one of the items in that cluster is associated with that feature; receiving and storing an input comprising an observed item having observed associated features; updating the parameters in the data structure on a basis of the received input and using a Bayesian update process; identifying features that have a similar feature parameter across all clusters and using a same default value for those feature parameters; and iterating the receiving and updating for a plurality of such inputs. | 1. A computer-implemented method of clustering items, each item having at least one associated feature, the method comprising: storing a data structure in memory the data structure holding a plurality of clusters; for each item, one or more associated features; for each cluster, at least one cluster membership parameter related to a prior probability distribution representing belief about whether any one of the items is a member of that cluster; for each cluster and feature combination, at least one feature parameter related to a prior probability distribution representing belief about whether any one of the items in that cluster is associated with that feature; receiving and storing an input comprising an observed item having observed associated features; updating the parameters in the data structure on a basis of the received input and using a Bayesian update process; identifying features that have a similar feature parameter across all clusters and using a same default value for those feature parameters; and iterating the receiving and updating for a plurality of such inputs. 10. A method as claimed in claim 1 which further comprises, within a cluster, checking whether replacing a feature parameter with a default value significantly changes results of the clustering method and, in an absence of a significant change, using the default value for that feature parameter. | 0.76875 |
8,407,587 | 6 | 7 | 6. An apparatus, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: responsive to importing a document in a non-Unicode encoding scheme into a text editor operating in a Unicode encoding scheme, determine, by a source encoding mechanism in an editor parameters module of the text editor, a source encoding of the originating document; determine, by a field definitions mechanism in an editor parameters module of the text editor, one or more field definitions that are in effect for a given line in the document in the Unicode encoding scheme, wherein the field definitions provide a predefined formatting structure of the individual lines of text in the document; determine one or more shift-out or shift-in bytes in the document; determine, by a validation process of the text editor, whether one or more field violations exist in the document as a result of importing the document in the non-Unicode encoding scheme into the text editor in the Unicode encoding scheme; responsive to a determination that importing the document into the text editor results in one or more field violations, provide an identification of the one or more field violations through a document management module of the text editor; determine, by a parser process, if a change to the document in the Unicode encoding scheme violates one of the one or more field definitions within the document in the non-Unicode encoding scheme; and responsive to a determination that the change violates one of the field definitions associated with the document in the non-Unicode encoding scheme, provide an indication to the text editor when a field definition violation is determined and denying the change to the document; responsive to a determination that the change does not violate one of the field definitions associated with the document in the non-Unicode encoding scheme, allow the change to the document; and maintain field definitions of the document as a result of the change, wherein maintaining field definitions of the document comprises deleting spaces in a field in the document when the change is an insert and wherein maintaining field definitions of the document comprises inserting spaces in the document when the change is a deletion. | 6. An apparatus, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: responsive to importing a document in a non-Unicode encoding scheme into a text editor operating in a Unicode encoding scheme, determine, by a source encoding mechanism in an editor parameters module of the text editor, a source encoding of the originating document; determine, by a field definitions mechanism in an editor parameters module of the text editor, one or more field definitions that are in effect for a given line in the document in the Unicode encoding scheme, wherein the field definitions provide a predefined formatting structure of the individual lines of text in the document; determine one or more shift-out or shift-in bytes in the document; determine, by a validation process of the text editor, whether one or more field violations exist in the document as a result of importing the document in the non-Unicode encoding scheme into the text editor in the Unicode encoding scheme; responsive to a determination that importing the document into the text editor results in one or more field violations, provide an identification of the one or more field violations through a document management module of the text editor; determine, by a parser process, if a change to the document in the Unicode encoding scheme violates one of the one or more field definitions within the document in the non-Unicode encoding scheme; and responsive to a determination that the change violates one of the field definitions associated with the document in the non-Unicode encoding scheme, provide an indication to the text editor when a field definition violation is determined and denying the change to the document; responsive to a determination that the change does not violate one of the field definitions associated with the document in the non-Unicode encoding scheme, allow the change to the document; and maintain field definitions of the document as a result of the change, wherein maintaining field definitions of the document comprises deleting spaces in a field in the document when the change is an insert and wherein maintaining field definitions of the document comprises inserting spaces in the document when the change is a deletion. 7. The apparatus of claim 6 , wherein the instructions further cause the processor to identify the field definition violation in the document in response to the indication. | 0.5 |
7,986,843 | 1 | 3 | 1. A computer-implemented method of managing information, the method comprising: receiving a message from a mobile device configured to connect to a mobile device network, the mobile device comprising a digital camera, and the message comprising a digital image taken by the digital camera and including information corresponding to words, wherein receiving the message comprises receiving an indication of type for a document represented in the digital image, the indication of type comprising a user specified category selected from a group including business cards and credit card receipts; determining the words from the digital image information using optical character recognition; post-processing the words to identify and correct common character misidentifications resulting from the optical character recognition, the post-processing comprising post-processing the words in accordance with a dictionary based language model selected from at least two dictionary based language models according to the indication of type for the document; indexing the digital image based on the words; and storing the digital image for later retrieval of the digital image based on one or more received search terms. | 1. A computer-implemented method of managing information, the method comprising: receiving a message from a mobile device configured to connect to a mobile device network, the mobile device comprising a digital camera, and the message comprising a digital image taken by the digital camera and including information corresponding to words, wherein receiving the message comprises receiving an indication of type for a document represented in the digital image, the indication of type comprising a user specified category selected from a group including business cards and credit card receipts; determining the words from the digital image information using optical character recognition; post-processing the words to identify and correct common character misidentifications resulting from the optical character recognition, the post-processing comprising post-processing the words in accordance with a dictionary based language model selected from at least two dictionary based language models according to the indication of type for the document; indexing the digital image based on the words; and storing the digital image for later retrieval of the digital image based on one or more received search terms. 3. The method of claim 1 , further comprising: receiving the one or more search terms; and retrieving the digital image based on the one or more search terms. | 0.784741 |
8,655,912 | 10 | 13 | 10. An article of manufacture comprising at least one non-transitory machine readable storage medium having one or more computer programs stored thereon, the one or more computer programs when executed causing a machine to: order a list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events, model the keywords based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword, the modeling including region-specific modeling to improve the regional accuracy of the RPC modeling, score the keywords based on the modeling, and cluster the keywords based on the scoring, wherein the RPC value prediction being further based on a category of first activity for users who have converted on a given keyword. | 10. An article of manufacture comprising at least one non-transitory machine readable storage medium having one or more computer programs stored thereon, the one or more computer programs when executed causing a machine to: order a list of keywords from high activity to low activity, the high activity corresponding to keywords with a statistically significant number of return on investment (ROI) events, the ROI events corresponding to revenue-generating events, model the keywords based on a set of variables, the modeling including generating a revenue per click (RPC) value prediction for each of the keywords, the RPC value prediction being based on the set of variables, past keyword revenue performance data, and historical bid density by category for each keyword, the modeling including region-specific modeling to improve the regional accuracy of the RPC modeling, score the keywords based on the modeling, and cluster the keywords based on the scoring, wherein the RPC value prediction being further based on a category of first activity for users who have converted on a given keyword. 13. The article of manufacture as claimed in claim 10 wherein the set of variables include demonstrated user behavior variables. | 0.713004 |
7,788,266 | 1 | 8 | 1. A user-interface method for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the method comprising: using an ordering criteria to rank and associate subsets of content items with corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; subsequent to ranking and associating the content items with strings of unresolved keystrokes, receiving a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items; selecting and presenting the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receiving subsequent unresolved keystrokes from the user and forming a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; an selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting the subset of content items associated with the first unresolved keystroke and selecting the subset of content items associated with the string of unresolved keystrokes is performed using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. | 1. A user-interface method for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the method comprising: using an ordering criteria to rank and associate subsets of content items with corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; subsequent to ranking and associating the content items with strings of unresolved keystrokes, receiving a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items; selecting and presenting the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receiving subsequent unresolved keystrokes from the user and forming a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; an selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting the subset of content items associated with the first unresolved keystroke and selecting the subset of content items associated with the string of unresolved keystrokes is performed using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. 8. The method of claim 1 wherein said unresolved keystroke entry is processed by a server system remote from said user. | 0.822388 |
9,122,985 | 1 | 4 | 1. A method performed by at least one computing device, the method comprising: receiving a first terminology comprising first concepts and corresponding first codes; receiving a second terminology comprising second concepts and corresponding second codes; mapping the first concepts and the second concepts to levels of a combined hierarchical ontology; associating some of the first concepts and the second concepts within the combined hierarchical ontology; and providing programmatic access to the combined hierarchical ontology, wherein the providing programmatic access comprises: receiving a request identifying an individual first concept-code pair, the request identifying a number of levels to traverse the combined hierarchical ontology, the number of levels being greater than one; traversing the combined hierarchical ontology the identified number of levels to identify an ancestor concept-code pair of the individual first concept-code pair, and identifying, in the combined hierarchical ontology, a sibling concept-code pair of the individual first concept-code pair that shares the ancestor concept-code pair with the individual first concept-code pair but has a different meaning than the individual first concept-code pair. | 1. A method performed by at least one computing device, the method comprising: receiving a first terminology comprising first concepts and corresponding first codes; receiving a second terminology comprising second concepts and corresponding second codes; mapping the first concepts and the second concepts to levels of a combined hierarchical ontology; associating some of the first concepts and the second concepts within the combined hierarchical ontology; and providing programmatic access to the combined hierarchical ontology, wherein the providing programmatic access comprises: receiving a request identifying an individual first concept-code pair, the request identifying a number of levels to traverse the combined hierarchical ontology, the number of levels being greater than one; traversing the combined hierarchical ontology the identified number of levels to identify an ancestor concept-code pair of the individual first concept-code pair, and identifying, in the combined hierarchical ontology, a sibling concept-code pair of the individual first concept-code pair that shares the ancestor concept-code pair with the individual first concept-code pair but has a different meaning than the individual first concept-code pair. 4. The method according to claim 1 , wherein the request identifies an individual first concept of the individual first concept-code pair. | 0.795858 |
9,135,653 | 137 | 139 | 137. The method of claim 118 wherein the receiving first activity information for a sender of a first link to at least one recipient comprises: sending of an e-mail including the first link by the sender via a mobile device. | 137. The method of claim 118 wherein the receiving first activity information for a sender of a first link to at least one recipient comprises: sending of an e-mail including the first link by the sender via a mobile device. 139. The method of claim 137 wherein the receiving second activity information when a recipient accesses the first link sent by the sender comprises: receiving of the e-mail including the first link by the recipient via a nonmobile device. | 0.5 |
8,606,564 | 2 | 7 | 2. The method as recited in claim 1 , wherein assigning a label to one or more of a plurality of segments of the text comprises: parsing the text into a sequence of a plurality of tokens; and assigning a label to one or more of the plurality of tokens, wherein the label assigned to the one or more of the plurality of tokens classifies the corresponding one or more of the plurality of tokens as temporal data in one of the plurality of classes of temporal data. | 2. The method as recited in claim 1 , wherein assigning a label to one or more of a plurality of segments of the text comprises: parsing the text into a sequence of a plurality of tokens; and assigning a label to one or more of the plurality of tokens, wherein the label assigned to the one or more of the plurality of tokens classifies the corresponding one or more of the plurality of tokens as temporal data in one of the plurality of classes of temporal data. 7. The method as recited in claim 2 , wherein assigning a label to one or more of the plurality of tokens is based, at least in part, upon a context of the one or more of the plurality of tokens within the text. | 0.863695 |
9,928,439 | 1 | 5 | 1. A method of removing text in an image by at least one computing device, the method comprising: identifying, by the at least one computing device, a region of interest in the image including text; transforming, by the at least one computing device, the region of interest to correct distortion based at least in part on a homography; using, by the at least one computing device, an optical character recognizer to recognize a character based on a detected font used within the text; receiving, by the at least one computing device, a user input to remove the character; removing, by the at least one computing device, the character from the image based on a content aware fill process; and outputting, by the at least one computing device, a result of the removing of the character from the image. | 1. A method of removing text in an image by at least one computing device, the method comprising: identifying, by the at least one computing device, a region of interest in the image including text; transforming, by the at least one computing device, the region of interest to correct distortion based at least in part on a homography; using, by the at least one computing device, an optical character recognizer to recognize a character based on a detected font used within the text; receiving, by the at least one computing device, a user input to remove the character; removing, by the at least one computing device, the character from the image based on a content aware fill process; and outputting, by the at least one computing device, a result of the removing of the character from the image. 5. The method of claim 1 , wherein the optical character recognizer further comprises a font classifier trained on multiple fonts using linear discriminant analysis. | 0.752994 |
9,639,574 | 17 | 20 | 17. The method of claim 14 , wherein determining which of the one or more record combinations to evaluate comprises maintaining a current record combination including a last non-discarded, non-ignored record read from the hierarchical data storage. | 17. The method of claim 14 , wherein determining which of the one or more record combinations to evaluate comprises maintaining a current record combination including a last non-discarded, non-ignored record read from the hierarchical data storage. 20. The method of claim 17 , further comprising: deconstructing the predicates of the received query into one or more conjuncts, each of the one or more conjuncts including a single operation; evaluating each of the conjuncts for the current record combination when a record is added to the record combination; when the conjunct is not satisfied, identifying the current record combination with the added record as a mismatch; and ignoring any record in the received hierarchically clustered data stream that is a child of the added record that resulted in the mismatch. | 0.5 |
9,117,146 | 16 | 17 | 16. The system of claim 15 , wherein identifying a training image of the object comprises: identifying the object in the query image; and identifying an object in the training image that corresponds to the object in the query image. | 16. The system of claim 15 , wherein identifying a training image of the object comprises: identifying the object in the query image; and identifying an object in the training image that corresponds to the object in the query image. 17. The system of claim 16 , wherein identifying the object in the query image comprises: removing background information in the query image to obtain a normalized query image; and identifying the object in the normalized query image. | 0.5 |
9,230,130 | 11 | 12 | 11. The computer readable non-transitory medium of claim 10 , wherein the response to the electronic signature request comprises the receipt of signature of the electronic signature document by the third user, and the method further comprises: storing a second data structure comprising information corresponding to the signature of the electronic signature document, including information identifying the third user, date information, history information, and form data entered by the third user. | 11. The computer readable non-transitory medium of claim 10 , wherein the response to the electronic signature request comprises the receipt of signature of the electronic signature document by the third user, and the method further comprises: storing a second data structure comprising information corresponding to the signature of the electronic signature document, including information identifying the third user, date information, history information, and form data entered by the third user. 12. The computer readable non-transitory medium of claim 11 , wherein after transferring custody of the electronic signature document from the first user to the second user, the first user retains a second access right to view the electronic signature document and to view the second data structure comprising information corresponding to the signature of the electronic signature document. | 0.5 |
9,003,383 | 10 | 11 | 10. The system of claim 9 , wherein said analytic engine includes a flowchart builder coupled to said atomic path analyzer to create an object oriented flowchart and for exporting said created flowchart. | 10. The system of claim 9 , wherein said analytic engine includes a flowchart builder coupled to said atomic path analyzer to create an object oriented flowchart and for exporting said created flowchart. 11. The system of claim 10 , and further including the partially ordered transitive flowchart system processor is coupled to said flowchart builder for running said exported flowchart using a single partially ordered transitive flowchart system processor for multitasking or for identifying flowchart Task objects that can be executed in separate partially-ordered transitive flowchart system processors to effectuate parallel processing. | 0.5 |
8,010,560 | 16 | 18 | 16. system comprising: one or more data remembrance components; one or more processors; a set of executable components that are stored in at least one of said one or more data remembrance components and that execute on at least one of said one or more processors, the set of executable components comprising: a first executable component that abduces a first answer set from information that comprises (a) a query, and (b) a policy that governs access to a resource, said first answer set satisfying a condition that said query is true under said policy in the presence of a set of one or more assertions that is consistent with said first answer set, said first answer set comprising a first assertion, a first variable, and a first constraint that have been chosen; and a second executable component makes a determination whether said first answer set is subsumed by a second answer set, said second answer set comprising a second assertion, a second variable, and a second constraint that have been chosen; and a communications component through which said system provides said first answer set, said second answer set, or both said first answer set and said second answer set. | 16. system comprising: one or more data remembrance components; one or more processors; a set of executable components that are stored in at least one of said one or more data remembrance components and that execute on at least one of said one or more processors, the set of executable components comprising: a first executable component that abduces a first answer set from information that comprises (a) a query, and (b) a policy that governs access to a resource, said first answer set satisfying a condition that said query is true under said policy in the presence of a set of one or more assertions that is consistent with said first answer set, said first answer set comprising a first assertion, a first variable, and a first constraint that have been chosen; and a second executable component makes a determination whether said first answer set is subsumed by a second answer set, said second answer set comprising a second assertion, a second variable, and a second constraint that have been chosen; and a communications component through which said system provides said first answer set, said second answer set, or both said first answer set and said second answer set. 18. The system of claim 16 , wherein said set of executable components further comprises: a third executable component that limits what types of assertions said first executable component may abduce, or which abduced assertions said first executable component may include in said first answer set. | 0.853261 |
7,716,050 | 8 | 13 | 8. The computer-implemented method of claim 1 further comprising: generating, for each word in a list of words to be recognized, an acoustic word model, the generating comprising generating a grouping of subword units representing a pronunciation of the word to be recognized using the single pronunciation estimator. | 8. The computer-implemented method of claim 1 further comprising: generating, for each word in a list of words to be recognized, an acoustic word model, the generating comprising generating a grouping of subword units representing a pronunciation of the word to be recognized using the single pronunciation estimator. 13. The computer-implemented method of claim 8 further comprising: processing an utterance; and scoring matches between the processed utterance and the acoustic word models. | 0.649798 |
10,121,286 | 23 | 26 | 23. A system for synchronizing an annotated 3D computer-aided design (CAD) model and a 2D drawing, the system comprising: a communications interface configured to receive an annotated 3D CAD model of a physical part or assembly; and a processing circuit configured to: generate a 2D drawing of the physical part or assembly using the annotated 3D CAD model; add supplemental content to the 2D drawing, wherein the supplemental content is not included in the annotated 3D CAD model; and modify the annotated 3D CAD model to include 2D drawing parameters that include the supplemental content added to the 2D drawing, wherein the 2D drawing parameters provide instructions for reproducing the 2D drawing including the supplemental content, such that the 2D drawing is not saved. | 23. A system for synchronizing an annotated 3D computer-aided design (CAD) model and a 2D drawing, the system comprising: a communications interface configured to receive an annotated 3D CAD model of a physical part or assembly; and a processing circuit configured to: generate a 2D drawing of the physical part or assembly using the annotated 3D CAD model; add supplemental content to the 2D drawing, wherein the supplemental content is not included in the annotated 3D CAD model; and modify the annotated 3D CAD model to include 2D drawing parameters that include the supplemental content added to the 2D drawing, wherein the 2D drawing parameters provide instructions for reproducing the 2D drawing including the supplemental content, such that the 2D drawing is not saved. 26. The system of claim 23 , wherein modifying the annotated 3D CAD model to include the 2D drawing parameters that include the supplemental content comprises: generating a plurality of data elements, each data element corresponding to a view depicted in the 2D drawing and being added to the 2D drawing parameters at least partially defining the corresponding view; and storing the plurality of data elements as properties of the annotated 3D CAD model. | 0.504367 |
9,619,751 | 10 | 11 | 10. The computer storage medium of claim 8 , wherein the collected information comprises metadata describing the current activities. | 10. The computer storage medium of claim 8 , wherein the collected information comprises metadata describing the current activities. 11. The computer storage medium of claim 10 , wherein determining the need for the presentation of the additional information comprises identifying a context of the current activities from the metadata and the profile data. | 0.561024 |
8,868,469 | 1 | 9 | 1. A method of identifying phrases in an electronic document comprising: identifying one or more phrase candidates in the electronic document; selecting one of the phrase candidates; numerically representing features of the selected phrase candidates to obtain a numeric feature representation associated with that phrase candidate by: identifying, from a predetermined dictionary map which maps words to unique numbers, the number associated with each word in the selected phrase candidate; and including the identified number associated with each word in the numeric feature representation; inputting the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, that the phrase candidate associated with that numeric feature representation is a phrase, wherein identifying phrase candidates in the electronic document comprises identifying word level n-grams in the document; and associating the electronic document with a label identifying the subject matter of the electronic document, wherein the label is based on the phrase. | 1. A method of identifying phrases in an electronic document comprising: identifying one or more phrase candidates in the electronic document; selecting one of the phrase candidates; numerically representing features of the selected phrase candidates to obtain a numeric feature representation associated with that phrase candidate by: identifying, from a predetermined dictionary map which maps words to unique numbers, the number associated with each word in the selected phrase candidate; and including the identified number associated with each word in the numeric feature representation; inputting the numeric feature representation into a machine learning classifier, the machine learning classifier being configured to determine, based on each numeric feature representation, that the phrase candidate associated with that numeric feature representation is a phrase, wherein identifying phrase candidates in the electronic document comprises identifying word level n-grams in the document; and associating the electronic document with a label identifying the subject matter of the electronic document, wherein the label is based on the phrase. 9. The method of claim 1 , further comprising: categorizing the electronic document based on the associated label. | 0.887574 |
8,255,798 | 1 | 5 | 1. A device, comprising: a touch screen display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including instructions for: detecting a movement of an object on the touch screen display; translating an electronic document displayed on the touch screen display in a first direction, in response to detecting the movement; displaying an area beyond an edge of the electronic document in response to the edge of the electronic document being reached while translating the electronic document in the first direction while the object is still detected on the touch screen display; and translating the document in a second direction until the area beyond the edge of the document is no longer displayed, in response to detecting that the object is no longer on the touch screen display. | 1. A device, comprising: a touch screen display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including instructions for: detecting a movement of an object on the touch screen display; translating an electronic document displayed on the touch screen display in a first direction, in response to detecting the movement; displaying an area beyond an edge of the electronic document in response to the edge of the electronic document being reached while translating the electronic document in the first direction while the object is still detected on the touch screen display; and translating the document in a second direction until the area beyond the edge of the document is no longer displayed, in response to detecting that the object is no longer on the touch screen display. 5. The device of claim 1 , wherein the first direction is a vertical direction, a horizontal direction, or a diagonal direction. | 0.89694 |
7,609,669 | 19 | 24 | 19. A method for delivering a message in a speech-enabled work environment that includes a plurality of users with terminal devices that perform applications using speech, the method comprising the steps of: executing at least one application, using user speech and speech recognition, through a terminal device that is communicating with a communications network; receiving the message, at the terminal device of a user, over the communications network; outputting the message as audio output to the user of the terminal device; receiving verbal confirmation spoken by the user that the audio output was at least one of accessed or understood; and transmitting an acknowledgement message from the terminal device over the communications network, the acknowledgement message being reflective of the receipt of the spoken verbal confirmation for indicating that the audio output was at least one of accessed or understood by the user. | 19. A method for delivering a message in a speech-enabled work environment that includes a plurality of users with terminal devices that perform applications using speech, the method comprising the steps of: executing at least one application, using user speech and speech recognition, through a terminal device that is communicating with a communications network; receiving the message, at the terminal device of a user, over the communications network; outputting the message as audio output to the user of the terminal device; receiving verbal confirmation spoken by the user that the audio output was at least one of accessed or understood; and transmitting an acknowledgement message from the terminal device over the communications network, the acknowledgement message being reflective of the receipt of the spoken verbal confirmation for indicating that the audio output was at least one of accessed or understood by the user. 24. The method of claim 19 , further comprising the step of: converting the message from text format to audio output. | 0.796875 |
8,671,364 | 31 | 40 | 31. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level; receive a control directive indicating selection of the selectable GUI element of the hierarchical level for decomposition into decomposed GUI elements of the different hierarchical level; and present the selectable GUI element of the hierarchical level adjoining with the decomposed GUI elements of the different hierarchical level in response to the control directive. | 31. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level; receive a control directive indicating selection of the selectable GUI element of the hierarchical level for decomposition into decomposed GUI elements of the different hierarchical level; and present the selectable GUI element of the hierarchical level adjoining with the decomposed GUI elements of the different hierarchical level in response to the control directive. 40. The article of manufacture of claim 31 , further comprising instructions that when executed enable the system to generate one or more reporting variables for an information pipe falling within a range of values for the multivariable decomposition visualization in response to a pipe filter control directive. | 0.5 |
8,738,365 | 1 | 8 | 1. A computer readable storage device storing a program of instructions executable by a machine to perform a method of diffusing evidence among candidate answers during question answering, comprising: identifying, by a processor, a relationship between a first candidate answer and a second candidate answer, wherein the candidate answers are generated by a question-answering computer process for answering a question, the candidate answers have associated supporting evidence, and the candidate answers have associated confidence scores; determining whether to transfer the associated supporting evidence from the first candidate answer to the second candidate answer, or to transfer the associated supporting evidence from the second candidate answer to the first candidate answer, by analyzing how the question is posed and types of the first candidate answer and the second candidate answer; in response to determining to transfer the associated supporting evidence from the first candidate answer to the second candidate answer, transferring all or some of the evidence from the first candidate answer to the second candidate answer based on the identified relationship, and computing a new confidence score for the second candidate answer based on the transferred evidence and second candidate answer's existing evidence; in response to determining to transfer the associated supporting evidence from the second candidate answer to the first candidate answer, transferring all or some of the evidence from the second candidate answer to the first candidate answer based on the identified relationship, and computing a new confidence score for the first candidate answer based on the transferred evidence and first candidate answer's existing evidence. | 1. A computer readable storage device storing a program of instructions executable by a machine to perform a method of diffusing evidence among candidate answers during question answering, comprising: identifying, by a processor, a relationship between a first candidate answer and a second candidate answer, wherein the candidate answers are generated by a question-answering computer process for answering a question, the candidate answers have associated supporting evidence, and the candidate answers have associated confidence scores; determining whether to transfer the associated supporting evidence from the first candidate answer to the second candidate answer, or to transfer the associated supporting evidence from the second candidate answer to the first candidate answer, by analyzing how the question is posed and types of the first candidate answer and the second candidate answer; in response to determining to transfer the associated supporting evidence from the first candidate answer to the second candidate answer, transferring all or some of the evidence from the first candidate answer to the second candidate answer based on the identified relationship, and computing a new confidence score for the second candidate answer based on the transferred evidence and second candidate answer's existing evidence; in response to determining to transfer the associated supporting evidence from the second candidate answer to the first candidate answer, transferring all or some of the evidence from the second candidate answer to the first candidate answer based on the identified relationship, and computing a new confidence score for the first candidate answer based on the transferred evidence and first candidate answer's existing evidence. 8. The computer readable storage device of claim 1 , wherein the identifying step is based on lexical knowledge extracted from unstructured text. | 0.738267 |
6,088,711 | 4 | 10 | 4. For an electronic system for creating and editing an electronic document, the document comprising a paragraph associated with at least one major formatting property and at least one minor formatting property, a method for defining a style for the paragraph, the method comprising the steps of: automatically identifying a paragraph type of the paragraph by examining the at least one major formatting property; determining an appropriate style to define for the paragraph based upon the paragraph type; determining whether the appropriate style has already been defined; and if not, then storing the at least one major formatting property and the at least one minor formatting property in association with the appropriate style, wherein the appropriate style defines the style for the paragraph. | 4. For an electronic system for creating and editing an electronic document, the document comprising a paragraph associated with at least one major formatting property and at least one minor formatting property, a method for defining a style for the paragraph, the method comprising the steps of: automatically identifying a paragraph type of the paragraph by examining the at least one major formatting property; determining an appropriate style to define for the paragraph based upon the paragraph type; determining whether the appropriate style has already been defined; and if not, then storing the at least one major formatting property and the at least one minor formatting property in association with the appropriate style, wherein the appropriate style defines the style for the paragraph. 10. The method recited in claim 4, wherein the step of identifying the paragraph type of the paragraph comprises the steps of: determining whether the paragraph is one line in length and, if not, then identifying the paragraph type as body text; if the paragraph is one line in length, then determining whether at least one major formatting property matches a plurality of major formatting properties of a previously defined body text style and, if so, then determining whether the paragraph ends in one of a predetermined set of punctuation marks and, if so, then identifying the paragraph type as body text; if the at least one major formatting property does not match the plurality of major formatting properties of a previously defined body text style, or if the paragraph does not end in a period, a question mark, an exclamation point, or a colon, then determining whether the paragraph begins with a capital letter; if the paragraph begins with a capital letter, then determining whether the paragraph ends with an exclamation point, question mark, or no punctuation and, if so, then determining whether the paragraph is one of a predetermined set of text characteristics and, if so, then identifying the paragraph type as a heading; and if the paragraph is not bold, italicized, or underlined, then determining whether the point size of the paragraph is larger than the point size for a normal style, and, if so, then identifying the paragraph type as a heading. | 0.5 |
9,519,871 | 14 | 18 | 14. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of contextual text adaptation, the method comprising: identifying a target user; receiving a corpus of documents in context of the target user; receiving a dictionary of words; receiving a dictionary of synonyms; generating a topic model algorithm based on the corpus of documents and the dictionary of words by machine learning, the topic model algorithm comprising a first function that predicts probability distribution of a plurality of topics in a given document, and a second function that predicts probability of a given word occurring in a document associated with a given topic; and storing the first function and the second function of the topic model algorithm in a storage device, receiving an input document; determining input document topics associated with the input document and a normalized weight associated with each of the input document topics by executing the first function; for each of a plurality of input document words in the input document, determining a probability that an input document word is associated with an input document topic for each of the input document topics by executing the second function; determining an aggregate probability for the input document word as a sum of products of the probability that an input document word is associated with an input document topic and the normalized weight of the input document topic; determining a synonym of the input document word based on the dictionary of synonyms; determining an aggregate probability for the synonym; comparing the aggregate probability for the synonym and the aggregate probability for the input document word; responsive to determining that the aggregate probability for the synonym is greater than the aggregate probability for the input document word, replacing the input document word with the synonym; and generating an output document comprising content of the input document with replaced words. | 14. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of contextual text adaptation, the method comprising: identifying a target user; receiving a corpus of documents in context of the target user; receiving a dictionary of words; receiving a dictionary of synonyms; generating a topic model algorithm based on the corpus of documents and the dictionary of words by machine learning, the topic model algorithm comprising a first function that predicts probability distribution of a plurality of topics in a given document, and a second function that predicts probability of a given word occurring in a document associated with a given topic; and storing the first function and the second function of the topic model algorithm in a storage device, receiving an input document; determining input document topics associated with the input document and a normalized weight associated with each of the input document topics by executing the first function; for each of a plurality of input document words in the input document, determining a probability that an input document word is associated with an input document topic for each of the input document topics by executing the second function; determining an aggregate probability for the input document word as a sum of products of the probability that an input document word is associated with an input document topic and the normalized weight of the input document topic; determining a synonym of the input document word based on the dictionary of synonyms; determining an aggregate probability for the synonym; comparing the aggregate probability for the synonym and the aggregate probability for the input document word; responsive to determining that the aggregate probability for the synonym is greater than the aggregate probability for the input document word, replacing the input document word with the synonym; and generating an output document comprising content of the input document with replaced words. 18. The computer readable storage medium of claim 14 , wherein the corpus of documents comprises web postings the target user accesses. | 0.82 |
9,189,361 | 1 | 2 | 1. A system for proactive management of performance of an application, the system comprising: a digital data processor configured to execute a performance monitor in communications coupling with one or more resources, and the performance monitor configured to: monitor (i) usage of the application by a user and/or one or more components thereof by the user, and (ii) consumption of the one or more resources during the usage of the application and/or the one or more components thereof by the user, wherein the resources include any of processing capacity, memory capacity, and/or network bandwidth, and signal an alert upon determining that such usage by the user and/or consumption of resources during such usage violates a model, wherein the model defines one or more quotas for the user with respect to usage of a component of the application by the user, wherein the one or more quotas defined by the model include a maximum resource consumption quota and an expected resource consumption quota, wherein the model indicates that the user is permitted to consume no more than a pre-determined amount of processor capacity and no more than a pre-determined amount of network bandwidth, and wherein the expected resource consumption quota is between 0.1-0.35 percent of processor capacity to be consumed by the user on average, and between 10-100 kilobytes per second on the network to be consumed by the user on average, during use of the application. | 1. A system for proactive management of performance of an application, the system comprising: a digital data processor configured to execute a performance monitor in communications coupling with one or more resources, and the performance monitor configured to: monitor (i) usage of the application by a user and/or one or more components thereof by the user, and (ii) consumption of the one or more resources during the usage of the application and/or the one or more components thereof by the user, wherein the resources include any of processing capacity, memory capacity, and/or network bandwidth, and signal an alert upon determining that such usage by the user and/or consumption of resources during such usage violates a model, wherein the model defines one or more quotas for the user with respect to usage of a component of the application by the user, wherein the one or more quotas defined by the model include a maximum resource consumption quota and an expected resource consumption quota, wherein the model indicates that the user is permitted to consume no more than a pre-determined amount of processor capacity and no more than a pre-determined amount of network bandwidth, and wherein the expected resource consumption quota is between 0.1-0.35 percent of processor capacity to be consumed by the user on average, and between 10-100 kilobytes per second on the network to be consumed by the user on average, during use of the application. 2. The system of claim 1 , wherein the performance monitor limits usage and/or consumption of resources. | 0.609023 |
7,574,631 | 1 | 7 | 1. A circuit arrangement for secure data processing for program data with a protected data record, comprising: an internal memory which provides a protected data record having instruction words and at least one first check word associated with the instruction words; an arithmetic and logic unit having an input coupled to the internal memory and which outputs the at least one first check word from the applied protected data record; a checking apparatus having an input coupled between the internal memory and the arithmetic and logic unit and which allocates at least one second check word to the instruction words in the protected data record; and a comparison apparatus having respective inputs coupled to the checking apparatus and the arithmetic and logic unit and which compares the at least one first check word with the at least one second check word and outputs an alarm signal when the at least one first check word does not match the at least one second check word. | 1. A circuit arrangement for secure data processing for program data with a protected data record, comprising: an internal memory which provides a protected data record having instruction words and at least one first check word associated with the instruction words; an arithmetic and logic unit having an input coupled to the internal memory and which outputs the at least one first check word from the applied protected data record; a checking apparatus having an input coupled between the internal memory and the arithmetic and logic unit and which allocates at least one second check word to the instruction words in the protected data record; and a comparison apparatus having respective inputs coupled to the checking apparatus and the arithmetic and logic unit and which compares the at least one first check word with the at least one second check word and outputs an alarm signal when the at least one first check word does not match the at least one second check word. 7. The circuit arrangement of claim 1 , further comprising a decoding apparatus coupled between the internal memory and the arithmetic and logic unit and which transforms the instruction words applied to its input. | 0.548523 |
8,621,339 | 1 | 4 | 1. A method for supplementing a web graph of linked web documents, the method comprising: identifying one or more experts for one of one or more categories; identifying one or more web documents tagged by the one or more experts for a given category; determining a corresponding category of the one or more web documents tagged by the one or more experts for the given category; assigning a proxy web document to each one of the one or more experts identified for the given category, the proxy web document representative of a corresponding one of the one or more experts; and linking one or more proxy web documents to the one or more web documents tagged by the one or more experts for the given category. | 1. A method for supplementing a web graph of linked web documents, the method comprising: identifying one or more experts for one of one or more categories; identifying one or more web documents tagged by the one or more experts for a given category; determining a corresponding category of the one or more web documents tagged by the one or more experts for the given category; assigning a proxy web document to each one of the one or more experts identified for the given category, the proxy web document representative of a corresponding one of the one or more experts; and linking one or more proxy web documents to the one or more web documents tagged by the one or more experts for the given category. 4. The method of claim 1 wherein identifying one or more documents tagged by the one or more experts for the given category further comprises identifying one or more documents tagged by the one or more experts for the given category located external to the existing web graph of web documents. | 0.501701 |
10,042,872 | 1 | 4 | 1. A method for database optimization, comprising: detecting a plurality of columns in an unoptimized database that co-appear in queries to the database; compacting the plurality of columns into a single hyper-column using a processor to form an optimized database, wherein each entry in the hyper-column comprises data from a corresponding entry in each of the plurality of columns; and generating an interface for the optimized database that accepts queries according to a schema for the unoptimized database and translates said queries into queries according to a schema for the optimized database. | 1. A method for database optimization, comprising: detecting a plurality of columns in an unoptimized database that co-appear in queries to the database; compacting the plurality of columns into a single hyper-column using a processor to form an optimized database, wherein each entry in the hyper-column comprises data from a corresponding entry in each of the plurality of columns; and generating an interface for the optimized database that accepts queries according to a schema for the unoptimized database and translates said queries into queries according to a schema for the optimized database. 4. The method of claim 1 , further comprising generating an index for the hyper-column. | 0.756983 |
7,496,854 | 82 | 84 | 82. The computer system of claim 79 , wherein the operation performed is entering additional data into a database. | 82. The computer system of claim 79 , wherein the operation performed is entering additional data into a database. 84. The computer system of claim 82 , wherein the additional data is located within the document. | 0.5 |
8,560,935 | 11 | 12 | 11. The system of claim 7 , further comprising the interface component receives two or more electronic documents that each include a set of questions and a respective set of fill-in fields, wherein the respective set of fill-in fields, for each of the two or more electronic documents, receive an answer to each respective question in the set of questions. | 11. The system of claim 7 , further comprising the interface component receives two or more electronic documents that each include a set of questions and a respective set of fill-in fields, wherein the respective set of fill-in fields, for each of the two or more electronic documents, receive an answer to each respective question in the set of questions. 12. The system of claim 11 , further comprising: the master field component creates the master field list for two or more electronic documents in which the master field list segregates the set of questions and the respective set of fill-in fields for the two or more electronic documents; and the form aggregation component leverages the master field list for two or more electronic documents to collect information received to update the set of questions and the respective set of fill-in fields on the two or more electronic documents. | 0.5 |
9,009,142 | 11 | 12 | 11. The method of claim 10 , including: receiving a second message subsequent to receiving the first message; associating the second message with the conversation; storing, in the index, one or more second-message index components that each include an identifier of the second message, including: one or more index components indicative of a plurality of message terms in the second message; one or more index components indicative of one or more conversation terms in the conversation, the one or more conversation terms comprising one or more terms that are not in the second message; and an index component identifying the second message as the representative message of the conversation; and removing, from the index, the first-message index component that identifies the first message as the representative message of the conversation. | 11. The method of claim 10 , including: receiving a second message subsequent to receiving the first message; associating the second message with the conversation; storing, in the index, one or more second-message index components that each include an identifier of the second message, including: one or more index components indicative of a plurality of message terms in the second message; one or more index components indicative of one or more conversation terms in the conversation, the one or more conversation terms comprising one or more terms that are not in the second message; and an index component identifying the second message as the representative message of the conversation; and removing, from the index, the first-message index component that identifies the first message as the representative message of the conversation. 12. The method of claim 11 , further comprising, after receiving the second message: removing, from the index, the one or more first-message index components indicative of conversation terms. | 0.5 |
7,908,285 | 1 | 8 | 1. A computer-implemented method for processing experimental data in a laboratory data management system according to an object model, the object model including a first pre-defined experiment class that is configured to be instantiated to define one or more experiment objects that represent data for particular experiments in the laboratory data management system, the method comprising: receiving, by a processor, input specifying a first set of one or more variable definition objects defining a set of variables for a first experiment type to be represented by the one or more instances of the first pre-defined experiment class, the variables in the set of variables having types selected from a predefined set of data types including attributes that are configured to be used to represent data for experiments in the laboratory data management system; receiving, by the processor, data for an experiment of the first experiment type, the data including a plurality of values corresponding to variables defined in the first set of one or more variable definition objects; storing a sparse representation of the data for the experiment of the first experiment type in a relational database table according to the set of types defined by the first set of one or more variable definition objects; and presenting a dense representation of the data for the experiment of the first experiment type, the dense representation being derived from the sparse representation by removing at least one empty data field from the sparse representation, and being presented in a relational database table defined according to the first set of one or more variable definition objects. | 1. A computer-implemented method for processing experimental data in a laboratory data management system according to an object model, the object model including a first pre-defined experiment class that is configured to be instantiated to define one or more experiment objects that represent data for particular experiments in the laboratory data management system, the method comprising: receiving, by a processor, input specifying a first set of one or more variable definition objects defining a set of variables for a first experiment type to be represented by the one or more instances of the first pre-defined experiment class, the variables in the set of variables having types selected from a predefined set of data types including attributes that are configured to be used to represent data for experiments in the laboratory data management system; receiving, by the processor, data for an experiment of the first experiment type, the data including a plurality of values corresponding to variables defined in the first set of one or more variable definition objects; storing a sparse representation of the data for the experiment of the first experiment type in a relational database table according to the set of types defined by the first set of one or more variable definition objects; and presenting a dense representation of the data for the experiment of the first experiment type, the dense representation being derived from the sparse representation by removing at least one empty data field from the sparse representation, and being presented in a relational database table defined according to the first set of one or more variable definition objects. 8. The method of claim 1 , further comprising: receiving input specifying a second set of one or more variable definition objects defining a set of variables for a second experiment type, the variables in the set of variables for the second experiment type having types selected from the predefined set of data types; receiving data for an experiment of the second experiment type, the data including a plurality of values corresponding to variables defined in the second set of one or more variable definition objects; storing a sparse representation of the data for the experiment of the second experiment type in a relational database table according to the set of types defined by the second set of one or more variable definition objects; and presenting a dense representation of the data for the experiment of the second experiment type, the dense representation being derived from the sparse representation by removing at least one empty data field from the sparse representation, and being presented in a relational database table defined according to the second set of one or more variable definition objects. | 0.5 |
9,323,741 | 13 | 14 | 13. The method of claim 12 , wherein said searching through one or more documents further comprises searching for said one or more keywords in said documents; and ranking said function match also according to said one or more keywords. | 13. The method of claim 12 , wherein said searching through one or more documents further comprises searching for said one or more keywords in said documents; and ranking said function match also according to said one or more keywords. 14. The method of claim 13 , wherein said searching for said one or more keywords in said documents comprising analyzing said one or more keywords to determine a scientific or mathematical category; determining whether said one or more documents comprises content in said scientific or mathematical category; and ranking said function match also according to said category determination. | 0.5 |
9,507,876 | 1 | 4 | 1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes each corresponding to a plurality of objects, respectively, associated with the online social network, each object being of a particular object-type; receiving, from a client device of the first user, a first search query comprising a selection of a first query-domain, the first query-domain corresponding to a first object-type; identifying, responsive to the first search query, a first set of objects of the plurality of objects matching the first object-type, each of the identified objects corresponding to a second node within a threshold degree of separation of the first node; sending, to the client device of the first user, a first search-results page responsive to the first search query, the first search-results page comprising references to one or more of the identified objects from the first set of objects and one or more query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects; and receiving, from the client device of the first user, a second search query comprising a selection of one or more of the query-filters in response to the first user activating the corresponding query-filter elements. | 1. A method comprising, by one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes each corresponding to a plurality of objects, respectively, associated with the online social network, each object being of a particular object-type; receiving, from a client device of the first user, a first search query comprising a selection of a first query-domain, the first query-domain corresponding to a first object-type; identifying, responsive to the first search query, a first set of objects of the plurality of objects matching the first object-type, each of the identified objects corresponding to a second node within a threshold degree of separation of the first node; sending, to the client device of the first user, a first search-results page responsive to the first search query, the first search-results page comprising references to one or more of the identified objects from the first set of objects and one or more query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects; and receiving, from the client device of the first user, a second search query comprising a selection of one or more of the query-filters in response to the first user activating the corresponding query-filter elements. 4. The method of claim 1 , wherein the first search-results page further comprises an additional-filters element, wherein the additional-filters element is activatable to generate a user interface comprising the one or more query-filter elements of the first search-results page and one or more additional query-filter elements, each query-filter element corresponding to a query-filter associated with the first query-domain, wherein each query-filter element is activatable to apply the associated query-filter to the identified objects. | 0.504596 |
8,601,578 | 5 | 6 | 5. The apparatus of claim 1 , wherein: the selected one of the business listing configuration rules includes a threshold; and the processor is further operative to transmit a threshold alert when a plurality of business listings having been identified as being potentially suspicious business listings exceed the threshold. | 5. The apparatus of claim 1 , wherein: the selected one of the business listing configuration rules includes a threshold; and the processor is further operative to transmit a threshold alert when a plurality of business listings having been identified as being potentially suspicious business listings exceed the threshold. 6. The apparatus of claim 5 , wherein the threshold is a number of business listings that have been identified as being potentially suspicious business listings. | 0.512121 |
8,433,576 | 13 | 15 | 13. The method of claim 12 , further comprising: iteratively displaying additional portions of the text sample to the user, and dynamically assembling additional domain-specific target language models respectively based on each of the additional portions of the text sample while they are being displayed. | 13. The method of claim 12 , further comprising: iteratively displaying additional portions of the text sample to the user, and dynamically assembling additional domain-specific target language models respectively based on each of the additional portions of the text sample while they are being displayed. 15. The method of claim 13 , wherein providing user-perceptible feedback comprises at least one of: displaying a phonetic representation of a portion of the text output corresponding to a miscue, the phonetic representation being displayed separate from the portion of the text output corresponding to the miscue; and displaying a score representing how much of the acoustic input is free of miscues. | 0.661591 |
9,536,350 | 9 | 11 | 9. The electronic device of claim 8 , wherein: the one or more interactions include the particular person speaking in the direction of the electronic device. | 9. The electronic device of claim 8 , wherein: the one or more interactions include the particular person speaking in the direction of the electronic device. 11. The electronic device of claim 9 , wherein: the at least one rule is satisfied if the particular person is associated with a particular privacy level. | 0.741611 |
9,990,059 | 12 | 13 | 12. A computer-implemented method, comprising: receiving ink content applied to a document via input from a pen to an input surface while in a transient ink mode, the transient ink mode effective to cause ink applied to the document to be applied to a transient ink layer separate from the document such that the ink does not becoming part of primary content of the document; detecting that the pen is removed from proximity to the input surface; initiating a timer responsive to said detecting; removing the ink content from being displayed on the document and propagating the ink content to the transient ink layer for the document responsive to expiry of the timer; and displaying a visual representation of a user, the visual representation being selectable to retrieve the transient ink layer and cause the ink content from the transient ink layer to be displayed along with the primary content. | 12. A computer-implemented method, comprising: receiving ink content applied to a document via input from a pen to an input surface while in a transient ink mode, the transient ink mode effective to cause ink applied to the document to be applied to a transient ink layer separate from the document such that the ink does not becoming part of primary content of the document; detecting that the pen is removed from proximity to the input surface; initiating a timer responsive to said detecting; removing the ink content from being displayed on the document and propagating the ink content to the transient ink layer for the document responsive to expiry of the timer; and displaying a visual representation of a user, the visual representation being selectable to retrieve the transient ink layer and cause the ink content from the transient ink layer to be displayed along with the primary content. 13. A computer-implemented method as recited in claim 12 , wherein said detecting comprises detecting that the pen is not in contact with the input surface and that the pen is not hovered over the input surface. | 0.574597 |
8,132,098 | 16 | 17 | 16. The system of claim 14 , wherein the operations further comprise: determining a second layout of text, the second layout of text comprising a second plurality of consecutive text lines; identifying each text line, in the second plurality of consecutive text lines, that ends in a hyphen; determining proximity of at least two non-consecutive text lines, in the second plurality of consecutive text lines, that end in hyphens; calculating a second hyphenation penalty value based on the determined proximity of the at least two non-consecutive lines, in the second plurality of consecutive text lines, that end in hyphens; and comparing the hyphenation penalty value to the second hyphenation penalty value. | 16. The system of claim 14 , wherein the operations further comprise: determining a second layout of text, the second layout of text comprising a second plurality of consecutive text lines; identifying each text line, in the second plurality of consecutive text lines, that ends in a hyphen; determining proximity of at least two non-consecutive text lines, in the second plurality of consecutive text lines, that end in hyphens; calculating a second hyphenation penalty value based on the determined proximity of the at least two non-consecutive lines, in the second plurality of consecutive text lines, that end in hyphens; and comparing the hyphenation penalty value to the second hyphenation penalty value. 17. The system of claim 16 , wherein the operations further comprise selecting an optimum layout from either the layout of text or the second layout of text, based on comparing the hyphenation penalty value to the second hyphenation penalty value. | 0.5 |
8,069,182 | 1 | 8 | 1. A method comprising: receiving a request from a source to access content of a target Web domain, the request being addressed to a domain address of the target Web domain; retrieving historical relevance data associated with at least one previous request from another source to the target Web domain from a database; identifying a new content Web domain that is determined to be relevant to the request based on a combination of the domain address of the target Web domain and the historical relevance data, the historical relevance data including one or more context factors collected from the at least one previous request to the target Web domain; and redirecting the source to access advertising content of the identified new content Web domain, responsive to the request. | 1. A method comprising: receiving a request from a source to access content of a target Web domain, the request being addressed to a domain address of the target Web domain; retrieving historical relevance data associated with at least one previous request from another source to the target Web domain from a database; identifying a new content Web domain that is determined to be relevant to the request based on a combination of the domain address of the target Web domain and the historical relevance data, the historical relevance data including one or more context factors collected from the at least one previous request to the target Web domain; and redirecting the source to access advertising content of the identified new content Web domain, responsive to the request. 8. The method of claim 1 wherein the historical relevance data conditionally maps the domain address of the target Web domain to a domain address of the new content Web domain. | 0.8 |
9,170,574 | 9 | 10 | 9. A BMS system according to claim 6 wherein the equipment model templates include a plurality of HVAC templates for respectively describing categories of equipment in an HVAC system. | 9. A BMS system according to claim 6 wherein the equipment model templates include a plurality of HVAC templates for respectively describing categories of equipment in an HVAC system. 10. A BMS system according to claim 9 wherein for at least one category of equipment in the HVAC system, the template is configured to additionally describe a region uniquely serviced by the piece of equipment. | 0.5 |
8,812,949 | 10 | 16 | 10. A system for automatically outputting semantically significant text from a markup language document, comprising: a data store storing a set of markup language documents, the set of documents including a first markup language document; a parser module to parse the first markup language document to produce a parse tree; a segmenter module to segment the parse tree into a set of segments including a first segment each of the segments included in said set of segments representing a unique path in the parse tree; and a processor module to: determine the total number of documents included in said set of documents that include said first segment; determine the percentage of said documents included in said set of documents that include said first segment based on said determined total number and the total number of documents included in said set of documents; determine whether said determined percentage meets or exceeds a threshold; and flag said first segment for search index exclusion in response to a determination that said determined percentage meets or exceeds the threshold. | 10. A system for automatically outputting semantically significant text from a markup language document, comprising: a data store storing a set of markup language documents, the set of documents including a first markup language document; a parser module to parse the first markup language document to produce a parse tree; a segmenter module to segment the parse tree into a set of segments including a first segment each of the segments included in said set of segments representing a unique path in the parse tree; and a processor module to: determine the total number of documents included in said set of documents that include said first segment; determine the percentage of said documents included in said set of documents that include said first segment based on said determined total number and the total number of documents included in said set of documents; determine whether said determined percentage meets or exceeds a threshold; and flag said first segment for search index exclusion in response to a determination that said determined percentage meets or exceeds the threshold. 16. The system according to claim 10 , wherein the threshold comprises a specified minimum frequency occurrence of the one or more segments. | 0.625668 |
8,412,599 | 1 | 8 | 1. A method of approving timesheets using an approval workflow engine, the method comprising: generating, with one or more processors associated with one or more computer systems, information configured to display a user interface with at least one or more input fields associated with one or more stages for workflows for processing timesheets, one or more input fields associated with one or more paths in each of the one or more stages, and one or more input fields for each step of each path in each of the one or more stages; receiving, at the one or more computer systems, information via the user interface specifying a set of timesheet approval rules for at least one path of at least one stage of a workflow for processing timesheets, each timesheet approval rule in the set of timesheet approval rules identifying one or more timesheet attributes and specifying one or more conditions that need to be satisfied by timesheet information for the timesheet approval rule to apply to a timesheet represented by the timesheet information; storing the set of timesheet approval rules in a database associated with the one or more computer systems; receiving, at the one or more computer systems, information representing a timesheet, wherein the information representing the timesheet includes a plurality of timesheet attributes and corresponding attribute values; applying, with one or more processors associated with the one or more computer systems, one or more timesheet approval rules in the set of stored timesheet approval rules to the information representing the timesheet to determine whether the one or more timesheet approval rules are satisfied by the corresponding attribute values of the plurality of timesheet attributes; and generating, with the one or more processors associated with the one or more computer systems, one or more approval notifications to one or more approvers or reviewers based on application of the timesheet approval rules. | 1. A method of approving timesheets using an approval workflow engine, the method comprising: generating, with one or more processors associated with one or more computer systems, information configured to display a user interface with at least one or more input fields associated with one or more stages for workflows for processing timesheets, one or more input fields associated with one or more paths in each of the one or more stages, and one or more input fields for each step of each path in each of the one or more stages; receiving, at the one or more computer systems, information via the user interface specifying a set of timesheet approval rules for at least one path of at least one stage of a workflow for processing timesheets, each timesheet approval rule in the set of timesheet approval rules identifying one or more timesheet attributes and specifying one or more conditions that need to be satisfied by timesheet information for the timesheet approval rule to apply to a timesheet represented by the timesheet information; storing the set of timesheet approval rules in a database associated with the one or more computer systems; receiving, at the one or more computer systems, information representing a timesheet, wherein the information representing the timesheet includes a plurality of timesheet attributes and corresponding attribute values; applying, with one or more processors associated with the one or more computer systems, one or more timesheet approval rules in the set of stored timesheet approval rules to the information representing the timesheet to determine whether the one or more timesheet approval rules are satisfied by the corresponding attribute values of the plurality of timesheet attributes; and generating, with the one or more processors associated with the one or more computer systems, one or more approval notifications to one or more approvers or reviewers based on application of the timesheet approval rules. 8. The method of claim 1 , further comprising transmitting, using the one or more computer systems, the one or more notifications to the one or more approvers or reviewers via email. | 0.662963 |
8,510,100 | 2 | 7 | 2. The method of claim 1 , further comprising: presenting a first text-based category in the text-based interface having various color selections for receiving a color to be modified in the document from the user; presenting a second text-based category in the text-based interface having selections for receiving a magnitude of the image modification or a resultant image modification; presenting a third text-based category in the text-based interface having selections different from the second text-based category for receiving the magnitude or the resultant image modification; receiving a selection respectively from the first, second and third text-based category; and compiling and presenting the human readable sentence in a window of the text-based interface representing the image modification while the modification is displayed in the image. | 2. The method of claim 1 , further comprising: presenting a first text-based category in the text-based interface having various color selections for receiving a color to be modified in the document from the user; presenting a second text-based category in the text-based interface having selections for receiving a magnitude of the image modification or a resultant image modification; presenting a third text-based category in the text-based interface having selections different from the second text-based category for receiving the magnitude or the resultant image modification; receiving a selection respectively from the first, second and third text-based category; and compiling and presenting the human readable sentence in a window of the text-based interface representing the image modification while the modification is displayed in the image. 7. The method of claim 2 , wherein the first text-based category comprises a first portion of the human readable sentence, the second text-based category comprises a second portion of the human readable sentence, and the third text-based category comprises a third portion of the human readable sentence. | 0.858341 |
9,613,265 | 1 | 3 | 1. A method for capturing a document by a mobile terminal apparatus, said method comprising: obtaining, by a document capturing device embodied on the mobile terminal apparatus, a two-dimensional image of the document; the document capturing device performing edge detection within the two-dimensional image to identify edges of the document; the document capturing device determining angles between detected edges; the document capturing device calculating, based on the detected edges and the angles determined, a three-dimensional position of the document relative to a position of the mobile terminal apparatus; the document capturing device calculating correction information to correct, by relative movement, the three-dimensional position of the document relative to the position of the mobile terminal apparatus; the document capturing device deriving first guidance information from the correction information; the document capturing device providing the first guidance information to a user of the mobile terminal apparatus, prompting the user to perform the relative movement such that the three-dimensional position of the document is correct relative to the position of the mobile terminal apparatus; and the document capturing device capturing the document. | 1. A method for capturing a document by a mobile terminal apparatus, said method comprising: obtaining, by a document capturing device embodied on the mobile terminal apparatus, a two-dimensional image of the document; the document capturing device performing edge detection within the two-dimensional image to identify edges of the document; the document capturing device determining angles between detected edges; the document capturing device calculating, based on the detected edges and the angles determined, a three-dimensional position of the document relative to a position of the mobile terminal apparatus; the document capturing device calculating correction information to correct, by relative movement, the three-dimensional position of the document relative to the position of the mobile terminal apparatus; the document capturing device deriving first guidance information from the correction information; the document capturing device providing the first guidance information to a user of the mobile terminal apparatus, prompting the user to perform the relative movement such that the three-dimensional position of the document is correct relative to the position of the mobile terminal apparatus; and the document capturing device capturing the document. 3. The method of claim 1 , further comprising: calculating, based on the correction information, an amount of the relative movement needed to correct the three-dimensional position of the document relative to the position of the mobile terminal apparatus; deriving second guidance information including the first guidance information and the amount of the relative movement needed to correct the three-dimensional position of the document relative to the position of the mobile terminal apparatus; and providing the second guidance information to the user of the mobile terminal apparatus, prompting the user to perform the amount of the relative movement. | 0.5 |
8,095,371 | 1 | 5 | 1. A method for providing voice responses to spoken input items received from a user during a session between the user and a voice response system, comprising: providing computer recognition of spoken input items; providing system responses to spoken input items; storing, in a dialog history log, a record of recognized spoken input items and system responses thereto, said record representing a dialog history; responsive to a determination that the system cannot provide a valid system response to spoken input items, using a dialog state determination model to determine the current state of the dialog with the user based on the dialog history log and a dialog state diagram definition file defining each expected dialog state for the session; forwarding the determined current dialog state to a visual information display remote from the user for use by a human operator other than the user; and forwarding a dialog state diagram including a representation of each dialog state defined by the dialog state diagram definition file, including at least one dialog state, other than a transition between dialog states, not yet entered during the session, to the visual information display for use by the human operator. | 1. A method for providing voice responses to spoken input items received from a user during a session between the user and a voice response system, comprising: providing computer recognition of spoken input items; providing system responses to spoken input items; storing, in a dialog history log, a record of recognized spoken input items and system responses thereto, said record representing a dialog history; responsive to a determination that the system cannot provide a valid system response to spoken input items, using a dialog state determination model to determine the current state of the dialog with the user based on the dialog history log and a dialog state diagram definition file defining each expected dialog state for the session; forwarding the determined current dialog state to a visual information display remote from the user for use by a human operator other than the user; and forwarding a dialog state diagram including a representation of each dialog state defined by the dialog state diagram definition file, including at least one dialog state, other than a transition between dialog states, not yet entered during the session, to the visual information display for use by the human operator. 5. The method according to claim 1 , wherein the method further comprises steps of: calculating the reliability of an item entered by the user by taking into account an input history; and presenting the item on the visual information display in a manner dependent on the calculated reliability. | 0.722117 |
8,495,163 | 9 | 12 | 9. A system for notifying one or more users of information, the system comprising: a processor; a memory for storing instructions that when executed cause the processor to: building subscribable objects to provide to one or more registered recipients, wherein the registered recipients register their interests with a subscription server through a subscription portal that enable registered recipients to create, modify, and delete interests, wherein each of the subscribable objects is built based upon one or more predefined templates, and wherein each the predefined templates identifies required attributes and optional attributes corresponding to roles assigned to the recipients; receive, at a subscription server, a notification request, wherein the notification request includes a subscribable object and a notification; identify, at the subscription server, at least one recipient of the notification; creating, at the subscription server, a communication flow expression for the notification request, wherein the communication flow expression comprises an identifier of the at least one recipient and at least one condition for a transmission of the notification; matching the subscribable object of the notification with at least one subscribable object of a subscription, wherein the at least one registered recipient is assigned to at least one role, wherein the at least one role identifies at least one privilege, and wherein the at least one privilege permits the at least one role to subscribe to the at least one subscribable object; and transmitting, from the subscription server, the communication flow expression and the notification request to a notification and response system, wherein the notification and response system executes the communication flow expression. | 9. A system for notifying one or more users of information, the system comprising: a processor; a memory for storing instructions that when executed cause the processor to: building subscribable objects to provide to one or more registered recipients, wherein the registered recipients register their interests with a subscription server through a subscription portal that enable registered recipients to create, modify, and delete interests, wherein each of the subscribable objects is built based upon one or more predefined templates, and wherein each the predefined templates identifies required attributes and optional attributes corresponding to roles assigned to the recipients; receive, at a subscription server, a notification request, wherein the notification request includes a subscribable object and a notification; identify, at the subscription server, at least one recipient of the notification; creating, at the subscription server, a communication flow expression for the notification request, wherein the communication flow expression comprises an identifier of the at least one recipient and at least one condition for a transmission of the notification; matching the subscribable object of the notification with at least one subscribable object of a subscription, wherein the at least one registered recipient is assigned to at least one role, wherein the at least one role identifies at least one privilege, and wherein the at least one privilege permits the at least one role to subscribe to the at least one subscribable object; and transmitting, from the subscription server, the communication flow expression and the notification request to a notification and response system, wherein the notification and response system executes the communication flow expression. 12. The system of claim 9 , wherein the notification is transmitted if a sender of the notification request has privileges that permit the sender to notify a first recipient. | 0.571429 |
9,525,953 | 14 | 15 | 14. The apparatus as recited in claim 10 , wherein means for modulating comprises filter means and gender separation means cooperatively modifying the announcement in the languages to distinguish the announcements from each other. | 14. The apparatus as recited in claim 10 , wherein means for modulating comprises filter means and gender separation means cooperatively modifying the announcement in the languages to distinguish the announcements from each other. 15. The apparatus as recited in claim 14 , where filter means comprises a low-pass filter and a high-pass filter and gender separation means comprises a first gender voice and a second gender voice; and wherein one of the announcements in a first language is modified by the low-pass filter and the first gender voice and the announcement in the other of the languages is modified by the high-pass filter and the second gender voice. | 0.5 |
9,819,618 | 1 | 2 | 1. A method comprising: receiving a query by a computing device; determining a plurality of discussion groups that are relevant to the query by the computing device, wherein each discussion group is associated with a plurality of messages and each message is associated with an author; for each discussion group of the plurality of discussion groups, determining an authority score for each author associated with a message of the discussion group by the computing device; for each author associated with a message, determining a preference score for the author for each discussion group of the plurality of discussion groups by the computing device, wherein determining the preference score comprises determining the preference score based on a proportion of a number of occurrences of the discussion group that the author participated in to a total number of occurrences of the plurality of discussion groups that the author participated in; and ranking the discussion groups of the plurality of discussion groups using the preference scores and the authority scores by the computing device, wherein using the preference scores and the authority scores comprises generating a stationary distribution of a Markov process for the query and the discussion groups using the preference scores and the authority scores, and wherein ranking the discussion groups comprises ranking the discussion groups using the generated stationary distribution. | 1. A method comprising: receiving a query by a computing device; determining a plurality of discussion groups that are relevant to the query by the computing device, wherein each discussion group is associated with a plurality of messages and each message is associated with an author; for each discussion group of the plurality of discussion groups, determining an authority score for each author associated with a message of the discussion group by the computing device; for each author associated with a message, determining a preference score for the author for each discussion group of the plurality of discussion groups by the computing device, wherein determining the preference score comprises determining the preference score based on a proportion of a number of occurrences of the discussion group that the author participated in to a total number of occurrences of the plurality of discussion groups that the author participated in; and ranking the discussion groups of the plurality of discussion groups using the preference scores and the authority scores by the computing device, wherein using the preference scores and the authority scores comprises generating a stationary distribution of a Markov process for the query and the discussion groups using the preference scores and the authority scores, and wherein ranking the discussion groups comprises ranking the discussion groups using the generated stationary distribution. 2. The method of claim 1 , further comprising providing the ranked discussion groups in response to the query. | 0.836795 |
9,442,899 | 11 | 13 | 11. A text data embedding method to be implemented by an image forming apparatus, the text data embedding method comprising: obtaining an image file by document scanning; obtaining a text string from each line of text by performing character recognition on the image file, wherein each text string respectively corresponds to one line of text in the image file; splitting each text string into a plurality of short text strings in accordance with a predetermined rule, wherein at least one of the plurality of short text strings which form one text string corresponding to one line of text in the image file comprises a plurality of characters; determining a uniform font size for each text string such that the plurality of short text strings, which form the text string and which include the at least one short text string comprising the plurality of characters, have the same uniform font size; determining an x-axis position for each of the short text strings to be embedded in the image file, based on x-coordinates of characters at a forefront of the respective short text strings, the short text strings including the at least one short text string comprising the plurality of characters, wherein an x-axis of each short text string is aligned along forward and backward reading directions; and embedding text data of the short text strings in the image file at the respective determined x-axis positions in the determined uniform font size for the entire text string. | 11. A text data embedding method to be implemented by an image forming apparatus, the text data embedding method comprising: obtaining an image file by document scanning; obtaining a text string from each line of text by performing character recognition on the image file, wherein each text string respectively corresponds to one line of text in the image file; splitting each text string into a plurality of short text strings in accordance with a predetermined rule, wherein at least one of the plurality of short text strings which form one text string corresponding to one line of text in the image file comprises a plurality of characters; determining a uniform font size for each text string such that the plurality of short text strings, which form the text string and which include the at least one short text string comprising the plurality of characters, have the same uniform font size; determining an x-axis position for each of the short text strings to be embedded in the image file, based on x-coordinates of characters at a forefront of the respective short text strings, the short text strings including the at least one short text string comprising the plurality of characters, wherein an x-axis of each short text string is aligned along forward and backward reading directions; and embedding text data of the short text strings in the image file at the respective determined x-axis positions in the determined uniform font size for the entire text string. 13. The text data embedding method as recited in claim 11 , wherein the uniform font size for the entire text string is defined as any one of the following: (1) a greatest height among heights of the characters in the text string; (2) a smallest height among the heights of the characters in the text string; and (3) an average height of the characters in the text string. | 0.762148 |
7,610,194 | 15 | 16 | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. 16. The apparatus of claim 15 , wherein said frequency count is assigned to said selected word if said selected word is in a non first order position in said list and is selected for a first time. | 0.730028 |
9,864,782 | 10 | 14 | 10. A system for identifying a desired phrase, the system comprising: a controller; a memory coupled to the controller, wherein the memory is configured to store program instructions executable by the controller; wherein in response to executing the program instructions, the controller is configured to: receive user-defined criteria through a user interface, wherein the user-defined criteria includes a rhyme type, wherein the rhyme type is selected from the group consisting of perfect, additive, family, subtractive, assonance, and consonance; determine a stress pattern associated with the user-defined criteria, wherein the stress pattern indicates a relative stress of each syllable of the user-defined criteria; access a database including a plurality of phrases, wherein each phrase includes at least one word, wherein each phrase is associated with a stress pattern; select a matching phrase from the plurality of phrases within the database, wherein the matching phrase is associated with a stress pattern that matches the received user-defined criteria; and display the matching phrase on the user interface. | 10. A system for identifying a desired phrase, the system comprising: a controller; a memory coupled to the controller, wherein the memory is configured to store program instructions executable by the controller; wherein in response to executing the program instructions, the controller is configured to: receive user-defined criteria through a user interface, wherein the user-defined criteria includes a rhyme type, wherein the rhyme type is selected from the group consisting of perfect, additive, family, subtractive, assonance, and consonance; determine a stress pattern associated with the user-defined criteria, wherein the stress pattern indicates a relative stress of each syllable of the user-defined criteria; access a database including a plurality of phrases, wherein each phrase includes at least one word, wherein each phrase is associated with a stress pattern; select a matching phrase from the plurality of phrases within the database, wherein the matching phrase is associated with a stress pattern that matches the received user-defined criteria; and display the matching phrase on the user interface. 14. The system of claim 10 wherein the controller is configured to: access a plurality of phrase sources each including a plurality of phrases, wherein each plurality of phrase includes at least one word; identify a stress pattern for each of the plurality of phrases; calculate a frequency of occurrence of each phrase in the plurality of phrases; and input the identified plurality of phrases, the associated frequency of each phrase, and the associated stress pattern of each phrase into the database. | 0.5 |
8,954,330 | 1 | 4 | 1. In a computing environment, a method performed at least in part on at least one processor, comprising, detecting symbolic activity between at least two users of a given environment, including receiving sets of input data corresponding to one or more input modalities, processing a model associated with context-dependent grammar for the given environment, using the model to interpret the symbolic activity within the sets of input data, and identifying one or more commands directed to a target output mechanism based on the symbolic activity. | 1. In a computing environment, a method performed at least in part on at least one processor, comprising, detecting symbolic activity between at least two users of a given environment, including receiving sets of input data corresponding to one or more input modalities, processing a model associated with context-dependent grammar for the given environment, using the model to interpret the symbolic activity within the sets of input data, and identifying one or more commands directed to a target output mechanism based on the symbolic activity. 4. The method of claim 1 further comprising generating feedback associated with executing the one or more commands using utility data. | 0.692661 |
8,312,025 | 2 | 9 | 2. The information processing apparatus according to claim 1 , further comprising an initial information creation device configured to create initial information from each of said meta information items included in said sorted meta information based on said predetermined conditions, before adding the created initial information to each of said meta information items included in said sorted meta information, thereby creating automatically said sorted meta information furnished with said initial information. | 2. The information processing apparatus according to claim 1 , further comprising an initial information creation device configured to create initial information from each of said meta information items included in said sorted meta information based on said predetermined conditions, before adding the created initial information to each of said meta information items included in said sorted meta information, thereby creating automatically said sorted meta information furnished with said initial information. 9. The information processing apparatus according to claim 2 , further comprising an information output device configured to cause an external apparatus to display said sorted meta information furnished with said initial information created automatically. | 0.665354 |
9,122,710 | 15 | 16 | 15. The apparatus of claim 14 , wherein the operations further comprise: determining whether the analysis of the content data includes a source-specific pattern analysis algorithm; in an instance in which the analysis includes the source-specific pattern analysis algorithm, generating a source-specific representation of the new business reference that is included in the content data; and updating the source-specific pattern analysis algorithm using the source-specific representation. | 15. The apparatus of claim 14 , wherein the operations further comprise: determining whether the analysis of the content data includes a source-specific pattern analysis algorithm; in an instance in which the analysis includes the source-specific pattern analysis algorithm, generating a source-specific representation of the new business reference that is included in the content data; and updating the source-specific pattern analysis algorithm using the source-specific representation. 16. The apparatus of claim 15 , wherein the source-specific pattern analysis algorithm is a trainable pattern recognition algorithm, and wherein updating the source-specific pattern analysis algorithm using the source-specific representation of the new business reference comprises: updating a training data set using the source-specific representation of the new business reference; and updating the trainable pattern recognition algorithm using the updated training data set. | 0.5 |
8,682,666 | 1 | 7 | 1. A computer implemented method of analyzing speech utterances of a speaker in a given situation and context and determining behavioral, psychological and speech style characteristics of the speaker in the given situation, said computer implemented method comprising: creating a speech parameters reference database for classifying speech utterances according to various behavioral, psychological and speech styles characteristics, wherein the creating a speech parameters reference database for classifying speech utterances comprises: selecting manually a certain speaking context; selecting manually the behavioral, psychological and speech styles characteristics to be analyzed in the selected context; obtaining a plurality of speech utterances of people in the selected context; grouping manually the speech utterances into groups representing similar behavioral, psychological and speech styles characteristics; pre-processing each of the speech utterances in said groups of utterances representing similar behavioral, psychological and speech styles characteristics, into silent and active speech segments; dividing the active speech segments into strings of equal length blocks, wherein said blocks having primary speech parameters including pitch and amplitude parameters; deriving a plurality of secondary speech parameters from said primary parameters; and determining the unique secondary speech parameters, parameter combinations and parameters' values that are common to each group of utterances and represent the typical behavioral, psychological or speech styles characteristics of each group; obtaining speech utterances of a speaker in a specific situation and context; pre-processing the obtained utterances into silent and active speech segments and dividing the active speech segments into strings of equal length blocks, said blocks having primary speech parameters including pitch and amplitude parameters; and deriving a plurality of secondary speech parameters from said primary parameters; calculating speaker's unique speech parameters, parameters combinations and parameters' values representative of situational behavioral, psychological and speech styles characteristics, from said secondary parameters in the speech utterance; determining and scoring the situational behavioral, psychological and speech style characteristics in the speech utterance by comparing the calculated parameters with the pre-defined reference database of speech parameters; outputting the determined and scored results, wherein derived plurality of secondary speech parameters includes at least one of: average pause length, sum of pauses per time unit, average length of short silences, sum of short silences pertime unit, average length of equal pitch segments, sum of equal pitch segments pertime unit, average length of rising pitch segments, sum of rising pitch segments pertime unit, average length of falling pitch segments, sum of falling pitch segments pertime unit, average amplitude dispersion within equal pitch segments, average amplitude dispersion within rising pitch segments, average amplitude dispersion within falling pitch segments, pitch variance and range pertime unit, average pitch slope pertime unit, patterns of spectral shape and spectral envelope of the speech signal over time, patterns of sequential order of rising, falling and equal pitch trends over time. | 1. A computer implemented method of analyzing speech utterances of a speaker in a given situation and context and determining behavioral, psychological and speech style characteristics of the speaker in the given situation, said computer implemented method comprising: creating a speech parameters reference database for classifying speech utterances according to various behavioral, psychological and speech styles characteristics, wherein the creating a speech parameters reference database for classifying speech utterances comprises: selecting manually a certain speaking context; selecting manually the behavioral, psychological and speech styles characteristics to be analyzed in the selected context; obtaining a plurality of speech utterances of people in the selected context; grouping manually the speech utterances into groups representing similar behavioral, psychological and speech styles characteristics; pre-processing each of the speech utterances in said groups of utterances representing similar behavioral, psychological and speech styles characteristics, into silent and active speech segments; dividing the active speech segments into strings of equal length blocks, wherein said blocks having primary speech parameters including pitch and amplitude parameters; deriving a plurality of secondary speech parameters from said primary parameters; and determining the unique secondary speech parameters, parameter combinations and parameters' values that are common to each group of utterances and represent the typical behavioral, psychological or speech styles characteristics of each group; obtaining speech utterances of a speaker in a specific situation and context; pre-processing the obtained utterances into silent and active speech segments and dividing the active speech segments into strings of equal length blocks, said blocks having primary speech parameters including pitch and amplitude parameters; and deriving a plurality of secondary speech parameters from said primary parameters; calculating speaker's unique speech parameters, parameters combinations and parameters' values representative of situational behavioral, psychological and speech styles characteristics, from said secondary parameters in the speech utterance; determining and scoring the situational behavioral, psychological and speech style characteristics in the speech utterance by comparing the calculated parameters with the pre-defined reference database of speech parameters; outputting the determined and scored results, wherein derived plurality of secondary speech parameters includes at least one of: average pause length, sum of pauses per time unit, average length of short silences, sum of short silences pertime unit, average length of equal pitch segments, sum of equal pitch segments pertime unit, average length of rising pitch segments, sum of rising pitch segments pertime unit, average length of falling pitch segments, sum of falling pitch segments pertime unit, average amplitude dispersion within equal pitch segments, average amplitude dispersion within rising pitch segments, average amplitude dispersion within falling pitch segments, pitch variance and range pertime unit, average pitch slope pertime unit, patterns of spectral shape and spectral envelope of the speech signal over time, patterns of sequential order of rising, falling and equal pitch trends over time. 7. The method of claim 1 , further comprising providing learning-system features by using ongoing analysis of speakers' behavioral, psychological and speech style characteristics for the purpose of improving the speech parameters reference database and the classifying process. | 0.705319 |
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