patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|---|---|---|
9,786,326 | 14 | 15 | 14. A method for playing multimedia data, comprising: receiving, by an electronic device, multimedia data for play back and storing the multimedia data in a multimedia data buffer, wherein the multimedia data comprises audio data; playing back the multimedia data from the multimedia data buffer by the electronic device; pausing play back of the multimedia data by the electronic device at a pause position; extracting, by the electronic device, a target section of the audio data preceding the pause position, the target section being a specified duration in length and comprising a plurality of semantic statements; identifying a respective time interval between each pair of adjacent audio signals in the target section; determining, for each pair of adjacent audio signals, whether the respective time interval exceeds a first predefined time interval; when the respective time interval exceeds the first predefined time interval, identifying the respective time interval as comprising a beginning of a semantic statement; selecting a position within one of the respective time intervals comprising a beginning of a semantic statement; setting the selected position as a resume play back position; and resuming play back of the multimedia data by the electronic device from the resume play back position when a resume condition has been met. | 14. A method for playing multimedia data, comprising: receiving, by an electronic device, multimedia data for play back and storing the multimedia data in a multimedia data buffer, wherein the multimedia data comprises audio data; playing back the multimedia data from the multimedia data buffer by the electronic device; pausing play back of the multimedia data by the electronic device at a pause position; extracting, by the electronic device, a target section of the audio data preceding the pause position, the target section being a specified duration in length and comprising a plurality of semantic statements; identifying a respective time interval between each pair of adjacent audio signals in the target section; determining, for each pair of adjacent audio signals, whether the respective time interval exceeds a first predefined time interval; when the respective time interval exceeds the first predefined time interval, identifying the respective time interval as comprising a beginning of a semantic statement; selecting a position within one of the respective time intervals comprising a beginning of a semantic statement; setting the selected position as a resume play back position; and resuming play back of the multimedia data by the electronic device from the resume play back position when a resume condition has been met. 15. The method of claim 14 , wherein the one of the respective time intervals is the respective time interval that immediately precedes the pause position. | 0.627404 |
6,082,775 | 1 | 5 | 1. A counterfeit-resistant document, comprising: a substrate; and a validation mark disposed on said substrate, said validation mark comprising a unique chemical signature specific to an identifying aspect of said document. | 1. A counterfeit-resistant document, comprising: a substrate; and a validation mark disposed on said substrate, said validation mark comprising a unique chemical signature specific to an identifying aspect of said document. 5. The counterfeit-resistant document of claim 1, wherein said unique chemical signature comprises a unique molecular code. | 0.519531 |
8,032,448 | 21 | 28 | 21. A method for implementation by one or more data processors comprising: receiving, by at least one data processor, data characterizing a transaction of transactions between a consumer and merchant; linking, by at least one data processor, the merchant with one of a plurality of pre-defined merchant clusters, the merchant clusters defined by a frequency at which merchants historically shared customers, the merchant clusters being generated by: selecting a plurality of high categorical information elements from the transactions, linking each high categorical information element with a context vector in a vector space such that high categorical information elements that co-occur in the transactions have context vectors that are similarly oriented in the vector space, the co-occurrence representing that context vectors corresponding to the co-occurring high categorical information elements are less than a predetermined distance apart in the vector space for more than a predetermined number of transactions, and clustering the context vectors of the high categorical information elements into a number of merchant clusters that is less than number of high categorical information elements, each merchant cluster being a low categorical information cluster; determining, by at least one data processor, an affinity of the customer to an associated merchant cluster; generating, by at least one data processor, a risk score using at least one predictive model and at least the determined affinity; and initiating, by at least one data processor, provision of data characterizing the generated score. | 21. A method for implementation by one or more data processors comprising: receiving, by at least one data processor, data characterizing a transaction of transactions between a consumer and merchant; linking, by at least one data processor, the merchant with one of a plurality of pre-defined merchant clusters, the merchant clusters defined by a frequency at which merchants historically shared customers, the merchant clusters being generated by: selecting a plurality of high categorical information elements from the transactions, linking each high categorical information element with a context vector in a vector space such that high categorical information elements that co-occur in the transactions have context vectors that are similarly oriented in the vector space, the co-occurrence representing that context vectors corresponding to the co-occurring high categorical information elements are less than a predetermined distance apart in the vector space for more than a predetermined number of transactions, and clustering the context vectors of the high categorical information elements into a number of merchant clusters that is less than number of high categorical information elements, each merchant cluster being a low categorical information cluster; determining, by at least one data processor, an affinity of the customer to an associated merchant cluster; generating, by at least one data processor, a risk score using at least one predictive model and at least the determined affinity; and initiating, by at least one data processor, provision of data characterizing the generated score. 28. A method as in claim 21 , wherein the at least one predictive model further utilizes a variable representing historical transactions that were deemed to have been fraudulent among the merchants in the associated merchant cluster. | 0.579422 |
7,747,608 | 17 | 23 | 17. A database system comprising: a database in communication with a network; an interface in communication with the network; a memory; and a processor in communication with the memory, the interface, and the database; wherein the processor: forms at least one query of a first query language selected from a set of query languages and based at least in part on a set of constraints of the first query language to obtain at least part of desired information; forms at least one query of at least one additional query language from the set of query languages and based at least in part on a set of constraints of the at least one additional query language to obtain at least part of the desired information; and separates input members from calculated members, wherein the input members are queried with the least one query in the first query language and the calculated members are queried with the at least one query in the at least one additional query language; wherein the at least one query of the first query language and the at least one query of the at least one additional language obtain at least all of the desired information. | 17. A database system comprising: a database in communication with a network; an interface in communication with the network; a memory; and a processor in communication with the memory, the interface, and the database; wherein the processor: forms at least one query of a first query language selected from a set of query languages and based at least in part on a set of constraints of the first query language to obtain at least part of desired information; forms at least one query of at least one additional query language from the set of query languages and based at least in part on a set of constraints of the at least one additional query language to obtain at least part of the desired information; and separates input members from calculated members, wherein the input members are queried with the least one query in the first query language and the calculated members are queried with the at least one query in the at least one additional query language; wherein the at least one query of the first query language and the at least one query of the at least one additional language obtain at least all of the desired information. 23. The database system of claim 17 , wherein the first query language is SQL and the at least one additional query language is MDX. | 0.877551 |
6,058,387 | 10 | 11 | 10. The system defined in claim 1, wherein the model object stands as a proxy for a computer model. | 10. The system defined in claim 1, wherein the model object stands as a proxy for a computer model. 11. The system defined in claim 10, wherein the model object comprises a formal definition of the computer model in terms of the at least one process object and the location of executable computer model code. | 0.5 |
8,949,340 | 1 | 35 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for identifying content from one or more of a plurality of data sources; computer code for transforming the content into one or more messages; computer code for delivering a first message of the one or more messages to a handset for presentation; computer code for managing a message flow based on user responses, the message flow determining a next message based on a user response to a previous message; computer code for receiving a delivery mode selection of at least two delivery modes, the at least two delivery modes including a first delivery mode in which at least a first portion of the content is to be delivered to a user and a second delivery mode in which at least a second portion of the content is to be delivered to the user, at least one of the two delivery modes including a short message service delivery mode involving a short message service; computer code for delivering the at least first portion of the content to the user utilizing the first delivery mode; computer code for delivering the at least second portion of the content to the user utilizing the second delivery mode; computer code for receiving a command sequence including a first constant portion and a second variable portion, utilizing the short message service; computer code for delivering a response to the command sequence utilizing the short message service, the response including response information identified as a function of both the first constant portion and second variable portion of the command sequence; computer code for delivering a content menu utilizing the short message service in the form of a menu short message service message including: a first menu selection option indicating a first menu short form command including a first one or more characters associated with a first content, a second menu selection option indicating a second menu short form command including a second one or more characters associated with a second content, and a third menu selection option indicating a third menu short form command including a third one or more characters associated with a third content; computer code for receiving the first menu short form command associated with the first content; computer code for receiving the second menu short form command associated with the second content; computer code for receiving the third menu short form command associated with the third content; computer code for, in response to the receipt of the first menu short form command associated with the first content, delivering the first content; computer code for, in response to the receipt of the second menu short form command associated with the second content, delivering the second content; and computer code for, in response to the receipt of the third menu short form command associated with the third content, delivering the third content. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for identifying content from one or more of a plurality of data sources; computer code for transforming the content into one or more messages; computer code for delivering a first message of the one or more messages to a handset for presentation; computer code for managing a message flow based on user responses, the message flow determining a next message based on a user response to a previous message; computer code for receiving a delivery mode selection of at least two delivery modes, the at least two delivery modes including a first delivery mode in which at least a first portion of the content is to be delivered to a user and a second delivery mode in which at least a second portion of the content is to be delivered to the user, at least one of the two delivery modes including a short message service delivery mode involving a short message service; computer code for delivering the at least first portion of the content to the user utilizing the first delivery mode; computer code for delivering the at least second portion of the content to the user utilizing the second delivery mode; computer code for receiving a command sequence including a first constant portion and a second variable portion, utilizing the short message service; computer code for delivering a response to the command sequence utilizing the short message service, the response including response information identified as a function of both the first constant portion and second variable portion of the command sequence; computer code for delivering a content menu utilizing the short message service in the form of a menu short message service message including: a first menu selection option indicating a first menu short form command including a first one or more characters associated with a first content, a second menu selection option indicating a second menu short form command including a second one or more characters associated with a second content, and a third menu selection option indicating a third menu short form command including a third one or more characters associated with a third content; computer code for receiving the first menu short form command associated with the first content; computer code for receiving the second menu short form command associated with the second content; computer code for receiving the third menu short form command associated with the third content; computer code for, in response to the receipt of the first menu short form command associated with the first content, delivering the first content; computer code for, in response to the receipt of the second menu short form command associated with the second content, delivering the second content; and computer code for, in response to the receipt of the third menu short form command associated with the third content, delivering the third content. 35. The computer program product of claim 1 , further comprising: computer code for identifying a type of the handset; and computer code for altering at least one aspect of at least one of the transforming or delivering, based on the type. | 0.898729 |
7,962,495 | 9 | 12 | 9. A data storage system, comprising: one or more processors; a data store; an ontology coupled to the data store and comprising a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; a parser coupled to the ontology and configured to receive input data and transform the input data into modified data to store in a property specified by one of the property types according to one or more parser definitions; wherein each of the object property types comprises one or more of the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform portions of first input data into modified input data that is to be stored in components of one of the object property types of the ontology for the data store. | 9. A data storage system, comprising: one or more processors; a data store; an ontology coupled to the data store and comprising a plurality of data object types and a plurality of object property types; wherein each object property type, of the plurality of object property types, includes a data type of data that is associated with said each object property type; a parser coupled to the ontology and configured to receive input data and transform the input data into modified data to store in a property specified by one of the property types according to one or more parser definitions; wherein each of the object property types comprises one or more of the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform portions of first input data into modified input data that is to be stored in components of one of the object property types of the ontology for the data store. 12. The system of claim 9 , wherein the one or more parser definitions comprise one or more transformation expressions, wherein each of the transformation expressions comprises one or more syntactic patterns and a property type identifier associated with each of the syntactic patterns. | 0.806757 |
10,152,543 | 1 | 8 | 1. A machine-implemented method, comprising: identifying content items provided in response to a query including a set of search terms associated with a topic; receiving an indication of selection of at least one content item of the content items, wherein the selection of the at least one content item provides access to the at least one content item; associating, in response to receiving the indication, the set of search terms of the query with the topic of the selected at least one content item; analyzing the set of search terms based on the content items provided in response to the query as search results; selecting one or more terms from the set of search terms based on the analysis; generating a label from the selected one or more terms by restricting titles of the content items to be excluded from the label; and applying the label to the content items relating to the topic. | 1. A machine-implemented method, comprising: identifying content items provided in response to a query including a set of search terms associated with a topic; receiving an indication of selection of at least one content item of the content items, wherein the selection of the at least one content item provides access to the at least one content item; associating, in response to receiving the indication, the set of search terms of the query with the topic of the selected at least one content item; analyzing the set of search terms based on the content items provided in response to the query as search results; selecting one or more terms from the set of search terms based on the analysis; generating a label from the selected one or more terms by restricting titles of the content items to be excluded from the label; and applying the label to the content items relating to the topic. 8. The method of claim 1 , further comprising providing the label for display along with the content item relating to the topic. | 0.722944 |
8,260,772 | 1 | 6 | 1. A non-transitory computer readable storage medium, comprising executable instructions to: receive a selection of a first section of a website; add a report retrieval component to the selected first section of the website, the report retrieval component being a portable segment of code that is installed and executed within the selected first section of the website without access to source code of the website; receive a selection of a second section of the website; automatically extract, from the second selected section of the website, one or more keywords describing content on the second section of the website; search for reports corresponding to the one or more keywords, at least one report including information automatically retrieved from a data source by a report generation product, the report generation product structuring the information in accordance with a report schema that specifies the form in which the information is presented; retrieve additional information associated a user of the website comprising the user's role in an organization; filter the reports based on data access permissions associated with the user of the website and the retrieved additional information; and display a highly ranked report to supplement the data provided by the website, the highly ranked report comprising the reports that are ranked based on results of a query run by a web service, the query being associated with the one or more keywords. | 1. A non-transitory computer readable storage medium, comprising executable instructions to: receive a selection of a first section of a website; add a report retrieval component to the selected first section of the website, the report retrieval component being a portable segment of code that is installed and executed within the selected first section of the website without access to source code of the website; receive a selection of a second section of the website; automatically extract, from the second selected section of the website, one or more keywords describing content on the second section of the website; search for reports corresponding to the one or more keywords, at least one report including information automatically retrieved from a data source by a report generation product, the report generation product structuring the information in accordance with a report schema that specifies the form in which the information is presented; retrieve additional information associated a user of the website comprising the user's role in an organization; filter the reports based on data access permissions associated with the user of the website and the retrieved additional information; and display a highly ranked report to supplement the data provided by the website, the highly ranked report comprising the reports that are ranked based on results of a query run by a web service, the query being associated with the one or more keywords. 6. The computer readable storage medium of claim 1 , wherein a plurality of reports is displayed on the website. | 0.761702 |
9,798,785 | 18 | 20 | 18. The method of claim 1 , further comprising updating the preference information based on the external search result if a dynamic search preference of the search preference is set. | 18. The method of claim 1 , further comprising updating the preference information based on the external search result if a dynamic search preference of the search preference is set. 20. The method of claim 18 , wherein the updating of the preference information comprises: based on a priority reflection result with respect to a user preference according to a search response, adjusting a reflection weight value for priority reflection. | 0.503891 |
9,318,108 | 3 | 36 | 3. A non-transitory computer-readable medium for implementing an automated assistant on one or more computing devices, the computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: invoking the automated assistant; causing a first output to be displayed in a conversation interface of the automated assistant, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input. | 3. A non-transitory computer-readable medium for implementing an automated assistant on one or more computing devices, the computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: invoking the automated assistant; causing a first output to be displayed in a conversation interface of the automated assistant, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input. 36. The computer-readable medium of claim 3 , wherein one of the plurality of core competencies is searching for a restaurant. | 0.894825 |
8,631,386 | 1 | 8 | 1. A system for developing web services, comprising: a Design Time Framework including a code generator that receives a first set of configuration files from a user and generates source code artifacts in an object oriented programming language based on the received first set of configuration files, wherein the first set of configuration files comprises an XML schema file, an XML descriptor file, and an XML rule file, wherein the XML schema file comprises XML schema annotations specifying properties of fields in the XML schema file, wherein an output of the Design Time Framework results from a compiling of the source code artifacts in an object oriented programming language based on the XML schema file, and the output comprises binary objects in a binary format and having field properties specified by the XML schema annotations; an Object-Service Framework that receives a second set of configuration files from the user, wherein the Object-Service Framework comprises a set of pre-built runtime services, wherein each of the pre-built runtime services extends the Object-Service Framework and comprises binary code that was compiled before the compiling of the source code artifacts of the Design Time Framework in an object oriented programming language based on the XML schema file, wherein behaviors of the pre-built runtime services can be dynamically changed using the second set of configuration files, and wherein the Object Service Framework defines an application program interface (API) for each of the pre-built runtime services and wherein the pre-built runtime services interact with the source code artifacts of the Design Time Framework through the application program interface and wherein the pre-built runtime services extend the application program interface, and for CRUD services of the pre-built runtime services that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework to perform on a persistent database of the system at least one of create, retrieve, update, or delete instances of information structures, wherein information is passed between the CRUD services and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for security field services of the pre-built runtime services that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and obtains security policy types, security policy operations, and resource values in the second set of configuration files to control the access to the web service and fields of the web service, wherein information is passed between the security field services and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML marshall service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to create XML formatted data having a first XML format, wherein information is passed between the XML marshall service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML transformation service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework to transform the created XML formatted data having the first XML format to XML formatted data having a second XML format, different from the first XML format, wherein information is passed between the XML transformation service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML schema validation service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to validate and convert an input XML formatted data into an instance of the binary form of the Design Time Framework, wherein information is passed between the XML schema validation service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, and for a key value service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to validate and convert data formatted as name-value pair into an instance of the binary output form of the Design Time Framework, wherein information is passed between the a key value service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework; and a Run Time Framework, running on a machine including a processor, that comprises pre-built binary code, wherein in response to an incoming event for the web service, the Run Time Framework retrieves from the second set of configuration files a selection of the pre-built runtime services to be placed in a flow for the web service and an order in which the selected pre-built runtime services will be placed in the flow. | 1. A system for developing web services, comprising: a Design Time Framework including a code generator that receives a first set of configuration files from a user and generates source code artifacts in an object oriented programming language based on the received first set of configuration files, wherein the first set of configuration files comprises an XML schema file, an XML descriptor file, and an XML rule file, wherein the XML schema file comprises XML schema annotations specifying properties of fields in the XML schema file, wherein an output of the Design Time Framework results from a compiling of the source code artifacts in an object oriented programming language based on the XML schema file, and the output comprises binary objects in a binary format and having field properties specified by the XML schema annotations; an Object-Service Framework that receives a second set of configuration files from the user, wherein the Object-Service Framework comprises a set of pre-built runtime services, wherein each of the pre-built runtime services extends the Object-Service Framework and comprises binary code that was compiled before the compiling of the source code artifacts of the Design Time Framework in an object oriented programming language based on the XML schema file, wherein behaviors of the pre-built runtime services can be dynamically changed using the second set of configuration files, and wherein the Object Service Framework defines an application program interface (API) for each of the pre-built runtime services and wherein the pre-built runtime services interact with the source code artifacts of the Design Time Framework through the application program interface and wherein the pre-built runtime services extend the application program interface, and for CRUD services of the pre-built runtime services that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework to perform on a persistent database of the system at least one of create, retrieve, update, or delete instances of information structures, wherein information is passed between the CRUD services and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for security field services of the pre-built runtime services that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and obtains security policy types, security policy operations, and resource values in the second set of configuration files to control the access to the web service and fields of the web service, wherein information is passed between the security field services and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML marshall service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to create XML formatted data having a first XML format, wherein information is passed between the XML marshall service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML transformation service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework to transform the created XML formatted data having the first XML format to XML formatted data having a second XML format, different from the first XML format, wherein information is passed between the XML transformation service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, for an XML schema validation service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to validate and convert an input XML formatted data into an instance of the binary form of the Design Time Framework, wherein information is passed between the XML schema validation service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework, and for a key value service that extend the Object-Service Framework, the Object-Service Framework searches the output of the Design Time Framework and retrieves dynamic properties specified in the second set of configuration files to validate and convert data formatted as name-value pair into an instance of the binary output form of the Design Time Framework, wherein information is passed between the a key value service and source code artifacts of the Design Time Framework by way of the application program interface (API) of the Object Service Framework; and a Run Time Framework, running on a machine including a processor, that comprises pre-built binary code, wherein in response to an incoming event for the web service, the Run Time Framework retrieves from the second set of configuration files a selection of the pre-built runtime services to be placed in a flow for the web service and an order in which the selected pre-built runtime services will be placed in the flow. 8. The system of claim 1 wherein the web service is a first web service, the Object-Service Framework receives a third set of configuration files, different from the second set of configuration files, and the Run Time Framework generates a second web service, different from the first web service without alteration of the set of pre-built runtime services. | 0.629668 |
9,183,760 | 6 | 7 | 6. An apparatus for recognizing sign language using at least one electromyogram sensor and at least one gyro sensor, the apparatus comprising: a processor configured to store a set of Gaussian candidate models for a plurality of fingerspelling motions and to group the set of Gaussian candidate models into predetermined gyro groups; a signal receiving part configured to receive a first gyro measurement signal from at least one gyro sensor and a first electromyogram measurement signal from the at least one electromyogram sensor, wherein the at least one gyro sensor and the at least one electromyogram sensor are attached to a body of a subject, and wherein the first gyro measurement signal includes a first pitch rotation and a first roll rotation; a group determining part configured to determine a first gyro group which is in closest proximity to the first gyro measurement signal among the predetermined gyro groups; a model acquiring part configured to acquire a first Gaussian model for the first electromyogram measurement signal; and a sign language recognizing part configured to compare the first Gaussian model with the set of Gaussian candidate models in the first gyro group, and to recognize a first fingerspelling motion which corresponds to the first Gaussian candidate model. | 6. An apparatus for recognizing sign language using at least one electromyogram sensor and at least one gyro sensor, the apparatus comprising: a processor configured to store a set of Gaussian candidate models for a plurality of fingerspelling motions and to group the set of Gaussian candidate models into predetermined gyro groups; a signal receiving part configured to receive a first gyro measurement signal from at least one gyro sensor and a first electromyogram measurement signal from the at least one electromyogram sensor, wherein the at least one gyro sensor and the at least one electromyogram sensor are attached to a body of a subject, and wherein the first gyro measurement signal includes a first pitch rotation and a first roll rotation; a group determining part configured to determine a first gyro group which is in closest proximity to the first gyro measurement signal among the predetermined gyro groups; a model acquiring part configured to acquire a first Gaussian model for the first electromyogram measurement signal; and a sign language recognizing part configured to compare the first Gaussian model with the set of Gaussian candidate models in the first gyro group, and to recognize a first fingerspelling motion which corresponds to the first Gaussian candidate model. 7. The apparatus of claim 6 , wherein the apparatus further comprises a clustering part configured: to obtain a first rotational angle coordinate sample for each of the plurality of fingerspelling motions using roll and pitch rotation values acquired from the at least one gyro sensor; to measure a distance from a first central coordinate for each of the predetermined gyro groups with respect to the first rotational angle coordinate sample and to assign the first rotational angle coordinate sample to a group in closest proximity to the first rotational angle coordinate sample; to calculate a second central coordinate according to an average value of the first rotational angle coordinate sample and the first central coordinate; and to repeat the processes of the measuring and the calculating. | 0.5 |
7,509,406 | 32 | 37 | 32. The method of claim 24 , further comprising: determining whether the warning time has been reached; and in response to determining that the warning time has been reached, rendering a warning message. | 32. The method of claim 24 , further comprising: determining whether the warning time has been reached; and in response to determining that the warning time has been reached, rendering a warning message. 37. The computer program product of claim 32 , wherein the control logic further comprises computer readable program code means for causing the computer to identify an asset that serves as an entry point for the hosted application and launch at least one of help content and the hosted application based on the asset identified. | 0.732463 |
4,685,135 | 4 | 5 | 4. The system of claim 3 wherein said allophone rules processor means comprises a rules microprocessor. | 4. The system of claim 3 wherein said allophone rules processor means comprises a rules microprocessor. 5. The system of claim 4 wherein said allophone rule means has a plurality of allophonic code signals comprising a plurality of allophone rules arranged in respective character sets as determined by the character and the neighboring characters on each side thereof stored in a common section of said read-only-memory for each of the digital characters representative of printed data that may be input to the system. | 0.5 |
8,935,299 | 1 | 2 | 1. A computer-implemented method comprising: providing an interface by a social networking system to a page administrator, the interface comprising controls for administering a page in the social networking system; identifying a plurality of field objects added by page administrators to pages hosted by the social networking system and administered by the administrators; identifying field types of the added field objects, wherein at least one of the field types is the field type for a plurality of the field objects; identifying page types of the pages to which the field objects were added, wherein at least one of the page types is the page type for a plurality of the pages; determining, based on the identified field types and on the identified page types, a degree of association of a first field type with a first page type; determining that the degree of association of the first field type with the first page type is greater than a threshold degree of association, some pages of the first page type lacking fields of the first field type; determining, for a first page of the social network, that the first page lacks a field of the first field type; and responsive to determining that the degree of association of the first field type with the first page type is greater than the threshold degree of association, and that the first page lacks a field of the first type, initiating an addition of a field of the first field type to the first page without a request therefor from a first administrator of the first page. | 1. A computer-implemented method comprising: providing an interface by a social networking system to a page administrator, the interface comprising controls for administering a page in the social networking system; identifying a plurality of field objects added by page administrators to pages hosted by the social networking system and administered by the administrators; identifying field types of the added field objects, wherein at least one of the field types is the field type for a plurality of the field objects; identifying page types of the pages to which the field objects were added, wherein at least one of the page types is the page type for a plurality of the pages; determining, based on the identified field types and on the identified page types, a degree of association of a first field type with a first page type; determining that the degree of association of the first field type with the first page type is greater than a threshold degree of association, some pages of the first page type lacking fields of the first field type; determining, for a first page of the social network, that the first page lacks a field of the first field type; and responsive to determining that the degree of association of the first field type with the first page type is greater than the threshold degree of association, and that the first page lacks a field of the first type, initiating an addition of a field of the first field type to the first page without a request therefor from a first administrator of the first page. 2. The computer-implemented method of claim 1 , wherein initiating the addition comprises automatically adding a field of the first field type to the first page. | 0.865159 |
8,983,944 | 7 | 8 | 7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module. | 7. An apparatus for providing information about a main knowledge stream, the apparatus comprising: a storage module for storing information about a plurality of documents; an information process module for obtaining reference links representing reference relationships among reference documents for each of the documents from information about the documents stored in the storage module, defining one or more paths connecting the reference links for each of the plurality of documents, determining a longest path among the defined paths as a basic path for each of the plurality of documents, calculating probability values of the reference links by overlapping the determined basic paths, determining a first document from among the documents and an input reference link for the first document, performing a Markov chain model using a probability value of the input reference link, and calculating the information about the main knowledge stream for the first document using a result obtained by performing the Markov chain model; and an output module for providing the information about the main knowledge stream for the first document calculated by the information process module. 8. The apparatus according to claim 7 , wherein the information process module determines an output reference link for the first document based on the probability value of the input reference link using the Markov chain model, calculates an output reference link using the Markov chain model for a second document, which has the output reference link for the first document as an input reference link, and connects the calculated reference links to provide the information about the main knowledge stream. | 0.5 |
7,831,594 | 9 | 13 | 9. A computer-readable medium having computer-executable instructions for performing a method for utilizing historical query information to estimate a static execution time of database query: receiving a database query; accessing a prediction of query runtime tree built from historical query information; and processing said database query through said prediction of query runtime tree to estimate a static execution runtime of said database query based upon historical information pertaining to historical database queries similar to said database query, said processing comprising traversing said prediction of query runtime tree on the basis of at least one query feature associated with said database query, said traversing comprising determining a time range estimate of said static execution time based upon a similarity of said at least one query feature to a historical query feature shared by a grouping of historical database queries stored in an element of said prediction runtime query tree. | 9. A computer-readable medium having computer-executable instructions for performing a method for utilizing historical query information to estimate a static execution time of database query: receiving a database query; accessing a prediction of query runtime tree built from historical query information; and processing said database query through said prediction of query runtime tree to estimate a static execution runtime of said database query based upon historical information pertaining to historical database queries similar to said database query, said processing comprising traversing said prediction of query runtime tree on the basis of at least one query feature associated with said database query, said traversing comprising determining a time range estimate of said static execution time based upon a similarity of said at least one query feature to a historical query feature shared by a grouping of historical database queries stored in an element of said prediction runtime query tree. 13. The computer-readable medium of claim 9 , wherein said traversing said prediction of query runtime tree on the basis of at least one query feature associated with said database query comprises: utilizing a multiple linear regression function in a leaf element of said prediction of query runtime tree to determine said static execution time for said database query. | 0.501351 |
7,653,594 | 13 | 16 | 13. The system of claim 1 programmed to decide whether to offer a transaction incentive to said first consumer based upon said predictive data in said first predictive field for said first consumer. | 13. The system of claim 1 programmed to decide whether to offer a transaction incentive to said first consumer based upon said predictive data in said first predictive field for said first consumer. 16. The system of claim 13 wherein a term of said transaction incentive is purchase of a specified brand in said first correlated class. | 0.597633 |
9,658,824 | 3 | 4 | 3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item. | 3. A system, comprising: at least one computing device; and at least one application executable in the at least one computing device, wherein, when executed, the at least one application causes the at least one computing device to at least: obtain a plurality of customer review search queries from a plurality of users, the plurality of customer review search queries being obtained to search a collection of customer reviews for a specific item; extract a set of relevant topics for the specific item by analyzing the plurality of customer review search queries; and generate a user interface based at least in part on at least some of the set of relevant topics for the specific item. 4. The system of claim 3 , wherein, when executed, the at least one application further causes the at least one computing device to at least: extract a set of additional relevant topics directly from the collection of customer reviews for the specific item; and include the set of additional relevant topics into the set of relevant topics. | 0.715719 |
8,386,912 | 10 | 24 | 10. The method of claim 1 further comprising determining a predefined set of preferences; and storing the versions of the documents in accordance with the determined preferences. | 10. The method of claim 1 further comprising determining a predefined set of preferences; and storing the versions of the documents in accordance with the determined preferences. 24. The method of claim 10 wherein the set of preferences includes a preference for adding intellectual property protection to a document. | 0.708861 |
9,373,082 | 3 | 8 | 3. A method, comprising: in a processor, defining one or more measurable science inquiry skills; in a computer, measuring the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; providing to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; and providing to the subject person guidance on how to better conduct scientific inquiry, wherein the tracking model tracks the subject person's development of the one or more science inquiry skills over time and across one or more science topics or science domains, and the tracking utilizes at least one of a data-mining based model and a knowledge-engineering model. | 3. A method, comprising: in a processor, defining one or more measurable science inquiry skills; in a computer, measuring the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; providing to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; and providing to the subject person guidance on how to better conduct scientific inquiry, wherein the tracking model tracks the subject person's development of the one or more science inquiry skills over time and across one or more science topics or science domains, and the tracking utilizes at least one of a data-mining based model and a knowledge-engineering model. 8. The method of claim 3 , wherein the tracking uses at least one of the data-mining based model and the knowledge-engineering based model to aggregate information about the subject person and to provide at least one measurement or evaluation of the proficiency for the subject person in one or more science inquiry skills. | 0.5 |
9,898,526 | 1 | 6 | 1. A computer-implemented system for inclusion-based electronically stored information item cluster visual representation, comprising: a non-transitory computer readable storage medium comprising program code; and a computer processor configured coupled to the storage medium, wherein the processor is configured to execute the program code to perform steps to: maintain a set of reference electronically stored information items; select from the set a subset of the electronically stored information items, each of the reference electronically stored information items in the subset associated with a classification code, each of the classification codes associated with a visual representation different from the visual representations of the remaining classification codes; combine the subset with a set of uncoded electronically stored information items, each of the uncoded electronically stored information items associated with a visual representation different from the visual representations of the classification codes; group the combined electronically stored information items into clusters, further comprising: convert each of the combined electronically stored information items into one or more tokens; generate a score vector for each of the electronically stored information items based on the tokens associated with that electronically stored information item, further comprising: score each of the tokens; generate paired values for each of the combined electronically stored information items comprising paring the token with the score associated with that token; and for each of the combined electronically stored information items, order the paired values along a vector for that combined electronically stored information item to create the score vector for that electronically stored information item, wherein the tokens are ordered along the vector based on a frequency of the tokens within that combined electronically stored information item; and compare the score vector for each of the combined electronically stored information items, wherein the clustering is performed based on the comparison; and visually represent each of the clusters comprising displaying the visual representation associated with the code of each of the reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information item in that cluster. | 1. A computer-implemented system for inclusion-based electronically stored information item cluster visual representation, comprising: a non-transitory computer readable storage medium comprising program code; and a computer processor configured coupled to the storage medium, wherein the processor is configured to execute the program code to perform steps to: maintain a set of reference electronically stored information items; select from the set a subset of the electronically stored information items, each of the reference electronically stored information items in the subset associated with a classification code, each of the classification codes associated with a visual representation different from the visual representations of the remaining classification codes; combine the subset with a set of uncoded electronically stored information items, each of the uncoded electronically stored information items associated with a visual representation different from the visual representations of the classification codes; group the combined electronically stored information items into clusters, further comprising: convert each of the combined electronically stored information items into one or more tokens; generate a score vector for each of the electronically stored information items based on the tokens associated with that electronically stored information item, further comprising: score each of the tokens; generate paired values for each of the combined electronically stored information items comprising paring the token with the score associated with that token; and for each of the combined electronically stored information items, order the paired values along a vector for that combined electronically stored information item to create the score vector for that electronically stored information item, wherein the tokens are ordered along the vector based on a frequency of the tokens within that combined electronically stored information item; and compare the score vector for each of the combined electronically stored information items, wherein the clustering is performed based on the comparison; and visually represent each of the clusters comprising displaying the visual representation associated with the code of each of the reference electronically stored information items in that cluster and the visual representation associated with each of the uncoded electronically stored information item in that cluster. 6. The system according to claim 1 , wherein the visual representation of one of the reference documents associated with one of the classification codes comprises at least one of a symbol, shape, and color. | 0.804554 |
8,016,680 | 19 | 21 | 19. The game of claim 13 further comprising providing one or more first group activities with a reward independent of errors in target education skill practice. | 19. The game of claim 13 further comprising providing one or more first group activities with a reward independent of errors in target education skill practice. 21. The game of claim 19 further comprising varying the scoring of first group activities between the score dependant on errors in target education skill practice and the score independent of errors in target education skill practice. | 0.5 |
8,538,240 | 3 | 4 | 3. The computer readable medium of claim 1 , wherein the presentation segment includes at least one pair of an inline style and text data for the region of text. | 3. The computer readable medium of claim 1 , wherein the presentation segment includes at least one pair of an inline style and text data for the region of text. 4. The computer readable medium of claim 3 , wherein the inline style for the respective one of the at least one region of text are identical to each other. | 0.5 |
8,856,125 | 17 | 20 | 17. A system comprising: a data store storing label data that specifies a set of initial labels for a non-text content item, wherein the non-text content item is associated with each of a plurality of web pages, and wherein each initial label includes one or more words; and one or more computers coupled to the data store, the one or more computers storing instructions that cause the one or more computers to interact with the data store and perform operations comprising: identifying a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item, wherein each initial label includes one or more words; grouping, for each of two or more sets of matching web pages among the plurality of web pages, initial labels that are associated with the set of matching web pages into a label group, the initial labels for different set of matching web pages being grouped to different label groups; grouping different sets of matching labels from the set of initial labels into different label groups; and selecting, as a final label for the non-text content item, an n-gram of one or more words that is included in at least a threshold number of different label groups. | 17. A system comprising: a data store storing label data that specifies a set of initial labels for a non-text content item, wherein the non-text content item is associated with each of a plurality of web pages, and wherein each initial label includes one or more words; and one or more computers coupled to the data store, the one or more computers storing instructions that cause the one or more computers to interact with the data store and perform operations comprising: identifying a non-text content item that is associated with each of a plurality of web pages; receiving label data that includes a set of initial labels for the non-text content item, wherein each initial label includes one or more words; grouping, for each of two or more sets of matching web pages among the plurality of web pages, initial labels that are associated with the set of matching web pages into a label group, the initial labels for different set of matching web pages being grouped to different label groups; grouping different sets of matching labels from the set of initial labels into different label groups; and selecting, as a final label for the non-text content item, an n-gram of one or more words that is included in at least a threshold number of different label groups. 20. The system of claim 17 , wherein the instructions cause the one or more computers to group different sets of matching labels from the set of initial labels into different label groups by performing operations comprising: identifying, from among the set of initial labels, a first set of at least two initial labels that have at least a threshold measure of similarity; grouping the first set of at least two initial labels into a first label group; identifying, from among the set of initial labels, a second set of at least two initial labels that have at least a threshold measure of similarity; and grouping the second set of at least two initial labels into a second label group. | 0.5 |
8,014,765 | 5 | 6 | 5. The system in accordance with claim 1 , wherein the control codes are removed from a line 21 of a vertical blanking interval (VBI) in a video signal. | 5. The system in accordance with claim 1 , wherein the control codes are removed from a line 21 of a vertical blanking interval (VBI) in a video signal. 6. The system in accordance with claim 5 , further comprising a decoder to decode the caption data for presentation on the captioning device. | 0.5 |
9,761,222 | 16 | 17 | 16. The method as recited in claim 12 , further comprising: identifying the occurrence of a particular event, wherein the particular event is associated with the goal process; and initiating an action from the sequential list of actions based upon the occurrence of a particular event. | 16. The method as recited in claim 12 , further comprising: identifying the occurrence of a particular event, wherein the particular event is associated with the goal process; and initiating an action from the sequential list of actions based upon the occurrence of a particular event. 17. The system as recited in claim 16 , wherein the particular event occurs after the conversation is completed. | 0.5 |
9,245,254 | 1 | 35 | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. 35. The method of claim 1 , further comprising: performing one or more of the receiving data representing speech signals from a voice conference amongst multiple speakers, the determining speaker-related information associated with the multiple speakers, the recording conference history information based on the speaker-related information, and/or the presenting at least some of the conference history information within a conference call provider system. | 0.652736 |
9,229,787 | 1 | 8 | 1. A method for propagating modification operations for Service-oriented Architecture (SOA) objects in a SOA, wherein the SOA comprises at least two SOA objects connected by at least one relationship that defines one SOA object as referencing SOA object and another SOA object as referenced SOA object, the method comprising: receiving a request for propagating a modification operation from the referencing SOA object to the referenced SOA object; evaluating at least one propagation rule to determine, based upon the at least one propagation rule and aspects of the referenced SOA object, whether the requested modification can be performed on the referenced SOA object; determining, using at least one processor, that the requested modification cannot be performed in accordance with the at least one propagation rule; and in response to the determination that the requested modification cannot be performed in accordance with the at least one propagation rule, evaluating at least one approval rule to determine whether the requested modification can be performed on the referenced SOA object, and modifying, in a memory associated with the at least one processor, the referenced SOA object in accordance with the requested modification and based on the at least one approval rule, wherein the evaluating at least one approval rule to determine whether the requested modification can be performed on the referenced SOA object comprises accessing the at least one approval rule in a SOA registry, wherein the at least one rule is associated in the SOA registry with a type of the referenced SOA object. | 1. A method for propagating modification operations for Service-oriented Architecture (SOA) objects in a SOA, wherein the SOA comprises at least two SOA objects connected by at least one relationship that defines one SOA object as referencing SOA object and another SOA object as referenced SOA object, the method comprising: receiving a request for propagating a modification operation from the referencing SOA object to the referenced SOA object; evaluating at least one propagation rule to determine, based upon the at least one propagation rule and aspects of the referenced SOA object, whether the requested modification can be performed on the referenced SOA object; determining, using at least one processor, that the requested modification cannot be performed in accordance with the at least one propagation rule; and in response to the determination that the requested modification cannot be performed in accordance with the at least one propagation rule, evaluating at least one approval rule to determine whether the requested modification can be performed on the referenced SOA object, and modifying, in a memory associated with the at least one processor, the referenced SOA object in accordance with the requested modification and based on the at least one approval rule, wherein the evaluating at least one approval rule to determine whether the requested modification can be performed on the referenced SOA object comprises accessing the at least one approval rule in a SOA registry, wherein the at least one rule is associated in the SOA registry with a type of the referenced SOA object. 8. The method of claim 1 , wherein the at least one of the SOA objects is a web service. | 0.917448 |
10,157,192 | 1 | 6 | 1. A system for searching images, the system comprising: a photo identification component configured to: generate a photo query interface populated with a user interface element associated with at least one of a face query attribute, a face position query attribute, or a location query attribute; display the photo query interface to a user, wherein the user interface element displayed in the photo query interface is movable from a first position in the photo query interface to one or more other positions in the photo query interface; receive a photo query constructed based upon a dragging and dropping, by the user, of the user interface element from the first position to a second position in the photo query interface; associate the face query attribute with a photo feature detection model; utilize the photo feature detection model to identify facial features in the face query attribute; identify, based upon the facial features, one or more photos having attributes corresponding to the photo query; and present the one or more photos to the user as photo search results. | 1. A system for searching images, the system comprising: a photo identification component configured to: generate a photo query interface populated with a user interface element associated with at least one of a face query attribute, a face position query attribute, or a location query attribute; display the photo query interface to a user, wherein the user interface element displayed in the photo query interface is movable from a first position in the photo query interface to one or more other positions in the photo query interface; receive a photo query constructed based upon a dragging and dropping, by the user, of the user interface element from the first position to a second position in the photo query interface; associate the face query attribute with a photo feature detection model; utilize the photo feature detection model to identify facial features in the face query attribute; identify, based upon the facial features, one or more photos having attributes corresponding to the photo query; and present the one or more photos to the user as photo search results. 6. The system of claim 1 , the photo identification component configured to: associate the location query attribute with the photo feature detection model; and utilize the photo feature detection model to extract a background comprising the location query attribute. | 0.659847 |
8,824,785 | 13 | 14 | 13. The method of claim 12 wherein determining the region of the document corresponding to the handwritten information further comprises: (a) determining a top edge, a bottom edge, a right edge and a left edge of the document, wherein the edges are determined based on an orientation of the typographic information relative to the document; (b) identifying an upper-left most pixel of the plurality of pixels of the handwritten information, wherein the upper-left most pixel comprises a pixel located closest to the top edge of the document and closest to the left edge of the document; (c) determining a top bound of the region of the document based on a top line running through the upper-left most pixel, wherein the top line is parallel to the top edge of the document and the bottom edge of the document; (d) determining a bottom pixel of the plurality of pixels of the handwritten information wherein the bottom pixel is located a height number of pixels below the upper-left most pixel; (e) determining a bottom bound of the region of the document based on a bottom line running through the bottom pixel, wherein the bottom line is parallel to the top edge of the document and the bottom edge of the document; (f) determining a leftmost pixel of the plurality of pixels of the handwritten information located within the top bound and the bottom bound, wherein the leftmost pixel is located at the left edge of the document, or the leftmost pixel comprises a closet pixel to the left edge of the document which is located within the top bound and the bottom bound and has no other pixels within a buffer number of pixels to the left; (g) determining a left bound of the region of the document based on a left line running through the leftmost pixel, wherein the left line is parallel to the left edge of the document and the right edge of the document; (h) determining a rightmost pixel of the plurality of pixels of the handwritten information located within the top bound and the bottom bound, wherein the rightmost pixel is located at the right edge of the document or the rightmost pixel comprises a closest pixel to the right edge of the document which is located within the top bound and the bottom bound and has no other pixels with the buffer number of pixels to the right; (i) determining a right bound of the region of the document based on a right line running through the rightmost pixel, wherein the right line is parallel to the left edge of the document and the right edge of the document; (j) determining the bottom pixel of the plurality of pixels of the handwritten information which is located within the left bound and the right bound, wherein the bottom pixel is located at the bottom edge of the document or the bottom pixel is a closest pixel to the bottom edge of the document with no other pixels within the buffer number of pixels below; (k) determining the bottom bound of the region of the document based on a bottom line running through the bottom pixel, wherein the bottom line is parallel to the top edge of the document and the bottom edge of the document; (l) repeating steps (d)-(k) using the bottom bound determined in step (k), the left bound determined in step (g), and the right bound determined in step (i) until the bottom bound, left bound and right bound remain constant; and (m) determining the region of the document based on an area enclosed by the top bound, the bottom bound, the left bound and the right bound. | 13. The method of claim 12 wherein determining the region of the document corresponding to the handwritten information further comprises: (a) determining a top edge, a bottom edge, a right edge and a left edge of the document, wherein the edges are determined based on an orientation of the typographic information relative to the document; (b) identifying an upper-left most pixel of the plurality of pixels of the handwritten information, wherein the upper-left most pixel comprises a pixel located closest to the top edge of the document and closest to the left edge of the document; (c) determining a top bound of the region of the document based on a top line running through the upper-left most pixel, wherein the top line is parallel to the top edge of the document and the bottom edge of the document; (d) determining a bottom pixel of the plurality of pixels of the handwritten information wherein the bottom pixel is located a height number of pixels below the upper-left most pixel; (e) determining a bottom bound of the region of the document based on a bottom line running through the bottom pixel, wherein the bottom line is parallel to the top edge of the document and the bottom edge of the document; (f) determining a leftmost pixel of the plurality of pixels of the handwritten information located within the top bound and the bottom bound, wherein the leftmost pixel is located at the left edge of the document, or the leftmost pixel comprises a closet pixel to the left edge of the document which is located within the top bound and the bottom bound and has no other pixels within a buffer number of pixels to the left; (g) determining a left bound of the region of the document based on a left line running through the leftmost pixel, wherein the left line is parallel to the left edge of the document and the right edge of the document; (h) determining a rightmost pixel of the plurality of pixels of the handwritten information located within the top bound and the bottom bound, wherein the rightmost pixel is located at the right edge of the document or the rightmost pixel comprises a closest pixel to the right edge of the document which is located within the top bound and the bottom bound and has no other pixels with the buffer number of pixels to the right; (i) determining a right bound of the region of the document based on a right line running through the rightmost pixel, wherein the right line is parallel to the left edge of the document and the right edge of the document; (j) determining the bottom pixel of the plurality of pixels of the handwritten information which is located within the left bound and the right bound, wherein the bottom pixel is located at the bottom edge of the document or the bottom pixel is a closest pixel to the bottom edge of the document with no other pixels within the buffer number of pixels below; (k) determining the bottom bound of the region of the document based on a bottom line running through the bottom pixel, wherein the bottom line is parallel to the top edge of the document and the bottom edge of the document; (l) repeating steps (d)-(k) using the bottom bound determined in step (k), the left bound determined in step (g), and the right bound determined in step (i) until the bottom bound, left bound and right bound remain constant; and (m) determining the region of the document based on an area enclosed by the top bound, the bottom bound, the left bound and the right bound. 14. The method of claim 13 further comprising: (n) storing an indication of the region and the plurality of characters corresponding to the handwritten information located within the region. | 0.5 |
9,160,993 | 5 | 7 | 5. A computer implemented method, comprising: acquiring an image of an object using a camera of a computing device; analyzing the image to identify an object type for the object and a projection template for the object type; determining a graphical element to be projected proximate to the object according to the projection template for the object; and projecting the graphical element proximate to the object. | 5. A computer implemented method, comprising: acquiring an image of an object using a camera of a computing device; analyzing the image to identify an object type for the object and a projection template for the object type; determining a graphical element to be projected proximate to the object according to the projection template for the object; and projecting the graphical element proximate to the object. 7. The computer implemented method of claim 5 , further comprising: projecting a first graphical element proximate to the object before acquiring the image of the object. | 0.747774 |
8,014,765 | 7 | 20 | 7. A method for sending caption information to one or more mobile devices, the method comprising: transcribing audio to generate device-generated caption data having control codes, the transcribing audio comprises transcribing audio from an audio event simultaneously with an occurrence of the audio event; removing the control codes from the caption data to produce unencoded text data by removing control codes from a line 21 of a vertical blanking interval (VBI) of a video signal; sending the unencoded text data to one or more mobile devices over a communication network, the sending the unencoded text data comprises sending the unencoded text data to one or more mobile devices coincidentally with the transcribing audio from the audio event; and sending the caption data to a captioning device, the sending the caption data comprises: sending the unencoded text data to the one or more mobile devices simultaneously with the sending of the caption data to the captioning device; and sending the caption data to the captioning device coincidentally with the transcribing audio from the audio event. | 7. A method for sending caption information to one or more mobile devices, the method comprising: transcribing audio to generate device-generated caption data having control codes, the transcribing audio comprises transcribing audio from an audio event simultaneously with an occurrence of the audio event; removing the control codes from the caption data to produce unencoded text data by removing control codes from a line 21 of a vertical blanking interval (VBI) of a video signal; sending the unencoded text data to one or more mobile devices over a communication network, the sending the unencoded text data comprises sending the unencoded text data to one or more mobile devices coincidentally with the transcribing audio from the audio event; and sending the caption data to a captioning device, the sending the caption data comprises: sending the unencoded text data to the one or more mobile devices simultaneously with the sending of the caption data to the captioning device; and sending the caption data to the captioning device coincidentally with the transcribing audio from the audio event. 20. The method in accordance with claim 7 , wherein the communication network comprises a server. | 0.780543 |
7,895,167 | 6 | 9 | 6. The log record analyzing system of claim 1 , further comprising a Complex Event Processing (CEP) module configured to receive said raw log data from at least one computerized system, said CEP module being configured to forward said received raw log data to said parsing engine, wherein said forwarding is done according to a set of predetermined rules. | 6. The log record analyzing system of claim 1 , further comprising a Complex Event Processing (CEP) module configured to receive said raw log data from at least one computerized system, said CEP module being configured to forward said received raw log data to said parsing engine, wherein said forwarding is done according to a set of predetermined rules. 9. The log record analyzing system of claim 6 , wherein said set of predetermined rules comprises at least one of the following rules: static rule, dynamic rule, deterministic rule, statistical rule, event driven rule, and time and date based rule. | 0.561837 |
8,204,896 | 9 | 15 | 9. An image processing method, comprising: scanning image information regarding an original document, the original document including character addition information added manually to at least one character string in the original document; extracting layout information regarding character regions and the character addition information added to the at least one character string within the character regions from the image information; converting the character regions included in the layout information into character information; extracting one or more keywords comprising the at least one character string from the character information in response to determining that the character addition information added to the at least one character string has a predefined image characteristic; searching by use of the one or more keywords and generating meta-information based on information retrieved by the searching; and generating an electronic document according to a description of a predetermined format by adding the meta-information to the character information. | 9. An image processing method, comprising: scanning image information regarding an original document, the original document including character addition information added manually to at least one character string in the original document; extracting layout information regarding character regions and the character addition information added to the at least one character string within the character regions from the image information; converting the character regions included in the layout information into character information; extracting one or more keywords comprising the at least one character string from the character information in response to determining that the character addition information added to the at least one character string has a predefined image characteristic; searching by use of the one or more keywords and generating meta-information based on information retrieved by the searching; and generating an electronic document according to a description of a predetermined format by adding the meta-information to the character information. 15. The method to claim 9 , wherein the search information includes associated information corresponding to the one or more keywords, a Web page in which the associated information is described, or a uniform resource locator (URL) regarding the Web page. | 0.636103 |
9,536,069 | 1 | 2 | 1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device. | 1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device. 2. The process of claim 1 , wherein the protected resource is a software application, software service, website, web service, data, hardware device, mobile app, smartphone app, physical area, physical item, bank account, trading account, credit limit, monetary balance, reward points, computer device, or communication device. | 0.501529 |
9,483,138 | 16 | 19 | 16. A non-transitory computer-readable storage medium storing program instructions that when executed on one or more computers cause the one or more computers to perform acts comprising: collecting information about a user manipulation of a stylus indicative of six degrees of freedom movement of the stylus relative to an initial position of the stylus in three-dimensional space relative to a touch input surface and information regarding touch or pressure input applied to the touch input surface; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, wherein the stylus gesture is one of a plurality of stylus gestures that are recognized by the one or more computers to perform at least one of a plurality of actions in a graphics application, and the plurality of stylus gestures includes a twisting motion, a waving motion above the touch input surface, a brush switching gesture in which a proximity of the stylus relative the touch input surface is changed with at least a rate of change that corresponds to the brush switching gesture and changes from the initial position relative the touch input surface that is within a first pre-defined distance threshold of the touch input surface to an ending position that is further away from the touch input surface and beyond a second pre-defined distance threshold, a quick motion toward the touch input surface, shaking the stylus directed away from the touch input surface, or shaking the stylus directed towards the touch input surface; determining which of the plurality of actions to perform based on the recognized stylus gesture, wherein an action of switching between paintbrushes of a brush tool is performed in response to recognition of the brush switching gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. | 16. A non-transitory computer-readable storage medium storing program instructions that when executed on one or more computers cause the one or more computers to perform acts comprising: collecting information about a user manipulation of a stylus indicative of six degrees of freedom movement of the stylus relative to an initial position of the stylus in three-dimensional space relative to a touch input surface and information regarding touch or pressure input applied to the touch input surface; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, wherein the stylus gesture is one of a plurality of stylus gestures that are recognized by the one or more computers to perform at least one of a plurality of actions in a graphics application, and the plurality of stylus gestures includes a twisting motion, a waving motion above the touch input surface, a brush switching gesture in which a proximity of the stylus relative the touch input surface is changed with at least a rate of change that corresponds to the brush switching gesture and changes from the initial position relative the touch input surface that is within a first pre-defined distance threshold of the touch input surface to an ending position that is further away from the touch input surface and beyond a second pre-defined distance threshold, a quick motion toward the touch input surface, shaking the stylus directed away from the touch input surface, or shaking the stylus directed towards the touch input surface; determining which of the plurality of actions to perform based on the recognized stylus gesture, wherein an action of switching between paintbrushes of a brush tool is performed in response to recognition of the brush switching gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. 19. The storage medium of claim 16 , wherein the collected information comprises one or more of: spatial information collected during the manipulation of the stylus, directional information collected during the manipulation of the stylus, acceleration data collected during the manipulation of the stylus, the initial position of the stylus, the ending position of the stylus, an initial orientation of the stylus, or an ending orientation of the stylus. | 0.5 |
9,183,535 | 16 | 24 | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. 24. The non-transitory computer-readable storage medium of claim 16 , wherein the computer program instructions further comprise instructions for: generating, from the social network model, a list of the at least two candidate entities for the ambiguous entity, the candidate entities being entities from the user's social network model; scoring the candidate entities based at least in part on a strength of a relationship between a candidate entity and the user; and exposing one or more best scoring candidate entities to the user for selection. | 0.5 |
7,895,241 | 1 | 2 | 1. A method for integrating oilfield data in a plurality of formats, the method comprising: storing the oilfield data associated with a plurality of oilfield entities in a first data repository; obtaining, using a computer, a first target metamodel comprising a first structural description of a first plurality of data entities of the first data repository, wherein the first structural description describes database rows and columns of the first data repository; obtaining, using the computer, a domain metamodel interleaved with a first mapping specification, the domain metamodel comprising a second structural description of a domain model, defining a plurality of domain objects within a hierarchy of an oilfield domain, for representing the plurality of oilfield entities in an application programming interface (API); associating, using the computer, the first plurality of data entities of the first target metamodel with the plurality of domain objects of the domain metamodel using the first mapping specification; forming, using the computer, the API based on the domain metamodel, the first target metamodel, and the first mapping specification; generating a domain model source code based on the domain metamodel, the first target metamodel, and the first mapping specification using an automatic code generator; compiling the domain model source code to implement the API; generating a plurality of domain object instances corresponding to the plurality of oilfield entities, wherein at least one of the plurality of domain object instances is instantiated from a domain object of the plurality of domain objects compiled from the domain model source code; and identifying an association between the plurality of oilfield entities with the first plurality of data entities based on the at least one of the plurality of domain object instances; receiving, by the API, a database operation for the domain metamodel, wherein the database operation comprises a plurality of elements that generate a result using data in the domain metamodel; determining that one element of the plurality of elements in the database operation for the domain metamodel is needed to generate the result in a form required by the database operation; executing the database operation after a status of the one element in the database operation is changed from optional to mandatory, and generating the result in the form required by the database operation. | 1. A method for integrating oilfield data in a plurality of formats, the method comprising: storing the oilfield data associated with a plurality of oilfield entities in a first data repository; obtaining, using a computer, a first target metamodel comprising a first structural description of a first plurality of data entities of the first data repository, wherein the first structural description describes database rows and columns of the first data repository; obtaining, using the computer, a domain metamodel interleaved with a first mapping specification, the domain metamodel comprising a second structural description of a domain model, defining a plurality of domain objects within a hierarchy of an oilfield domain, for representing the plurality of oilfield entities in an application programming interface (API); associating, using the computer, the first plurality of data entities of the first target metamodel with the plurality of domain objects of the domain metamodel using the first mapping specification; forming, using the computer, the API based on the domain metamodel, the first target metamodel, and the first mapping specification; generating a domain model source code based on the domain metamodel, the first target metamodel, and the first mapping specification using an automatic code generator; compiling the domain model source code to implement the API; generating a plurality of domain object instances corresponding to the plurality of oilfield entities, wherein at least one of the plurality of domain object instances is instantiated from a domain object of the plurality of domain objects compiled from the domain model source code; and identifying an association between the plurality of oilfield entities with the first plurality of data entities based on the at least one of the plurality of domain object instances; receiving, by the API, a database operation for the domain metamodel, wherein the database operation comprises a plurality of elements that generate a result using data in the domain metamodel; determining that one element of the plurality of elements in the database operation for the domain metamodel is needed to generate the result in a form required by the database operation; executing the database operation after a status of the one element in the database operation is changed from optional to mandatory, and generating the result in the form required by the database operation. 2. The method of claim 1 , further comprising: identifying an association between the plurality of oilfield entities and the first plurality of data entities based on the at least one of a plurality of hierarchical mapping units and a mapping constraint, wherein the first mapping specification comprises the plurality of hierarchical mapping units, and wherein at least one of the plurality of hierarchical mapping units is associated with the mapping constraint. | 0.545988 |
7,856,472 | 4 | 24 | 4. The method of claim 3 , and further comprising, utilizing the at least one window, displaying, in response to a first user interaction, the first additional information associated with the first message. | 4. The method of claim 3 , and further comprising, utilizing the at least one window, displaying, in response to a first user interaction, the first additional information associated with the first message. 24. The method of claim 4 , wherein the first additional information is displayed utilizing a graphical user interface element of variable size that is determined by the user. | 0.5 |
7,743,327 | 16 | 18 | 16. The method as set forth in claim 12 , wherein the at least one validation criterion comprises: validate conditional upon no linked text fragments being within a substantial copy of the contiguous group of text fragments identified as table of content entries. | 16. The method as set forth in claim 12 , wherein the at least one validation criterion comprises: validate conditional upon no linked text fragments being within a substantial copy of the contiguous group of text fragments identified as table of content entries. 18. The method as set forth in claim 16 , wherein the substantial copy is a partial copy of the contiguous group of text fragments identified as table of content entries. | 0.840525 |
10,135,887 | 26 | 27 | 26. The computer readable medium of claim 21 , wherein the first annotation is a sponsored annotation and the method further comprises: receiving an indication of a selection from a first user to view the source video content; determining if the first user has opted out of receiving sponsored annotations; and if the first user has not opted out of receiving sponsored annotations, providing the first annotation and associated metadata for display or play of the first annotation, wherein the first annotation is synchronized with the source video content. | 26. The computer readable medium of claim 21 , wherein the first annotation is a sponsored annotation and the method further comprises: receiving an indication of a selection from a first user to view the source video content; determining if the first user has opted out of receiving sponsored annotations; and if the first user has not opted out of receiving sponsored annotations, providing the first annotation and associated metadata for display or play of the first annotation, wherein the first annotation is synchronized with the source video content. 27. The computer readable medium of claim 26 , further comprising tracking a number of viewings of the sponsored annotation. | 0.5 |
7,580,571 | 3 | 5 | 3. The method of claim 1 , wherein the converting step comprises the steps of: forming one or more circumscribed rectangles for each of the consecutive characters; and extracting one or more parameters from each of the circumscribed rectangles, the parameters being used as the layout information. | 3. The method of claim 1 , wherein the converting step comprises the steps of: forming one or more circumscribed rectangles for each of the consecutive characters; and extracting one or more parameters from each of the circumscribed rectangles, the parameters being used as the layout information. 5. The method of claim 3 , wherein the converting step further comprises the steps of: forming a character line based on a plurality of circumscribed rectangles of the one or more circumscribed rectangles, the plurality of circumscribed rectangles being located closely to each other; and normalizing each of the parameters with respect to the character line using a line parameter obtained from the character line, the normalized parameters being used as the layout information. | 0.505165 |
9,727,925 | 1 | 9 | 1. A method implemented with a processor, comprising: identifying an internal social network for an enterprise; collecting a set of messages from the internal social network; performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise; performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages; identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points; as a result of the performed semantic analysis, clustering together messages that are similar to each other; categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages; associating each category of the plurality of categories with one or more tags; associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages; determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations; and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. | 1. A method implemented with a processor, comprising: identifying an internal social network for an enterprise; collecting a set of messages from the internal social network; performing semantic filtering to the set of messages, the semantic filtering reducing an excess noise associated with data that is not relevant to the enterprise; performing semantic analysis upon the set of messages collected from the internal social network to determine a contextual significance of one or more terms in the set of messages; identifying themes in the set of messages, the themes pertaining to at least one of customer preferences, demographic information, industry trends, customer view points; as a result of the performed semantic analysis, clustering together messages that are similar to each other; categorizing the set of messages into a plurality of categories based at least in part on the contextual significance of the one or more terms in the set of messages; associating each category of the plurality of categories with one or more tags; associating respective tags to the set of messages that are categorized as a result of the semantic analysis to generate a set of tagged messages; determining associations between the one or more tags and one or more enterprise applications corresponding to the enterprise such that the set of tagged messages are sent to respective ones of the one or more enterprise applications based at least in part on the determined associations; and storing the tagged messages in an actionable social message store, the actionable message store storing in a table format, for each message, one or more of a source of the message, a topic parameter associated with the message, data associated with the message, and the one or more tags associated with the message, wherein the semantic analysis performed comprises latent semantic analysis (LSA), the LSA referring to a form of statistical language modeling that distinguishes two identical words based on a semantic significance of the word. 9. The method of claim 1 , wherein the one or more enterprise applications is a Human resources (“HR”) application, customer relations management (“CRM”) application, enterprise resource planning (“ERP”) application, or supply chain management application. | 0.5 |
8,725,732 | 21 | 30 | 21. A storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying one or more first subject matter categories in a plurality of subject matter categories, each of the first subject matter categories being a hierarchical classification of a plurality of confirmed valid search results for queries, and wherein at least one query for each identified first subject matter category includes a term in text; for each first subject matter category in the first subject matter categories: selecting one or more terms wherein each of the one or more terms occurs in the text and in one or more queries having confirmed valid search results that are in the first subject matter category; identifying one or more terms from the selected terms that each match a refinement level in the first subject matter category hierarchical classification; boosting an initial weight of the first subject matter category by a value based on the refinement level to acquire a first boosted weight; boosting the first boosted weight by a value based on a count of the selected terms to acquire a second boosted weight; selecting the first matter category if the second boosted weight satisfies a first threshold; and recommending content associated with one or more of the selected first subject matter categories. | 21. A storage device having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying one or more first subject matter categories in a plurality of subject matter categories, each of the first subject matter categories being a hierarchical classification of a plurality of confirmed valid search results for queries, and wherein at least one query for each identified first subject matter category includes a term in text; for each first subject matter category in the first subject matter categories: selecting one or more terms wherein each of the one or more terms occurs in the text and in one or more queries having confirmed valid search results that are in the first subject matter category; identifying one or more terms from the selected terms that each match a refinement level in the first subject matter category hierarchical classification; boosting an initial weight of the first subject matter category by a value based on the refinement level to acquire a first boosted weight; boosting the first boosted weight by a value based on a count of the selected terms to acquire a second boosted weight; selecting the first matter category if the second boosted weight satisfies a first threshold; and recommending content associated with one or more of the selected first subject matter categories. 30. The storage device of claim 21 wherein the text is a web page or an email message. | 0.885027 |
6,014,639 | 16 | 20 | 16. A computer-implemented method for interrogating an electronic catalog where catalog objects are arranged as entities at nodes in a node hierarchy, said method comprising: providing attribute relevance value for attributes of the entities; and enabling use of said attribute relevance values of the attributes in forward-checking parametric searching. | 16. A computer-implemented method for interrogating an electronic catalog where catalog objects are arranged as entities at nodes in a node hierarchy, said method comprising: providing attribute relevance value for attributes of the entities; and enabling use of said attribute relevance values of the attributes in forward-checking parametric searching. 20. The method of claim 16, including attributing an attribute relevance value of irrelevant to an attribute which is irrelevant to any entities of a node in a hierarchy. | 0.791155 |
6,094,671 | 4 | 46 | 4. A media distribution network system as claimed in claim 1 wherein the transmission system includes a one-way link adapted to transmit the envelope of aggregate data from the producer station to one or more remote receiving stations. | 4. A media distribution network system as claimed in claim 1 wherein the transmission system includes a one-way link adapted to transmit the envelope of aggregate data from the producer station to one or more remote receiving stations. 46. A media distribution network system as claimed in claim 4 wherein the mark-up language document includes, or includes a tag to, a company logo or trade identity identification of a source of origin for data provided by the mark-up language document. | 0.704439 |
9,226,047 | 1 | 3 | 1. A method for restricting access to digital video content based on recognition of a TV station logo embedded within the video content that varies according to the video usage rights, the method comprising: extracting the TV station logo from the video content by combining several frames of video content; identifying the TV station logo by comparing the TV station logo to known TV station logos that most closely matches said TV station logo extracted from the video content, where the known TV station logos are associated with user profiles of copyright rights holders, and wherein at least some of the known TV station logos are supplied by rights holders for content analysis to identify their owned content; estimating a first match probability of the likely copyright rights holder based on the identified TV station logo; identifying a second media object within at least one frame of the video content different from the TV station logo; extracting at least a second semantic property from the second specified media object within at least one frame of the video content; matching said at least second semantic property of the second specified media object against the known semantic properties of known media objects associated with user profiles of copyright rights holders; comparing matches between said at least second semantic property and the known semantic properties to a second threshold value; estimating a second match probability of the likely copyright rights holder based on the second compared matches; combining the first match probability and the second match probability into a combined match probability; identifying a copyright rights holder based on at least the combined match probability; retrieving rules governing distribution rights of the content based at least on identification of the copyright rights holder; and restricting access to the digital video content in accordance with the retrieved rules. | 1. A method for restricting access to digital video content based on recognition of a TV station logo embedded within the video content that varies according to the video usage rights, the method comprising: extracting the TV station logo from the video content by combining several frames of video content; identifying the TV station logo by comparing the TV station logo to known TV station logos that most closely matches said TV station logo extracted from the video content, where the known TV station logos are associated with user profiles of copyright rights holders, and wherein at least some of the known TV station logos are supplied by rights holders for content analysis to identify their owned content; estimating a first match probability of the likely copyright rights holder based on the identified TV station logo; identifying a second media object within at least one frame of the video content different from the TV station logo; extracting at least a second semantic property from the second specified media object within at least one frame of the video content; matching said at least second semantic property of the second specified media object against the known semantic properties of known media objects associated with user profiles of copyright rights holders; comparing matches between said at least second semantic property and the known semantic properties to a second threshold value; estimating a second match probability of the likely copyright rights holder based on the second compared matches; combining the first match probability and the second match probability into a combined match probability; identifying a copyright rights holder based on at least the combined match probability; retrieving rules governing distribution rights of the content based at least on identification of the copyright rights holder; and restricting access to the digital video content in accordance with the retrieved rules. 3. The method of claim 1 , wherein said TV station logo is visibly embedded within the video content. | 0.880615 |
8,935,166 | 6 | 9 | 6. A system as claimed in claim 1 further comprising: a remote computing device for converting an audio dictation; and means to update a voice recognition logic. | 6. A system as claimed in claim 1 further comprising: a remote computing device for converting an audio dictation; and means to update a voice recognition logic. 9. A system as claimed in claim 6 further comprising means to display the converted audio dictation on a user computing device. | 0.568027 |
6,148,286 | 20 | 21 | 20. The apparatus of claim 18, further comprising: means for receiving a selection of the fist match; means, responsive to the means for receiving a selection of the first match, for providing additional information about the first match, the information selected from the set consisting of textual information, pictorial information, animation information, and combinations thereof. | 20. The apparatus of claim 18, further comprising: means for receiving a selection of the fist match; means, responsive to the means for receiving a selection of the first match, for providing additional information about the first match, the information selected from the set consisting of textual information, pictorial information, animation information, and combinations thereof. 21. The apparatus of claim 20 wherein the additional information is provided via a medium or media selected from the set consisting of networks, television, interactive television, online services, and combinations thereof. | 0.72125 |
7,973,959 | 1 | 10 | 1. A document administration system comprising: a document administration apparatus including: a document administration information storage section that stores administration information containing at least document identification information assigned to a document and a retention period of the document, and a document image storage section; and a document destruction apparatus including: an identification information reader that reads, from the document, the document identification information assigned to the document, a first determination section that determines, based on a reading result by the identification information reader, as to whether or not the document identification information is assigned to the document, and a document reader, wherein if the document meets a predetermined read condition, the document reader reads the document to acquire an image of the document, and if no document identification information is assigned to the document, the document reader reads the document to acquire the image of the document and the document image storage section stores the image of the document acquired by the document reader. | 1. A document administration system comprising: a document administration apparatus including: a document administration information storage section that stores administration information containing at least document identification information assigned to a document and a retention period of the document, and a document image storage section; and a document destruction apparatus including: an identification information reader that reads, from the document, the document identification information assigned to the document, a first determination section that determines, based on a reading result by the identification information reader, as to whether or not the document identification information is assigned to the document, and a document reader, wherein if the document meets a predetermined read condition, the document reader reads the document to acquire an image of the document, and if no document identification information is assigned to the document, the document reader reads the document to acquire the image of the document and the document image storage section stores the image of the document acquired by the document reader. 10. The system according to claim 1 , wherein the predetermined read condition includes a condition that the document is not permitted to be destructed is satisfied. | 0.892996 |
9,854,330 | 9 | 12 | 9. A method comprising: generating a fingerprint data using a television, wherein the fingerprint data is any one of an audio fingerprint data and a video fingerprint data; matching primary data generated from the fingerprint data with targeted data based on a relevancy factor using a relevancy-matching server; looking in a data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough. | 9. A method comprising: generating a fingerprint data using a television, wherein the fingerprint data is any one of an audio fingerprint data and a video fingerprint data; matching primary data generated from the fingerprint data with targeted data based on a relevancy factor using a relevancy-matching server; looking in a data repository for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data using the relevancy-matching server, wherein the primary data is any one of a content identification data and a content identification history; constraining an executable environment in a security sandbox of a mobile device; executing a sandboxed application in the executable environment of the mobile device; associating the mobile device with the television based on: executing a sandbox-reachable service on the television; automatically announcing, through the television, the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device; identifying the sandbox-reachable service offered through the television based on receiving, through the discovery module, the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television; and establishing bidirectional communication between the mobile device and the television based on the sandboxed application reaching the sandbox-reachable service to render the primary data available across the sandbox-reachable service and the sandboxed application; processing an embedded object within the sandboxed application; and executing the embedded object through the sandboxed application to cause rendering of the targeted data therethrough. 12. The method of claim 9 : wherein the embedded object comprises at least one of a script, an image, a player, an iframe, and other external media included in the sandboxed application. | 0.812877 |
8,554,742 | 8 | 10 | 8. A process operable on one or more computers for identifying duplicate records among a plurality of records in a database, each record having a plurality of fields, comprising: (a) setting a threshold match probability; (b) calculating record match probabilities for each of a plurality of possible patterns, wherein each pattern is a different permutation of comparisons between said fields and wherein each record match probability is a posterior probability that two records are duplicates given that the two records fit the respective pattern; (c) identifying patterns having record match probabilities meeting or exceeding said threshold match probability; (d) disregarding patterns having record match probabilities lower than said threshold match probability; (e) determining which records pairs within the plurality of records have one or more of said identified patterns; and (f) analyzing said record pairs to determine whether said record pairs are duplicates; wherein steps (b)-(d) occur prior to steps (e) and (f). | 8. A process operable on one or more computers for identifying duplicate records among a plurality of records in a database, each record having a plurality of fields, comprising: (a) setting a threshold match probability; (b) calculating record match probabilities for each of a plurality of possible patterns, wherein each pattern is a different permutation of comparisons between said fields and wherein each record match probability is a posterior probability that two records are duplicates given that the two records fit the respective pattern; (c) identifying patterns having record match probabilities meeting or exceeding said threshold match probability; (d) disregarding patterns having record match probabilities lower than said threshold match probability; (e) determining which records pairs within the plurality of records have one or more of said identified patterns; and (f) analyzing said record pairs to determine whether said record pairs are duplicates; wherein steps (b)-(d) occur prior to steps (e) and (f). 10. The process according to claim 8 , wherein results of said comparisons between said fields are: match, no match, and absent. | 0.728814 |
8,205,149 | 2 | 3 | 2. The method of claim 1 , wherein: the step of choosing the plurality of formatting characteristics of the cell in the spreadsheet further comprises selecting an option of choosing the formatting characteristics from a formatted cell in the spreadsheet; and in response to selecting the option, changing the shape of the cursor from a first shape to a second shape distinct from the first shape, whereby the distinct second shape denotes to a user that moving the cursor over a cell and clicking the mouse button will determine the formatting characterizes of that cell and apply the formatting characteristics of that cell to the fields of the find dialog. | 2. The method of claim 1 , wherein: the step of choosing the plurality of formatting characteristics of the cell in the spreadsheet further comprises selecting an option of choosing the formatting characteristics from a formatted cell in the spreadsheet; and in response to selecting the option, changing the shape of the cursor from a first shape to a second shape distinct from the first shape, whereby the distinct second shape denotes to a user that moving the cursor over a cell and clicking the mouse button will determine the formatting characterizes of that cell and apply the formatting characteristics of that cell to the fields of the find dialog. 3. The method of claim 2 , wherein the second shape of the cursor is shaped like an eyedropper. | 0.5 |
7,536,521 | 6 | 7 | 6. A computer storage device for use with a file system managing logical data files of data, the computer storage device comprising: a storage medium having a plurality of blocks storing data and metadata, the metadata mapping data of logical data files to blocks; an interface accepting instructions from the file system to read data from blocks and write data to blocks; a controller implementing: (a) an access monitor circuit communicating with the interface to identify metadata stored on the storage medium and to determine from the metadata and from subsequent access to data blocks other than the metadata, whether blocks are live or dead; and (b) a media access circuit changing writing of data to a given block or reading of data from a given block based on whether the block has died as determined by the controller. | 6. A computer storage device for use with a file system managing logical data files of data, the computer storage device comprising: a storage medium having a plurality of blocks storing data and metadata, the metadata mapping data of logical data files to blocks; an interface accepting instructions from the file system to read data from blocks and write data to blocks; a controller implementing: (a) an access monitor circuit communicating with the interface to identify metadata stored on the storage medium and to determine from the metadata and from subsequent access to data blocks other than the metadata, whether blocks are live or dead; and (b) a media access circuit changing writing of data to a given block or reading of data from a given block based on whether the block has died as determined by the controller. 7. The computer storage device of claim 6 wherein the media access circuit shreds a block to erase previous data of the block when the access monitor circuit determines that the block has changed from live to dead. | 0.654839 |
7,650,324 | 12 | 13 | 12. A system providing reference information, including: a first computing system that executes a first process for generating the shell document on a display, rendering the shell document for editing by an author, and receiving a first request from the author to insert a reference to a first fragment object in the shell document, the first request including a parameter provided by the author, wherein the shell document is separate from the fragment object and the first fragment object is of a first type; and a second computing system having a storage device and configured to: provide to display, a list of fragment objects by searching through the storage device using the parameter as search criteria, the fragment objects being stored in the storage device; receiving, from the first computing system, a selection of the first fragment object, the fragment object being a known fragment object and being selected from the list of fragment objects; comparing a predetermined rule associated with the first fragment object with the first type to determine an identity of a first property that is compatible with the first fragment object; search, in the storage device, for the first property; determine whether the first property can be dynamically generated when the search is unsuccessful, wherein a message is provided to indicate that the first property is not available when the search result is unsuccessful and when the first property cannot be dynamically generated; retrieving the first property from the storage device when the search is successful; generate, based on the predetermined rule, the first property when it is determined that the first property can be dynamically generated, the first property including textual information describing a characteristic of the fragment object, wherein the first property included in the response data is the retrieved first property when the search is successful, and wherein the first property included in the response data is the generated first property when the search is unsuccessful; generate the reference to the first fragment object based on the first request; and provide to the first computing system the generated reference to the first fragment object and the first property; wherein the first computing system updates the rendering of the shell document by editing the rendered shell document based on commands inputted by the author and by including the reference to the first fragment object and the first property into an author identified location within the rendered shell document the first property conveying the characteristic of the fragment object in a user-ascertainable format by using the textual information to describe the characteristic of the fragment object, the reference being inserted without inserting the fragment object, that is known, in the shell document. | 12. A system providing reference information, including: a first computing system that executes a first process for generating the shell document on a display, rendering the shell document for editing by an author, and receiving a first request from the author to insert a reference to a first fragment object in the shell document, the first request including a parameter provided by the author, wherein the shell document is separate from the fragment object and the first fragment object is of a first type; and a second computing system having a storage device and configured to: provide to display, a list of fragment objects by searching through the storage device using the parameter as search criteria, the fragment objects being stored in the storage device; receiving, from the first computing system, a selection of the first fragment object, the fragment object being a known fragment object and being selected from the list of fragment objects; comparing a predetermined rule associated with the first fragment object with the first type to determine an identity of a first property that is compatible with the first fragment object; search, in the storage device, for the first property; determine whether the first property can be dynamically generated when the search is unsuccessful, wherein a message is provided to indicate that the first property is not available when the search result is unsuccessful and when the first property cannot be dynamically generated; retrieving the first property from the storage device when the search is successful; generate, based on the predetermined rule, the first property when it is determined that the first property can be dynamically generated, the first property including textual information describing a characteristic of the fragment object, wherein the first property included in the response data is the retrieved first property when the search is successful, and wherein the first property included in the response data is the generated first property when the search is unsuccessful; generate the reference to the first fragment object based on the first request; and provide to the first computing system the generated reference to the first fragment object and the first property; wherein the first computing system updates the rendering of the shell document by editing the rendered shell document based on commands inputted by the author and by including the reference to the first fragment object and the first property into an author identified location within the rendered shell document the first property conveying the characteristic of the fragment object in a user-ascertainable format by using the textual information to describe the characteristic of the fragment object, the reference being inserted without inserting the fragment object, that is known, in the shell document. 13. The system of claim 12 , wherein the shell document includes a reference to a second fragment object having a corresponding second property and wherein the first computing system renders an updated shell document on a user interface, the updated shell document including the reference to the first fragment object, the first property, the reference to the second fragment object and the second property. | 0.566098 |
9,311,568 | 1 | 7 | 1. A computer-implemented method for selecting a representative image for a recipe from among a plurality of recipe images, the method comprising: receiving a recipe comprising classified recipe text describing preparation of a food product and a plurality of candidate images; generating image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determining, by a processor, image probabilities of the plurality of candidate images depicting the finished food product described by the recipe, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; ranking the plurality of candidate images according to the determined image probabilities; selecting a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and storing the selected representative image in association with the retrieved recipe. | 1. A computer-implemented method for selecting a representative image for a recipe from among a plurality of recipe images, the method comprising: receiving a recipe comprising classified recipe text describing preparation of a food product and a plurality of candidate images; generating image features for the plurality of candidate images, features of a candidate image representative of at least one of: classified recipe text proximate to the candidate image and position of the candidate image within the recipe; determining, by a processor, image probabilities of the plurality of candidate images depicting the finished food product described by the recipe, the image probabilities determined using an image model, image feature weights, and the generated image features, the image feature weights computed based on training recipes comprising classified training recipe text and training recipe images, the training recipe images including representative training images corresponding to the training recipes; ranking the plurality of candidate images according to the determined image probabilities; selecting a representative image from the candidate images according to the ranking of the candidate images, the selected representative image having a highest image probability of the determined image probabilities; and storing the selected representative image in association with the retrieved recipe. 7. The method of claim 1 , wherein the generated features of the candidate image include a feature corresponding to a histogram of oriented gradients within the candidate image. | 0.918131 |
9,501,295 | 12 | 14 | 12. The computer program product of claim 11 , wherein said resulting composite values list of valid locales and languages combinations is used at least for one of the following processes: adjustment of a user interface; and presenting a list of language and locale combination options for selection to a user. | 12. The computer program product of claim 11 , wherein said resulting composite values list of valid locales and languages combinations is used at least for one of the following processes: adjustment of a user interface; and presenting a list of language and locale combination options for selection to a user. 14. The computer program product of claim 12 , wherein said presenting process of said list of at least one language and locale combination option is performed during at least one of the following processes: changing user preferred locale and language settings, and creating a new user account and setting at least one user preferred locale and at least one user preferred language. | 0.759748 |
9,838,259 | 1 | 4 | 1. A method for managing client defined response requirements in a domain name system (DNS) query implemented by a network traffic management system comprising one or more network traffic apparatuses, client devices, or server devices, the method comprising: determining when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncating the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receiving the internet protocol address from the at least one of a plurality of servers; determining when a format of the received internet protocol address conforms to one or more policies; and performing one or more actions based on the determination of the conformance of the received internet protocol address. | 1. A method for managing client defined response requirements in a domain name system (DNS) query implemented by a network traffic management system comprising one or more network traffic apparatuses, client devices, or server devices, the method comprising: determining when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncating the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receiving the internet protocol address from the at least one of a plurality of servers; determining when a format of the received internet protocol address conforms to one or more policies; and performing one or more actions based on the determination of the conformance of the received internet protocol address. 4. The method as set forth in claim 1 wherein the determining if the format of the received internet protocol address conforms to the one or more policies further comprises processing the received response to perform one or more actions based on one or more rules when the internet protocol address is determined to be non-conforming to the one or more policies. | 0.642292 |
5,500,919 | 35 | 44 | 35. A processor according to claim 33, wherein said controller includes a graphical user interface. | 35. A processor according to claim 33, wherein said controller includes a graphical user interface. 44. A processor according to claim 35, wherein said graphical user interface includes means to vary text-to-speech conversion parameters. | 0.843607 |
8,290,960 | 10 | 11 | 10. The information handling system of claim 9 wherein the instructions executed by at least one of the processors perform additional actions comprising: receiving a priority value from an information consumer, wherein the priority value is associated with the selected trust factor, and wherein the priority value is used by the assigned algorithm to generate the resulting trust factor metadata score. | 10. The information handling system of claim 9 wherein the instructions executed by at least one of the processors perform additional actions comprising: receiving a priority value from an information consumer, wherein the priority value is associated with the selected trust factor, and wherein the priority value is used by the assigned algorithm to generate the resulting trust factor metadata score. 11. The information handling system of claim 10 wherein the instructions executed by at least one of the processors perform additional actions comprising: receiving a changed priority value from the information consumer that results in a changed trust factor metadata score when executed by the assigned algorithm. | 0.5 |
9,288,285 | 1 | 5 | 1. A computer-implemented method of recommending content to a user, comprising: identifying classified public content stored on a server appliance or a repository that is communicably coupled to the server appliance; identifying private content of a user stored on a client appliance or a repository that is communicably coupled to the client appliance, the client appliance communicably coupled to the server appliance through a network; receiving, from the user, i) a request for a recommendation of content and ii) a selection of a level of a hierarchical structure associated with the request for the recommendation of content; based on the selected level, determining one or more proxy keywords associated with one or more keywords of the request; generating a representative query based on i) the one or more proxy keywords and ii) the request for the recommendation of content; determining, based on the representative query, a portion of the classified public content stored on a server appliance or the repository that is communicably coupled to the server appliance; determining, based on the request, a portion of the private content stored on the client appliance or the repository that is communicably coupled to the client appliance; and preparing, for presentation to the user, the portion of the classified public content based on the representative query and the portion of the private content based on the request for the recommendation of content. | 1. A computer-implemented method of recommending content to a user, comprising: identifying classified public content stored on a server appliance or a repository that is communicably coupled to the server appliance; identifying private content of a user stored on a client appliance or a repository that is communicably coupled to the client appliance, the client appliance communicably coupled to the server appliance through a network; receiving, from the user, i) a request for a recommendation of content and ii) a selection of a level of a hierarchical structure associated with the request for the recommendation of content; based on the selected level, determining one or more proxy keywords associated with one or more keywords of the request; generating a representative query based on i) the one or more proxy keywords and ii) the request for the recommendation of content; determining, based on the representative query, a portion of the classified public content stored on a server appliance or the repository that is communicably coupled to the server appliance; determining, based on the request, a portion of the private content stored on the client appliance or the repository that is communicably coupled to the client appliance; and preparing, for presentation to the user, the portion of the classified public content based on the representative query and the portion of the private content based on the request for the recommendation of content. 5. The computer-implemented method of claim 1 , further comprising: identifying public content communicably exposed to the server appliance, the public content comprising a plurality of electronic documents; generating a plurality of model parameters based on a topic model process performed on the plurality of electronic documents; and classifying the public content based on the model parameters to generate the classified public content. | 0.5 |
7,694,315 | 1 | 3 | 1. A method for facilitating extension of application functionality by generating one or more application programming interfaces (API) on a computing device that facilitate document development using domain terminology rather than native terminology of a host application, the method comprising: accessing a schema component, using a processor of the computing device, the schema component including a schema element representative of at least one domain terminology term of one or more problems for solving in a host application, wherein the at least one domain terminology term is different from native terminology utilized in a general API of the host application, wherein the native terminology identifies elements by at least one of cell address or range, and the domain terminology identifies the same elements with textual descriptive terms; mapping the schema element to a construct of the general API of the host application, using a mapping component executed by the processor such that the domain terminology that includes the textual descriptive terms maps to the native terminology that includes the at least one of cell address or range information, thereby enabling the host application to operate on the domain terminology utilizing the textual descriptive terms; and generating a new API based upon the mapping created by the mapping component, using a generating component executed by the processor, wherein the new API interfacing with the host application and facilitating document development using the textual descriptive terms of the domain terminology in the host application in lieu of the cell address or range information of the native terminology of the host application. | 1. A method for facilitating extension of application functionality by generating one or more application programming interfaces (API) on a computing device that facilitate document development using domain terminology rather than native terminology of a host application, the method comprising: accessing a schema component, using a processor of the computing device, the schema component including a schema element representative of at least one domain terminology term of one or more problems for solving in a host application, wherein the at least one domain terminology term is different from native terminology utilized in a general API of the host application, wherein the native terminology identifies elements by at least one of cell address or range, and the domain terminology identifies the same elements with textual descriptive terms; mapping the schema element to a construct of the general API of the host application, using a mapping component executed by the processor such that the domain terminology that includes the textual descriptive terms maps to the native terminology that includes the at least one of cell address or range information, thereby enabling the host application to operate on the domain terminology utilizing the textual descriptive terms; and generating a new API based upon the mapping created by the mapping component, using a generating component executed by the processor, wherein the new API interfacing with the host application and facilitating document development using the textual descriptive terms of the domain terminology in the host application in lieu of the cell address or range information of the native terminology of the host application. 3. The method of claim 1 , further comprising: using a separation component to generate a data island in a document of the host application; making the data island in the document of the host application editable without launching of the host application; and synchronizing contents of the data island and the document, such that the document is updated with modified information of the data island when the document is launched within the host application. | 0.5 |
9,373,075 | 6 | 7 | 6. A computer program product comprising a non-transitory 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: provide a sentiment analysis model to a sentiment analysis algorithm; train the sentiment analysis model using a genetic algorithm based on a training corpus of documents with corresponding desired sentiment analysis values for a given domain to form a trained sentiment analysis model; wherein training the sentiment analysis model comprises for each given training document in the training corpus: performing the sentiment analysis algorithm on the given training document to form a sentiment analysis result; making modifications to the sentiment analysis model to form individual models; identifying a best fitness individual model from the plurality of individual models using the genetic algorithm, wherein the best fitness individual model minimizes a distance from desired sentiment analysis values corresponding to the given training document, wherein fitness of each individual model is based on an absolute value of distance from a generated sentiment value to a desired sentiment value weighted by an amount of change from an initial value in the sentiment analysis model; and storing the best fitness individual model as the trained sentiment analysis model; perform the sentiment analysis algorithm on an input document using the trained sentiment analysis model to form a domain-specific sentiment analysis result; and output the domain-specific sentiment analysis result; provide the domain-specific sentiment analysis result to a question answering system; and perform analysis of an input question or a candidate answer in the question answering system using the domain-specific sentiment analysis result. | 6. A computer program product comprising a non-transitory 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: provide a sentiment analysis model to a sentiment analysis algorithm; train the sentiment analysis model using a genetic algorithm based on a training corpus of documents with corresponding desired sentiment analysis values for a given domain to form a trained sentiment analysis model; wherein training the sentiment analysis model comprises for each given training document in the training corpus: performing the sentiment analysis algorithm on the given training document to form a sentiment analysis result; making modifications to the sentiment analysis model to form individual models; identifying a best fitness individual model from the plurality of individual models using the genetic algorithm, wherein the best fitness individual model minimizes a distance from desired sentiment analysis values corresponding to the given training document, wherein fitness of each individual model is based on an absolute value of distance from a generated sentiment value to a desired sentiment value weighted by an amount of change from an initial value in the sentiment analysis model; and storing the best fitness individual model as the trained sentiment analysis model; perform the sentiment analysis algorithm on an input document using the trained sentiment analysis model to form a domain-specific sentiment analysis result; and output the domain-specific sentiment analysis result; provide the domain-specific sentiment analysis result to a question answering system; and perform analysis of an input question or a candidate answer in the question answering system using the domain-specific sentiment analysis result. 7. The computer program product of claim 6 , wherein making modifications to the sentiment analysis model using the genetic algorithm comprises modifying rules or token values in the sentiment analysis model. | 0.5 |
9,633,004 | 7 | 10 | 7. The method of claim 1 , further comprising: identifying a second type of concept referred to by the primary user intent; identifying a second substring from the textual representation corresponding to the second type of concept; and determining a secondary user intent for the second substring, wherein performing the task flow is further based on the secondary user intent for the second substring. | 7. The method of claim 1 , further comprising: identifying a second type of concept referred to by the primary user intent; identifying a second substring from the textual representation corresponding to the second type of concept; and determining a secondary user intent for the second substring, wherein performing the task flow is further based on the secondary user intent for the second substring. 10. The method of claim 7 , wherein determining the secondary user intent for the second substring comprises: determining a confidence score for a plurality of interpretations of the second substring; and determining the secondary user intent for the second substring based on an interpretation of the plurality of interpretations of the second substring having the highest confidence score. | 0.531175 |
6,088,707 | 12 | 30 | 12. A computer system, comprising: (a) a computer display; and (b) a processor, coupled to the computer display and configured to display on the computer display a first hypertext document including at least one hypertext link definition that points to a second hypertext document, the processor further configured to maintain status information associated with a previous copy of the second hypertext document, determine whether the second hypertext document has been updated by comparing status information for the second hypertext document with that of the previous copy of the second hypertext document, and to indicate within the first hypertext document whether the second hypertext document has been updated since a predetermined time, wherein the status information associated with the previous copy of the second hypertext document is selected from the group consisting of a checksum, a document size, an author, an area selection within the previous copy of the second hypertext document, a keyword search expression, a numeric expression, a numeric threshold, a keyword list, and combinations thereof. | 12. A computer system, comprising: (a) a computer display; and (b) a processor, coupled to the computer display and configured to display on the computer display a first hypertext document including at least one hypertext link definition that points to a second hypertext document, the processor further configured to maintain status information associated with a previous copy of the second hypertext document, determine whether the second hypertext document has been updated by comparing status information for the second hypertext document with that of the previous copy of the second hypertext document, and to indicate within the first hypertext document whether the second hypertext document has been updated since a predetermined time, wherein the status information associated with the previous copy of the second hypertext document is selected from the group consisting of a checksum, a document size, an author, an area selection within the previous copy of the second hypertext document, a keyword search expression, a numeric expression, a numeric threshold, a keyword list, and combinations thereof. 30. The computer system of claim 12, wherein the status information associated with the previous copy of the second hypertext document includes a keyword list. | 0.919371 |
9,424,522 | 1 | 2 | 1. An information processing system comprising: a working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology; and a reasoning system comprising a plurality of reasoning modules which are configured to process different ones of the abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different. | 1. An information processing system comprising: a working memory comprising a semantic graph which comprises a plurality of abstractions, wherein the abstractions individually include an individual which is defined according to an ontology; and a reasoning system comprising a plurality of reasoning modules which are configured to process different ones of the abstractions of the semantic graph, wherein a first of the reasoning modules is configured to process a plurality of abstractions which include individuals of a first classification type of the ontology and a second of the reasoning modules is configured to process a plurality of abstractions which include individuals of a second classification type of the ontology, wherein the first and second classification types are different. 2. The system of claim 1 further comprising a plurality of reifiers configured to assert the plurality of abstractions including the individuals of the first and second classification types into the semantic graph. | 0.738386 |
7,716,224 | 6 | 13 | 6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. | 6. A method, implemented at least partially by a handheld electronic book reader device, the method comprising: under control of one or more systems of the handheld electronic book reader device configured with executable instructions, generating a searchable item index of terms in an electronic item; and generating a searchable master index of terms in the electronic item and other electronic items in a collection of electronic items stored in memory of the handheld electronic book reader device, wherein the master index comprises a list of terms used in electronic items in the collection and, for each term, a reference to one or more item index entries for the respective term, and wherein each reference to an item index entry comprises an identifier of the electronic item in which the term appears, a number of times the term appears in the respective electronic item, and a position at which the term is indexed in the item index for the respective electronic item. 13. The method of claim 6 , wherein the master index of terms is organized alphabetically. | 0.833333 |
8,239,299 | 1 | 7 | 1. A computer-implemented system that facilitates data management, comprising: at least one processor; a type component of a financial intelligence system that executes on the at least one processor to create and assign types to system entities, the types associated with behaviors defined by member properties; a rules component that executes on the at least one processor to generate rules based on the types; a type content component that executes on the at least one processor to store the rules as a hierarchy of classes, the hierarchy of classes including a tree of application types and, for each application type in the tree, a set of rules associated with the application type; a type creator component that performs a depth-first traversal of the rules of at least one application type in the tree of application types to create an instance of the at least one application type; and a runtime engine that executes on the at least one processor to generate an application that employs the behaviors based on execution of the rules associated with the instance of the at least one application type. | 1. A computer-implemented system that facilitates data management, comprising: at least one processor; a type component of a financial intelligence system that executes on the at least one processor to create and assign types to system entities, the types associated with behaviors defined by member properties; a rules component that executes on the at least one processor to generate rules based on the types; a type content component that executes on the at least one processor to store the rules as a hierarchy of classes, the hierarchy of classes including a tree of application types and, for each application type in the tree, a set of rules associated with the application type; a type creator component that performs a depth-first traversal of the rules of at least one application type in the tree of application types to create an instance of the at least one application type; and a runtime engine that executes on the at least one processor to generate an application that employs the behaviors based on execution of the rules associated with the instance of the at least one application type. 7. The system of claim 1 , further comprising a type constraint checker for checking that the rules are valid for a given model. | 0.683168 |
8,579,288 | 5 | 6 | 5. A method of administrating a math game comprises the steps of: providing a set of game pieces, wherein the set of game pieces comprises a bubble pop machine, a plurality of bubble pop bags, a plurality of tokens, a plurality of scrolls, an equation pad, a master pad, a plurality of printed math expressions, and a plurality of printed math equations; providing a plurality of players; dividing the plurality of players into a plurality of groups, wherein the plurality of groups each comprise a subset of the plurality of players; placing the equation pad so that is visible by the plurality of players; placing the master pad in a central area; dividing the plurality of bubble pop bags between the plurality of players; dividing the plurality of scrolls between the plurality of players; placing the plurality of tokens into the bubble pop machine; activating the bubble pop machine in order to eject the plurality of tokens from the bubble pop machine; instructing the plurality of players to move and collect the plurality of tokens; assembling the plurality of players around the master pad; giving each of the plurality of players a turn and directing the plurality of players to match the plurality of tokens to the master pad during the turn; awarding a point for correctly matching the plurality of tokens to the master pad; and declaring a particular group from the plurality of groups with the most points to be the winner. | 5. A method of administrating a math game comprises the steps of: providing a set of game pieces, wherein the set of game pieces comprises a bubble pop machine, a plurality of bubble pop bags, a plurality of tokens, a plurality of scrolls, an equation pad, a master pad, a plurality of printed math expressions, and a plurality of printed math equations; providing a plurality of players; dividing the plurality of players into a plurality of groups, wherein the plurality of groups each comprise a subset of the plurality of players; placing the equation pad so that is visible by the plurality of players; placing the master pad in a central area; dividing the plurality of bubble pop bags between the plurality of players; dividing the plurality of scrolls between the plurality of players; placing the plurality of tokens into the bubble pop machine; activating the bubble pop machine in order to eject the plurality of tokens from the bubble pop machine; instructing the plurality of players to move and collect the plurality of tokens; assembling the plurality of players around the master pad; giving each of the plurality of players a turn and directing the plurality of players to match the plurality of tokens to the master pad during the turn; awarding a point for correctly matching the plurality of tokens to the master pad; and declaring a particular group from the plurality of groups with the most points to be the winner. 6. The method of administering a math game as claimed in claim 5 further comprises the steps of: forming the groups by calling out a particular printed identifier from a plurality of printed identifiers, wherein the plurality of printed identifiers are located on the plurality of printed bubble pop bags; and wherein each of the plurality of printed identifiers comprises a shape, a color, and a number. | 0.671545 |
9,818,401 | 19 | 20 | 19. The method of claim 18 , wherein said adaptation object comprises an adaptation grammar. | 19. The method of claim 18 , wherein said adaptation object comprises an adaptation grammar. 20. The method of claim 19 , wherein said adaptation grammar comprises a slotted adaptation grammar. | 0.9631 |
7,533,172 | 1 | 4 | 1. A peer-to-peer network system, comprising: a plurality of peers, wherein each peer comprises a network node configured to communicate with one or more other ones of said peers over one or more networks; a plurality of peer services or content provided by one or more of said peers; a service or content advertisement for each of said services or content, wherein each service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; a peer advertisement for each of said peers, wherein each peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein one or more of said peers are configured to publish their corresponding peer advertisements and one or more of said service or content advertisements in the peer-to-peer network system to be discoverable by other peers; and wherein each advertisement is a separate programming language independent metadata document. | 1. A peer-to-peer network system, comprising: a plurality of peers, wherein each peer comprises a network node configured to communicate with one or more other ones of said peers over one or more networks; a plurality of peer services or content provided by one or more of said peers; a service or content advertisement for each of said services or content, wherein each service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; a peer advertisement for each of said peers, wherein each peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein one or more of said peers are configured to publish their corresponding peer advertisements and one or more of said service or content advertisements in the peer-to-peer network system to be discoverable by other peers; and wherein each advertisement is a separate programming language independent metadata document. 4. The peer-to-peer network system as recited in claim 1 , further comprising: a plurality of peer groups, wherein each peer group comprises a plurality of said peers; and a peer group advertisement for each said peer group, wherein each peer group advertisement comprises an identification of a corresponding peer group and an indication of a common set of services available to members of that peer group. | 0.618914 |
8,959,523 | 16 | 18 | 16. The computer program product as described in claim 15 wherein the bin packing problem is solved at each level of the hierarchical tree using virtual machine-to-physical entity constraints associated with that level and the placement algorithm. | 16. The computer program product as described in claim 15 wherein the bin packing problem is solved at each level of the hierarchical tree using virtual machine-to-physical entity constraints associated with that level and the placement algorithm. 18. The computer program product as described in claim 16 wherein the placement algorithm used at a first level differs from the placement algorithm used at a second level. | 0.643154 |
9,063,753 | 1 | 12 | 1. A method comprising: storing a business object at a business object infrastructure repository, the business object having a plurality of nodes, including at least one exit node associated with a code snippet written in a programming language; responsive to a request received from a client device, executing the business object at a processing framework until the exit node is reached; loading, from the repository, the code snippet that is written in the programming language and associated with the exit node; selecting a virtual machine interpreter, from a plurality of virtual machine interpreters, for the code snippet that is associated with the exit node of the business object based on the programming language of the code snippet that is associated with the exit node of the business object; calling the code snippet via the selected virtual machine interpreter; and returning to the business object via the exit node and resuming execution of the business object; wherein the exit node that is included in the business object and associated with the code snippet written in the programming language is a first exit node that is included in the business object and associated with a first code snippet written in a first programming language; wherein the loading, from the repository, the code snippet that is written in the programming language and associated with the exit node comprises: loading, from the repository, the first code snippet that is written in the first programming language and associated with the first exit node; wherein the selecting a virtual machine interpreter, from a plurality of virtual machine interpreters, for the code snippet based on the programming language of the code snippet comprises: selecting a first virtual machine interpreter for the first code snippet based on the first programming language of the first code snippet; and wherein the returning to the business object via the exit node and resuming execution of the business object comprises: returning to the business object via the first exit node and resuming execution of the business object until a second exit node of the business object is reached, the second exit node of the business object being associated with a second code snippet written in a second programming language that is different than the first programming language in which the first code snippet that is associated with the first exit node of the business object is written. | 1. A method comprising: storing a business object at a business object infrastructure repository, the business object having a plurality of nodes, including at least one exit node associated with a code snippet written in a programming language; responsive to a request received from a client device, executing the business object at a processing framework until the exit node is reached; loading, from the repository, the code snippet that is written in the programming language and associated with the exit node; selecting a virtual machine interpreter, from a plurality of virtual machine interpreters, for the code snippet that is associated with the exit node of the business object based on the programming language of the code snippet that is associated with the exit node of the business object; calling the code snippet via the selected virtual machine interpreter; and returning to the business object via the exit node and resuming execution of the business object; wherein the exit node that is included in the business object and associated with the code snippet written in the programming language is a first exit node that is included in the business object and associated with a first code snippet written in a first programming language; wherein the loading, from the repository, the code snippet that is written in the programming language and associated with the exit node comprises: loading, from the repository, the first code snippet that is written in the first programming language and associated with the first exit node; wherein the selecting a virtual machine interpreter, from a plurality of virtual machine interpreters, for the code snippet based on the programming language of the code snippet comprises: selecting a first virtual machine interpreter for the first code snippet based on the first programming language of the first code snippet; and wherein the returning to the business object via the exit node and resuming execution of the business object comprises: returning to the business object via the first exit node and resuming execution of the business object until a second exit node of the business object is reached, the second exit node of the business object being associated with a second code snippet written in a second programming language that is different than the first programming language in which the first code snippet that is associated with the first exit node of the business object is written. 12. The method of claim 1 , wherein the business object that includes the exit node is customized by the code snippet that is associated with the exit node of the business object. | 0.902505 |
4,602,152 | 3 | 4 | 3. A bar code information source as set forth in claim 2, wherein only bar code words with the predetermined number of bits of data in which a preponderance of said first bar spaces occurs as compared to said second bar spaces are present. | 3. A bar code information source as set forth in claim 2, wherein only bar code words with the predetermined number of bits of data in which a preponderance of said first bar spaces occurs as compared to said second bar spaces are present. 4. A bar code information source as set forth in claim 3, wherein said first bar spaces are respectively representative of "one", and said second bar spaces are respectively representative of "zero". | 0.5 |
10,102,288 | 1 | 5 | 1. An apparatus, comprising: a processor circuit; and a server application for execution by the processor circuit, the server application comprising: a query processing component to receive a first search query from a first user comprising one or more search terms; a search component to provide search results for the first search query in a search result list, the search result list comprising one or more search result items; and a topic board component to manage a writable topic board for the first search query, the writable topic board being part of a user interface view of a client application and comprising one or more search result items as shared documents that can be modified by and shared among multiple users, wherein the one or more search result items are search results from a second search query of a second user, wherein the topic board component receives a control directive from a first client application associated with the first user to share at least one document, from the one or more search results, with a second client application associated with the second user such that the user interface view associated with the writable topic board displays the at least one document. | 1. An apparatus, comprising: a processor circuit; and a server application for execution by the processor circuit, the server application comprising: a query processing component to receive a first search query from a first user comprising one or more search terms; a search component to provide search results for the first search query in a search result list, the search result list comprising one or more search result items; and a topic board component to manage a writable topic board for the first search query, the writable topic board being part of a user interface view of a client application and comprising one or more search result items as shared documents that can be modified by and shared among multiple users, wherein the one or more search result items are search results from a second search query of a second user, wherein the topic board component receives a control directive from a first client application associated with the first user to share at least one document, from the one or more search results, with a second client application associated with the second user such that the user interface view associated with the writable topic board displays the at least one document. 5. The apparatus of claim 1 , wherein the topic board component maps the first and second search queries to a query board. | 0.725225 |
9,697,186 | 1 | 3 | 1. A method comprising: extracting a portion of style information from at least one source of style information, the portion of style information extracted corresponding to content that is identified by a user for copying from a source document, at least some of the style information being demarcated separately from the user-identified content, and the portion of style information being extracted from a source of style information that is external to the source document from which the user-identified content is identified responsive to a determination that the at least one source of style information includes an external source of style information; storing the portion of style information that is extracted with the user-identified content that is extracted in a clipboard store; and responsive to input to paste at least one portion of the stored content at a specified location within a target document, reconstructing the at least one portion of stored content at the specified location using the extracted portion of style information to have a same visual appearance at the specified location as in the source document. | 1. A method comprising: extracting a portion of style information from at least one source of style information, the portion of style information extracted corresponding to content that is identified by a user for copying from a source document, at least some of the style information being demarcated separately from the user-identified content, and the portion of style information being extracted from a source of style information that is external to the source document from which the user-identified content is identified responsive to a determination that the at least one source of style information includes an external source of style information; storing the portion of style information that is extracted with the user-identified content that is extracted in a clipboard store; and responsive to input to paste at least one portion of the stored content at a specified location within a target document, reconstructing the at least one portion of stored content at the specified location using the extracted portion of style information to have a same visual appearance at the specified location as in the source document. 3. The method as recited in claim 1 , wherein the at least one source of style information is inline in the source document with the identified content. | 0.731449 |
7,739,213 | 1 | 3 | 1. A method for capturing expert knowledge and data comprising: receiving by a processing device expert knowledge and data entered via an editing device; storing the received expert knowledge and data into one or more tables of a database system, a first subset of the data being represented in the one or more tables as conclusion data, a second subset of the data being represented as observation data, and a third subset of the data being represented as relationship data; and generating by the processing device, based on the one or more tables, a probabilistic model that captures the entered expert knowledge and data, the probabilistic model including a structure of layers of nodes with at least one grouping layer disposed in-between a conclusion layer having a plurality of conclusion nodes designated as parent nodes and formed based on the stored conclusion data, and an evidence layer having a plurality of observation nodes designated as children nodes and formed based on the stored observation data, wherein a group node in the at least one grouping layer represents an aggregation of conclusions in two or more of the conclusion nodes in the conclusion layer, wherein the structure of layers of nodes includes directed arcs between the nodes based on the stored relationship data, with none of the directed arcs connecting two nodes in a same layer, and wherein at least one of the arcs is between the group node and at least one of the plurality of observation nodes, wherein, the generated probabilistic model is configured to be invoked by a reasoning engine for outputting probabilities of one or more conclusions or aggregation of the conclusions, in response to input observations, during a decision making process. | 1. A method for capturing expert knowledge and data comprising: receiving by a processing device expert knowledge and data entered via an editing device; storing the received expert knowledge and data into one or more tables of a database system, a first subset of the data being represented in the one or more tables as conclusion data, a second subset of the data being represented as observation data, and a third subset of the data being represented as relationship data; and generating by the processing device, based on the one or more tables, a probabilistic model that captures the entered expert knowledge and data, the probabilistic model including a structure of layers of nodes with at least one grouping layer disposed in-between a conclusion layer having a plurality of conclusion nodes designated as parent nodes and formed based on the stored conclusion data, and an evidence layer having a plurality of observation nodes designated as children nodes and formed based on the stored observation data, wherein a group node in the at least one grouping layer represents an aggregation of conclusions in two or more of the conclusion nodes in the conclusion layer, wherein the structure of layers of nodes includes directed arcs between the nodes based on the stored relationship data, with none of the directed arcs connecting two nodes in a same layer, and wherein at least one of the arcs is between the group node and at least one of the plurality of observation nodes, wherein, the generated probabilistic model is configured to be invoked by a reasoning engine for outputting probabilities of one or more conclusions or aggregation of the conclusions, in response to input observations, during a decision making process. 3. The method of claim 1 , wherein the structure of layers of nodes further comprises one or more other directed arcs, each of the other directed arcs originating at a node of the conclusion layer and ending at a node of the evidence layer. | 0.871932 |
8,700,547 | 17 | 18 | 17. The method according to claim 14 , further comprising: characterizing clustering of the at least three different types of objects using at least three different tentative cluster characterization matrices, respectively; and iteratively improving each tentative cluster characterization matrix using linear combinations of the associated feature matrix and the associated relation matrix other matrices. | 17. The method according to claim 14 , further comprising: characterizing clustering of the at least three different types of objects using at least three different tentative cluster characterization matrices, respectively; and iteratively improving each tentative cluster characterization matrix using linear combinations of the associated feature matrix and the associated relation matrix other matrices. 18. The method according to claim 17 , wherein during each iteration, a tentative cluster matrix is updated as the k leading eigenvectors of the linear combinations. | 0.5 |
9,183,835 | 1 | 2 | 1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising carrying out a completed speech session via a mobile device without any physical interaction with the mobile device, wherein the speech session includes receiving a speech input from a user, processing the speech input into speech recognition results using an automatic speech recognition (ASR) process, identifying a primary session context from the speech recognition results, identifying an ancillary session context from the; recognition results, obtaining service results responsive to both the primary session context and the ancillary session context identified from the speech recognition results, and providing the service results to the user. | 1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising carrying out a completed speech session via a mobile device without any physical interaction with the mobile device, wherein the speech session includes receiving a speech input from a user, processing the speech input into speech recognition results using an automatic speech recognition (ASR) process, identifying a primary session context from the speech recognition results, identifying an ancillary session context from the; recognition results, obtaining service results responsive to both the primary session context and the ancillary session context identified from the speech recognition results, and providing the service results to the user. 2. The method set forth in claim 1 , wherein the method further comprises carrying out the speech session using the steps of: (a) receiving the speech input at the mobile device via a short range wireless connection; (b) identifying a cloud service associated with the primary session context or the ancillary session context; (c) sending a service request to the cloud service; (d) receiving the service result from the cloud service; (e) generating a speech response using the service result; and (f) sending the speech response as audio speech from the mobile device via the short range wireless connection. | 0.5 |
8,972,958 | 9 | 10 | 9. The method of claim 8 , wherein the adapting the custom instruction description file for hardware timing of the reconfigurable processor comprises: implementing timing constraints, from a timing manager timing constraint set, based upon hardware timing of the reconfigurable processor. | 9. The method of claim 8 , wherein the adapting the custom instruction description file for hardware timing of the reconfigurable processor comprises: implementing timing constraints, from a timing manager timing constraint set, based upon hardware timing of the reconfigurable processor. 10. The method of claim 9 , wherein the timing constraints are based upon physical timing of reconfigurable processor capabilities. | 0.5 |
8,745,055 | 10 | 15 | 10. A computer implemented method of clustering documents, the method comprising: generating document vectors for each of a plurality of documents of a corpus, wherein each document vector comprises a plurality of terms from the corresponding document and a frequency score for each term; generating a plurality of reference vectors based on the document vectors, wherein each reference vector comprises a plurality of terms from the document vectors and a frequency score for each term, wherein the frequency score for each term in each reference vector comprises a random or pseudo-random value; comparing the document vectors to each of the reference vectors to generate similarity values for each of the document vectors; sorting the document vectors based on the similarity values for the document vectors to form a sorted list; and forming clusters of documents based on the similarity values between adjacent document vectors in the sorted list. | 10. A computer implemented method of clustering documents, the method comprising: generating document vectors for each of a plurality of documents of a corpus, wherein each document vector comprises a plurality of terms from the corresponding document and a frequency score for each term; generating a plurality of reference vectors based on the document vectors, wherein each reference vector comprises a plurality of terms from the document vectors and a frequency score for each term, wherein the frequency score for each term in each reference vector comprises a random or pseudo-random value; comparing the document vectors to each of the reference vectors to generate similarity values for each of the document vectors; sorting the document vectors based on the similarity values for the document vectors to form a sorted list; and forming clusters of documents based on the similarity values between adjacent document vectors in the sorted list. 15. The method of claim 10 , wherein the step of sorting the document vectors comprises sorting the document vectors in descending order by the similarity values. | 0.554945 |
7,620,614 | 6 | 8 | 6. The method according to claim 5 , wherein the cross-document structure priority information includes a retrieval count of a structure that is taken of, at every time specified in the query condition, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit in a descending order of the retrieval count of the structure, and stores the extracted data onto the first storage unit. | 6. The method according to claim 5 , wherein the cross-document structure priority information includes a retrieval count of a structure that is taken of, at every time specified in the query condition, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit in a descending order of the retrieval count of the structure, and stores the extracted data onto the first storage unit. 8. The method according to claim 6 , wherein the cross-document structure priority information includes at least one of information regarding registered data structures, which are those to be preferentially stored on the first storage unit, and information regarding excluded data structures which are those not to be stored on the fist storage unit, wherein the information regarding the registered data structures and the information regarding the excluded data structures are both received through the input unit, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit, based on one of the information regarding registered data structures and the information regarding excluded data structures, and stores the extracted data onto the first storage unit as the partial documents of the documents to be retrieved. | 0.5 |
9,129,020 | 8 | 13 | 8. A computer-readable medium bearing computer-executable instructions which, when executed on a computing system comprising at least a processor executing instructions retrieved from the medium, carry out a method for responding to a search query from a user, the method comprising: obtaining network navigation data of a first plurality of computer users, and for each of the first plurality of computer users: identifying a set of interest circles corresponding to the computer user based on the computer user's network navigation data; and storing the set of interest circles in an interest circles store in association with the computer user; receiving a search query from a requesting computer user, the search query being directed to a query topic; obtaining a set of search results responsive to the search query; and determining whether the requesting user has an interest circle corresponding to the query topic and, upon the condition of determining that the requesting user does not have an interest circle corresponding to the query topic: identifying a second plurality of computer users, each of the second plurality of computer users being identified as having an established interest circle corresponding to the query topic, wherein identifying the second plurality of computer users comprises identifying the second plurality of computer users irrespective of any user-established relationship with the requesting computer user; ordering the set of search results according to the interest circles of the identified second plurality of computer users; and returning higher ordered search results to the requesting computer user. | 8. A computer-readable medium bearing computer-executable instructions which, when executed on a computing system comprising at least a processor executing instructions retrieved from the medium, carry out a method for responding to a search query from a user, the method comprising: obtaining network navigation data of a first plurality of computer users, and for each of the first plurality of computer users: identifying a set of interest circles corresponding to the computer user based on the computer user's network navigation data; and storing the set of interest circles in an interest circles store in association with the computer user; receiving a search query from a requesting computer user, the search query being directed to a query topic; obtaining a set of search results responsive to the search query; and determining whether the requesting user has an interest circle corresponding to the query topic and, upon the condition of determining that the requesting user does not have an interest circle corresponding to the query topic: identifying a second plurality of computer users, each of the second plurality of computer users being identified as having an established interest circle corresponding to the query topic, wherein identifying the second plurality of computer users comprises identifying the second plurality of computer users irrespective of any user-established relationship with the requesting computer user; ordering the set of search results according to the interest circles of the identified second plurality of computer users; and returning higher ordered search results to the requesting computer user. 13. The computer-readable medium of claim 8 , wherein the requesting computer user is one of the first plurality of computer users. | 0.89685 |
7,555,477 | 8 | 13 | 8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. | 8. A computerized method for providing relevant paid content, the method comprising: receiving a search request; determining a plurality of contextual uses associated with the search request, wherein contextual uses comprise majority and minority contextual uses associated with the search request; determining type of content suitable to represent each of the determined contextual uses; and identifying at least one paid content relevant for each of the determined contextual uses. 13. The method of claim 8 , wherein the paid content comprises at least a link to a web site. | 0.901274 |
8,209,175 | 8 | 9 | 8. The method for content sensing a user's communication of claim 1 , wherein the first uncertainty value generated for the first content word is a result of subtracting the first certainty value generated for the first content word from one. | 8. The method for content sensing a user's communication of claim 1 , wherein the first uncertainty value generated for the first content word is a result of subtracting the first certainty value generated for the first content word from one. 9. The method for content sensing a user's communication of claim 8 , wherein the second uncertainty value generated for the first content word is a result of multiplying the first uncertainty value generated for the first content word by one minus the second certainty value generated for the first content word. | 0.5 |
9,880,997 | 14 | 19 | 14. A method, comprising: obtaining, by a device, information identifying type classifications via an interface or from a memory, the interface including one or more of a communication interface or a user interface, each type classification, of the type classifications, indicating that terms classified under the type classification are expressed by a particular type of value of a plurality of types of values, the plurality of types of values including character strings and numeric values; obtaining, by the device and via the interface, text to be processed to infer one or more type classifications associated with unique terms, the text being included in a file associated with development of a computer program for a computer system, and each respective term, of the terms, being associated with a plurality of different possible values of a same type classification of the one or more type classifications; standardizing, by the device, the text to prepare the text for processing by adjusting at least one character in the text of the file; processing, by the device, the text that has been standardized to identify terms in the text based on delimiting characters in the text; associating, by the device, at least one tag with the identified terms in the text, the at least one tag being one or more of a part-of-speech tag, an entity tag, or a term tag; extracting, by the device and based on the at least one tag associated with the terms, one or more terms, of the terms identified in the text, as unique terms for which to infer the one or more type classifications, a quantity of the unique terms being fewer than a quantity of the terms identified in the text; generating a data structure that stores the unique terms; inferring, by the device, a type relationship between a particular term, of the unique terms stored in the data structure, and a particular type classification, of the one or more type classifications, by performing one or more type classification techniques, the one or more type classification techniques including at least one of: a name-based analysis that compares the particular term to a set of name-based type indicators associated with the particular type classification, a context-based analysis that compares a modifier, that modifies the particular term, to a set of context-based type indicators associated with the particular type classification, a synonym-based analysis that compares a synonym, of the particular term, to the set of name-based type indicators associated with the particular type classification, or a value-based analysis that compares a value, that appears within a threshold proximity of the particular term, to a set of value-based type indicators or a set of value-based type patterns associated with the particular type classification; classifying, by the device, the unique terms by assigning the one or more type classifications to the unique terms based on performing the one or more type classification techniques; providing, for display via the interface and by the device, information associated with development of the computer program, the information associated with development of the computer program identifying the type relationship, between the particular term and the particular type classification, based on inferring the type relationship and further based on performing the one or more type classification techniques; receiving, via the interface and by the device, a set of test data rules from a user or from another device; generating, by the device, test data based on the set of test data rules, the test data including the unique terms to be classified, type classifications under which the unique terms are to be classified, and values for the unique terms; applying, by the device, the test data to the computer program, the computer program being designed based on the text that was processed to infer one or more type classifications for the unique terms extracted from the text, and the applying of the test data to the computer program includes input of the test data to the computer program and executing the computer program to: classify the test data to obtain a confidence score associated with the classifying a unique term, of the unique terms, under each of the type classifications determined to be associated with the unique term; and providing, by the device and for display to the user or to another device, the test data, the one or more type classifications generated from the test data, and the confidence score associated with the one or more type classifications. | 14. A method, comprising: obtaining, by a device, information identifying type classifications via an interface or from a memory, the interface including one or more of a communication interface or a user interface, each type classification, of the type classifications, indicating that terms classified under the type classification are expressed by a particular type of value of a plurality of types of values, the plurality of types of values including character strings and numeric values; obtaining, by the device and via the interface, text to be processed to infer one or more type classifications associated with unique terms, the text being included in a file associated with development of a computer program for a computer system, and each respective term, of the terms, being associated with a plurality of different possible values of a same type classification of the one or more type classifications; standardizing, by the device, the text to prepare the text for processing by adjusting at least one character in the text of the file; processing, by the device, the text that has been standardized to identify terms in the text based on delimiting characters in the text; associating, by the device, at least one tag with the identified terms in the text, the at least one tag being one or more of a part-of-speech tag, an entity tag, or a term tag; extracting, by the device and based on the at least one tag associated with the terms, one or more terms, of the terms identified in the text, as unique terms for which to infer the one or more type classifications, a quantity of the unique terms being fewer than a quantity of the terms identified in the text; generating a data structure that stores the unique terms; inferring, by the device, a type relationship between a particular term, of the unique terms stored in the data structure, and a particular type classification, of the one or more type classifications, by performing one or more type classification techniques, the one or more type classification techniques including at least one of: a name-based analysis that compares the particular term to a set of name-based type indicators associated with the particular type classification, a context-based analysis that compares a modifier, that modifies the particular term, to a set of context-based type indicators associated with the particular type classification, a synonym-based analysis that compares a synonym, of the particular term, to the set of name-based type indicators associated with the particular type classification, or a value-based analysis that compares a value, that appears within a threshold proximity of the particular term, to a set of value-based type indicators or a set of value-based type patterns associated with the particular type classification; classifying, by the device, the unique terms by assigning the one or more type classifications to the unique terms based on performing the one or more type classification techniques; providing, for display via the interface and by the device, information associated with development of the computer program, the information associated with development of the computer program identifying the type relationship, between the particular term and the particular type classification, based on inferring the type relationship and further based on performing the one or more type classification techniques; receiving, via the interface and by the device, a set of test data rules from a user or from another device; generating, by the device, test data based on the set of test data rules, the test data including the unique terms to be classified, type classifications under which the unique terms are to be classified, and values for the unique terms; applying, by the device, the test data to the computer program, the computer program being designed based on the text that was processed to infer one or more type classifications for the unique terms extracted from the text, and the applying of the test data to the computer program includes input of the test data to the computer program and executing the computer program to: classify the test data to obtain a confidence score associated with the classifying a unique term, of the unique terms, under each of the type classifications determined to be associated with the unique term; and providing, by the device and for display to the user or to another device, the test data, the one or more type classifications generated from the test data, and the confidence score associated with the one or more type classifications. 19. The method of claim 14 , where the one or more type classifications include at least one of: a numeric values type classification that indicates values associated with the respective term are represented by numeric values, or a floating point values type classification that indicates values associated with the respective term are represented by floating point values. | 0.676776 |
10,019,983 | 10 | 12 | 10. A computer system with a digital microprocessor and associated memory configured for executing software programs, the system being configured for predicting speech recognition performance, comprising: using a performance prediction module to determine at least one feature vector for an input into the speech recognition system, wherein the at least one feature vector includes features that comprise at least two features selected from the group comprising: the number of phonemes, the number of syllables, and the number of stressed vowels; creating a prediction model by: selecting a set of keywords; computing an other feature vector of desired features for each of the keywords; inputting the other feature vector into the model learning module, wherein the model learning module adjusts parameters to minimize a cost function; and saving the results from the model learning module as the prediction model for prediction of a figure of merit of the input; passing the at least one feature vector into the prediction model; using the performance prediction module to apply the prediction model to predict a figure of merit for the speech recognition system, wherein the figure of merit is indicative of the accuracy of performance of the speech recognition system, wherein the figure of merit Om) is predicted using a mathematical expression fom = ∑ i = 1 N a i ( x i - b i ) 2 N represents an upper limit on a number of features based on the determined feature vector used to learn the prediction, i represents the index of features, x i represents the i-th feature in the determined feature vector, and the equation parameters a and b are learned values; using the performance prediction module to report the predicted figure of merit for the speech recognition system performance; and adjusting the recognition engine based on the predicted figure of merit. | 10. A computer system with a digital microprocessor and associated memory configured for executing software programs, the system being configured for predicting speech recognition performance, comprising: using a performance prediction module to determine at least one feature vector for an input into the speech recognition system, wherein the at least one feature vector includes features that comprise at least two features selected from the group comprising: the number of phonemes, the number of syllables, and the number of stressed vowels; creating a prediction model by: selecting a set of keywords; computing an other feature vector of desired features for each of the keywords; inputting the other feature vector into the model learning module, wherein the model learning module adjusts parameters to minimize a cost function; and saving the results from the model learning module as the prediction model for prediction of a figure of merit of the input; passing the at least one feature vector into the prediction model; using the performance prediction module to apply the prediction model to predict a figure of merit for the speech recognition system, wherein the figure of merit is indicative of the accuracy of performance of the speech recognition system, wherein the figure of merit Om) is predicted using a mathematical expression fom = ∑ i = 1 N a i ( x i - b i ) 2 N represents an upper limit on a number of features based on the determined feature vector used to learn the prediction, i represents the index of features, x i represents the i-th feature in the determined feature vector, and the equation parameters a and b are learned values; using the performance prediction module to report the predicted figure of merit for the speech recognition system performance; and adjusting the recognition engine based on the predicted figure of merit. 12. The system of claim 10 , wherein the input comprises at least one word. | 0.823113 |
8,806,345 | 1 | 3 | 1. A non-transitory article of manufacture comprising computer readable instructions stored thereon which when executed by a processor cause a computing environment to: receive, from a remote computer system, a data stream containing information from at least one instance of a data object with a structure unknown to the computing environment, the data stream comprising: a header, wherein the header of the data stream includes metadata describing one or more structure elements of the data object, and a body, wherein the body of the data stream includes the information from the at least one instance of the data object; extract the information from the at least one instance of the data object from the body of the data stream in accordance with the one or more structure elements described in the metadata; and dynamically create a user interface (UI) based on the one or more structure elements of the data object, wherein the UI includes a first area to show the one or more structure elements based on a description in the metadata, a second area to present information from the at least one instance of the data object corresponding to a selected element from the one or more structure elements, and a UI control mechanism to allow a user to select the element of the one or more structure elements, and to change a structure of the selected element or the information from the at least one instance of the data object corresponding to the selected element. | 1. A non-transitory article of manufacture comprising computer readable instructions stored thereon which when executed by a processor cause a computing environment to: receive, from a remote computer system, a data stream containing information from at least one instance of a data object with a structure unknown to the computing environment, the data stream comprising: a header, wherein the header of the data stream includes metadata describing one or more structure elements of the data object, and a body, wherein the body of the data stream includes the information from the at least one instance of the data object; extract the information from the at least one instance of the data object from the body of the data stream in accordance with the one or more structure elements described in the metadata; and dynamically create a user interface (UI) based on the one or more structure elements of the data object, wherein the UI includes a first area to show the one or more structure elements based on a description in the metadata, a second area to present information from the at least one instance of the data object corresponding to a selected element from the one or more structure elements, and a UI control mechanism to allow a user to select the element of the one or more structure elements, and to change a structure of the selected element or the information from the at least one instance of the data object corresponding to the selected element. 3. The article of manufacture of claim 1 , comprising further computer readable instructions stored thereon which when executed by the processor cause the computing environment to: receive supplementary information in the header of the data stream related to the data object, wherein the supplementary information is selected from a group consisting of: a default value of a property of the data object; a start index indicating a position of an instance in an order of instances of the data object persisted in a computer system, wherein information from the instance with the start index position is included into the body of the data stream; a number of instances of the data object persisted in the computer system from which information is included in the body of the data stream; and a total number of instances of the data object persisted in the computer system. | 0.5 |
8,812,547 | 1 | 4 | 1. A method of detecting in a data stream a complex string of a complex dictionary comprising a set of complex strings, each complex string comprising at least one word in which each character is an indefinite character, the method comprising executing processor-readable instructions causing at least one processor to perform steps of: transforming said complex dictionary into: a segmented dictionary comprising a string prefix and string segments of each complex string in said complex dictionary, each string segment comprising a simple string and a segment suffix, said simple string containing characters defined in an alphabet; and a set of segment descriptors, each segment descriptor defining content of a corresponding string segment in said segmented dictionary; locating in said data stream selected simple strings defined in said segmented dictionary; selecting candidate string segments, from said segmented dictionary, containing said selected simple strings subject to ascertaining congruence of a portion of said data stream, succeeding each said selected simple string, and a segment suffix of a corresponding string segment in said segmented dictionary; and updating a state variable associated with said each complex string according to gauged spans in said data stream between successive positions at which simple strings belonging to said each complex string begin; determining, at each said position, a subset of said candidate string segments belonging to said each complex string; and correlating, at each said position, said state variable with locations, within said each complex string, of candidate string segments of said subset of said candidate string segments. | 1. A method of detecting in a data stream a complex string of a complex dictionary comprising a set of complex strings, each complex string comprising at least one word in which each character is an indefinite character, the method comprising executing processor-readable instructions causing at least one processor to perform steps of: transforming said complex dictionary into: a segmented dictionary comprising a string prefix and string segments of each complex string in said complex dictionary, each string segment comprising a simple string and a segment suffix, said simple string containing characters defined in an alphabet; and a set of segment descriptors, each segment descriptor defining content of a corresponding string segment in said segmented dictionary; locating in said data stream selected simple strings defined in said segmented dictionary; selecting candidate string segments, from said segmented dictionary, containing said selected simple strings subject to ascertaining congruence of a portion of said data stream, succeeding each said selected simple string, and a segment suffix of a corresponding string segment in said segmented dictionary; and updating a state variable associated with said each complex string according to gauged spans in said data stream between successive positions at which simple strings belonging to said each complex string begin; determining, at each said position, a subset of said candidate string segments belonging to said each complex string; and correlating, at each said position, said state variable with locations, within said each complex string, of candidate string segments of said subset of said candidate string segments. 4. The method of claim 1 wherein said locating is based on one of a generic trie-based search and an Aho-Corasick automaton. | 0.863736 |
8,024,326 | 5 | 8 | 5. The method of claim 1 , wherein the data associated with the first related query comprises an instance score for the first related query. | 5. The method of claim 1 , wherein the data associated with the first related query comprises an instance score for the first related query. 8. The method of claim 5 , wherein the instance score for the first related query comprises selections of any article provided in search results for the first related query in a context of the search query, wherein the selections are in the context of the search query when the selections are made within a threshold timing or sequencing of the search query being submitted to the computer system. | 0.5 |
9,858,358 | 1 | 6 | 1. A method performed by a data processing apparatus, the method comprising: receiving, during a current search session for a user device, a set of queries; identifying, as similar search sessions, multiple previous user search sessions based on a query path that the current search session shares with the similar search sessions, each similar search session including at least a threshold percentage of search queries that match search queries in the set of queries of the current search session; identifying, as concluding search queries, each search query that concluded at least one of the similar search sessions by being a final search query received during the at least one similar search session; determining, for each concluding search query, a popularity of the concluding search query based on a total number of the similar search sessions that the concluding search query concluded; selecting, from the concluding search queries and as a most popular query modification, a given concluding search query in response to (i) the popularity of the given search query being greater than the popularity of each other concluding search query and (ii) the popularity of the given concluding search query being greater than a suggestion threshold; and providing, to the user device, query suggestion data that initiates presentation of the given search query as the most popular query modification associated with the current search session at the user device. | 1. A method performed by a data processing apparatus, the method comprising: receiving, during a current search session for a user device, a set of queries; identifying, as similar search sessions, multiple previous user search sessions based on a query path that the current search session shares with the similar search sessions, each similar search session including at least a threshold percentage of search queries that match search queries in the set of queries of the current search session; identifying, as concluding search queries, each search query that concluded at least one of the similar search sessions by being a final search query received during the at least one similar search session; determining, for each concluding search query, a popularity of the concluding search query based on a total number of the similar search sessions that the concluding search query concluded; selecting, from the concluding search queries and as a most popular query modification, a given concluding search query in response to (i) the popularity of the given search query being greater than the popularity of each other concluding search query and (ii) the popularity of the given concluding search query being greater than a suggestion threshold; and providing, to the user device, query suggestion data that initiates presentation of the given search query as the most popular query modification associated with the current search session at the user device. 6. The method of claim 1 , wherein identifying, as similar search sessions, multiple previous search sessions comprises identifying, as the similar search sessions, each previous search session that includes all of the queries of the current search session. | 0.782203 |
10,067,933 | 1 | 6 | 1. A method of determining the origin or an area of influence of an author, comprising: providing a repository including non-transient computer readable storage medium; storing on the repository a plurality of areas, each area corresponding to a geospatial area in which a dialect is prevalent; storing on the repository a plurality of dialect components each associated with a language and one of the areas; receiving a text communication; determining the language of the text communication; identifying at least one dialect component associated with the language of the text communication is present in the text communication; retrieving the area to which the identified dialect component is associated; calculating a probability surface value according to P ij = 1 - ⋂ i = 1 n d ij l j . where P ij is a probability surface value for the area contained by dialect polygon i for language j, l j is an area contained within language area j, d ij is an area contained by dialect area i for language j, and ∩ represents intersection; and presenting representations of the retrieved areas and the probability surface value on a display. | 1. A method of determining the origin or an area of influence of an author, comprising: providing a repository including non-transient computer readable storage medium; storing on the repository a plurality of areas, each area corresponding to a geospatial area in which a dialect is prevalent; storing on the repository a plurality of dialect components each associated with a language and one of the areas; receiving a text communication; determining the language of the text communication; identifying at least one dialect component associated with the language of the text communication is present in the text communication; retrieving the area to which the identified dialect component is associated; calculating a probability surface value according to P ij = 1 - ⋂ i = 1 n d ij l j . where P ij is a probability surface value for the area contained by dialect polygon i for language j, l j is an area contained within language area j, d ij is an area contained by dialect area i for language j, and ∩ represents intersection; and presenting representations of the retrieved areas and the probability surface value on a display. 6. The method of claim 1 wherein a probability surface value is calculated and presented on the display. | 0.882883 |
9,817,677 | 15 | 16 | 15. One or more non-transitory computer storage devices having computer-executable instructions embodied thereon that, when executed, facilitate a method for rule based data driven validation, the method comprising: receiving over a communication network a target data object in a validation request from an executing software application; identifying one or more target data member items of the target data object based on stored data type definitions; identifying a data type and any inherited data type for the one or more target data member items; identifying one or more rules applicable to each target data item based on a target data identifier associated with each applicable rule having a same data type or an inherited data type of the target data item by a rule engine identifying one or more rule instance data items based on the one or more target data items, at least one rule instance data item comprises a condition which is implemented as another rule instance data item accessible by the rule engine like any other rule instance data item, and the rule engine identifies one or more rules linked to the identified one or more rule instance data items as the one or more applicable rules; executing the identified one or more applicable rules after rule execution criteria has determined whether the condition has been satisfied based on execution of the another rule instance data item to determine whether the at least one rule instance data item is to be executed, the condition being satisfied when the target data identifier, embedded between condition tags of the at least one rule instance, has a value satisfying the one or more applicable rules; returning a validation result data object, aggregated for each rule executed for each of the target data items in the target data object, including a validation status to the software application, the validation result data object determined based on execution of the one or more rules stored in a centralized rule store and wherein the validation is decoupled from and performed independently from any application processing the one or more target data items to be validated, wherein the target data object identifies each target data member item by a class identifier and a property identifier; and identifying a data type and any inherited data type for the one or more target data item members comprises determining data types and class membership based on identifying matches with the class identifier and the property identifier for each target data member item and the data type and any inherited data type. | 15. One or more non-transitory computer storage devices having computer-executable instructions embodied thereon that, when executed, facilitate a method for rule based data driven validation, the method comprising: receiving over a communication network a target data object in a validation request from an executing software application; identifying one or more target data member items of the target data object based on stored data type definitions; identifying a data type and any inherited data type for the one or more target data member items; identifying one or more rules applicable to each target data item based on a target data identifier associated with each applicable rule having a same data type or an inherited data type of the target data item by a rule engine identifying one or more rule instance data items based on the one or more target data items, at least one rule instance data item comprises a condition which is implemented as another rule instance data item accessible by the rule engine like any other rule instance data item, and the rule engine identifies one or more rules linked to the identified one or more rule instance data items as the one or more applicable rules; executing the identified one or more applicable rules after rule execution criteria has determined whether the condition has been satisfied based on execution of the another rule instance data item to determine whether the at least one rule instance data item is to be executed, the condition being satisfied when the target data identifier, embedded between condition tags of the at least one rule instance, has a value satisfying the one or more applicable rules; returning a validation result data object, aggregated for each rule executed for each of the target data items in the target data object, including a validation status to the software application, the validation result data object determined based on execution of the one or more rules stored in a centralized rule store and wherein the validation is decoupled from and performed independently from any application processing the one or more target data items to be validated, wherein the target data object identifies each target data member item by a class identifier and a property identifier; and identifying a data type and any inherited data type for the one or more target data item members comprises determining data types and class membership based on identifying matches with the class identifier and the property identifier for each target data member item and the data type and any inherited data type. 16. The one or more non-transitory computer storage devices of claim 15 wherein the target data member item is defined to be of a class data type; and the inherited data type of the target data member item includes any base class of the class data type. | 0.637536 |
9,101,961 | 15 | 16 | 15. A non-transitory computer readable medium storing a word recognition program that, when executed by a processor, causes a computer to perform the following word recognition method: receiving input of a word image representing a plurality of characters; recognizing the word image and selecting a first word candidate and a second word candidate based on a plurality of words registered in a word dictionary; and identifying unmatched characters between the first word candidate and the second word candidate; compare a first it with a second image, the first image corresponding to a portion of the word image and the second image corresponding to the unmatched characters; and determining a likelihood of the first word candidate based on a the comparison between the first image and the second image. | 15. A non-transitory computer readable medium storing a word recognition program that, when executed by a processor, causes a computer to perform the following word recognition method: receiving input of a word image representing a plurality of characters; recognizing the word image and selecting a first word candidate and a second word candidate based on a plurality of words registered in a word dictionary; and identifying unmatched characters between the first word candidate and the second word candidate; compare a first it with a second image, the first image corresponding to a portion of the word image and the second image corresponding to the unmatched characters; and determining a likelihood of the first word candidate based on a the comparison between the first image and the second image. 16. The non-transitory computer readable medium according to claim 15 , wherein the program, when executed by the processor, further causes the computer to perform the following step of the word recognition method: determining the unmatched characters by comparing the first word candidate and the second word candidate character by character based on an edit distance indicating the number of operations for editing characters upon conversion from the first word candidate to the second word candidate. | 0.529026 |
7,668,849 | 11 | 19 | 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. 19. The system of claim 11 , wherein the data processing module further comprises computer instructions for translating a portion of the unstructured data into another language before storing the portion in the data structure. | 0.5 |
8,487,936 | 14 | 20 | 14. The portable electronic device according to claim 1 , wherein, when scrolling in a first scroll direction among a plurality of scroll directions, a first scroll character font among a plurality of different scroll character fonts is used, and, when scrolling in a second scroll direction among the plurality of scroll directions, a second scroll character font among the plurality of different scroll character fonts is used. | 14. The portable electronic device according to claim 1 , wherein, when scrolling in a first scroll direction among a plurality of scroll directions, a first scroll character font among a plurality of different scroll character fonts is used, and, when scrolling in a second scroll direction among the plurality of scroll directions, a second scroll character font among the plurality of different scroll character fonts is used. 20. The portable electronic device according to claim 14 , wherein, if termination of scrolling is detected, use of the still character font is resumed. | 0.86055 |
9,165,038 | 1 | 5 | 1. A method comprising: determining, by a device, whether: a first search term, of a search query, matches a first term at a first hierarchical level of a hierarchical taxonomy, and a second search term, of the search query, matches a second term at a second hierarchical level of the hierarchical taxonomy, the second hierarchical level being different from the first hierarchical level, the search query being submitted by a user device; determining, by the device, that the first search term and the second search term exist in a hierarchical relationship when: the first search term matches the first term, and the second search term matches the second term; generating, by the device, an interpretation for a combination of the first search term and the second search term based on: determining that the first search term and the second search term exist in the hierarchical relationship, and a location associated with the user device; determining, by the device, a score for the interpretation of the combination of the first search term and the second search term; and identifying, by the device, search results based on the interpretation of the combination of the first search term and the second search term when the score exceeds a threshold, the search results being provided for display. | 1. A method comprising: determining, by a device, whether: a first search term, of a search query, matches a first term at a first hierarchical level of a hierarchical taxonomy, and a second search term, of the search query, matches a second term at a second hierarchical level of the hierarchical taxonomy, the second hierarchical level being different from the first hierarchical level, the search query being submitted by a user device; determining, by the device, that the first search term and the second search term exist in a hierarchical relationship when: the first search term matches the first term, and the second search term matches the second term; generating, by the device, an interpretation for a combination of the first search term and the second search term based on: determining that the first search term and the second search term exist in the hierarchical relationship, and a location associated with the user device; determining, by the device, a score for the interpretation of the combination of the first search term and the second search term; and identifying, by the device, search results based on the interpretation of the combination of the first search term and the second search term when the score exceeds a threshold, the search results being provided for display. 5. The method of claim 1 , where the first search term and the second search term are adjacent search terms. | 0.784 |
9,274,782 | 1 | 2 | 1. A method for analyzing workflows associated with a computer application, the computer application installed in a client environment, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of and the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing an updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including the customized functionality and the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality. | 1. A method for analyzing workflows associated with a computer application, the computer application installed in a client environment, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of and the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing an updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including the customized functionality and the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality. 2. The method of claim 1 , further comprising: generating, with a workflow editor tool, the second metadata describing the customized workflow; and storing the second metadata in a metadata store. | 0.736559 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.