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8,751,240 | 1 | 6 |
1. A method, comprising: performing, via a server processor, automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining, via the server processor, a meaning of the utterance based, on the recognized speech; forming a query, by the server processor, indicating the meaning of the utterance and based on a plurality of searching resources; sending the query, by the server processor, based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to obtain second address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis.
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1. A method, comprising: performing, via a server processor, automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining, via the server processor, a meaning of the utterance based, on the recognized speech; forming a query, by the server processor, indicating the meaning of the utterance and based on a plurality of searching resources; sending the query, by the server processor, based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to obtain second address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis. 6. The method of claim 1 , wherein the web-based search engine comprises a knowledge base of web pages.
| 0.64726 |
7,912,816 | 15 | 20 |
15. An apparatus configured to index data, the apparatus comprising: one or more processors; and logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to: receive input from a user defining a classification and an analytic for the classification; determine a definition of relevance parameters that characterize the classification; populate a cortex of unstructured data in a tangible computer readable database, the cortex of unstructured data being populated based on the classification; determine relevant data from unstructured data based on the definition of relevance parameters, the relevant data being data that is determined to be relevant to the classification defined by the user; analyze the relevant data from unstructured data based on the relevance parameters to determine attributes in the relevant data; generate an index of the attributes from the relevant data based on the analyzing of the relevant data; store the index in the cortex; and receive a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index useable by an analytics tool to provide results for the query using the analytics measure applied to the unstructured data in the relevant data indexed in the classification.
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15. An apparatus configured to index data, the apparatus comprising: one or more processors; and logic encoded in one or more tangible media for execution by the one or more processors and when executed operable to: receive input from a user defining a classification and an analytic for the classification; determine a definition of relevance parameters that characterize the classification; populate a cortex of unstructured data in a tangible computer readable database, the cortex of unstructured data being populated based on the classification; determine relevant data from unstructured data based on the definition of relevance parameters, the relevant data being data that is determined to be relevant to the classification defined by the user; analyze the relevant data from unstructured data based on the relevance parameters to determine attributes in the relevant data; generate an index of the attributes from the relevant data based on the analyzing of the relevant data; store the index in the cortex; and receive a query from an analytics tool, the query specifying the classification and an analytics measure, wherein the index useable by an analytics tool to provide results for the query using the analytics measure applied to the unstructured data in the relevant data indexed in the classification. 20. The apparatus of claim 15 , wherein the relevant data can also include structured data.
| 0.869253 |
7,478,081 | 8 | 9 |
8. The method of claim 7 further comprising: implementing an approximation algorithm as a utility of the DBMS.
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8. The method of claim 7 further comprising: implementing an approximation algorithm as a utility of the DBMS. 9. The method of claim 8 wherein the approximation algorithm provides a near optimal solution to an NP-hard n-gram selection problem, the method further comprising: providing the approximation algorithm with a definable ratio bound of the optimal solution.
| 0.5 |
8,713,013 | 8 | 10 |
8. A system, comprising: a processor; and memory storing code stored that when executed causes the processor to: convert an interactive voice response menu of prompts into a web page comprising a graphical version of the interactive voice response menu of prompts; store the webpage in the memory; receive a search request sent from a requesting device, the search request comprising a communications address as a search term; search the web page for the communications address; determine a match between the communications address and a portion of the web page; receive a tag in response to the match that is assigned to the portion of the web page, the tag describing a category and a subcategory associated with a hierarchical tree branch of the interactive voice response menu of prompts; retrieve a quick code of sequential responses to the hierarchical tree branch of the interactive voice response menu of prompts; send the quick code and the tag as a response to the search request; receive a call at the interactive voice response menu of prompts; receive the quick code as inputs to the interactive voice response menu of prompts; and navigate to the hierarchical tree branch represented by the quick code.
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8. A system, comprising: a processor; and memory storing code stored that when executed causes the processor to: convert an interactive voice response menu of prompts into a web page comprising a graphical version of the interactive voice response menu of prompts; store the webpage in the memory; receive a search request sent from a requesting device, the search request comprising a communications address as a search term; search the web page for the communications address; determine a match between the communications address and a portion of the web page; receive a tag in response to the match that is assigned to the portion of the web page, the tag describing a category and a subcategory associated with a hierarchical tree branch of the interactive voice response menu of prompts; retrieve a quick code of sequential responses to the hierarchical tree branch of the interactive voice response menu of prompts; send the quick code and the tag as a response to the search request; receive a call at the interactive voice response menu of prompts; receive the quick code as inputs to the interactive voice response menu of prompts; and navigate to the hierarchical tree branch represented by the quick code. 10. The system according to claim 8 , further comprising code that causes the processor to send the quick code and the tag to a client device.
| 0.727969 |
7,778,957 | 7 | 9 |
7. The method according to claim 1 , further comprising storing said one or more word lists and displaying said stored one or more word lists when a subsequent message is generated using said handheld electronic device.
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7. The method according to claim 1 , further comprising storing said one or more word lists and displaying said stored one or more word lists when a subsequent message is generated using said handheld electronic device. 9. The method according to claim 7 , wherein said one or more word lists are stored separately from said handheld electronic device.
| 0.709251 |
8,874,541 | 10 | 12 |
10. A system for identifying search keywords for searching for an online information resource, the system comprising: a processor; and a social online information resource publishing application executable by the processor and configured to: receive, from a business, a request for the search keywords relating to content of the online information resource of the business; generate, in response to receiving the request, a post comprising information about the business, a request to a plurality of users in a social network to provide the search keywords relating to the content of the online information resource of the business, and a link to a search keyword recommendation page; publish, using a social network application, the post to a newsfeed in the social network, wherein the plurality of users in the social network subscribe to the newsfeed; receive, in response to publishing the post and from the plurality of users, a plurality of search keywords relating to the content of the online information resource from the search keyword recommendation page; rank, in response to receiving a plurality of search keywords, the search keywords in order from most popular to least popular; present, to the business, search keywords based at least in part upon the ranking; receive, from the business, a selection of at least one search keyword from the search keywords that were presented to the business; and publish the online information resource comprising the selected at least one search keyword.
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10. A system for identifying search keywords for searching for an online information resource, the system comprising: a processor; and a social online information resource publishing application executable by the processor and configured to: receive, from a business, a request for the search keywords relating to content of the online information resource of the business; generate, in response to receiving the request, a post comprising information about the business, a request to a plurality of users in a social network to provide the search keywords relating to the content of the online information resource of the business, and a link to a search keyword recommendation page; publish, using a social network application, the post to a newsfeed in the social network, wherein the plurality of users in the social network subscribe to the newsfeed; receive, in response to publishing the post and from the plurality of users, a plurality of search keywords relating to the content of the online information resource from the search keyword recommendation page; rank, in response to receiving a plurality of search keywords, the search keywords in order from most popular to least popular; present, to the business, search keywords based at least in part upon the ranking; receive, from the business, a selection of at least one search keyword from the search keywords that were presented to the business; and publish the online information resource comprising the selected at least one search keyword. 12. The system of claim 10 , wherein the search keyword recommendation page comprises a request for a specified number of search keywords relating to the content of the online information resource of the business.
| 0.797529 |
10,122,670 | 2 | 3 |
2. The method as recited in claim 1 , further comprising identifying the previous social networking activities of the recipient.
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2. The method as recited in claim 1 , further comprising identifying the previous social networking activities of the recipient. 3. The method as recited in claim 2 , wherein identifying the previous social networking activities of the recipient further comprises one or more of identifying one or more electronic message interactions performed by the recipient, identifying one or more locations associated with the recipient, identifying one or more social network transactions performed by the recipient, identifying one or more connections of the recipient, identifying recipient-provided profile information, or identifying one or more translation ratings provided by the recipient.
| 0.5 |
8,260,849 | 9 | 10 |
9. An integration services network for providing a client machine with access to one or more web services over a network comprising: an asynchronous communications interface to store a first web service description file describing how to interact with a web service using asynchronous communications; a conversion engine configured to translate the first web service description file into a second web service description file, the second web description file describing how to interact with the web service using synchronous communications, the conversion engine situated on one or more computing devices; and a synchronous communications interface to receive a request from the client machine to use synchronous communications between the client machine and the web service and to provide the second web service description file to the client machine.
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9. An integration services network for providing a client machine with access to one or more web services over a network comprising: an asynchronous communications interface to store a first web service description file describing how to interact with a web service using asynchronous communications; a conversion engine configured to translate the first web service description file into a second web service description file, the second web description file describing how to interact with the web service using synchronous communications, the conversion engine situated on one or more computing devices; and a synchronous communications interface to receive a request from the client machine to use synchronous communications between the client machine and the web service and to provide the second web service description file to the client machine. 10. The integration services network of claim 9 , wherein providing the second web service description file to the client machine to define interaction with the web service includes providing data for generation of client machine code to interact with the at least one web service.
| 0.838876 |
8,812,556 | 3 | 5 |
3. The method of claim 1 , the storing including serializing the modification data in an XML-based document.
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3. The method of claim 1 , the storing including serializing the modification data in an XML-based document. 5. The method of claim 3 , wherein the XML-based document comprises an Ant script.
| 0.803828 |
9,690,776 | 11 | 12 |
11. A system comprising: a statistical model for receiving at least a first natural language expression and a second natural language expression during a conversational session, wherein each of the first natural language expression and the second natural language expression include at least one of words, terms, and phrases; a single-turn model for determining a first prediction of at least one of a domain classification, intent classification, and slot type of each of the first natural language expression and the second natural language expression; a multi-turn model for determining a second prediction of at least one of a domain classification, intent classification, and slot type of each of the first natural language expression and the second natural language expression; a combination model for combining the first prediction and the second prediction of each of the first natural language expression and the second natural language expression to produce a final prediction relative to an intent of at least the second natural language expression; and a final model for performing an action based on the final prediction of at least the second natural language expression.
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11. A system comprising: a statistical model for receiving at least a first natural language expression and a second natural language expression during a conversational session, wherein each of the first natural language expression and the second natural language expression include at least one of words, terms, and phrases; a single-turn model for determining a first prediction of at least one of a domain classification, intent classification, and slot type of each of the first natural language expression and the second natural language expression; a multi-turn model for determining a second prediction of at least one of a domain classification, intent classification, and slot type of each of the first natural language expression and the second natural language expression; a combination model for combining the first prediction and the second prediction of each of the first natural language expression and the second natural language expression to produce a final prediction relative to an intent of at least the second natural language expression; and a final model for performing an action based on the final prediction of at least the second natural language expression. 12. The system of claim 11 , wherein performing an action based on the final prediction comprises responding to the second natural language expression.
| 0.735088 |
8,862,255 | 30 | 33 |
30. A computer-readable, non-transitory storage medium having at least one computer-executable component for providing synchronized content, the at least one computer-executable component comprising: a content synchronization module operative to: generate audio content based at least in part on textual content; cause output of the generated audio content; cause presentation of the textual content; maintain synchronization between an output pointer of the textual content and an associated position of the generated audio content, wherein the associated position advances during output of the generated audio content, and wherein the output pointer indicates a position within the textual content corresponding to a current output position of the generated audio content; obtain an input pointer referencing a location within the textual content from an input device; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the generated audio content; determine a segment of textual content based at least in part on a difference between the determined position of the output pointer and the location within the textual content referenced by the input pointer; determine a length of time required to output audio content corresponding to the determined segment of textual content; and modify an attribute associated with the output of the generated audio content based at least in part on the determined length of time.
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30. A computer-readable, non-transitory storage medium having at least one computer-executable component for providing synchronized content, the at least one computer-executable component comprising: a content synchronization module operative to: generate audio content based at least in part on textual content; cause output of the generated audio content; cause presentation of the textual content; maintain synchronization between an output pointer of the textual content and an associated position of the generated audio content, wherein the associated position advances during output of the generated audio content, and wherein the output pointer indicates a position within the textual content corresponding to a current output position of the generated audio content; obtain an input pointer referencing a location within the textual content from an input device; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the generated audio content; determine a segment of textual content based at least in part on a difference between the determined position of the output pointer and the location within the textual content referenced by the input pointer; determine a length of time required to output audio content corresponding to the determined segment of textual content; and modify an attribute associated with the output of the generated audio content based at least in part on the determined length of time. 33. The computer-readable, non-transitory storage medium of claim 30 , wherein deter lining the length of time required to output audio content corresponding to the determined segment of textual content comprises generating audio content corresponding to the determined segment of textual content.
| 0.594262 |
8,656,379 | 2 | 3 |
2. The computer-implemented method of claim 1 , further comprising: for each type of type descriptor definition, using the singleton attribute of the single copy to bind all references to the type to the single copy; and executing the executable file based at least in part on whether or not the dynamic type of the first variable is the same as the dynamic type of the second variable.
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2. The computer-implemented method of claim 1 , further comprising: for each type of type descriptor definition, using the singleton attribute of the single copy to bind all references to the type to the single copy; and executing the executable file based at least in part on whether or not the dynamic type of the first variable is the same as the dynamic type of the second variable. 3. The computer-implemented method of claim 2 , further comprising: determining that the dynamic type of the first variable is the same as the dynamic type of the second variable responsive to each of the addresses of the type descriptor definitions of the first and second variables comprising the same particular address in memory of one of the single copies of one of the type descriptor definitions; and determining that the dynamic type of the first variable is different than the dynamic type of the second variable responsive to the address of the type descriptor definition of the first variable being different than the address of the type descriptor definition of the second variable.
| 0.5 |
9,513,785 | 15 | 18 |
15. A method for creating customized definitions for user interfaces provided by a field device editor, the method comprising the steps of: maintaining in a device definition database a default device template, wherein the default device template includes a first definition of an editor interface; retrieving device description information corresponding to a selected device type from the device definition database; modifying on demand the first definition of the editor interface based on the retrieved information corresponding to the selected device type via a customization tool associated with the editor interface, thereby rendering a modified version of the first definition of the editor interface, wherein the customization tool is invoked via a control exposed by the editor interface corresponding to the selected device type; and storing the modified version.
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15. A method for creating customized definitions for user interfaces provided by a field device editor, the method comprising the steps of: maintaining in a device definition database a default device template, wherein the default device template includes a first definition of an editor interface; retrieving device description information corresponding to a selected device type from the device definition database; modifying on demand the first definition of the editor interface based on the retrieved information corresponding to the selected device type via a customization tool associated with the editor interface, thereby rendering a modified version of the first definition of the editor interface, wherein the customization tool is invoked via a control exposed by the editor interface corresponding to the selected device type; and storing the modified version. 18. The method of claim 15 wherein the modifying step comprises defining new screens to a set of interface screens of the field device editor.
| 0.5 |
9,876,751 | 15 | 20 |
15. A method comprising: providing, on a computer display, a user interface including a radial arrangement of a plurality of topics extracted from data streams associated with user activities occurring across a plurality of network servers, the radial arrangement including: a first topic of the plurality of topics represented as a center node at a center of the radial arrangement, the first topic being a main topic of the radial arrangement; a first subset of topics represented as a first subset of nodes arranged at a radial distance from the center node, wherein the first subset of topics includes one or more topics from the plurality of topics having a relevancy score in relation to the first topic that exceeds a first threshold; and for at least one topic of the first subset of topics, a second subset of topics represented as a second subset of nodes, the second subset of nodes arranged at a second radial distance outward from a respective node that corresponds to said at least one topic; wherein the first subset of topics are accompanied a corresponding first set of labels displayed proximate to the first subset of nodes representing the first subset of topics; and in response to a selection by a user of a first label from the corresponding first set of labels, updating the radial arrangement using a second topic associated with the selected first label as the main topic represented by the center node of the radial arrangement.
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15. A method comprising: providing, on a computer display, a user interface including a radial arrangement of a plurality of topics extracted from data streams associated with user activities occurring across a plurality of network servers, the radial arrangement including: a first topic of the plurality of topics represented as a center node at a center of the radial arrangement, the first topic being a main topic of the radial arrangement; a first subset of topics represented as a first subset of nodes arranged at a radial distance from the center node, wherein the first subset of topics includes one or more topics from the plurality of topics having a relevancy score in relation to the first topic that exceeds a first threshold; and for at least one topic of the first subset of topics, a second subset of topics represented as a second subset of nodes, the second subset of nodes arranged at a second radial distance outward from a respective node that corresponds to said at least one topic; wherein the first subset of topics are accompanied a corresponding first set of labels displayed proximate to the first subset of nodes representing the first subset of topics; and in response to a selection by a user of a first label from the corresponding first set of labels, updating the radial arrangement using a second topic associated with the selected first label as the main topic represented by the center node of the radial arrangement. 20. The method of claim 15 , wherein each label of the corresponding first set of labels is sized according to a number of occurrence of a corresponding topic associated with the label occurring within the user activities.
| 0.767296 |
7,958,158 | 17 | 18 |
17. A system, comprising: a database; a processor; and a memory containing a program, which when executed by the processor is configured to perform an operation, comprising: receiving a database query; determining at least one data element required for executing the database query; identifying, from a plurality of storage devices, a storage device storing the determined at least one data element; adding the received database query to a first queue of a plurality of queues each having a plurality of queued queries, each of the queues having a predefined association with a respective storage device of the plurality of storage devices, wherein the predefined association of the first queue is a first predefined association with the identified storage device storing the determined at least one data element, wherein each of the queued queries of a given of one of the queues requires one or more data elements stored in the respective storage device in order to be executed, wherein each queued query is received during a specified time period, and wherein the specified time period is selected according to an energy consumption objective; and after the specified time period: dispatching the plurality of queued queries from the first queue; retrieving, from the respective storage device, data elements required for executing the dispatched queries; and executing the dispatched queries, using the retrieved data elements as inputs.
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17. A system, comprising: a database; a processor; and a memory containing a program, which when executed by the processor is configured to perform an operation, comprising: receiving a database query; determining at least one data element required for executing the database query; identifying, from a plurality of storage devices, a storage device storing the determined at least one data element; adding the received database query to a first queue of a plurality of queues each having a plurality of queued queries, each of the queues having a predefined association with a respective storage device of the plurality of storage devices, wherein the predefined association of the first queue is a first predefined association with the identified storage device storing the determined at least one data element, wherein each of the queued queries of a given of one of the queues requires one or more data elements stored in the respective storage device in order to be executed, wherein each queued query is received during a specified time period, and wherein the specified time period is selected according to an energy consumption objective; and after the specified time period: dispatching the plurality of queued queries from the first queue; retrieving, from the respective storage device, data elements required for executing the dispatched queries; and executing the dispatched queries, using the retrieved data elements as inputs. 18. The system of claim 17 , wherein the storage device is a hard-disk drive.
| 0.754777 |
8,845,428 | 1 | 3 |
1. A method of coordinating real-world gathering to expand and promote an event associated with a community of an online game, the method comprising: encouraging players of the online game community to participate in a real-world gathering by providing incentives for participants at the real-world gathering, wherein the real-world gathering is an event separate from the online game to expand and promote the online game community; promoting familiarity among the participants by providing and introducing online game community titles of the participants at the real-world gathering; providing online benefits and rewards to the participants for participating in the real-world gathering; enabling online participants of the real-world gathering to track the real-world gathering on a map; and enabling the online participants to communicate with the participants at the real-world gathering, wherein the communication between the online participant and the participants at the real-world gathering includes sending messages and tips.
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1. A method of coordinating real-world gathering to expand and promote an event associated with a community of an online game, the method comprising: encouraging players of the online game community to participate in a real-world gathering by providing incentives for participants at the real-world gathering, wherein the real-world gathering is an event separate from the online game to expand and promote the online game community; promoting familiarity among the participants by providing and introducing online game community titles of the participants at the real-world gathering; providing online benefits and rewards to the participants for participating in the real-world gathering; enabling online participants of the real-world gathering to track the real-world gathering on a map; and enabling the online participants to communicate with the participants at the real-world gathering, wherein the communication between the online participant and the participants at the real-world gathering includes sending messages and tips. 3. The method of claim 1 , wherein the incentives include allowing the participants at the real-world gathering to form a clan within the online game.
| 0.758065 |
8,645,421 | 1 | 4 |
1. A computer-implemented method for providing data records, comprising: accessing a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identifying one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generating, by one or more data processors, an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generating, by the one or more processors, a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receiving, a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; providing the one or more records from the particular new level to the predictive model; and processing, by the one or more processors, the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results.
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1. A computer-implemented method for providing data records, comprising: accessing a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identifying one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generating, by one or more data processors, an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generating, by the one or more processors, a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receiving, a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; providing the one or more records from the particular new level to the predictive model; and processing, by the one or more processors, the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results. 4. The method of claim 1 , wherein one level of the attribute hierarchy is associated with climate zones, demographic groups, store types, sales volumes, brands, prices, or store sizes.
| 0.567757 |
9,620,128 | 20 | 21 |
20. The computationally-implemented method of claim 18 , wherein said facilitating acquisition of adaptation result data that is based on particular party feedback regarding the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: requesting particular party feedback regarding the speech-facilitated transaction; receiving particular party feedback regarding the speech-facilitated transaction as adaptation result data; and determining whether to modify the adaptation data based at least in part on the received adaptation result data.
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20. The computationally-implemented method of claim 18 , wherein said facilitating acquisition of adaptation result data that is based on particular party feedback regarding the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: requesting particular party feedback regarding the speech-facilitated transaction; receiving particular party feedback regarding the speech-facilitated transaction as adaptation result data; and determining whether to modify the adaptation data based at least in part on the received adaptation result data. 21. The computationally-implemented method of claim 20 , wherein said requesting particular party feedback regarding the speech-facilitated transaction comprises: requesting that the target device collect feedback from the particular party.
| 0.617834 |
9,047,339 | 16 | 17 |
16. The non-transitory computer-readable medium of claim 15 , where the instructions further comprise: one or more instructions to generate a link to the search query; and one or more instructions to provide the link, to the search query, with the one or more search results.
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16. The non-transitory computer-readable medium of claim 15 , where the instructions further comprise: one or more instructions to generate a link to the search query; and one or more instructions to provide the link, to the search query, with the one or more search results. 17. The non-transitory computer-readable medium of claim 16 , where the instructions further comprise: one or more instructions to identify at least one search result based on another search performed using the search query, the other search being performed based on selection of the link to the search query; and one or more instructions to provide the at least one search result identified based on the other search.
| 0.5 |
7,934,660 | 17 | 18 |
17. The data collection system of claim 7 , wherein the computer initiates the transfer of the configuration data by removing extraneous data from the extensible markup language document.
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17. The data collection system of claim 7 , wherein the computer initiates the transfer of the configuration data by removing extraneous data from the extensible markup language document. 18. The data collection system of claim 17 , wherein the extraneous data comprises data which is not required by the data collection terminal to implement parameter settings contained in the configuration data.
| 0.5 |
8,224,830 | 1 | 5 |
1. A method for reducing a set of strings to approximately match to a first string by determining an edit distance between the first string and the set of strings is within a predetermined threshold, the method comprising: (a) receiving, by a device, a request to approximately match a first string with a set of strings using a predetermined edit distance; (b) generating, by a device, a difference histogram comprising a distribution of a difference in a first number of occurrences of each character of a character set in the first string of the request and a second number of occurrences of each character of the character set in a second string of the set of strings, by incrementing each cell in the difference histogram corresponding to each character in the first string by a positive value and decrementing each cell in the difference histogram corresponding to each character set in the second string by a negative value; (c) determining, by a device, via the difference histogram that a first sum of values across a plurality of cells of the difference histogram is greater than a predetermined threshold and that a second sum of negative values across a second plurality of cells of the difference histogram is less than a negative of the predetermined threshold; and (d) identifying, by the device, the second string as having an edit distance from the first string greater than the predetermined edit distance in response to the determination.
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1. A method for reducing a set of strings to approximately match to a first string by determining an edit distance between the first string and the set of strings is within a predetermined threshold, the method comprising: (a) receiving, by a device, a request to approximately match a first string with a set of strings using a predetermined edit distance; (b) generating, by a device, a difference histogram comprising a distribution of a difference in a first number of occurrences of each character of a character set in the first string of the request and a second number of occurrences of each character of the character set in a second string of the set of strings, by incrementing each cell in the difference histogram corresponding to each character in the first string by a positive value and decrementing each cell in the difference histogram corresponding to each character set in the second string by a negative value; (c) determining, by a device, via the difference histogram that a first sum of values across a plurality of cells of the difference histogram is greater than a predetermined threshold and that a second sum of negative values across a second plurality of cells of the difference histogram is less than a negative of the predetermined threshold; and (d) identifying, by the device, the second string as having an edit distance from the first string greater than the predetermined edit distance in response to the determination. 5. The method of claim 1 , wherein step(a) comprises determining the first string and the second string are the same and identifying the second string as having an edit distance of zero.
| 0.740223 |
7,668,372 | 12 | 16 |
12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document.
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12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document. 16. A method according to claim 12 further comprising evaluating a syntax or semantics of the chosen field when the input is received to associate the chosen field with the region of the read document, wherein the association is executed dependent on said evaluation.
| 0.733 |
8,185,523 | 13 | 14 |
13. The method of claim 12 , wherein the machine learning technique comprises a form of statistical classification.
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13. The method of claim 12 , wherein the machine learning technique comprises a form of statistical classification. 14. The method of claim 13 , wherein the statistical classification is any one of a logistic regression analysis, a support vector machine, neural networks, boosted trees, random forests, naive Bayes, and graphical models.
| 0.5 |
8,612,376 | 15 | 17 |
15. A finite automaton generation method, comprising: increasing a number of characters of a finite automaton transition condition which includes a transition condition with a fixed number of characters, to any specified number of characters; and outputting a finite automaton that has a transition condition with the number of characters thereof increased to any specified number of characters.
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15. A finite automaton generation method, comprising: increasing a number of characters of a finite automaton transition condition which includes a transition condition with a fixed number of characters, to any specified number of characters; and outputting a finite automaton that has a transition condition with the number of characters thereof increased to any specified number of characters. 17. The finite automaton generation method according to claim 15 , comprising: converting a received regular expression to a matrix that describes a finite automaton having a one-character transition condition; storing the converted matrix; performing conversion in which a number of characters of a transition condition of the finite automaton, described by the stored matrix, is increased; storing a halfway-converted finite automaton description matrix; and outputting a finite automaton that has the transition condition with a number of characters thereof increased to any specified number of characters.
| 0.619375 |
7,594,176 | 17 | 22 |
17. In a client/server environment, a server system for providing focused context-sensitive user support, comprising: a query processing module for receiving a query from a remotely located client, the query indicating that an error event has occurred at the remotely located client; a support items database, for storing a plurality of support items; a support engine, coupled to the query processing module and to the support items database, for: extracting from the query an application context for the remotely located client; retrieving, from the support items database, a support item responsive to the query and relevant to the application context; receiving a first feedback item for evaluating the support item, wherein the first feedback item exists prior to the error event; transmitting, to the remotely located client, at least one selected from a group consisting of the support item and a link to the support item; and a feedback engine, for receiving, from the remotely located client, a second feedback item based on a user evaluation of the support item in resolving the error event, and updating the first feedback item based on the second feedback item.
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17. In a client/server environment, a server system for providing focused context-sensitive user support, comprising: a query processing module for receiving a query from a remotely located client, the query indicating that an error event has occurred at the remotely located client; a support items database, for storing a plurality of support items; a support engine, coupled to the query processing module and to the support items database, for: extracting from the query an application context for the remotely located client; retrieving, from the support items database, a support item responsive to the query and relevant to the application context; receiving a first feedback item for evaluating the support item, wherein the first feedback item exists prior to the error event; transmitting, to the remotely located client, at least one selected from a group consisting of the support item and a link to the support item; and a feedback engine, for receiving, from the remotely located client, a second feedback item based on a user evaluation of the support item in resolving the error event, and updating the first feedback item based on the second feedback item. 22. The system of claim 17 , further comprising: a feedback database, coupled to the feedback engine and to the support engine, for storing the first feedback item.
| 0.638767 |
7,926,037 | 1 | 4 |
1. A computer-readable storage having computer-executable instructions for verifying a program, comprising: converting a programming language of the program into an intermediate language; eliminating loops within the program represented by the intermediate language such that the program corresponds to an acyclic intermediate language representation of the program; converting the program from the acyclic intermediate language representation into a passive, acyclic intermediate language representation comprising a plurality of program blocks each corresponding to a specific section of the program; determining dominators for the passive, acyclic intermediate language representation of the program, wherein the passive command module converts the intermediate language representation of the program to a passive intermediate language program by replacing assignment statements in the intermediate language representation with assume statements; and generating a verification condition from the passive, acyclic intermediate language representation of the program, the verification condition comprising a plurality of hierarchically structured block equations each assigned to one of the plurality of program blocks, wherein each block equation comprises a first term associated with an assigned program block and a term associated with each dominating program block according to the determined dominators, wherein the plurality of hierarchically structured block equations of the verification condition causes a theorem prover to: randomly evaluate a first level of the hierarchically structured block equations prior to evaluating a subordinate level of hierarchical structured block equations, evaluate the subordinate level of hierarchical structured block equations when the first level of hierarchically structured block equations is valid; and ignore the subordinate level of hierarchically structured block equations when the first level of hierarchically structure block equations is not valid.
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1. A computer-readable storage having computer-executable instructions for verifying a program, comprising: converting a programming language of the program into an intermediate language; eliminating loops within the program represented by the intermediate language such that the program corresponds to an acyclic intermediate language representation of the program; converting the program from the acyclic intermediate language representation into a passive, acyclic intermediate language representation comprising a plurality of program blocks each corresponding to a specific section of the program; determining dominators for the passive, acyclic intermediate language representation of the program, wherein the passive command module converts the intermediate language representation of the program to a passive intermediate language program by replacing assignment statements in the intermediate language representation with assume statements; and generating a verification condition from the passive, acyclic intermediate language representation of the program, the verification condition comprising a plurality of hierarchically structured block equations each assigned to one of the plurality of program blocks, wherein each block equation comprises a first term associated with an assigned program block and a term associated with each dominating program block according to the determined dominators, wherein the plurality of hierarchically structured block equations of the verification condition causes a theorem prover to: randomly evaluate a first level of the hierarchically structured block equations prior to evaluating a subordinate level of hierarchical structured block equations, evaluate the subordinate level of hierarchical structured block equations when the first level of hierarchically structured block equations is valid; and ignore the subordinate level of hierarchically structured block equations when the first level of hierarchically structure block equations is not valid. 4. The computer-readable storage of claim 1 , wherein converting the program to the passive, acyclic intermediate language representation produces a program represented by a passive, acyclic control-flow graph.
| 0.5 |
8,566,080 | 1 | 8 |
1. A method for text processing, comprising: determining a plurality of characters in a text, wherein the text comprises double-byte coded characters; determining whether a number of bytes included in each text segment is even or odd; detecting which of the plurality of characters represent punctuations; dividing the text into a plurality of different text segments using the detected punctuations as separators between the different text segments; and performing a plurality of discrete decoding operations, one for each of the plurality of different text segments, wherein one or more of the plurality of different text segments comprise at least one occurrence of unrecognizable codes that are unable to be successfully decoded as comprehensible characters without inferences being made, wherein decoding operations on text segments lacking unrecognizable codes are unaffected by other decoding operations on text segments including unrecognizable codes; and when performing the plurality of discrete decoding operations and only when the number of word segments included in one of the text segments is odd, decoding from a head of the text segment rearward, as a first decoding result of the text segment, and decoding from a tail of the text segment frontward, as a second decoding result of the text segment.
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1. A method for text processing, comprising: determining a plurality of characters in a text, wherein the text comprises double-byte coded characters; determining whether a number of bytes included in each text segment is even or odd; detecting which of the plurality of characters represent punctuations; dividing the text into a plurality of different text segments using the detected punctuations as separators between the different text segments; and performing a plurality of discrete decoding operations, one for each of the plurality of different text segments, wherein one or more of the plurality of different text segments comprise at least one occurrence of unrecognizable codes that are unable to be successfully decoded as comprehensible characters without inferences being made, wherein decoding operations on text segments lacking unrecognizable codes are unaffected by other decoding operations on text segments including unrecognizable codes; and when performing the plurality of discrete decoding operations and only when the number of word segments included in one of the text segments is odd, decoding from a head of the text segment rearward, as a first decoding result of the text segment, and decoding from a tail of the text segment frontward, as a second decoding result of the text segment. 8. A method according to claim 1 , wherein the decoding operations performed for each text segments further comprises: determining whether the text segment comprises an ASCII coded character; when the text segment comprises an ASCII coded character, dividing the text segment further into two sub-text segments by using the ASCII coded character as a separator, and decoding the two sub-text segments using independent decoding operations.
| 0.702977 |
7,877,344 | 1 | 4 |
1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of concepts; identifying a plurality of meaning loaded entities within the meaning taxonomy; identifying a group of syntactic structures including at least one normalized syntactic structure and a plurality of non-normalized syntactic structures, the at least one normalized syntactic structure being used to standardize the plurality of non-normalized syntactic structures; associating the at least one normalized syntactic structure with at least one of the plurality of concepts; associating at least one of the plurality of non-normalized syntactic structures with the at least one normalized syntactic structure; and associating at least one of the plurality of documents with the at least one of the plurality of concepts based on a relationship between the at least one of the plurality of documents and the at least one of the plurality of non-normalized syntactic structures.
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1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of concepts; identifying a plurality of meaning loaded entities within the meaning taxonomy; identifying a group of syntactic structures including at least one normalized syntactic structure and a plurality of non-normalized syntactic structures, the at least one normalized syntactic structure being used to standardize the plurality of non-normalized syntactic structures; associating the at least one normalized syntactic structure with at least one of the plurality of concepts; associating at least one of the plurality of non-normalized syntactic structures with the at least one normalized syntactic structure; and associating at least one of the plurality of documents with the at least one of the plurality of concepts based on a relationship between the at least one of the plurality of documents and the at least one of the plurality of non-normalized syntactic structures. 4. The method according to claim 1 , wherein identifying the group of syntactic structures comprises identifying a sentence.
| 0.864629 |
8,620,686 | 1 | 10 |
1. A computer assisted method for accelerated planning and dynamic graphical mapping of a contextual awareness and creating an integrated composite decision plan using a plurality of client devices, an administrative processor and an administrative data storage connected to a network, and a plurality of computer instructions, the computer assisted method comprising: a. using an administrative data storage connected to an administrative processor and a network, and a plurality of client devices wherein the client devices are selected from the group: a cell phone, a laptop, a computer, and a tablet, to provide input when connected to the network to enable the administrative processor to perform a computer assisted geospatial analysis and create an integrated composite decision plan; b. using computer instructions in the administrative data storage to instruct the administrative processor to create a system interface; wherein the computer instructions simultaneously connect together the plurality of client devices, and a third party provider via the network to computer instructions in the administrative data storage using the administrative processor to register a client device and provide a system interface to request and store data from the third party provider; c. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the system interface to instruct the administrative processor to identify a contextual awareness; wherein the computer instructions identify the contextual awareness using key words, classification codes, and priority codes, and computer instructions that list situational awareness linked to the key word, classification code, and priority codes using a library of contextual awareness stored in the administrative data storage; d. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the client devices to instruct the administrative processor to collect raw data on the contextual awareness; wherein the computer instructions to collect the raw data comprise information from a member of the group: transportation facilities, health care facilities, first responder facilities, educational facilities, and combinations thereof; e. using computer instructions in the administrative data storage to instruct the administrative processor to store the collected raw data in the administrative data storage linked to the identified contextual awareness using the plurality of client devices in a plurality of client device protocols simultaneously; and f. using computer instructions in the administrative data storage to instruct the administrative processor to perform geospatial analysis on the collected raw data for the identified contextual awareness using the library of contextual awareness; wherein the computer instructions to perform the geospatial analysis consist of: (i) computer instructions to instruct the administrative processor to request compliance standards from a third party provider via the network for the identified contextual awareness, wherein the compliance standards from the third party provider are in a dynamic electronic library of searchable fields including best practices for a contextual awareness, materials specification standards for the contextual awareness, government standards for the contextual awareness from codes of federal regulation, government standards for the contextual awareness from other state, municipal, regulations, and community promulgated standards for the contextual awareness; (ii) computer instructions to instruct the administrative processor to form data specifications to achieve contextual awareness compliance for the identified contextual awareness wherein the computer instructions provide a projection of need for a geographic area for over a defined period of time for the identified contextual awareness using a projected use for facilities, equipment, disposable materials, personnel, transportation and related resources related to the identified contextual awareness; (iii) computer instructions to instruct the administrative processor to match the collected raw data to the data specifications for compliance enabling the identification of a location specific to existing facilities, existing equipment, existing disposable materials, existing personnel, existing transportation, and existing other related resources related to the identified contextual awareness for use in achieving contextual awareness compliance with the data specifications; (iv) computer instructions to instruct the administrative processor to perform data standardization, data checking, and data correction on the collected raw data to form cleaned data; and (v) computer instructions to instruct the administrative processor to use the cleaned data with the data specifications for compliance to calculate quantity of facilities needed and type of facilities needed, for the geographic area given the identified contextual awareness, quantity of equipment needed, quantity of disposable materials needed, quantity of personnel needed, and transportation needed for the geographic area, to meet data specifications for compliance for the identified contextual awareness; wherein the calculations are determined using computer instructions that calculate predictive dynamic decision plan modeling for the identified contextual awareness consisting of: a. computer instructions to instruct the administrative processor to identify single data points from the cleaned data for the geographic area; b. computer instructions to instruct the administrative processor to identify multiple internal data points from the cleaned data, wherein the multiple data points include geo-demographic zones, geographic zones, and zones formed using geographic spatial relationships; c. computer instructions to instruct the administrative processor to identify patterns of contextual awareness from the cleaned data wherein the patterns consist of concentrations of different contextual awareness, quantities of contextual awareness, and prevalence of contextual awareness by the geographic area; d. computer instructions to instruct the administrative processor to identify recurrences over time of the patterns of contextual awareness, wherein the recurrences of contextual awareness over time consist of: (a) frequency of contextual awareness, (b) duration of contextual awareness, and (c) past, present or future direction of events related to contextual awareness; e. computer instructions to instruct the administrative processor to perform issue disassembly and reassembly over time analysis; f. computer instructions to instruct the administrative processor to identify stakeholders which interact with one of the identified contextual awareness; g. computer instructions to instruct the administrative processor to sort contextual awarenesses chronologically to identify external issues related to contextual awareness compliance, using the library of contextual awareness in the administrative data storage; h. computer instructions to instruct the administrative processor to produce visual outputs from the administrative data storage to display predictive trends and patterns for the contextual awareness compliance using the cleaned data; i. computer instructions to instruct the administrative processor to transmit to stakeholders for collaborative decision making: tasks to reach contextual awareness compliance for each contextual awareness; and to identify resources required for tasks to reach contextual awareness compliance for each contextual awareness; and j. computer instructions to instruct the administrative processor to enable the stakeholders to create an integrated, composite decision plan with geographically sorted and prioritized actions identified by task, by quantity of the stakeholders needed, and by the resources needed to achieve contextual awareness compliance creating an integrated composite decision plan for: geographically defined facilities, equipment, disposable materials, personnel, and transportation.
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1. A computer assisted method for accelerated planning and dynamic graphical mapping of a contextual awareness and creating an integrated composite decision plan using a plurality of client devices, an administrative processor and an administrative data storage connected to a network, and a plurality of computer instructions, the computer assisted method comprising: a. using an administrative data storage connected to an administrative processor and a network, and a plurality of client devices wherein the client devices are selected from the group: a cell phone, a laptop, a computer, and a tablet, to provide input when connected to the network to enable the administrative processor to perform a computer assisted geospatial analysis and create an integrated composite decision plan; b. using computer instructions in the administrative data storage to instruct the administrative processor to create a system interface; wherein the computer instructions simultaneously connect together the plurality of client devices, and a third party provider via the network to computer instructions in the administrative data storage using the administrative processor to register a client device and provide a system interface to request and store data from the third party provider; c. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the system interface to instruct the administrative processor to identify a contextual awareness; wherein the computer instructions identify the contextual awareness using key words, classification codes, and priority codes, and computer instructions that list situational awareness linked to the key word, classification code, and priority codes using a library of contextual awareness stored in the administrative data storage; d. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the client devices to instruct the administrative processor to collect raw data on the contextual awareness; wherein the computer instructions to collect the raw data comprise information from a member of the group: transportation facilities, health care facilities, first responder facilities, educational facilities, and combinations thereof; e. using computer instructions in the administrative data storage to instruct the administrative processor to store the collected raw data in the administrative data storage linked to the identified contextual awareness using the plurality of client devices in a plurality of client device protocols simultaneously; and f. using computer instructions in the administrative data storage to instruct the administrative processor to perform geospatial analysis on the collected raw data for the identified contextual awareness using the library of contextual awareness; wherein the computer instructions to perform the geospatial analysis consist of: (i) computer instructions to instruct the administrative processor to request compliance standards from a third party provider via the network for the identified contextual awareness, wherein the compliance standards from the third party provider are in a dynamic electronic library of searchable fields including best practices for a contextual awareness, materials specification standards for the contextual awareness, government standards for the contextual awareness from codes of federal regulation, government standards for the contextual awareness from other state, municipal, regulations, and community promulgated standards for the contextual awareness; (ii) computer instructions to instruct the administrative processor to form data specifications to achieve contextual awareness compliance for the identified contextual awareness wherein the computer instructions provide a projection of need for a geographic area for over a defined period of time for the identified contextual awareness using a projected use for facilities, equipment, disposable materials, personnel, transportation and related resources related to the identified contextual awareness; (iii) computer instructions to instruct the administrative processor to match the collected raw data to the data specifications for compliance enabling the identification of a location specific to existing facilities, existing equipment, existing disposable materials, existing personnel, existing transportation, and existing other related resources related to the identified contextual awareness for use in achieving contextual awareness compliance with the data specifications; (iv) computer instructions to instruct the administrative processor to perform data standardization, data checking, and data correction on the collected raw data to form cleaned data; and (v) computer instructions to instruct the administrative processor to use the cleaned data with the data specifications for compliance to calculate quantity of facilities needed and type of facilities needed, for the geographic area given the identified contextual awareness, quantity of equipment needed, quantity of disposable materials needed, quantity of personnel needed, and transportation needed for the geographic area, to meet data specifications for compliance for the identified contextual awareness; wherein the calculations are determined using computer instructions that calculate predictive dynamic decision plan modeling for the identified contextual awareness consisting of: a. computer instructions to instruct the administrative processor to identify single data points from the cleaned data for the geographic area; b. computer instructions to instruct the administrative processor to identify multiple internal data points from the cleaned data, wherein the multiple data points include geo-demographic zones, geographic zones, and zones formed using geographic spatial relationships; c. computer instructions to instruct the administrative processor to identify patterns of contextual awareness from the cleaned data wherein the patterns consist of concentrations of different contextual awareness, quantities of contextual awareness, and prevalence of contextual awareness by the geographic area; d. computer instructions to instruct the administrative processor to identify recurrences over time of the patterns of contextual awareness, wherein the recurrences of contextual awareness over time consist of: (a) frequency of contextual awareness, (b) duration of contextual awareness, and (c) past, present or future direction of events related to contextual awareness; e. computer instructions to instruct the administrative processor to perform issue disassembly and reassembly over time analysis; f. computer instructions to instruct the administrative processor to identify stakeholders which interact with one of the identified contextual awareness; g. computer instructions to instruct the administrative processor to sort contextual awarenesses chronologically to identify external issues related to contextual awareness compliance, using the library of contextual awareness in the administrative data storage; h. computer instructions to instruct the administrative processor to produce visual outputs from the administrative data storage to display predictive trends and patterns for the contextual awareness compliance using the cleaned data; i. computer instructions to instruct the administrative processor to transmit to stakeholders for collaborative decision making: tasks to reach contextual awareness compliance for each contextual awareness; and to identify resources required for tasks to reach contextual awareness compliance for each contextual awareness; and j. computer instructions to instruct the administrative processor to enable the stakeholders to create an integrated, composite decision plan with geographically sorted and prioritized actions identified by task, by quantity of the stakeholders needed, and by the resources needed to achieve contextual awareness compliance creating an integrated composite decision plan for: geographically defined facilities, equipment, disposable materials, personnel, and transportation. 10. The method of claim 1 , wherein the computer instructions that list situational awareness use situational awarenesses from the library of contextual awareness which are medical awarenesses.
| 0.779176 |
9,037,993 | 13 | 16 |
13. A non-transitory processor-readable medium having stored thereon processor-executable instructions configured to cause a personal computing device processor to perform operations comprising: displaying on a display of a device at least one pallet illustrating associations between a series of unique non-descriptive graphical figures and corresponding unique text-based characters, wherein each text-based character corresponds to one of a plurality of keys comprising an input mechanism of the device and wherein each unique non-descriptive graphical figure is associated with a corresponding text-based character, wherein the series of unique non-descriptive graphical figures comprises a series of unique background colors and a series of unique pen colors; receiving input of a text-based character corresponding to a unique non-descriptive graphical figure and displaying the non-descriptive graphical figure in a predetermined display location in accordance with a defined sequence scheme comprising rules for the order of entry of a sequence, and repeating receiving input of a text-based character corresponding to a next non-descriptive graphical figure and displaying the next non-descriptive graphical figure in a next predetermined display location in accordance with the defined sequence scheme until receipt of the sequence is complete; and processing the input text-based characters as a user password.
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13. A non-transitory processor-readable medium having stored thereon processor-executable instructions configured to cause a personal computing device processor to perform operations comprising: displaying on a display of a device at least one pallet illustrating associations between a series of unique non-descriptive graphical figures and corresponding unique text-based characters, wherein each text-based character corresponds to one of a plurality of keys comprising an input mechanism of the device and wherein each unique non-descriptive graphical figure is associated with a corresponding text-based character, wherein the series of unique non-descriptive graphical figures comprises a series of unique background colors and a series of unique pen colors; receiving input of a text-based character corresponding to a unique non-descriptive graphical figure and displaying the non-descriptive graphical figure in a predetermined display location in accordance with a defined sequence scheme comprising rules for the order of entry of a sequence, and repeating receiving input of a text-based character corresponding to a next non-descriptive graphical figure and displaying the next non-descriptive graphical figure in a next predetermined display location in accordance with the defined sequence scheme until receipt of the sequence is complete; and processing the input text-based characters as a user password. 16. The non-transitory processor-readable medium of claim 13 , wherein the defined sequence scheme further comprises: a rule requiring that each non-descriptive graphical figure contains a continuous segment that begins at an edge of the non-descriptive graphical figure and ends at another edge of the same non-descriptive graphical figure, or is a non-descriptive graphical figure that has no segment therein; and a rule requiring that an overall image of the completed sequence of non-descriptive graphical figures includes an outline of an image as provided by the continuous segments, such that the overall image that is shown is fully bounded.
| 0.534433 |
7,945,478 | 7 | 10 |
7. A computerized method for processing historical vehicle replacement part database queries, the computerized method comprising: receiving input data at a data preprocessing unit, the input data including a digital representation of vehicle parts in a supplier's vehicle parts inventory; preprocessing the input data using the data preprocessing unit to generate historical vehicle replacement part database records each corresponding to one of the vehicle parts in the supplier's vehicle parts inventory, the preprocessing including converting part name and description information for each part into a unique part identifier associated with each part record to permit location of a part record using translation of the part name and description information into a corresponding part identifier; storing each historical vehicle replacement part database record in a database system using a database server coupled to the data preprocessing unit; receiving a user query at a web server, the user query being transmitted by a responding party client system, the user query having data corresponding to information contained in a subrogation claim received from a demanding party, different from the responding party, the user query data including a first vehicle parts list, a vehicle make, model and year, a historical date, and a geographic area of interest; transmitting the user query to an application server coupled to the web server by a data network, the application server being programmed to connect operatively to the database server and to the web server over the data network; generating a database query comprising information from the user query and information from a rule set, the database query being generated by the application server; querying, at the application server, the database system by sending the database query to the database server; receiving a database query result from the database server at the application server, the database query result being responsive to the querying, the database query result including a second list of vehicle parts matching the database query, the second list of vehicle parts including those parts corresponding to the parts in the first vehicle parts list and which are suitable for use on the vehicle make, model and year and which were available on the historical date, were located within the geographic area of interest, and which conform to a rule set; verifying automatically, at the application server, the accuracy of the subrogation claim by comparing the database query result with the subrogation claim information to generate a subrogation claim accuracy verification result; generating automatically, at the application server, an independent subrogation claim value based only on the subrogation claim accuracy verification result; generating dynamic content for transmitting to the client system using the application server, the dynamic content including a portion of the database query result and the independent subrogation claim value; and transmitting the dynamic content to the client system in response to the user query received from the client over an external communication link.
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7. A computerized method for processing historical vehicle replacement part database queries, the computerized method comprising: receiving input data at a data preprocessing unit, the input data including a digital representation of vehicle parts in a supplier's vehicle parts inventory; preprocessing the input data using the data preprocessing unit to generate historical vehicle replacement part database records each corresponding to one of the vehicle parts in the supplier's vehicle parts inventory, the preprocessing including converting part name and description information for each part into a unique part identifier associated with each part record to permit location of a part record using translation of the part name and description information into a corresponding part identifier; storing each historical vehicle replacement part database record in a database system using a database server coupled to the data preprocessing unit; receiving a user query at a web server, the user query being transmitted by a responding party client system, the user query having data corresponding to information contained in a subrogation claim received from a demanding party, different from the responding party, the user query data including a first vehicle parts list, a vehicle make, model and year, a historical date, and a geographic area of interest; transmitting the user query to an application server coupled to the web server by a data network, the application server being programmed to connect operatively to the database server and to the web server over the data network; generating a database query comprising information from the user query and information from a rule set, the database query being generated by the application server; querying, at the application server, the database system by sending the database query to the database server; receiving a database query result from the database server at the application server, the database query result being responsive to the querying, the database query result including a second list of vehicle parts matching the database query, the second list of vehicle parts including those parts corresponding to the parts in the first vehicle parts list and which are suitable for use on the vehicle make, model and year and which were available on the historical date, were located within the geographic area of interest, and which conform to a rule set; verifying automatically, at the application server, the accuracy of the subrogation claim by comparing the database query result with the subrogation claim information to generate a subrogation claim accuracy verification result; generating automatically, at the application server, an independent subrogation claim value based only on the subrogation claim accuracy verification result; generating dynamic content for transmitting to the client system using the application server, the dynamic content including a portion of the database query result and the independent subrogation claim value; and transmitting the dynamic content to the client system in response to the user query received from the client over an external communication link. 10. The computerized method of claim 7 , wherein the historical date includes a historical date range.
| 0.902299 |
8,265,933 | 22 | 24 |
22. At least one non-transitory computer-readable storage medium containing a program which, when executed on at least one computer, performs a method of performing voice recognition, at least in part, using a language model incorporating a plurality of words and a plurality of n-grams, each of the plurality of n-grams formed by two or more of the plurality of words and defining a probability of occurrence of each word in the respective n-gram given the occurrence of one of the two or more of the plurality of words forming the respective n-gram, the method comprising: receiving a first text comprising a sequence of one or more words from a first participant in a text-based conversation with a second participant via at least one first user device; receiving a voice response provided by the second participant in the text-based conversation in response to the first text; selecting at least one of the plurality of n-grams from the language model that includes at least one word in the first text; and automatically recognizing at least a portion of the voice response to provide a second text, at least in part, by using the at least one selected n-gram, wherein automatically recognizing comprises determining whether a number of messages from the first participant to the second participant exceeds a predetermined threshold.
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22. At least one non-transitory computer-readable storage medium containing a program which, when executed on at least one computer, performs a method of performing voice recognition, at least in part, using a language model incorporating a plurality of words and a plurality of n-grams, each of the plurality of n-grams formed by two or more of the plurality of words and defining a probability of occurrence of each word in the respective n-gram given the occurrence of one of the two or more of the plurality of words forming the respective n-gram, the method comprising: receiving a first text comprising a sequence of one or more words from a first participant in a text-based conversation with a second participant via at least one first user device; receiving a voice response provided by the second participant in the text-based conversation in response to the first text; selecting at least one of the plurality of n-grams from the language model that includes at least one word in the first text; and automatically recognizing at least a portion of the voice response to provide a second text, at least in part, by using the at least one selected n-gram, wherein automatically recognizing comprises determining whether a number of messages from the first participant to the second participant exceeds a predetermined threshold. 24. The at least one non-transitory computer-readable storage medium of claim 22 , wherein when the number of messages from the first participant to the second participant exceeds a predetermined threshold, automatically recognizing the at least a portion of the voice response includes using a history of recognized words and received texts between the first participant and the second participant.
| 0.5 |
9,471,560 | 11 | 18 |
11. A system comprising: one or more hardware processors; a non-transitory computer-readable medium storing instructions, which, when executed, are operable to cause the one or more processors to perform operations comprising: receiving a sequence of keyboard events representing keystrokes input to a virtual keyboard of a device; traversing a hierarchical data structure according to the sequence of keyboard events to determine candidate words; constructing a word lattice based on a language model, including deriving path weights from candidate word statistics and keyboard error model data, wherein deriving the path weights is based on a function having one or more first parameters including the candidate word statistics and one or more second parameters including the keyboard error model data; searching the word lattice for N best paths, where N is a positive integer; determining one or more candidate sentences comprising candidate words based on the N best paths.
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11. A system comprising: one or more hardware processors; a non-transitory computer-readable medium storing instructions, which, when executed, are operable to cause the one or more processors to perform operations comprising: receiving a sequence of keyboard events representing keystrokes input to a virtual keyboard of a device; traversing a hierarchical data structure according to the sequence of keyboard events to determine candidate words; constructing a word lattice based on a language model, including deriving path weights from candidate word statistics and keyboard error model data, wherein deriving the path weights is based on a function having one or more first parameters including the candidate word statistics and one or more second parameters including the keyboard error model data; searching the word lattice for N best paths, where N is a positive integer; determining one or more candidate sentences comprising candidate words based on the N best paths. 18. The system of claim 11 , where the hierarchical data structure is a trie data structure comprising a plurality trie nodes, each trie node including a sort keys data field, a probability data field, and a word address data field, the sort keys data field storing a plurality of forms of a character of the language, the probability data field storing data indicating a relative probability that characters associated with the trie node follow characters associated with an ancestor of the trie node, the word address data field storing an address of a location of a first word in a word list with which the trie node is associated.
| 0.71364 |
7,904,424 | 1 | 7 |
1. A method for managing document data used for reproducing a document the method comprising: in a case where second generation document data can be generated by replicating first generation document data that is original document data and (n+1)-th (n≧2) generation document data can be generated by replicating n-th generation document data, combining the first generation document data and child identification data in one unit, the child identification data indicating the second generation document data generated by replicating the first generation document data; combining k-th (N≧2) generation document data and parent identification data in one unit, the parent identification data indicating which of other (k−1)-th generation document data is replicated to generate the k-th generation document data; incorporating, into the unit where the first generation document data is combined, an event execution permission/denial determination program for implementing a determination portion that determines permission/denial of execution of an event relating to document data whose generation is younger than the second generation document data, and incorporating, into each of the units where the document data is combined, an information exchange program for implementing an information exchange portion that sends and receives information, and when the event relating to the k-th generation document data is executed, implementing, in a computer managing the k-th generation document data, the information exchange portion relating to the k-th generation document data by causing the computer to execute the information exchange program, implementing, in each computer managing document data that is in a direct line from the k-th generation document data and is older than the k-th generation document data, the information exchange portion relating to each piece of the older document data by causing each of the computers to execute the information exchange program, implementing, in a computer managing the first generation document data, the determination portion by causing the computer to execute the determination program, giving, to the determination portion implemented in the computer managing the first generation document data, a request to the effect that execution of the event relating to the k-th generation document data should be permitted, by causing each of the information exchange portions relating to each piece of the older document data to relay the request in a manner to deliver the request from the information exchange portion relating to the k-th generation document data to older generation document data based on parent attribute information, causing the determination portion to determine whether execution of the event relating to the k-th generation document data is permitted, and executing the event in a case where the determination portion determines that execution of the event relating to the k-th generation document data is permitted.
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1. A method for managing document data used for reproducing a document the method comprising: in a case where second generation document data can be generated by replicating first generation document data that is original document data and (n+1)-th (n≧2) generation document data can be generated by replicating n-th generation document data, combining the first generation document data and child identification data in one unit, the child identification data indicating the second generation document data generated by replicating the first generation document data; combining k-th (N≧2) generation document data and parent identification data in one unit, the parent identification data indicating which of other (k−1)-th generation document data is replicated to generate the k-th generation document data; incorporating, into the unit where the first generation document data is combined, an event execution permission/denial determination program for implementing a determination portion that determines permission/denial of execution of an event relating to document data whose generation is younger than the second generation document data, and incorporating, into each of the units where the document data is combined, an information exchange program for implementing an information exchange portion that sends and receives information, and when the event relating to the k-th generation document data is executed, implementing, in a computer managing the k-th generation document data, the information exchange portion relating to the k-th generation document data by causing the computer to execute the information exchange program, implementing, in each computer managing document data that is in a direct line from the k-th generation document data and is older than the k-th generation document data, the information exchange portion relating to each piece of the older document data by causing each of the computers to execute the information exchange program, implementing, in a computer managing the first generation document data, the determination portion by causing the computer to execute the determination program, giving, to the determination portion implemented in the computer managing the first generation document data, a request to the effect that execution of the event relating to the k-th generation document data should be permitted, by causing each of the information exchange portions relating to each piece of the older document data to relay the request in a manner to deliver the request from the information exchange portion relating to the k-th generation document data to older generation document data based on parent attribute information, causing the determination portion to determine whether execution of the event relating to the k-th generation document data is permitted, and executing the event in a case where the determination portion determines that execution of the event relating to the k-th generation document data is permitted. 7. The method according to claim 1 , wherein the event is editing document data as a target.
| 0.93343 |
8,004,539 | 26 | 27 |
26. The method of claim 1 , further comprising: hiding, by the graphical editing tool, the converted transformation object during the operations on the other objects.
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26. The method of claim 1 , further comprising: hiding, by the graphical editing tool, the converted transformation object during the operations on the other objects. 27. The method of claim 26 , further comprising: displaying, by the graphical editing tool, the converted transformation object if the graphical object is selected after the operations on the other objects.
| 0.5 |
8,423,498 | 8 | 11 |
8. A system according to claim 6 , wherein the database processing component of the processor is further configured to associate each parsed portion of the scenario sample with one of an importance level factor, a fidelity level factor, and an intercultural fidelity level factor.
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8. A system according to claim 6 , wherein the database processing component of the processor is further configured to associate each parsed portion of the scenario sample with one of an importance level factor, a fidelity level factor, and an intercultural fidelity level factor. 11. A system according to claim 8 , wherein the database processing component of the processor is further configured to associate each parsed portion of the scenario sample with an intercultural fidelity level factor associated with a required intercultural proficiency element.
| 0.512281 |
8,575,465 | 14 | 17 |
14. The method for scoring a singing voice as claimed in claim 13 , wherein the reference PCR is finalized after verifying thereof.
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14. The method for scoring a singing voice as claimed in claim 13 , wherein the reference PCR is finalized after verifying thereof. 17. The method for scoring a singing voice as claimed in claim 14 , wherein based on the result of the verification, parameters for determining the reference PCR are modified for re-determining the reference PCR.
| 0.728205 |
9,639,173 | 2 | 3 |
2. The human interface device of claim 1 , wherein the foldable cover comprises a plurality of divided sections, and at least one of the divided sections comprises a power source supplying power to the human interface device.
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2. The human interface device of claim 1 , wherein the foldable cover comprises a plurality of divided sections, and at least one of the divided sections comprises a power source supplying power to the human interface device. 3. The human interface device of claim 2 , wherein the foldable cover comprises a first electrode of the power source, and the first electrode is connected to a second electrode provided on the human interface device when the cover covers the text input unit.
| 0.5 |
7,672,007 | 1 | 2 |
1. An automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information.
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1. An automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. 2. A system as claimed in claim 1 , in which at least one of said application programs is a digital archiving program.
| 0.779026 |
9,613,033 | 1 | 2 |
1. A method for providing emotionally relevant content to users, comprising: receiving, from a first user, a user emotion label for content; labeling the content based upon the user emotion label to create labeled content; defining an emotional transition trigger for a second user comprising defining a timeout trigger for a first emotional content type; and responsive to a triggering of the emotional transition trigger comprising the second user consuming content of the first emotional content type for a threshold amount of time corresponding to the timeout trigger, providing the labeled content to the second user based upon the labeled content having a second emotional content type different than the first emotional content type.
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1. A method for providing emotionally relevant content to users, comprising: receiving, from a first user, a user emotion label for content; labeling the content based upon the user emotion label to create labeled content; defining an emotional transition trigger for a second user comprising defining a timeout trigger for a first emotional content type; and responsive to a triggering of the emotional transition trigger comprising the second user consuming content of the first emotional content type for a threshold amount of time corresponding to the timeout trigger, providing the labeled content to the second user based upon the labeled content having a second emotional content type different than the first emotional content type. 2. The method of claim 1 , the receiving a user emotion label comprising: providing an emotion labeling interface comprising a set of emotions for selection by the first user; and receiving a selection of an emotion by the first user, from the emotion labeling interface, as the user emotion label for the content.
| 0.702087 |
9,934,330 | 17 | 20 |
17. A non-transitory, computer-readable memory device comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a query; identifying a first replaceable token, a second replaceable token, and a third replaceable token in the query, wherein: the first replaceable token comprises a first alias that designates a first instance of a first parameter; the second replaceable token comprises a second alias that designates a second instance of the first parameter; the third replaceable token comprises the first alias that designates a reuse of the first instance of a first parameter in the query; retrieving a parameter definition for the parameter from a plurality of parameter definitions, wherein the parameter definition comprises a text prompt that requests an input providing a value for the parameter; generating a first graphical user interface (GUI) comprising the text prompt that requests an input providing a value for the parameter; receiving and through the first GUI, input representing a first value for the parameter; replacing the first replaceable token and the third replaceable token in the query with the first value for the parameter; generating a second GUI comprising the text prompt that requests an input providing a value for the parameter; receiving and through the first GUI, input representing a second value of the parameter; replacing the second replaceable token in the query with the second value for the parameter; and submitting the query for evaluation.
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17. A non-transitory, computer-readable memory device comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a query; identifying a first replaceable token, a second replaceable token, and a third replaceable token in the query, wherein: the first replaceable token comprises a first alias that designates a first instance of a first parameter; the second replaceable token comprises a second alias that designates a second instance of the first parameter; the third replaceable token comprises the first alias that designates a reuse of the first instance of a first parameter in the query; retrieving a parameter definition for the parameter from a plurality of parameter definitions, wherein the parameter definition comprises a text prompt that requests an input providing a value for the parameter; generating a first graphical user interface (GUI) comprising the text prompt that requests an input providing a value for the parameter; receiving and through the first GUI, input representing a first value for the parameter; replacing the first replaceable token and the third replaceable token in the query with the first value for the parameter; generating a second GUI comprising the text prompt that requests an input providing a value for the parameter; receiving and through the first GUI, input representing a second value of the parameter; replacing the second replaceable token in the query with the second value for the parameter; and submitting the query for evaluation. 20. The non-transitory, computer-readable memory device of claim 17 , wherein the parameter definition further comprises: a parameter name; a default value for the parameter; a field designating whether multiple values are allowed; a field designating whether the parameter is optional or mandatory; and an item or field that is related to the parameter.
| 0.748222 |
8,150,814 | 7 | 12 |
7. A non-transitory computer-readable medium containing instructions for controlling a computer system to perform a method for data cleansing using rule based formatting, the method comprising: obtaining a first input data and a second input data, wherein said first input data is tokenized according to a data dictionary, wherein said second input data is tokenized according to the data dictionary; parsing said first input data and said second input data using a predefined parsing rule including an option operator, wherein the option operator indicates that a particular index defined in the predefined parsing rule is optional; obtaining a formatting rule, wherein said formatting rule includes one or more formatting rule components including at least one conditional format operator, wherein the at least one conditional format operator indicates whether to include a particular string literal in an output data based on the existence of a particular token; including a first token in a first output data if a first formatting rule component in the formatting rule is a first valid index to said first tokenized input data, wherein said first token is associated with said first valid index, and including a first string literal in said first output data if said first formatting rule component in the formatting rule is a string literal; including a second token in a second output data if said first formatting rule component in the formatting rule is a second valid index to said second tokenized input data, wherein said second token is associated with said second valid index and including a second string literal in said second output data if said first formatting rule component in the formatting rule is the string literal; and formatting said first output data and said second output data according to the formatting rule.
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7. A non-transitory computer-readable medium containing instructions for controlling a computer system to perform a method for data cleansing using rule based formatting, the method comprising: obtaining a first input data and a second input data, wherein said first input data is tokenized according to a data dictionary, wherein said second input data is tokenized according to the data dictionary; parsing said first input data and said second input data using a predefined parsing rule including an option operator, wherein the option operator indicates that a particular index defined in the predefined parsing rule is optional; obtaining a formatting rule, wherein said formatting rule includes one or more formatting rule components including at least one conditional format operator, wherein the at least one conditional format operator indicates whether to include a particular string literal in an output data based on the existence of a particular token; including a first token in a first output data if a first formatting rule component in the formatting rule is a first valid index to said first tokenized input data, wherein said first token is associated with said first valid index, and including a first string literal in said first output data if said first formatting rule component in the formatting rule is a string literal; including a second token in a second output data if said first formatting rule component in the formatting rule is a second valid index to said second tokenized input data, wherein said second token is associated with said second valid index and including a second string literal in said second output data if said first formatting rule component in the formatting rule is the string literal; and formatting said first output data and said second output data according to the formatting rule. 12. The non-transitory computer-readable medium of claim 7 wherein said first string literal is included in said first output data if a first token associated with a second formatting rule component to the immediate left of said first formatting rule component and a second token associated with a third formatting rule component to the immediate right of said first formatting rule component both exist.
| 0.5 |
10,162,315 | 20 | 23 |
20. A tangible, non-transitory, computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to display a graphical programming interface that allows a user to: generate a typical component template that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; generate a first and a second adapter component template, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; generate a graphical programming interface to allow for modification of the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein modification of the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices, respectively to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; and instantiate the typical component template with each of first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively, wherein the first native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified first adapter component template, and wherein the second native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified second adapter component template.
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20. A tangible, non-transitory, computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to display a graphical programming interface that allows a user to: generate a typical component template that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; generate a first and a second adapter component template, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; generate a graphical programming interface to allow for modification of the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein modification of the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices, respectively to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; and instantiate the typical component template with each of first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively, wherein the first native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified first adapter component template, and wherein the second native control component, when executed, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the modified second adapter component template. 23. The tangible, non-transitory, computer-readable medium of claim 20 , wherein the instructions, when executed by one or more processors, cause the one or more processors to generate the one or more configurable logic algorithms to provide one or more logic states based on whether conditions are satisfied in accordance with the one or more configurable logical expressions.
| 0.743188 |
9,536,266 | 1 | 6 |
1. A computer-implemented method for automatically checking and acting on one or more factual claims, the method being executed using one or more processors and comprising: receiving, by the one or more processors, a factual claim comprising claim information and a date corresponding to an occurrence of the factual claim; and in response to receiving the factual claim, automatically performing real-time operations comprising: processing, by the one or more processors, the claim information based on a domain vocabulary to identify at least one of one or more keywords and one or more categories, identifying one or more facts relevant to the factual claim by querying one or more context sources based on the date, determining an accuracy of the factual claim based on the one or more facts, generating, by the one or more processors, a confidence score reflecting an overall confidence in one or more factual claims based on respective accuracies, and transmitting, by the one or more processors, the factual claim and the confidence score for display in a graphical user interface (GUI).
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1. A computer-implemented method for automatically checking and acting on one or more factual claims, the method being executed using one or more processors and comprising: receiving, by the one or more processors, a factual claim comprising claim information and a date corresponding to an occurrence of the factual claim; and in response to receiving the factual claim, automatically performing real-time operations comprising: processing, by the one or more processors, the claim information based on a domain vocabulary to identify at least one of one or more keywords and one or more categories, identifying one or more facts relevant to the factual claim by querying one or more context sources based on the date, determining an accuracy of the factual claim based on the one or more facts, generating, by the one or more processors, a confidence score reflecting an overall confidence in one or more factual claims based on respective accuracies, and transmitting, by the one or more processors, the factual claim and the confidence score for display in a graphical user interface (GUI). 6. The method of claim 1 , wherein identifying one or more facts relevant to the factual claim comprises: generating one or more queries based on one or more keywords associated with the factual claim; querying one or more context sources based on the one or more queries; and receiving the one or more facts in response to querying the one or more context sources.
| 0.596239 |
9,953,652 | 5 | 15 |
5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a transcription of at least a portion of an utterance, wherein the transcription comprises a sequence of tokens corresponding to at least a portion of a search query; identifying a first subset of the sequence of tokens as a reference to an entity in the transcription based at least partly on a first frequency with which at least a first token of the first subset occurs in a plurality of previously submitted search queries; identifying a second subset of the sequence of tokens as a reference to an attribute of the entity in the transcription based at least partly on a second frequency with which at least a second token of the second subset occurs with the first token in the plurality of previously submitted search queries, wherein the second token occurring with the first token comprises the second token and first token both occurring in a same search query of the plurality of previously submitted search queries; generating search terms using the reference to the entity and the reference to the attribute, wherein the search terms include the first subset and second subset, and wherein the search terms exclude a third subset of the sequence of tokens; and generating search results responsive to the search query by identifying an item in a product catalog using the search terms, wherein the product catalog indicates the item comprises an instance of the entity having the attribute.
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5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating a transcription of at least a portion of an utterance, wherein the transcription comprises a sequence of tokens corresponding to at least a portion of a search query; identifying a first subset of the sequence of tokens as a reference to an entity in the transcription based at least partly on a first frequency with which at least a first token of the first subset occurs in a plurality of previously submitted search queries; identifying a second subset of the sequence of tokens as a reference to an attribute of the entity in the transcription based at least partly on a second frequency with which at least a second token of the second subset occurs with the first token in the plurality of previously submitted search queries, wherein the second token occurring with the first token comprises the second token and first token both occurring in a same search query of the plurality of previously submitted search queries; generating search terms using the reference to the entity and the reference to the attribute, wherein the search terms include the first subset and second subset, and wherein the search terms exclude a third subset of the sequence of tokens; and generating search results responsive to the search query by identifying an item in a product catalog using the search terms, wherein the product catalog indicates the item comprises an instance of the entity having the attribute. 15. The computer-implemented method of claim 5 , wherein identifying the second subset as the reference to the attribute comprises using a statistical model to process information regarding a location of a token relative to another token within the transcription.
| 0.770506 |
8,044,791 | 3 | 6 |
3. The method as claimed in claim 1 , wherein a portable controller is used for control or operation, the method further comprising picking up the spoken commands and forwarding the spoken commands to a speech recognition unit using the portable controller.
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3. The method as claimed in claim 1 , wherein a portable controller is used for control or operation, the method further comprising picking up the spoken commands and forwarding the spoken commands to a speech recognition unit using the portable controller. 6. The method as claimed in claim 3 , wherein the portable controller assumes the control or operation of the first target system based on a proximity of the portable controller to the first target system to be controlled or operated.
| 0.60339 |
9,424,342 | 1 | 9 |
1. A method performed by data processing apparatus, the method comprising: identifying a search query from a search query log that includes data specifying search queries corresponding to particular geographic regions; generating a geo-query count that represents a total number of times that the search query was received over a specified period in a geographic region; comparing the geo-query count to a corresponding expected query count for the search query in the geographic region, wherein the expected query count is a baseline number of times that the search query is expected to be received in the geographic region based on the number of times that the search query is received in a baseline geographic region that is different than the geographic region; determining that the search query has a geo-query count that exceeds the corresponding expected query count by at least a threshold amount; and classifying the search query as a local query for the geographic region.
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1. A method performed by data processing apparatus, the method comprising: identifying a search query from a search query log that includes data specifying search queries corresponding to particular geographic regions; generating a geo-query count that represents a total number of times that the search query was received over a specified period in a geographic region; comparing the geo-query count to a corresponding expected query count for the search query in the geographic region, wherein the expected query count is a baseline number of times that the search query is expected to be received in the geographic region based on the number of times that the search query is received in a baseline geographic region that is different than the geographic region; determining that the search query has a geo-query count that exceeds the corresponding expected query count by at least a threshold amount; and classifying the search query as a local query for the geographic region. 9. The method of claim 1 , further comprising computing the expected query count for the search query in the geographic region based on a total query count for the geographic region and a query share for the baseline geographic region, where the query share represents a percentage of the number of queries in the baseline geographic region that match the search query.
| 0.586323 |
7,966,172 | 1 | 4 |
1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression.
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1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression. 4. The method of claim 1 , further comprising: making a copy of a portion of the displayed natural language expression, the copy of the portion of the displayed natural language expression includes one or more changeable embedded fields displayed in the portion of the displayed natural language expression; displaying the copy of the portion of the displayed natural language expression with the one or more changeable embedded fields displayed in the copy of the portion of the displayed natural language expression; changing data in at least one of the one or more changeable embedded fields displayed in the copy of the portion of the displayed natural language expression; modifying the copy of the portion of the displayed natural language expression based on the changing data; displaying the natural language expression with the portion of the displayed natural language expression and the copy of the portion, the copy of the portion being displayed with the changed data in the at least one of the one or more changeable embedded fields.
| 0.5 |
8,117,198 | 1 | 2 |
1. A computer-implemented method for generating a task-enhanced search engine index, the method comprising: determining associations between user tasks and resources accessed by a user while performing various tasks, wherein determining the associations includes determining associations for a particular task in connection with a plurality of resources identified for use in the context of the particular task, and wherein the associations determined for the particular task are determined according to task-related information provided based on use of the plurality of resources in the context of the particular task; filtering the plurality of resources, as filtered resources, for the particular task according to the associations determined for the particular task; storing, as stored associations, the associations determined for the particular task with respect to the filtered resources for each of the user tasks; computing from the stored associations task-related metadata for each of the resources; storing the computed task-related metadata in a search engine index; predicting a predicted task using the computer task-related metadata stored in the search engine index, wherein the predicted task is different from the particular task, and wherein predicting the predicted task includes determining that performing the particular task indicates a probability of subsequently performing the predicted task according to the computer-task related metadata; and generating search results in response to a search query by the user, the search results being generated according to the predicted task and the search engine index.
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1. A computer-implemented method for generating a task-enhanced search engine index, the method comprising: determining associations between user tasks and resources accessed by a user while performing various tasks, wherein determining the associations includes determining associations for a particular task in connection with a plurality of resources identified for use in the context of the particular task, and wherein the associations determined for the particular task are determined according to task-related information provided based on use of the plurality of resources in the context of the particular task; filtering the plurality of resources, as filtered resources, for the particular task according to the associations determined for the particular task; storing, as stored associations, the associations determined for the particular task with respect to the filtered resources for each of the user tasks; computing from the stored associations task-related metadata for each of the resources; storing the computed task-related metadata in a search engine index; predicting a predicted task using the computer task-related metadata stored in the search engine index, wherein the predicted task is different from the particular task, and wherein predicting the predicted task includes determining that performing the particular task indicates a probability of subsequently performing the predicted task according to the computer-task related metadata; and generating search results in response to a search query by the user, the search results being generated according to the predicted task and the search engine index. 2. The method of claim 1 wherein determining associations between user tasks and resources accessed by a user while performing various tasks comprises tagging resources with tasks based on the contents of an events database and a task database.
| 0.502041 |
9,864,920 | 1 | 4 |
1. A document validation system, comprising: a processor; and a non-transitory, computer-readable memory containing programming instructions that are configured to cause the processor to: receive a scan image of a certified document, access a repository of security templates and identify and retrieve, from the repository, a security template for the document, wherein the security template comprises one or more security element locations, prompt a user to provide a validation document, receive the validation document in response to the prompt, wherein the validation document comprises content that should appear at one or more of the security element locations, use the identified security template to identify the location of one or more security elements on the certified document that correspond to one or more of the security element locations of the identified security template, apply the validation document to the identified security template to identify expected content that should appear on the certified document at the identified one or more security element locations on the certified document, analyze the scan image to identify actual content that appears on the certified document at the identified one or more security element locations on the certified document, determine whether the expected content matches the actual content, and output a report of the result to the user.
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1. A document validation system, comprising: a processor; and a non-transitory, computer-readable memory containing programming instructions that are configured to cause the processor to: receive a scan image of a certified document, access a repository of security templates and identify and retrieve, from the repository, a security template for the document, wherein the security template comprises one or more security element locations, prompt a user to provide a validation document, receive the validation document in response to the prompt, wherein the validation document comprises content that should appear at one or more of the security element locations, use the identified security template to identify the location of one or more security elements on the certified document that correspond to one or more of the security element locations of the identified security template, apply the validation document to the identified security template to identify expected content that should appear on the certified document at the identified one or more security element locations on the certified document, analyze the scan image to identify actual content that appears on the certified document at the identified one or more security element locations on the certified document, determine whether the expected content matches the actual content, and output a report of the result to the user. 4. The system of claim 1 , wherein the instructions to identify the security template comprise instructions to: identify document content comprising one or more words, phrases, text formats, or data structures in the scan image; and apply a template matching technique to select, from the repository, a security template that corresponds to the identified document content.
| 0.632874 |
9,558,276 | 1 | 12 |
1. A computer-implemented method, comprising: determining, by the agent device, availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmitting availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detecting data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participating in a real-time interaction option as an active relevant agent associated with the topic data.
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1. A computer-implemented method, comprising: determining, by the agent device, availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmitting availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detecting data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participating in a real-time interaction option as an active relevant agent associated with the topic data. 12. The method of claim 1 , wherein data corresponding to an agent is stored in multiple databases.
| 0.805882 |
8,838,560 | 1 | 11 |
1. A computer program product, comprising a non-transitory computer readable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method, comprising: classifying each of a plurality of websites using at least one of a plurality of classifications; acquiring data associated with the plurality of websites, wherein the data includes data pertaining to one or more ranked positions within a range of ranked positions that are associated with the plurality of websites and associated with one or more search engine results with respect to one or more keywords; wherein the data pertaining to the one or more ranked positions includes a first number of ranked positions associated with a subset of the one or more websites; and analyzing the data to achieve a result.
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1. A computer program product, comprising a non-transitory computer readable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method, comprising: classifying each of a plurality of websites using at least one of a plurality of classifications; acquiring data associated with the plurality of websites, wherein the data includes data pertaining to one or more ranked positions within a range of ranked positions that are associated with the plurality of websites and associated with one or more search engine results with respect to one or more keywords; wherein the data pertaining to the one or more ranked positions includes a first number of ranked positions associated with a subset of the one or more websites; and analyzing the data to achieve a result. 11. The computer program product of claim 1 , wherein the data includes an average click rate for a web link associated with at least one website of the one or more websites, wherein the web link is listed within one or more search engine results.
| 0.655028 |
8,352,467 | 4 | 5 |
4. The method of claim 1 , wherein: identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are associated by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources comprises: calculating an aggregated trust rank based on two or more trust ranks; and determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term comprises: determining the relevance score of each of the one or more resources that have the annotation label term based on the respective aggregated trust rank.
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4. The method of claim 1 , wherein: identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are associated by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources comprises: calculating an aggregated trust rank based on two or more trust ranks; and determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term comprises: determining the relevance score of each of the one or more resources that have the annotation label term based on the respective aggregated trust rank. 5. The method of claim 4 , wherein calculating an aggregated trust rank comprises calculating an aggregated trust rank according to a weighing function, and the weighting function is one of a linear weighting function, an asymptotic weighting function, a decaying weighting function or a sigmoid weighting function.
| 0.5 |
9,483,159 | 9 | 13 |
9. The method of claim 1 wherein the icon is grouped in a characterization group based on a characterization of the information.
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9. The method of claim 1 wherein the icon is grouped in a characterization group based on a characterization of the information. 13. The method of claim 9 wherein when a user selects the characterization group, comments within the characterization group are displayed in a list form for a user to view and/or select for more information.
| 0.5 |
10,127,913 | 35 | 48 |
35. A method of encoding of syntactic elements of a data stream, wherein: before beginning of encoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of the cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of encoding of at least a portion of bits of the data stream: a group of context models is selected that comprises at least two context models of different size; values of at least two context elements associated the selected group of context models are calculated; selection of the cells in context models is carried out using values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, which data is used for entropy encoding of a current bit of the data stream, and/or for selecting a mode of writing encoded bits into the data stream directly; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met.
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35. A method of encoding of syntactic elements of a data stream, wherein: before beginning of encoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of the cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of encoding of at least a portion of bits of the data stream: a group of context models is selected that comprises at least two context models of different size; values of at least two context elements associated the selected group of context models are calculated; selection of the cells in context models is carried out using values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, which data is used for entropy encoding of a current bit of the data stream, and/or for selecting a mode of writing encoded bits into the data stream directly; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met. 48. The method of encoding according to claim 35 , wherein in the process of encoding at least one encoded syntactic element is binarized, and at least one context element is calculated using values of the syntactic elements encoded so far and/or values of the already encoded bits of a current syntactic element.
| 0.668432 |
8,656,335 | 8 | 14 |
8. A system for analyzing an RTL-level circuit description netlist to produce a higher level circuit description, the system comprising: one or more hardware processors; a memory that contains instructions for execution by the one or more hardware processors; and a database for storing the RTL-level circuit description netlist and the higher-level circuit description, wherein: the one or more hardware processors are configured to: receiving the netlist, the netlist including a hierarchy of IP block instances on two or more levels, the IP block instances having one or more ports with signal names and properties attached, wherein at least some of the signal names or properties on at least one net in the circuit descriptions netlist are dissimilar; propagate signal names and properties from at least a first IP block instance to a second IP block instance according to connectivity between the first and second IP block instances as represented in the netlist, wherein by said propagating at least one signal name or property on the first IP block instance is assigned to the second IP block instance, thereby replacing an existing signal name or property on the second IP block instance; group together the signal names into a plurality of groups according to the signal properties and the connectivity; assign at least one of the groups of signal names to a higher-level interface definition; and save the grouped signal names in the database.
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8. A system for analyzing an RTL-level circuit description netlist to produce a higher level circuit description, the system comprising: one or more hardware processors; a memory that contains instructions for execution by the one or more hardware processors; and a database for storing the RTL-level circuit description netlist and the higher-level circuit description, wherein: the one or more hardware processors are configured to: receiving the netlist, the netlist including a hierarchy of IP block instances on two or more levels, the IP block instances having one or more ports with signal names and properties attached, wherein at least some of the signal names or properties on at least one net in the circuit descriptions netlist are dissimilar; propagate signal names and properties from at least a first IP block instance to a second IP block instance according to connectivity between the first and second IP block instances as represented in the netlist, wherein by said propagating at least one signal name or property on the first IP block instance is assigned to the second IP block instance, thereby replacing an existing signal name or property on the second IP block instance; group together the signal names into a plurality of groups according to the signal properties and the connectivity; assign at least one of the groups of signal names to a higher-level interface definition; and save the grouped signal names in the database. 14. The system of claim 8 , wherein after performing propagation of signal names and properties by traversing a design hierarchy resulting in differing signal groupings between multiple interconnected IP block instances, a single signal grouping is chosen from said differing signal groupings by heuristic analysis, wherein: a signal grouping is chosen that appears maximally in all of said multiple interconnected IP block instances; or a signal grouping is chosen that is the intersection of all signals appearing in signal groupings at each of said multiple interconnected IP block instances; or a signal grouping is chosen that is the union of all signals appearing in signal groupings at each of said multiple interconnected IP block instances.
| 0.5 |
9,867,012 | 1 | 17 |
1. A method for detecting whispered speech of a user of a mobile computerized device, the method comprises: detecting, by the mobile computerized device, whispered speech context; and attempting to detect, by the mobile computerized device and by using whispered speech detection parameters, the whispered speech; wherein at least one whispered speech detection parameter of the whispered speech detection parameters differs from at least one corresponding non-whispered speech parameter that is used for detecting non-whispered speech; wherein the attempting to detect the whispered speech comprises: applying a whispered speech trigger detection process for detecting a whispered speech trigger; wherein a detecting of the whispered speech trigger is followed by applying a whispered speech recognition process for detecting the whispered speech; wherein the whispered speech recognition process differs from the whispered speech trigger detection process; and wherein the whispered speech trigger detection process is associated with a power consumption that is lower than a power consumption associated with the applying of the speech recognition process.
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1. A method for detecting whispered speech of a user of a mobile computerized device, the method comprises: detecting, by the mobile computerized device, whispered speech context; and attempting to detect, by the mobile computerized device and by using whispered speech detection parameters, the whispered speech; wherein at least one whispered speech detection parameter of the whispered speech detection parameters differs from at least one corresponding non-whispered speech parameter that is used for detecting non-whispered speech; wherein the attempting to detect the whispered speech comprises: applying a whispered speech trigger detection process for detecting a whispered speech trigger; wherein a detecting of the whispered speech trigger is followed by applying a whispered speech recognition process for detecting the whispered speech; wherein the whispered speech recognition process differs from the whispered speech trigger detection process; and wherein the whispered speech trigger detection process is associated with a power consumption that is lower than a power consumption associated with the applying of the speech recognition process. 17. The method according to claim 1 , wherein the applying of the whispered speech trigger detection process comprises searching for a predefined whispered speech content.
| 0.634615 |
7,571,383 | 13 | 15 |
13. A reporting system tangibly embodied on a computer readable media, comprising: a document database that sequentially stores inputted document data; a concept database that stores a plurality of pre-specified concepts using a hierarchical structure in which a first concept including a second concept is a higher layer of the second concept; a document data concept extracting section that extracts document concepts on the basis of keywords contained in said respective document data, the document concepts being said concepts corresponding to the document data; a concept ratio calculating section that calculates a ratio of the number of said document data corresponding to each of said concepts to the number of said document data in said document database; a relative frequency calculating section that calculates a relative frequency indicating the magnitude of the ratio calculated by said concept ratio calculating section with respect to a reference ratio corresponding to each of said concepts; a frequent concept selecting section that selects said concepts in which said relative frequency is at least a pre-specified threshold among said plurality of concepts; a preferred concept selecting section that selects one of a first concept selected by said frequent concept selection section and a second concept corresponding to a higher layer of said first concept, on the basis of the relative frequencies of said first and second concepts; a reporting section that reports to a user that said concept of said first concept or said second concept selected by said preferred concept selecting section has a higher relative frequency; and a concept extraction rule database that stores concept extraction rules comprising sets of one or more of the keywords and the concept indicating meanings of the one or more keywords, wherein the retrieval statement concept extracting section extracts the concept contained in the concept extraction rule as the retrieval statement concept if said retrieval statement comprises the one or more keywords contained in any of the concept extraction rules, wherein the document data concept extracting section extracts the concept contained in the concept extraction rule and uses said concept as the document concept if said document data include the one or more keywords contained in any of the concept extraction rules, and wherein the retrieval system further comprises; a retrieval index database that stores, for each of the document data, an association between the document data and the document concept of the document data extracted by the document data concept extracting section, wherein the concept retrieving section outputs said document data corresponding to the document concept of said document concept stored in the retrieval index database before the retrieval statement is inputted; a synonym database that stores an association between a predetermined word or phrase and the keyword that is a synonym of the word or phrase; a document data normalizing section that normalizes the document data by replacing the word or phrase contained in each of said document data with the keyword that is the synonym of the word or phrase; and a retrieval statement normalizing section that normalizes the retrieval statement by replacing the word or phrase contained in said retrieval statement with the keyword that is the synonym of the word or phrase, wherein the document data concept extracting section extracts the document concept from the normalized document data, and the retrieval statement concept extracting section extracts the retrieval statement concept from the normalized retrieval statement; wherein the concept retrieving section comprises; a higher concept acquiring section that acquires a retrieval statement higher concept that is a higher-layer concept of said retrieval statement concept if the retrieval statement concept does not match the document concept; and a generalized concept output section that outputs the document data as a retrieval result if the retrieval statement higher concept matches the document concept; wherein: the concept database stores each of said plurality of concepts as a node of the first or second hierarchical structure, the document data concept extracting section extracts the first document concept belonging to the first hierarchical structure and the second document concept belonging to the second hierarchical structure in association with the document data, the retrieval statement concept extracting section extracts the retrieval statement concept belonging to the first hierarchical structure and the second retrieval statement concept belonging to the second hierarchical structure in association with the retrieval statement, the higher concept acquiring section acquires the first retrieval statement higher concept that is a higher layer of the first retrieval statement concept and the second retrieval statement higher concept that is a higher layer of the second retrieval statement concept if the first retrieval statement concept does not match the first document concept and if the second retrieval statement concept does not match the second document concept, and the generalized concept output section outputs the first document data as a retrieval result if the number of the first document data in which the first retrieval statement higher concept is the same as the second retrieval statement concept and in which the first document concept is the same as the second document concept is smaller than that of the second document data in which the first retrieval statement higher concept is the same as the second retrieval statement concept and in which the first document concept is the same as the second document concept, or wherein the concept retrieving section comprises: a lower concept acquiring section that, if all the document data having the document concept that is the same as the retrieval statement concept have the document concept that is the same as a retrieval statement lower concept that is a lower layer of the retrieval statement concept, replaces the retrieval statement concept with the retrieval statement lower concept and a specialized concept output section that outputs the document data in which the retrieval statement lower concept matches the document concept, as a retrieval unit and wherein; the concept database stores the plurality of concepts that identify a plurality of defects in a product, the document database stores the document data indicating contents of each of the plurality of defects, the retrieval statement concept extracting section extracts the retrieval statement concept corresponding to the retrieval statement used to retrieve said defects in the product, and the retrieval result outputting section outputs the document data retrieved by the concept retrieving section, as said document data indicating the contents of the defects in the product inputted by a user; or wherein; the concept database stores the plurality of concepts in a lower layer of the concept indicating that there are defects in components of the product, using a hierarchical structure in which the concepts indicating states of the defects in the components are provided, the document data concept extracting section extracts the document concept indicating that there is a defect in one of the components, on the basis of the keyword contained in the document data, the retrieval statement concept extracting section extracts the retrieval statement concept indicating the state of the defect in the one of said components, on the basis of the keyword contained in the retrieval statement, and wherein the concept retrieving section comprises: a higher concept acquiring section that acquires a retrieval statement higher concept that is the concept indicating that there is the defect in the one of said components, the concept being a higher layer of the retrieval statement concept; and a generalized concept outputting section that outputs, as a retrieval result, the document data having the document concept indicating that there is the defect in the one of the components, the document concept matching the retrieval statement higher concept; and further comprising a component database that uses a hierarchical structure to store inclusive relationships among the components of the product, wherein; the document data concept extracting section further extracts the document concept indicating the component described in the document data, on the basis of the keyword contained in the document data, the retrieval statement concept extracting section further extracts the retrieval statement concept indicating the component described in the retrieval statement concept extracting section, on the basis of the keyword contained in the retrieval statement, the higher concept acquiring section acquires the concept that is a higher layer of the first retrieval statement concept indicating that there is the defect in the component or a state of the defect in the component, and the concept that is a higher layer of the second retrieval statement concept indicating the component, and the generalized concept outputting section outputs, as a retrieval result, the document data having the document concept that matches the first retrieval statement concept and the document concept that matches the second retrieval statement concept if at least one of the first retrieval statement concept and the second retrieval statement concept is the concept in the higher laver; or a product database that uses a hierarchical structure to store inclusive relationships among the names of a plurality of the products, wherein the document data concept extracting section further extracts the document concept indicating the product name described in the document data, on the basis of the keyword contained in said document data, the retrieval statement concept extracting section further extracts the retrieval statement concept indicating the product name described in the retrieval statement concept extracting section, on the basis of the keyword contained in the retrieval statement, the higher concept acquiring section acquires the concept that is a higher layer of the first retrieval statement concept indicating that there is the defect in the component or a state of the defect in the component, and the concept that is a higher layer of the second retrieval statement concept indicating the product name, and the generalized concept outputting section outputs, as a retrieval result, the document data having the document concept that matches the first retrieval statement concept and the document concept that matches the second retrieval statement concept if at least one of the first retrieval statement concept and the second retrieval statement concept is the concept in the higher layer.
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13. A reporting system tangibly embodied on a computer readable media, comprising: a document database that sequentially stores inputted document data; a concept database that stores a plurality of pre-specified concepts using a hierarchical structure in which a first concept including a second concept is a higher layer of the second concept; a document data concept extracting section that extracts document concepts on the basis of keywords contained in said respective document data, the document concepts being said concepts corresponding to the document data; a concept ratio calculating section that calculates a ratio of the number of said document data corresponding to each of said concepts to the number of said document data in said document database; a relative frequency calculating section that calculates a relative frequency indicating the magnitude of the ratio calculated by said concept ratio calculating section with respect to a reference ratio corresponding to each of said concepts; a frequent concept selecting section that selects said concepts in which said relative frequency is at least a pre-specified threshold among said plurality of concepts; a preferred concept selecting section that selects one of a first concept selected by said frequent concept selection section and a second concept corresponding to a higher layer of said first concept, on the basis of the relative frequencies of said first and second concepts; a reporting section that reports to a user that said concept of said first concept or said second concept selected by said preferred concept selecting section has a higher relative frequency; and a concept extraction rule database that stores concept extraction rules comprising sets of one or more of the keywords and the concept indicating meanings of the one or more keywords, wherein the retrieval statement concept extracting section extracts the concept contained in the concept extraction rule as the retrieval statement concept if said retrieval statement comprises the one or more keywords contained in any of the concept extraction rules, wherein the document data concept extracting section extracts the concept contained in the concept extraction rule and uses said concept as the document concept if said document data include the one or more keywords contained in any of the concept extraction rules, and wherein the retrieval system further comprises; a retrieval index database that stores, for each of the document data, an association between the document data and the document concept of the document data extracted by the document data concept extracting section, wherein the concept retrieving section outputs said document data corresponding to the document concept of said document concept stored in the retrieval index database before the retrieval statement is inputted; a synonym database that stores an association between a predetermined word or phrase and the keyword that is a synonym of the word or phrase; a document data normalizing section that normalizes the document data by replacing the word or phrase contained in each of said document data with the keyword that is the synonym of the word or phrase; and a retrieval statement normalizing section that normalizes the retrieval statement by replacing the word or phrase contained in said retrieval statement with the keyword that is the synonym of the word or phrase, wherein the document data concept extracting section extracts the document concept from the normalized document data, and the retrieval statement concept extracting section extracts the retrieval statement concept from the normalized retrieval statement; wherein the concept retrieving section comprises; a higher concept acquiring section that acquires a retrieval statement higher concept that is a higher-layer concept of said retrieval statement concept if the retrieval statement concept does not match the document concept; and a generalized concept output section that outputs the document data as a retrieval result if the retrieval statement higher concept matches the document concept; wherein: the concept database stores each of said plurality of concepts as a node of the first or second hierarchical structure, the document data concept extracting section extracts the first document concept belonging to the first hierarchical structure and the second document concept belonging to the second hierarchical structure in association with the document data, the retrieval statement concept extracting section extracts the retrieval statement concept belonging to the first hierarchical structure and the second retrieval statement concept belonging to the second hierarchical structure in association with the retrieval statement, the higher concept acquiring section acquires the first retrieval statement higher concept that is a higher layer of the first retrieval statement concept and the second retrieval statement higher concept that is a higher layer of the second retrieval statement concept if the first retrieval statement concept does not match the first document concept and if the second retrieval statement concept does not match the second document concept, and the generalized concept output section outputs the first document data as a retrieval result if the number of the first document data in which the first retrieval statement higher concept is the same as the second retrieval statement concept and in which the first document concept is the same as the second document concept is smaller than that of the second document data in which the first retrieval statement higher concept is the same as the second retrieval statement concept and in which the first document concept is the same as the second document concept, or wherein the concept retrieving section comprises: a lower concept acquiring section that, if all the document data having the document concept that is the same as the retrieval statement concept have the document concept that is the same as a retrieval statement lower concept that is a lower layer of the retrieval statement concept, replaces the retrieval statement concept with the retrieval statement lower concept and a specialized concept output section that outputs the document data in which the retrieval statement lower concept matches the document concept, as a retrieval unit and wherein; the concept database stores the plurality of concepts that identify a plurality of defects in a product, the document database stores the document data indicating contents of each of the plurality of defects, the retrieval statement concept extracting section extracts the retrieval statement concept corresponding to the retrieval statement used to retrieve said defects in the product, and the retrieval result outputting section outputs the document data retrieved by the concept retrieving section, as said document data indicating the contents of the defects in the product inputted by a user; or wherein; the concept database stores the plurality of concepts in a lower layer of the concept indicating that there are defects in components of the product, using a hierarchical structure in which the concepts indicating states of the defects in the components are provided, the document data concept extracting section extracts the document concept indicating that there is a defect in one of the components, on the basis of the keyword contained in the document data, the retrieval statement concept extracting section extracts the retrieval statement concept indicating the state of the defect in the one of said components, on the basis of the keyword contained in the retrieval statement, and wherein the concept retrieving section comprises: a higher concept acquiring section that acquires a retrieval statement higher concept that is the concept indicating that there is the defect in the one of said components, the concept being a higher layer of the retrieval statement concept; and a generalized concept outputting section that outputs, as a retrieval result, the document data having the document concept indicating that there is the defect in the one of the components, the document concept matching the retrieval statement higher concept; and further comprising a component database that uses a hierarchical structure to store inclusive relationships among the components of the product, wherein; the document data concept extracting section further extracts the document concept indicating the component described in the document data, on the basis of the keyword contained in the document data, the retrieval statement concept extracting section further extracts the retrieval statement concept indicating the component described in the retrieval statement concept extracting section, on the basis of the keyword contained in the retrieval statement, the higher concept acquiring section acquires the concept that is a higher layer of the first retrieval statement concept indicating that there is the defect in the component or a state of the defect in the component, and the concept that is a higher layer of the second retrieval statement concept indicating the component, and the generalized concept outputting section outputs, as a retrieval result, the document data having the document concept that matches the first retrieval statement concept and the document concept that matches the second retrieval statement concept if at least one of the first retrieval statement concept and the second retrieval statement concept is the concept in the higher laver; or a product database that uses a hierarchical structure to store inclusive relationships among the names of a plurality of the products, wherein the document data concept extracting section further extracts the document concept indicating the product name described in the document data, on the basis of the keyword contained in said document data, the retrieval statement concept extracting section further extracts the retrieval statement concept indicating the product name described in the retrieval statement concept extracting section, on the basis of the keyword contained in the retrieval statement, the higher concept acquiring section acquires the concept that is a higher layer of the first retrieval statement concept indicating that there is the defect in the component or a state of the defect in the component, and the concept that is a higher layer of the second retrieval statement concept indicating the product name, and the generalized concept outputting section outputs, as a retrieval result, the document data having the document concept that matches the first retrieval statement concept and the document concept that matches the second retrieval statement concept if at least one of the first retrieval statement concept and the second retrieval statement concept is the concept in the higher layer. 15. The reporting system according to claim 13 , wherein said preferred concept selecting section selects said first concept if the relative frequency of said first concept is higher than the relative frequency of said second concept by at least a pre-specified rate, and selects said second concept if the relative frequency of said first concept is not higher than the relative frequency of said second concept by at least said pre-specified rate.
| 0.932237 |
7,627,514 | 17 | 18 |
17. A computer readable medium having stored thereon computer-executable instructions for causing a computer system to execute the steps in a method for determining an auction format for a market, said method comprising the steps of: selecting characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders; selecting a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said historical auctions data, and said characteristics of said market based on segments of said historical auctions related to a specified item; selecting at least a first estimated structure of said market, which describes at least a first factor that affects how bidders behave, and a second estimated structure of said market, which describes a second factor that affects how bidders behave, at least in part by inverting said relevant bidding model; predicting a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting a first outcome of said market based on said first bidding behavior; predicting at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting a second outcome of said market based on at least said second bidding behavior prediction; and determining said auction format for said market by evaluating said first outcome of said market and at least said second outcome of said market.
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17. A computer readable medium having stored thereon computer-executable instructions for causing a computer system to execute the steps in a method for determining an auction format for a market, said method comprising the steps of: selecting characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders; selecting a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said historical auctions data, and said characteristics of said market based on segments of said historical auctions related to a specified item; selecting at least a first estimated structure of said market, which describes at least a first factor that affects how bidders behave, and a second estimated structure of said market, which describes a second factor that affects how bidders behave, at least in part by inverting said relevant bidding model; predicting a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting a first outcome of said market based on said first bidding behavior; predicting at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting a second outcome of said market based on at least said second bidding behavior prediction; and determining said auction format for said market by evaluating said first outcome of said market and at least said second outcome of said market. 18. The computer readable medium as recited in claim 17 , wherein said selecting of said characteristics of said market step comprises the steps of: receiving a first user input, wherein said first user input comprises information identifying an item to be auctioned; accessing a database; retrieving from said database said historical bids data; retrieving from said database auction characteristics data, wherein said auction characteristics data comprise information relating to historical auctions of similar items; outputting said historical bids data; and outputting said auction characteristics data.
| 0.648727 |
9,075,462 | 2 | 3 |
2. The method of claim 1 , wherein the touch input device comprises a touchscreen display.
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2. The method of claim 1 , wherein the touch input device comprises a touchscreen display. 3. The method of claim 2 , further comprising displaying a graphical user interface element on the touchscreen display and wherein the finger-specific command is determined based on the identified finger and the graphical user interface element.
| 0.577586 |
5,575,508 | 10 | 11 |
10. A method for enhancing security of a negotiable document and deterring copying of the negotiable document, comprising the steps of: generating a first warning mark on a negotiable document backing, said first warning mark comprised of a first dot size pattern reproducible by various copier systems; generating a second warning mark on the negotiable document backing, said second warning mark comprised of a second dot size pattern reproducible by various copy systems; and generating a background pattern around the first and second warning marks, said backing pattern comprised of a third dot size pattern reproducible by various copy systems.
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10. A method for enhancing security of a negotiable document and deterring copying of the negotiable document, comprising the steps of: generating a first warning mark on a negotiable document backing, said first warning mark comprised of a first dot size pattern reproducible by various copier systems; generating a second warning mark on the negotiable document backing, said second warning mark comprised of a second dot size pattern reproducible by various copy systems; and generating a background pattern around the first and second warning marks, said backing pattern comprised of a third dot size pattern reproducible by various copy systems. 11. The method of claim 10 further including the steps of: printing a first pantographic background design within a signature area on a first side of a negotiable document; printing a second pantographic background design substantially covering a first side of the negotiable document and differing from the first pantographic background design; and generating a warning clause describing the pantographic background design of the signature area.
| 0.5 |
9,324,024 | 12 | 14 |
12. The method of claim 11 , wherein selecting a piece of text as background content includes selecting a word set that has at least a predetermined similarity to a normal word set that may be sent to the recipient in another message not including a pseudo message.
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12. The method of claim 11 , wherein selecting a piece of text as background content includes selecting a word set that has at least a predetermined similarity to a normal word set that may be sent to the recipient in another message not including a pseudo message. 14. The method of claim 12 , wherein the selected word set is in an eXtensible Markup Language (XML) format and is denoted as X c , and wherein X c is any candidate word set denoted X candidate such that: S = SIM ( M k , X candidate ) = 1 m · ∑ j = 0 m max i = 0 n [ sim ( w j ′ X w j M ) ] > T , where: S=SIM(M k , X candidate ) is a calculated similarity between a normal word set M k and X candidate ; T is the predetermined similarity; M k ={w 0 M , w 1 M , . . . , w i M , . . . , w n M }; i is an integer from 0 to n; X candidate ={w 0 X , w 1 X , . . . , w j X , . . . , w m X }; j is an integer from 0 to m; w i M denotes an arbitrary word in M k ; w j X denotes an arbitrary word in X candidate ; sim ( w i , w j ) = { 1 , w i = w j sim wordnet , w i ≠ w j ; and sim wordnet is a similarity calculated according to WordNet.
| 0.5 |
9,665,551 | 1 | 7 |
1. A computer-implemented method for selecting a subset of a set of comments associated with a group of documents, the method comprising: accessing, at memory locations, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and using a computer processor that is coupled to the memory location and programmed to select the subset: selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function.
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1. A computer-implemented method for selecting a subset of a set of comments associated with a group of documents, the method comprising: accessing, at memory locations, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and using a computer processor that is coupled to the memory location and programmed to select the subset: selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function. 7. The method of claim 1 , wherein the set of comments are currently unannotated.
| 0.861301 |
8,438,225 | 1 | 9 |
1. A method to be executed at least in part in a computing device for enabling traversal between an email exchange and a real time conversation, the method comprising: while facilitating a first email exchange including a trail of connected messages, replies and forwarded messages, receiving a request for activating a first real time conversation that includes at least one from a set of: audio communication, video communication, application sharing, and data sharing based on an email of the first email exchange, wherein the first email exchange is part of two or more conversations concurrently; ordering the first email exchange according to at least one from a set of: a temporal order and a grouping by different threads; reconstructing the email exchange in a story form including a topic to facilitate transitioning from the first email exchange to the first real time conversation; determining participants of the first real time conversation based on a context of the first email exchange and a user entry in an entry box presented on a user interface; populating the participants of the first real time conversation according to presence information associated with recipients of the first email exchange; excluding at least one of the participants of the email exchange based on permission levels and attributes of the first email exchange content; activating the first real time conversation, wherein a context for the first real time conversation is provided based on the context of the email and formatted based on a set of predefined rules and a user preference; and displaying the first real time conversation over the user interface wherein the user interface includes textual and graphical selectable controls, links to functionalities including one or more of: a calendar, a contact list that lists contacts categorized by user defined groups and their statuses, and a task list, a folder view providing a grouping of emails based on folder categories, a detailed view pane, and a conversation view pane displaying a list of available conversations and associated properties.
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1. A method to be executed at least in part in a computing device for enabling traversal between an email exchange and a real time conversation, the method comprising: while facilitating a first email exchange including a trail of connected messages, replies and forwarded messages, receiving a request for activating a first real time conversation that includes at least one from a set of: audio communication, video communication, application sharing, and data sharing based on an email of the first email exchange, wherein the first email exchange is part of two or more conversations concurrently; ordering the first email exchange according to at least one from a set of: a temporal order and a grouping by different threads; reconstructing the email exchange in a story form including a topic to facilitate transitioning from the first email exchange to the first real time conversation; determining participants of the first real time conversation based on a context of the first email exchange and a user entry in an entry box presented on a user interface; populating the participants of the first real time conversation according to presence information associated with recipients of the first email exchange; excluding at least one of the participants of the email exchange based on permission levels and attributes of the first email exchange content; activating the first real time conversation, wherein a context for the first real time conversation is provided based on the context of the email and formatted based on a set of predefined rules and a user preference; and displaying the first real time conversation over the user interface wherein the user interface includes textual and graphical selectable controls, links to functionalities including one or more of: a calendar, a contact list that lists contacts categorized by user defined groups and their statuses, and a task list, a folder view providing a grouping of emails based on folder categories, a detailed view pane, and a conversation view pane displaying a list of available conversations and associated properties. 9. The method of claim 1 , wherein the email is part of an email conversation, and wherein the context for the first real time conversation is further provided based on an attribute of the email conversation.
| 0.809524 |
8,909,810 | 77 | 78 |
77. The method of claim 76 , comprising determining a grouping an item of content received from a said node in accord with any of (a) a user designation, (b) supplementary information for that item of content, and (c) content of that item.
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77. The method of claim 76 , comprising determining a grouping an item of content received from a said node in accord with any of (a) a user designation, (b) supplementary information for that item of content, and (c) content of that item. 78. The method of claim 77 , wherein the supplementary information comprises any of (i) header information provided with transmission of the item of content, and (ii) metadata provided with the item of content.
| 0.5 |
8,266,077 | 1 | 2 |
1. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the term-frequency matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; converting the correlation values to distance values; creating a concept graph of connected components using the distance values that are greater than or less than a concept threshold, where each connected component is a concept set of terms that corresponds to a concept; and clustering documents that contain the terms of the concept set together.
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1. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the term-frequency matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; converting the correlation values to distance values; creating a concept graph of connected components using the distance values that are greater than or less than a concept threshold, where each connected component is a concept set of terms that corresponds to a concept; and clustering documents that contain the terms of the concept set together. 2. The method of claim 1 , wherein the filtering is performed with reference to a set of stop words.
| 0.73822 |
9,311,301 | 21 | 23 |
21. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computer to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities.
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21. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computer to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities. 23. The non-transitory computer-readable medium of claim 21 , wherein assigning the high-probability chains to the high-confidence buckets comprises: grouping the plurality of chains based on the respective context-based name and category such that chains having a same context-based name and same category are grouped together into a respective partition; within the respective partition, grouping chains that correspond to the same concept into sub-entities; and grouping together, across and within partitions, the sub-entities that correspond to the same concept.
| 0.662901 |
9,836,301 | 12 | 18 |
12. A non-transitory computer readable medium having stored thereon machine readable instructions for component discovery, the machine readable instructions, when executed, cause a processor to: determine business classes by excluding packages and classes in source code; extract code features from the business classes by extracting packaging information for each of the business classes, wherein extracting packaging information for each of the business classes includes extracting concept words embedded in business class names, extracting a packaging hierarchy as a string, and extracting a substring that describes the packaging hierarchy; estimate similarity for business class pairs based on the extracted features; cluster the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determine interfaces for the components based on the clustering by identifying public methods of the business classes in a cluster of the generated clusters that are called by the business classes of other clusters from the generated clusters.
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12. A non-transitory computer readable medium having stored thereon machine readable instructions for component discovery, the machine readable instructions, when executed, cause a processor to: determine business classes by excluding packages and classes in source code; extract code features from the business classes by extracting packaging information for each of the business classes, wherein extracting packaging information for each of the business classes includes extracting concept words embedded in business class names, extracting a packaging hierarchy as a string, and extracting a substring that describes the packaging hierarchy; estimate similarity for business class pairs based on the extracted features; cluster the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determine interfaces for the components based on the clustering by identifying public methods of the business classes in a cluster of the generated clusters that are called by the business classes of other clusters from the generated clusters. 18. The non-transitory computer readable medium according to claim 12 , further comprising machine readable instructions that when executed by the processor further cause the processor to: cluster a plurality of application portfolios that each includes a plurality of applications that use different types of source code including the source code.
| 0.70903 |
9,589,014 | 19 | 20 |
19. The computer system of claim 9 , wherein the one or more non-transitory computer-readable storage media further store instructions, which, when executed by the one or more processors, cause: using the user interface screen display, receiving input specifying one or more constraints, default values and other attributes of a parser definition.
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19. The computer system of claim 9 , wherein the one or more non-transitory computer-readable storage media further store instructions, which, when executed by the one or more processors, cause: using the user interface screen display, receiving input specifying one or more constraints, default values and other attributes of a parser definition. 20. The computer system of claim 19 , wherein the input specifying one or more constraints, default values and other attributes of a parser definition comprises an indication that a match to a particular property type component is not required.
| 0.5 |
8,271,542 | 6 | 7 |
6. A method according to claim 5 , wherein the step of automatically producing the particularly organized and selected set of metadata includes: automatically categorizing the data objects within the resource.
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6. A method according to claim 5 , wherein the step of automatically producing the particularly organized and selected set of metadata includes: automatically categorizing the data objects within the resource. 7. A method according to claim 6 , further comprising: translating the metadata from a base schema to the selected metadata schema.
| 0.5 |
9,613,125 | 1 | 3 |
1. A method comprising: storing in a database a first annotation and a second annotation, the first annotation relating to a first content unit and comprising a first semantic label and first content, the first semantic label comprising a term that does not appear in the first content and indicating a semantic classification of the first content, the second annotation relating to a second content unit and comprising a second semantic label and second content, the second semantic label comprising a term that does not appear in the second content and indicating a semantic classification of the second content, the semantic classification of the second content being different from the semantic classification of the first content, wherein the semantic classification of the first content indicates a meaning of the first content in context of the first content unit, wherein the first content does not explicitly appear in the first content unit, the term that indicates the semantic classification of the first content indicating a meaning of the first content in context of the first content unit from which the first content was determined, wherein the second content is a text excerpt of text of the second content unit, wherein the semantic classification of the second content indicates that the second content is an organizational and/or grammatical element of the text of the second content unit, wherein the storing comprises storing the first semantic label for the first annotation and the second semantic label for the second annotation in a first table of the database, and storing the first content of the first annotation and the second content of the second annotation in at least one second table of the database different from the first table.
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1. A method comprising: storing in a database a first annotation and a second annotation, the first annotation relating to a first content unit and comprising a first semantic label and first content, the first semantic label comprising a term that does not appear in the first content and indicating a semantic classification of the first content, the second annotation relating to a second content unit and comprising a second semantic label and second content, the second semantic label comprising a term that does not appear in the second content and indicating a semantic classification of the second content, the semantic classification of the second content being different from the semantic classification of the first content, wherein the semantic classification of the first content indicates a meaning of the first content in context of the first content unit, wherein the first content does not explicitly appear in the first content unit, the term that indicates the semantic classification of the first content indicating a meaning of the first content in context of the first content unit from which the first content was determined, wherein the second content is a text excerpt of text of the second content unit, wherein the semantic classification of the second content indicates that the second content is an organizational and/or grammatical element of the text of the second content unit, wherein the storing comprises storing the first semantic label for the first annotation and the second semantic label for the second annotation in a first table of the database, and storing the first content of the first annotation and the second content of the second annotation in at least one second table of the database different from the first table. 3. The method of claim 1 , wherein the storing the first semantic label and the second semantic label in the first table of the database comprises storing the first semantic label and the second semantic label in one data structure in at least one computer-readable storage medium, the data structure specifying an organization of the first table.
| 0.849523 |
7,890,324 | 7 | 9 |
7. A method of temporarily providing one of a plurality of widgets to a user in the course of a multi-modal dialog with a computer device in a map-based application, the method comprising: after first user input received in a combination of a first mode and a second mode, determining whether further user input would be advantageous before the computer device presents information to the user; if further user input would be advantageous, selecting a widget from a plurality of widgets to yield a selected widget, the selected widget being associated with the further user input; maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via user interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the selected widget in a corner of the display for receiving the further user input as directed by the presented speech, wherein the further user input is received in a non-speech mode and provides distance range data that is shown on the display screen as the selected widget is adjusted by the further user input.
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7. A method of temporarily providing one of a plurality of widgets to a user in the course of a multi-modal dialog with a computer device in a map-based application, the method comprising: after first user input received in a combination of a first mode and a second mode, determining whether further user input would be advantageous before the computer device presents information to the user; if further user input would be advantageous, selecting a widget from a plurality of widgets to yield a selected widget, the selected widget being associated with the further user input; maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via user interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the selected widget in a corner of the display for receiving the further user input as directed by the presented speech, wherein the further user input is received in a non-speech mode and provides distance range data that is shown on the display screen as the selected widget is adjusted by the further user input. 9. The method of claim 7 , wherein the computer device dynamically generates the content of the selected widget according to the required further user input.
| 0.5 |
7,626,111 | 3 | 6 |
3. The method of claim 1 , wherein the classifying a mood and a genre of the music file using the generated music content summary includes: extracting a modified discrete cosine transformation (MDCT)-based timbre feature from the music content summary; extracting an MDCT-based tempo feature from the music content summary; and classifying the mood and the genre of the music file based on the extracted timbre feature tempo feature.
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3. The method of claim 1 , wherein the classifying a mood and a genre of the music file using the generated music content summary includes: extracting a modified discrete cosine transformation (MDCT)-based timbre feature from the music content summary; extracting an MDCT-based tempo feature from the music content summary; and classifying the mood and the genre of the music file based on the extracted timbre feature tempo feature. 6. The method of claim 3 , wherein the extracting a MDCT-based tempo feature from the music content summary includes: extracting the MDCT coefficients by decoding a part of the music content summary; selecting an MDCT coefficient of a predetermined sub-band from the MDCT coefficients; extracting an MDCT modulation spectrum (MS) from the selected MDCT coefficient by performing a Discrete Fourier Transformation (DFT); and dividing the extracted MDCT-MS into N sub-bands and extracting energy from the sub-bands usable as an MDCT-MS-based tempo feature.
| 0.5 |
9,785,681 | 8 | 10 |
8. A method for searching for content, the method comprising: receiving a media search query for one or more media assets; identifying a plurality of web search results from a corpus of web resources that are responsive to the media search query; determining contextual information from a subset of the web search results, wherein a plurality of media entities are determined from at least a portion of the contextual information; assigning a topic score for the each of the plurality of media entities based on occurrence in the web search results; selecting at least one media entity from the plurality of media entities based on the topic score; identifying a plurality of media assets from a corpus of media assets based at least in part on the selected media entity; and causing a subset of the plurality of media assets to be presented to a user in response to the media search query.
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8. A method for searching for content, the method comprising: receiving a media search query for one or more media assets; identifying a plurality of web search results from a corpus of web resources that are responsive to the media search query; determining contextual information from a subset of the web search results, wherein a plurality of media entities are determined from at least a portion of the contextual information; assigning a topic score for the each of the plurality of media entities based on occurrence in the web search results; selecting at least one media entity from the plurality of media entities based on the topic score; identifying a plurality of media assets from a corpus of media assets based at least in part on the selected media entity; and causing a subset of the plurality of media assets to be presented to a user in response to the media search query. 10. The method of claim 8 , further comprising rewriting the media search query by inserting one or more media terms prior to identifying the plurality of web search results from the corpus of web resources.
| 0.736641 |
9,542,933 | 3 | 24 |
3. The method of claim 2 , further comprising: performing second speech recognition on the outputted buffered audio signals, both those corresponding to the recognized speech element and those received subsequent to the buffered audio signals that correspond to the recognized speech element, wherein the second speech recognition is more sophisticated than the speech recognition performed using the locally-stored vocabulary.
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3. The method of claim 2 , further comprising: performing second speech recognition on the outputted buffered audio signals, both those corresponding to the recognized speech element and those received subsequent to the buffered audio signals that correspond to the recognized speech element, wherein the second speech recognition is more sophisticated than the speech recognition performed using the locally-stored vocabulary. 24. The method of claim 3 , wherein the speech recognition performed using the locally-stored vocabulary is performed by a processor circuit under a first power consumption constraint, and wherein the more sophisticated second speech recognition is performed using the same or a different processor circuit under a second and less restrictive power consumption constraint.
| 0.539604 |
8,976,375 | 1 | 2 |
1. An image forming apparatus including an operating panel capable of providing a screen display and a Web browser, the image forming apparatus comprising: a storage portion configured to store predetermined text that is data to be entered into a text entry box of a Web page; a text entry limiting portion configured to, when the Web page displayed on the operating panel by the Web browser contains the text entry box, limit text to be entered into the text entry box to the predetermined text stored in the storage portion; a display processing portion configured to, when the text entry limiting portion limits text to be entered, display a first selection screen and a second selection screen on the operating panel, wherein the first selection screen shows options of types of the predetermined text which are candidates for being entered into the text entry box, and the second selection screen being for a user to designate, as text to be entered into the text entry box, the predetermined text corresponding to a type selected from among the types on the first selection screen; an operation processing portion configured to inform the Web browser of the predetermined text designated by the user on the second selection screen; and a recording portion configured to make a record of a history that identifies the Web page and indicates a type of the predetermined text designated by the user, wherein when the Web page to be displayed by the Web browser is a Web page which is displayed before and whose history is already recorded, the display processing portion displays the first selection screen in such a manner that the type of the predetermined text indicated in the history takes precedence over other types.
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1. An image forming apparatus including an operating panel capable of providing a screen display and a Web browser, the image forming apparatus comprising: a storage portion configured to store predetermined text that is data to be entered into a text entry box of a Web page; a text entry limiting portion configured to, when the Web page displayed on the operating panel by the Web browser contains the text entry box, limit text to be entered into the text entry box to the predetermined text stored in the storage portion; a display processing portion configured to, when the text entry limiting portion limits text to be entered, display a first selection screen and a second selection screen on the operating panel, wherein the first selection screen shows options of types of the predetermined text which are candidates for being entered into the text entry box, and the second selection screen being for a user to designate, as text to be entered into the text entry box, the predetermined text corresponding to a type selected from among the types on the first selection screen; an operation processing portion configured to inform the Web browser of the predetermined text designated by the user on the second selection screen; and a recording portion configured to make a record of a history that identifies the Web page and indicates a type of the predetermined text designated by the user, wherein when the Web page to be displayed by the Web browser is a Web page which is displayed before and whose history is already recorded, the display processing portion displays the first selection screen in such a manner that the type of the predetermined text indicated in the history takes precedence over other types. 2. The image forming apparatus according to claim 1 , wherein the display processing portion extracts a plurality of sets of the predetermined text from data held in the image forming apparatus, and displays the plurality of sets of the predetermined text extracted on the second selection screen.
| 0.760484 |
8,132,093 | 1 | 6 |
1. A system for annotating instances of objects, comprising: a memory having stored therein computer-executable instructions; a computer processor that executes the computer-executable instructions; an agent that configures a plurality of object instances of an object to be annotated by annotations of different types, wherein an annotation of at least one object instance is a value of a specified type; and an interface configured to provide a set of annotation operations associated with said annotation of the at least one object instance, wherein said set of annotation operations are configured to annotate data associated with said annotation of the at least one object instance using a type corresponding to said specified type, wherein said set of annotation operations comprises a retrieve operation, wherein said retrieve operation is configurable to retrieve annotations according to a weakly typed scenario and a strongly typed scenario, wherein a particular type is used as a search key in the weakly typed scenario, and wherein a generic parameter is used as the search key in the strongly typed scenario.
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1. A system for annotating instances of objects, comprising: a memory having stored therein computer-executable instructions; a computer processor that executes the computer-executable instructions; an agent that configures a plurality of object instances of an object to be annotated by annotations of different types, wherein an annotation of at least one object instance is a value of a specified type; and an interface configured to provide a set of annotation operations associated with said annotation of the at least one object instance, wherein said set of annotation operations are configured to annotate data associated with said annotation of the at least one object instance using a type corresponding to said specified type, wherein said set of annotation operations comprises a retrieve operation, wherein said retrieve operation is configurable to retrieve annotations according to a weakly typed scenario and a strongly typed scenario, wherein a particular type is used as a search key in the weakly typed scenario, and wherein a generic parameter is used as the search key in the strongly typed scenario. 6. The system according to claim 1 , wherein said object instance is configured to be annotated by one of (a) an XML node and (b) a CodeDom object producer.
| 0.738255 |
7,873,992 | 7 | 8 |
7. The method of claim 6 , wherein a third processor executable parser successfully parses a first portion of the input stream to form a third output and the first processor executable parser successfully parses the first portion of the input stream to form a first output and further comprising: determining, by the processor executable parser selection agent, which of the first and third outputs most likely corresponds to the first portion.
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7. The method of claim 6 , wherein a third processor executable parser successfully parses a first portion of the input stream to form a third output and the first processor executable parser successfully parses the first portion of the input stream to form a first output and further comprising: determining, by the processor executable parser selection agent, which of the first and third outputs most likely corresponds to the first portion. 8. The method of claim 7 , wherein the determining step is performed using a least squares fit analysis and wherein step (d) is performed using a declarative programming rather than procedural programming approach.
| 0.5 |
4,057,849 | 2 | 3 |
2. A unit as recited in claim 1 wherein said address generator means includes counter means for generating address signals in sequence, said address transfer means being connected to said counter means for presetting said counter means with the value in said address recording means.
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2. A unit as recited in claim 1 wherein said address generator means includes counter means for generating address signals in sequence, said address transfer means being connected to said counter means for presetting said counter means with the value in said address recording means. 3. A unit as recited in claim 2 wherein said control means comprises: i. position means connected to said timing means for generating position signals that designate the display position of each character along its display line, ii. margin register means containing a number indicating a selected maximum line length and thereby defining a line-ending margin position, and iii. comparison means connected to said transfer means, said margin register means and said position means for inhibiting the transfer means when the position signals correspond to the number in said margin register means.
| 0.5 |
7,997,485 | 1 | 6 |
1. A computer-implemented system that facilitates content presentation, comprising: a profile component that facilitates user creation of user preferences data in a user profile of a user; a control component that facilitates the user's control to incrementally expose portions of the user preferences data from the user profile of the user to a vendor and to independently expose different amounts of the user preference data to each of a plurality of different vendors; and a content component that presents content of the vendor to the user based on the exposed portions of the user preferences data.
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1. A computer-implemented system that facilitates content presentation, comprising: a profile component that facilitates user creation of user preferences data in a user profile of a user; a control component that facilitates the user's control to incrementally expose portions of the user preferences data from the user profile of the user to a vendor and to independently expose different amounts of the user preference data to each of a plurality of different vendors; and a content component that presents content of the vendor to the user based on the exposed portions of the user preferences data. 6. The system of claim 1 , wherein the content component further presents the content of the vendor based on a preferred type of content expressed in the user preferences.
| 0.672414 |
9,097,548 | 12 | 15 |
12. A content delivery system comprising: a control unit for: determining a context for identifying a device within a geographic region, identifying a feature including a key feature and a contrastive feature of a candidate route, generating a route description based on the feature, generating a prompt based on the context for adding or removing the feature from the route description, and a communication unit, coupled to the control unit, for delivering the prompt on the device.
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12. A content delivery system comprising: a control unit for: determining a context for identifying a device within a geographic region, identifying a feature including a key feature and a contrastive feature of a candidate route, generating a route description based on the feature, generating a prompt based on the context for adding or removing the feature from the route description, and a communication unit, coupled to the control unit, for delivering the prompt on the device. 15. The system as claimed in claim 12 wherein the control unit is for generating a core description based on an expression format with a total usage count greater than another instance of the expression format.
| 0.5 |
9,967,228 | 3 | 4 |
3. The non-transitory, tangible, and computer-readable medium of claim 1 , wherein the time-variant data comprises real-time data.
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3. The non-transitory, tangible, and computer-readable medium of claim 1 , wherein the time-variant data comprises real-time data. 4. The non-transitory, tangible, and computer-readable medium of claim 3 , wherein the real-time data comprises a current temperature, a current density, a current time of day, or a combination thereof.
| 0.5 |
4,181,821 | 2 | 3 |
2. A circuit for recognizing an unknown utterance as one of a set of reference words according to claim 1 characterized in that the template signal generating means (112) further comprises means (222, 224, 225, 226, 228, 230) for successively partitioning said reference word feature signal sets into clusters of feature signal sets, the feature signal sets of each cluster having a predetermined degree of similarity; and means (600, 230, 216) for identifying a feature signal set in each cluster as the template signal representative of all feature signal sets in said cluster.
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2. A circuit for recognizing an unknown utterance as one of a set of reference words according to claim 1 characterized in that the template signal generating means (112) further comprises means (222, 224, 225, 226, 228, 230) for successively partitioning said reference word feature signal sets into clusters of feature signal sets, the feature signal sets of each cluster having a predetermined degree of similarity; and means (600, 230, 216) for identifying a feature signal set in each cluster as the template signal representative of all feature signal sets in said cluster. 3. A circuit for recognizing an unknown utterance as one of a set of reference words according to claim 2 wherein each feature signal set generating means comprises means for producing prediction parameter signals representative of the utterance; said similarity signal generating means comprises means jointly responsive to the prediction parameter signals of the unknown utterance and the prediction parameter sigals of each reference word template signal for producing a signal representative of the distance between said unknown utterance prediction parameter signals and said reference word template prediction parameter signals; characterized in that said selection means (130) further comprises means (1825) for selecting a plurality of the smallest distance signals for each reference word, said averaging means (135) comprises means (1830 1833, 1836) for forming a signal representative of the average of said selected distance signals for each reference word; and said identifying apparatus (140, 145) comprises means (1839, 1891) responsive to the average distance signals formed for all reference words for identifying the unknown utterance as the reference word having the least average distance signal.
| 0.5 |
8,131,778 | 1 | 7 |
1. A method for providing a versatile notepad, said method comprising: receiving an input content from a user at a dynamic notepad interface, during said receiving the input content, dynamically: determining information expressed in the received input content to correspond to at least one of the following predetermined expression types: an expression of time, an expression of a location, an expression of a statement, an expression of an individual, an expression of a list, and a combination of expressions of the time, the location, the statement, the list, and the individual; converting the determined information to a format of its corresponding one or more of the predetermined expression types; populating a separate data field of a data structure with the converted information based on the corresponding expression type of the converted information, each data field of said data structure corresponding to a different predetermined expression type; determining one or more discrete communication objects that all the populated data fields of the data structure correspond to, wherein the received input does not specify said one or more discrete communication objects; without further user input, dynamically generating at least one of said one or more determined discrete communication objects from the determined information, wherein the communication object is different from the dynamic notepad interface; and rendering the generated communication object to the user.
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1. A method for providing a versatile notepad, said method comprising: receiving an input content from a user at a dynamic notepad interface, during said receiving the input content, dynamically: determining information expressed in the received input content to correspond to at least one of the following predetermined expression types: an expression of time, an expression of a location, an expression of a statement, an expression of an individual, an expression of a list, and a combination of expressions of the time, the location, the statement, the list, and the individual; converting the determined information to a format of its corresponding one or more of the predetermined expression types; populating a separate data field of a data structure with the converted information based on the corresponding expression type of the converted information, each data field of said data structure corresponding to a different predetermined expression type; determining one or more discrete communication objects that all the populated data fields of the data structure correspond to, wherein the received input does not specify said one or more discrete communication objects; without further user input, dynamically generating at least one of said one or more determined discrete communication objects from the determined information, wherein the communication object is different from the dynamic notepad interface; and rendering the generated communication object to the user. 7. The method of claim 1 , wherein the one or more discrete communication objects comprises an appointment object, an electronic mail (e-mail) object, a task object, a to-do object, an instant messaging object, a private message object, a location/map description object, or an asynchronous “note” object.
| 0.768939 |
10,096,023 | 10 | 16 |
10. A data processing system for using a unique token in online transactions involving sensitive information to control access to the sensitive information, the data processing system comprising a processor and one or more storage devices embodying computer-readable program instructions that, when executed by the processor, cause the data processing system to: register at least one entity, the registering comprising associating the at least one entity with a subscription level; in response to receipt of the sensitive information from a merchant device, generate a unique token for use in place of the sensitive information, wherein the sensitive information comprises a character string stores as encrypted data; directly associate a sub-string of a character string with the unique token so that a direct association does not exist between the unique token and the character string, the character string comprising the sensitive information and the sub-string being configured to identify the character string without revealing the sensitive information; and access the character string stored as encrypted data in storage memory using the unique token and the sub-string to retrieve the sensitive information after transmission of a request for the sensitive information from a registered entity associated with a subscription level associated with a privilege to receive the requested sensitive information.
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10. A data processing system for using a unique token in online transactions involving sensitive information to control access to the sensitive information, the data processing system comprising a processor and one or more storage devices embodying computer-readable program instructions that, when executed by the processor, cause the data processing system to: register at least one entity, the registering comprising associating the at least one entity with a subscription level; in response to receipt of the sensitive information from a merchant device, generate a unique token for use in place of the sensitive information, wherein the sensitive information comprises a character string stores as encrypted data; directly associate a sub-string of a character string with the unique token so that a direct association does not exist between the unique token and the character string, the character string comprising the sensitive information and the sub-string being configured to identify the character string without revealing the sensitive information; and access the character string stored as encrypted data in storage memory using the unique token and the sub-string to retrieve the sensitive information after transmission of a request for the sensitive information from a registered entity associated with a subscription level associated with a privilege to receive the requested sensitive information. 16. The data processing system of claim 10 , wherein the computer-readable program instructions, when executed by the processor, further cause the data processing system to: verify that a computer device or a user retrieving the sensitive information is authorized to access the character string.
| 0.55287 |
9,058,382 | 1 | 6 |
1. A method performed by a computing device for generating a feature from a hierarchy of documents, the method comprising: providing a hierarchical organization of the documents, the hierarchical organization specifying parent/child relations between documents, one of the documents being a root document of the hierarchical organization that has no parent document, some of the documents of the hierarchical organization being leaf documents that have no child documents, each document other than the root document and the leaf documents having both a parent document and a child document, the parent/child relations occurring when a parent document contains a reference to a child document; generating a feature for each of the documents in the hierarchical organization of documents; and for each document, generating an aggregate feature from the generated features of the documents to represent the feature for the document by combining the generated feature for that document with the generated aggregate features for child documents of that document to generate an aggregate feature for that document by summing the features for child documents of that document, dividing that sum by the number of child documents to generate a quotient, and multiply the quotient by a weighting factor so that each document in the hierarchical organization with a child document has an aggregate feature derived from the generated feature for that document and the aggregate features of the child documents of that document.
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1. A method performed by a computing device for generating a feature from a hierarchy of documents, the method comprising: providing a hierarchical organization of the documents, the hierarchical organization specifying parent/child relations between documents, one of the documents being a root document of the hierarchical organization that has no parent document, some of the documents of the hierarchical organization being leaf documents that have no child documents, each document other than the root document and the leaf documents having both a parent document and a child document, the parent/child relations occurring when a parent document contains a reference to a child document; generating a feature for each of the documents in the hierarchical organization of documents; and for each document, generating an aggregate feature from the generated features of the documents to represent the feature for the document by combining the generated feature for that document with the generated aggregate features for child documents of that document to generate an aggregate feature for that document by summing the features for child documents of that document, dividing that sum by the number of child documents to generate a quotient, and multiply the quotient by a weighting factor so that each document in the hierarchical organization with a child document has an aggregate feature derived from the generated feature for that document and the aggregate features of the child documents of that document. 6. The method of claim 1 wherein the documents are web pages.
| 0.930046 |
9,529,863 | 15 | 21 |
15. A processor readable non-transitory storage media that includes instructions for ingesting data for a data model, wherein execution of the instructions by a hardware processor performs actions, comprising: providing one or more raw data sets to an ingestion engine, wherein each raw data set includes one or more raw records; providing one or more ingestion rules associated with one or more confidence scores and one or more known data sets based on a type of the one or more raw records; employing the ingestion engine to iteratively execute the one or more ingestion rules, performing further actions, including: providing a comparison of one or more portions of the one or more raw records to the one or more known data sets; transforming contents of the one or more raw records into one or more model record values based on the comparison to the one or more known data sets; storing the one or more model record values in one or more model records; providing a score value that indicates a confidence level that the one or more model records are correct based on the one or more confidence scores; and storing an association of the one or more ingestion rules used to transform the raw record contents into the model record values stored in the one or more model records; when the score value that indicates the confidence level of the one or more model records is less than a threshold value, performing further actions, including: providing a user-interface to interactively edit the one or more raw records or the one or more ingestion rules, wherein the edited one or more ingestion rules produce an increase change or a decrease change in the one or more confidence scores, wherein the one or more changed confidence scores are employed to provide the score value; and storing the one or more model records in a data store, wherein the one or more model records are added to the data model.
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15. A processor readable non-transitory storage media that includes instructions for ingesting data for a data model, wherein execution of the instructions by a hardware processor performs actions, comprising: providing one or more raw data sets to an ingestion engine, wherein each raw data set includes one or more raw records; providing one or more ingestion rules associated with one or more confidence scores and one or more known data sets based on a type of the one or more raw records; employing the ingestion engine to iteratively execute the one or more ingestion rules, performing further actions, including: providing a comparison of one or more portions of the one or more raw records to the one or more known data sets; transforming contents of the one or more raw records into one or more model record values based on the comparison to the one or more known data sets; storing the one or more model record values in one or more model records; providing a score value that indicates a confidence level that the one or more model records are correct based on the one or more confidence scores; and storing an association of the one or more ingestion rules used to transform the raw record contents into the model record values stored in the one or more model records; when the score value that indicates the confidence level of the one or more model records is less than a threshold value, performing further actions, including: providing a user-interface to interactively edit the one or more raw records or the one or more ingestion rules, wherein the edited one or more ingestion rules produce an increase change or a decrease change in the one or more confidence scores, wherein the one or more changed confidence scores are employed to provide the score value; and storing the one or more model records in a data store, wherein the one or more model records are added to the data model. 21. The media of claim 15 , wherein providing the one or more raw data sets to an ingestion engine, comprises further actions, including: caching at least a portion of the one or more raw data sets when network communication is disabled; and providing the cached at least portion of the one or more raw data sets when network communication is enabled.
| 0.592807 |
8,560,313 | 1 | 2 |
1. A method of speech recognition, comprising the steps of: (a) receiving audio including user speech and at least some transient noise associated with the speech; (b) converting the received audio into digital data; (c) segmenting the digital data into acoustic frames; (d) extracting acoustic feature vectors from the acoustic frames; (e) evaluating the acoustic frames for transient noise on a frame-by-frame basis; (f) rejecting those acoustic frames having transient noise, wherein steps (e) and (f) include assessing at least two time spaced samples within an acoustic frame to determine autocorrelation of the samples within the frame, and rejecting the acoustic frame if the autocorrelation is determined to be insufficient; (g) accepting as speech frames those acoustic frames having no transient noise; and thereafter (h) recognizing the user speech using the speech frames.
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1. A method of speech recognition, comprising the steps of: (a) receiving audio including user speech and at least some transient noise associated with the speech; (b) converting the received audio into digital data; (c) segmenting the digital data into acoustic frames; (d) extracting acoustic feature vectors from the acoustic frames; (e) evaluating the acoustic frames for transient noise on a frame-by-frame basis; (f) rejecting those acoustic frames having transient noise, wherein steps (e) and (f) include assessing at least two time spaced samples within an acoustic frame to determine autocorrelation of the samples within the frame, and rejecting the acoustic frame if the autocorrelation is determined to be insufficient; (g) accepting as speech frames those acoustic frames having no transient noise; and thereafter (h) recognizing the user speech using the speech frames. 2. The method of claim 1 , wherein the steps (e) and (g) include analyzing an acoustic frame to determine whether an acoustic frame includes a voiced or an unvoiced signal, and accepting the acoustic frame if the acoustic frame is determined to include a voiced signal.
| 0.887636 |
8,515,901 | 1 | 5 |
1. A people matching method, comprising: altering a computer-implemented directionally distinct relationship between a first person who is a first user of a computer-implemented system and a second person who is a second user of the computer-implemented system, wherein the altering of the directionally distinct relationship is explicitly performed by the first person; receiving a match of a first person with a third person, wherein the match is generated by a processor-based device and is based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is the altering of the directionally distinct relationship; and receiving a reason for the match, wherein the reason comprises one of the plurality of usage behaviors.
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1. A people matching method, comprising: altering a computer-implemented directionally distinct relationship between a first person who is a first user of a computer-implemented system and a second person who is a second user of the computer-implemented system, wherein the altering of the directionally distinct relationship is explicitly performed by the first person; receiving a match of a first person with a third person, wherein the match is generated by a processor-based device and is based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is the altering of the directionally distinct relationship; and receiving a reason for the match, wherein the reason comprises one of the plurality of usage behaviors. 5. The method of claim 1 , further comprising: receiving the match of the first person with the third person, wherein the match is generated in accordance with the inference, wherein the inference is based on a level of mutual interest expressed between the first person and the third person.
| 0.58046 |
7,505,463 | 31 | 34 |
31. The computer accessible medium of claim 30 , wherein in said resolving the program instructions are configured to implement modifying the action list of one or more of the conflicting rules.
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31. The computer accessible medium of claim 30 , wherein in said resolving the program instructions are configured to implement modifying the action list of one or more of the conflicting rules. 34. The computer accessible medium of claim 31 , wherein in said modifying the program instructions are configured to implement appending the actions of the lower priority conflicting rule to the actions of the higher priority conflicting rule if the packet set specified by the packet filter of the lower priority conflicting rule is a superset of the packet set specified by the packet filter of the higher priority rule.
| 0.510417 |
9,646,081 | 1 | 3 |
1. A computer implemented method for providing information related to a task in a case management system configured to process a plurality of cases, the computer implemented method comprising: identifying among the plurality of cases, by a server, a plurality of case clusters, wherein each of the plurality of case clusters is associated with a case similarity factor shared by at least two cases of the plurality of cases, and the case similarity factor is related to at least one of geographical case specific parameters and contextual case specific parameters; for a case cluster of the plurality of case clusters, identifying, by the server, a plurality of task clusters, wherein each of the plurality of task clusters is associated with a task similarity factor shared by at least two tasks of the task cluster, and tasks of the plurality of task clusters are performed on cases of the case cluster, and wherein for the case cluster of the plurality of case clusters, the task similarity factor is related to the case similarity factor and task specific parameters and the identifying the plurality of task clusters comprises: based on the task similarity factor, using task metadata, case metadata, and semantic entities to categorize the tasks into the plurality of task clusters, wherein the semantic entities are extracted from case documents used in performing the tasks; analyzing, by the server, reports and documents used to perform the at least two tasks of the task cluster sharing the task similarity factor; and when performing a task sharing the task similarity factor with the at least two tasks, providing, by the server, at least one report based on the reports and at least one summary based on the documents.
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1. A computer implemented method for providing information related to a task in a case management system configured to process a plurality of cases, the computer implemented method comprising: identifying among the plurality of cases, by a server, a plurality of case clusters, wherein each of the plurality of case clusters is associated with a case similarity factor shared by at least two cases of the plurality of cases, and the case similarity factor is related to at least one of geographical case specific parameters and contextual case specific parameters; for a case cluster of the plurality of case clusters, identifying, by the server, a plurality of task clusters, wherein each of the plurality of task clusters is associated with a task similarity factor shared by at least two tasks of the task cluster, and tasks of the plurality of task clusters are performed on cases of the case cluster, and wherein for the case cluster of the plurality of case clusters, the task similarity factor is related to the case similarity factor and task specific parameters and the identifying the plurality of task clusters comprises: based on the task similarity factor, using task metadata, case metadata, and semantic entities to categorize the tasks into the plurality of task clusters, wherein the semantic entities are extracted from case documents used in performing the tasks; analyzing, by the server, reports and documents used to perform the at least two tasks of the task cluster sharing the task similarity factor; and when performing a task sharing the task similarity factor with the at least two tasks, providing, by the server, at least one report based on the reports and at least one summary based on the documents. 3. The method of claim 1 , wherein analyzing, by the server, the reports and the documents used to perform the at least two tasks of the task cluster sharing the task similarity factor includes: monitoring, by the server, a filter criterion to generate the reports; and associating, by the server, the filter criterion and the reports with the at least two tasks.
| 0.705835 |
8,874,434 | 1 | 10 |
1. A method executed by a processor in communication with a memory storing a computer process tagger program that when executed by the processor generates a linguistic parse tree for a sentence, the method comprising the steps of: predicting by the computer process tagger a first level of chunk tags for the sentence; and predicting by the computer process at least a second level of chunk tags for the sentence using the first level or a previous level of chunk tags; from the predicted chunk tags, determining a sum of scores S in a graph G for a tag path [t] 1 N for words [w] 1 N as S ( [ w ] 1 N , [ t ] 1 N , θ ) = ∑ n = 1 N ( A t n - 1 t n + s ( x n ) t n ) , where N is the number of words, θ represents trained parameters of a neural network of the tagger with a fixed-sized word dictionary W, trained parameter matrices M 1 and M 2 , and transition score A, each node G tn is assigned a score s(x n ) t n from the neural network of the tagger, and given a pair of nodes G tn and G um , an edge is added with a transition score A tu on the graph; and outputting a graph with network scores provided for each G tn of the graph and additional transition scores for the edges of the graph.
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1. A method executed by a processor in communication with a memory storing a computer process tagger program that when executed by the processor generates a linguistic parse tree for a sentence, the method comprising the steps of: predicting by the computer process tagger a first level of chunk tags for the sentence; and predicting by the computer process at least a second level of chunk tags for the sentence using the first level or a previous level of chunk tags; from the predicted chunk tags, determining a sum of scores S in a graph G for a tag path [t] 1 N for words [w] 1 N as S ( [ w ] 1 N , [ t ] 1 N , θ ) = ∑ n = 1 N ( A t n - 1 t n + s ( x n ) t n ) , where N is the number of words, θ represents trained parameters of a neural network of the tagger with a fixed-sized word dictionary W, trained parameter matrices M 1 and M 2 , and transition score A, each node G tn is assigned a score s(x n ) t n from the neural network of the tagger, and given a pair of nodes G tn and G um , an edge is added with a transition score A tu on the graph; and outputting a graph with network scores provided for each G tn of the graph and additional transition scores for the edges of the graph. 10. The method of claim 1 , wherein the determining steps are performed with a deep convolutional neural network (CNN).
| 0.800336 |
8,165,987 | 1 | 2 |
1. An automatic rule generation system, comprising: a hardware computer that executes a computer program that implements the automatic rule generation system, the computer program including a rule generation module, a rule relaxation module, a rule testing module, an information extraction module, and a candidate suggestion module, wherein: the rule generation module receives a sample and generates a rule from the sample; the rule relaxation module generates a relaxed rule from the rule; the rule testing module generates a reverse index from a corpus, applies the relaxed rule to the reverse index to determine a superset of documents from the corpus that satisfy the relaxed rule as compared to a set of documents that satisfy the rules, and generates text segments from the superset of documents; the information extraction module generates modified text segments from the relaxed rule and the text segments; and the candidate suggestion module performs a candidate generation process using the modified text segments, wherein: if the candidate generation process generates no candidates from the modified text segments, the candidate suggestion module signals the rule relaxation module to generate a further relaxed rule to use as the relaxed rule, and if the candidate generation process generates a candidate from the modified text segments, the candidate suggestion module provides the candidate as an additional sample for the automatic rule generation system to generate another rule to use as the rule.
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1. An automatic rule generation system, comprising: a hardware computer that executes a computer program that implements the automatic rule generation system, the computer program including a rule generation module, a rule relaxation module, a rule testing module, an information extraction module, and a candidate suggestion module, wherein: the rule generation module receives a sample and generates a rule from the sample; the rule relaxation module generates a relaxed rule from the rule; the rule testing module generates a reverse index from a corpus, applies the relaxed rule to the reverse index to determine a superset of documents from the corpus that satisfy the relaxed rule as compared to a set of documents that satisfy the rules, and generates text segments from the superset of documents; the information extraction module generates modified text segments from the relaxed rule and the text segments; and the candidate suggestion module performs a candidate generation process using the modified text segments, wherein: if the candidate generation process generates no candidates from the modified text segments, the candidate suggestion module signals the rule relaxation module to generate a further relaxed rule to use as the relaxed rule, and if the candidate generation process generates a candidate from the modified text segments, the candidate suggestion module provides the candidate as an additional sample for the automatic rule generation system to generate another rule to use as the rule. 2. The automatic rule generation system of claim 1 , wherein a user evaluates a candidate and provides the candidate as the additional sample for the automatic rule generation system to generate another rule to use as the rule.
| 0.671014 |
8,108,389 | 16 | 19 |
16. The method of claim 15 wherein the tokens are placed into fields of at least one node based on their category.
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16. The method of claim 15 wherein the tokens are placed into fields of at least one node based on their category. 19. The method of claim 16 wherein the node pool is a database.
| 0.795455 |
8,386,465 | 59 | 61 |
59. A non-transitory computer-readable medium having encoded thereon a method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at a user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; performing at least one second predictive background query of the database in response to the at least one first predictive background query not encompassing the at least one generated query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query via the user interface in response to the at least one first predictive background query encompassing the at least one generated query.
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59. A non-transitory computer-readable medium having encoded thereon a method for decreasing the perceived end user latency while interacting with a database, the method comprising: aggregating metadata associated with media in the database; displaying on a user interface of an endpoint device, a first set of query results, wherein each query result in the displayed first set of query results representing a user selectable object that navigates to another set of query results displayable by the user interface wherein the endpoint device communicates with the digital media server via at least one of multiple connections between the endpoint device and the digital media server, wherein endpoint device and the digital media server negotiate a number of objects to be presented; performing at least one first predictive background query of the database based on the displayed first set of query results and prior to a user invoking any action within the user interface; receiving and storing the another set of query results for each of the query results in the displayed first set of query results from the at least one first predictive background query; receiving user input at a user interface; generating at least one query based on the user input; comparing the at least one generated query to the at least one first predictive background query; performing at least one second predictive background query of the database in response to the at least one first predictive background query not encompassing the at least one generated query; and displaying the another set of query results received from the at least one first predictive background query that correspond to the generated query via the user interface in response to the at least one first predictive background query encompassing the at least one generated query. 61. The method of claim 59 , further comprising performing the at least one generated query when the at least one first predictive background query and the at least one second predictive background query do not encompass the at least one generated query.
| 0.5 |
9,754,582 | 2 | 5 |
2. A method as claimed in claim 1 , wherein the input string is displayed to a user on a display of the user terminal.
|
2. A method as claimed in claim 1 , wherein the input string is displayed to a user on a display of the user terminal. 5. A method as claimed in claim 2 , wherein the pronounceable name is outputted to the display in editable form as an autosuggested replacement for the input string.
| 0.5 |
8,738,608 | 6 | 7 |
6. The data storage and/or retrieval system of claim 1 , wherein the plurality of entity type data tunnels comprise a plurality of combinative data tunnels, the plurality of attribute data tunnels comprise a plurality of combinative data tunnels, and the plurality of data cells of said combinative data tunnels are combinative data cells, wherein each respective instance of an attribute has one respective combinative data cell in all respective combinative data tunnels, wherein each of the combinative data cells has data for which a respective bounding operator evaluates to a boolean result which indicates either the likely possibility or the impossibility of the attribute instance corresponding to said combinative data cell being bounded for a given set of one or more operands, and wherein the storage engine accesses one or more of the plurality of combinative data tunnels based on one or more of said bounding operator and a given set of one or more operands.
|
6. The data storage and/or retrieval system of claim 1 , wherein the plurality of entity type data tunnels comprise a plurality of combinative data tunnels, the plurality of attribute data tunnels comprise a plurality of combinative data tunnels, and the plurality of data cells of said combinative data tunnels are combinative data cells, wherein each respective instance of an attribute has one respective combinative data cell in all respective combinative data tunnels, wherein each of the combinative data cells has data for which a respective bounding operator evaluates to a boolean result which indicates either the likely possibility or the impossibility of the attribute instance corresponding to said combinative data cell being bounded for a given set of one or more operands, and wherein the storage engine accesses one or more of the plurality of combinative data tunnels based on one or more of said bounding operator and a given set of one or more operands. 7. The data storage and/or retrieval system of claim 6 , wherein each instance of a respective attribute is expressed in unitary scale and as a significand with respect to a fixed radix point, each of the combinative data tunnels is respective to part of the significand, all of the combinative data tunnels are mutually exclusive in respect of the signficand, and all of the combinative data tunnels enclose the whole of the signficand.
| 0.5 |
9,460,709 | 8 | 11 |
8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving automatic speech recognition data from a mobile device, wherein the mobile device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; and transmitting, to the mobile device, a set of automatic speech recognition adaptation parameters which update the automatic speech recognition parameters of the mobile device, wherein the set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data.
|
8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving automatic speech recognition data from a mobile device, wherein the mobile device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; and transmitting, to the mobile device, a set of automatic speech recognition adaptation parameters which update the automatic speech recognition parameters of the mobile device, wherein the set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data. 11. The system of claim 8 , wherein the automatic speech recognition data comprises an automatic speech recognition output from the mobile device.
| 0.660465 |
5,416,903 | 1 | 6 |
1. A system for facilitating, for each of a plurality of end-user applications, the translation of end-user interface screens in said end-user applications from a first to a second language, having at least one subscreen, of a multilingual compatible data processing system comprising: means for generating a plurality of first files substantially comprising language independent information each corresponding to a different one of said end-user applications; means for generating a plurality of second files substantially comprising language dependant information alterable with effect independent of execution of said end-user applications, each of said second files corresponding to one of said first files; and formatting means for dynamically formatting, for display during execution of said each of said end-user applications, at least one of said end-user interface screens in said second language using information from one of said first files and one of said second files, said formatting means further comprising conversion means for automatically converting said at least one subscreen to a language dependent format.
|
1. A system for facilitating, for each of a plurality of end-user applications, the translation of end-user interface screens in said end-user applications from a first to a second language, having at least one subscreen, of a multilingual compatible data processing system comprising: means for generating a plurality of first files substantially comprising language independent information each corresponding to a different one of said end-user applications; means for generating a plurality of second files substantially comprising language dependant information alterable with effect independent of execution of said end-user applications, each of said second files corresponding to one of said first files; and formatting means for dynamically formatting, for display during execution of said each of said end-user applications, at least one of said end-user interface screens in said second language using information from one of said first files and one of said second files, said formatting means further comprising conversion means for automatically converting said at least one subscreen to a language dependent format. 6. The system of claim 1 wherein said first files and said second files are automatically generated from corresponding single source files using a data processing system program.
| 0.536458 |
7,752,200 | 1 | 10 |
1. A computer-implemented method for identifying search terms for advertising an item, the method comprising: identifying the item proposed for advertising; submitting a description of the item to a search engine service; receiving search results provided by the search engine service corresponding to the description of the item; analyzing web pages corresponding to the received search results to identify phrases of words within the web pages that are related to the item, the identifying of the phrases including generating a first score for at least some of the words of the web pages and generating a second score for phrases based at least in part on the first score of said at least some of the words within the phrases; the first score being generated based at least in part on a relative value of: a first average frequency of the word in the web pages, said first average frequency based at least in part upon a first frequency of the word for a plurality of the web pages corresponding to the received search results; a second average frequency of the word in a general corpus of web pages, said second average frequency based at least in part upon a second frequency of the word for the general corpus of web pages; the relative value of the first average frequency with respect to the second average frequency indicating a level of relevance of the word to the item; and deriving search terms for advertising the item from the identified phrases of the search results based at least in part upon the second score for each of the identified phrases.
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1. A computer-implemented method for identifying search terms for advertising an item, the method comprising: identifying the item proposed for advertising; submitting a description of the item to a search engine service; receiving search results provided by the search engine service corresponding to the description of the item; analyzing web pages corresponding to the received search results to identify phrases of words within the web pages that are related to the item, the identifying of the phrases including generating a first score for at least some of the words of the web pages and generating a second score for phrases based at least in part on the first score of said at least some of the words within the phrases; the first score being generated based at least in part on a relative value of: a first average frequency of the word in the web pages, said first average frequency based at least in part upon a first frequency of the word for a plurality of the web pages corresponding to the received search results; a second average frequency of the word in a general corpus of web pages, said second average frequency based at least in part upon a second frequency of the word for the general corpus of web pages; the relative value of the first average frequency with respect to the second average frequency indicating a level of relevance of the word to the item; and deriving search terms for advertising the item from the identified phrases of the search results based at least in part upon the second score for each of the identified phrases. 10. The method of claim 1 wherein a phrase is ended when a word that is similar to a word already in the phrase is encountered.
| 0.796474 |
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