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8,612,229 | 19 | 22 | 19. An apparatus for facilitating development of a computer-implemented natural language understanding (NLU) model associated with an NLU application, the apparatus comprising: at least one computer-readable medium encoded with instructions; and at least one processing unit coupled to the at least one computer-readable medium, wherein upon execution of the instructions by the at least one processing unit, the at least one processing unit: receives, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determines whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selects the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: adds the at least one expected user entry to an NLU entry data set associated with the NLU model, and trains the NLU model to associate the at least one expected user entry with the desired routing destination. | 19. An apparatus for facilitating development of a computer-implemented natural language understanding (NLU) model associated with an NLU application, the apparatus comprising: at least one computer-readable medium encoded with instructions; and at least one processing unit coupled to the at least one computer-readable medium, wherein upon execution of the instructions by the at least one processing unit, the at least one processing unit: receives, from a developer of the NLU application, at least one expected user entry and a corresponding desired routing destination; determines whether the NLU model associates the at least one expected user entry with the desired routing destination, the determining comprising: interpreting the at least one expected user entry via the NLU model to determine an actual routing destination for the at least one expected user entry, and comparing the actual routing destination to the desired routing destination; if it is determined that the actual routing destination of the at least one expected user entry matches the desired routing destination, selects the at least one expected user entry for presentation to a user during a help prompt of the NLU application as an example of a legitimate utterance the user could speak to be routed to the desired routing destination; and if it is determined that the actual routing destination does not match the desired routing destination: adds the at least one expected user entry to an NLU entry data set associated with the NLU model, and trains the NLU model to associate the at least one expected user entry with the desired routing destination. 22. The apparatus of claim 19 , wherein the at least one processing unit: increases a statistical weighting of the at least one expected user entry relative to another entry in the NLU data entry set. | 0.769585 |
7,761,320 | 8 | 9 | 8. The method in accordance with claim 1 , further comprising matching a specific individual with the new role template. | 8. The method in accordance with claim 1 , further comprising matching a specific individual with the new role template. 9. The method in accordance with claim 8 , further comprising determining whether each skill in the new role template is required or optional. | 0.5 |
8,706,747 | 14 | 18 | 14. The computer storage medium of claim 13 , in which translating the search query into the second format includes expanding the search query to create an expanded search query. | 14. The computer storage medium of claim 13 , in which translating the search query into the second format includes expanding the search query to create an expanded search query. 18. The computer storage medium of claim 14 , in which the expanded search query includes alternative encodings and alternative language translations of one or more of the search query terms. | 0.5 |
9,666,096 | 8 | 10 | 8. The totem of claim 1 , wherein each of the plurality of letter implementations of each of the letter language families include at least one of a raised and recessed surface area, said area functioning to allow a user to physically feel a shape of the implementation. | 8. The totem of claim 1 , wherein each of the plurality of letter implementations of each of the letter language families include at least one of a raised and recessed surface area, said area functioning to allow a user to physically feel a shape of the implementation. 10. The totem of claim 8 , wherein the letter implementations of one or more of the letter language families includes a material that is different from a material of another letter implementations of another letter language family. | 0.5 |
9,632,654 | 1 | 6 | 1. A smart knowledge discovery and augmentation system, comprising: an electronic device having a display screen operable to display a portion of a reference document using a first display layer and augmented content using a second display layer, the electronic device operable (i) to allow user interaction with the portion of the reference document for selection of a reference topic to be augmented, and (ii) to communicate with a remote server, wherein the reference document includes digital data information stored locally on the electronic device or via the remote server; and a ranking engine configured to prune out a portion of a set of features extracted from the reference document, wherein the augmented content is generated using a set of discovery patterns and a causality graph, wherein the set of discovery patterns is dynamically generated based on context aware competency questions relevant to content of the reference document, and wherein the causality graph is generated using (i) a set of prior topics that are relevant to content of the reference document, (ii) the reference topic to be augmented, (iii) a set of at least two causal relationships, (iv) a set of actors relevant to the set of at least two causal relationships, (v) a set of topics and a set of categories associated with the set of topics, and (vi) the set of discovery patterns. | 1. A smart knowledge discovery and augmentation system, comprising: an electronic device having a display screen operable to display a portion of a reference document using a first display layer and augmented content using a second display layer, the electronic device operable (i) to allow user interaction with the portion of the reference document for selection of a reference topic to be augmented, and (ii) to communicate with a remote server, wherein the reference document includes digital data information stored locally on the electronic device or via the remote server; and a ranking engine configured to prune out a portion of a set of features extracted from the reference document, wherein the augmented content is generated using a set of discovery patterns and a causality graph, wherein the set of discovery patterns is dynamically generated based on context aware competency questions relevant to content of the reference document, and wherein the causality graph is generated using (i) a set of prior topics that are relevant to content of the reference document, (ii) the reference topic to be augmented, (iii) a set of at least two causal relationships, (iv) a set of actors relevant to the set of at least two causal relationships, (v) a set of topics and a set of categories associated with the set of topics, and (vi) the set of discovery patterns. 6. The smart knowledge discovery and augmentation system of claim 1 , wherein the user interaction with the portion of the reference document includes at least one of a manipulation of a region of the first display layer, and a manipulation of a region of the second display layer. | 0.570336 |
7,962,326 | 1 | 4 | 1. A semantic answering system that returns natural language answers in an S-A-O (subject-action-object) format in response to a natural language question, wherein the S-A-O format represents semantic relationships between the S, A, and O elements, the system comprising: a problem statement generator that processes the natural language question to extract a problem statement in a format X-A-O, S-A-X, S-X-O, or S-X-X, wherein S, A, and O are semantic elements in the natural language question, X indicates absence of an S, A, or O; a knowledge base comprising an answer database including a set of answer S-A-Os and, for each answer S-A-O, a link to a source document; a semantic server configured to perform a non-keyword query of the knowledge base using the semantic elements and semantic relationships from the problem statement to find at least one answer S-A-O, wherein the at least one answer S-A-O includes the A and O, S and A, S and O, or S from the problem statement and an S, A, or O to replace each X in the problem statement, thereby completing the S-A-O format; and a communication device configured to output the at least one answer S-A-O to a computer. | 1. A semantic answering system that returns natural language answers in an S-A-O (subject-action-object) format in response to a natural language question, wherein the S-A-O format represents semantic relationships between the S, A, and O elements, the system comprising: a problem statement generator that processes the natural language question to extract a problem statement in a format X-A-O, S-A-X, S-X-O, or S-X-X, wherein S, A, and O are semantic elements in the natural language question, X indicates absence of an S, A, or O; a knowledge base comprising an answer database including a set of answer S-A-Os and, for each answer S-A-O, a link to a source document; a semantic server configured to perform a non-keyword query of the knowledge base using the semantic elements and semantic relationships from the problem statement to find at least one answer S-A-O, wherein the at least one answer S-A-O includes the A and O, S and A, S and O, or S from the problem statement and an S, A, or O to replace each X in the problem statement, thereby completing the S-A-O format; and a communication device configured to output the at least one answer S-A-O to a computer. 4. A system as set forth in claim 1 , wherein the user apparatus converts the at least one answer S-A-O into audio signals. | 0.800325 |
8,674,850 | 1 | 8 | 1. A computer-implemented method for selectively providing weather notifications to a crew of an aircraft, the computer-implemented method comprising: receiving weather information and parsing the weather information into weather components; associating a threshold with each weather component; determining a relevance code for each of a plurality of predetermined phases of flight according to the threshold of each weather component, wherein weather components during any particular phase of flight have different relevance codes; determining a target phase of flight of the plurality of predetermined phases of flight associated with the aircraft; determining a relevance for each weather component based on the corresponding relevance code during the target phase of flight; and providing a notification associated with the weather information according to the relevance of at least one weather component for the target phase of flight. | 1. A computer-implemented method for selectively providing weather notifications to a crew of an aircraft, the computer-implemented method comprising: receiving weather information and parsing the weather information into weather components; associating a threshold with each weather component; determining a relevance code for each of a plurality of predetermined phases of flight according to the threshold of each weather component, wherein weather components during any particular phase of flight have different relevance codes; determining a target phase of flight of the plurality of predetermined phases of flight associated with the aircraft; determining a relevance for each weather component based on the corresponding relevance code during the target phase of flight; and providing a notification associated with the weather information according to the relevance of at least one weather component for the target phase of flight. 8. The computer-implemented method of claim 1 , further comprising utilizing airport data corresponding to a destination airport to transform the weather information into at least one value corresponding to the weather component associated with the destination airport, wherein determining the relevance for the weather information according to the target phase of flight comprises utilizing the at least one value to select the threshold associated with the weather component and to determine the relevance code associated with the target phase of flight according to the threshold of the weather component, and wherein providing the notification associated with the weather information according to the relevance for the target phase of flight comprises providing the notification associated with the weather information according to the relevance code for the target phase of flight. | 0.5 |
8,970,854 | 13 | 14 | 13. The document management apparatus according to claim 5 , wherein the edit part identification section identifies at least one of a position of deletion processing, a start position of deletion processing, a start position of a deletion range, and an end position of the deletion range based on the electronic manuscript, which is located at the specified reference page and is extracted by the edit reference manuscript extraction section, and the document editing processing section includes a deletion processing section that, with adopting as a reference the at least one of the position of the deletion processing, the start position of the deletion processing, the start position of the deletion range, and the end position of the deletion range identified by the edit part identification section, deletes a given number of sheets of electronic manuscripts in the electronic document stored in the storage section. | 13. The document management apparatus according to claim 5 , wherein the edit part identification section identifies at least one of a position of deletion processing, a start position of deletion processing, a start position of a deletion range, and an end position of the deletion range based on the electronic manuscript, which is located at the specified reference page and is extracted by the edit reference manuscript extraction section, and the document editing processing section includes a deletion processing section that, with adopting as a reference the at least one of the position of the deletion processing, the start position of the deletion processing, the start position of the deletion range, and the end position of the deletion range identified by the edit part identification section, deletes a given number of sheets of electronic manuscripts in the electronic document stored in the storage section. 14. The document management apparatus according to claim 13 , wherein when the electronic manuscripts, which is located at the specified reference page and is extracted by the edit reference manuscript extraction section, indicate individual deletion positions, the deletion processing section deletes from the edit electronic document the electronic manuscripts at the specified reference page. | 0.700758 |
9,436,747 | 15 | 16 | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: identifying, by one or more computers, a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying, by the one or more computers, a structure of a portion of the structured document that includes at least one term of the seed query; generating, by the one or more computers, a query template that specifies the structure and a portion of the structure from which text should be extracted; generating, by the one or more computers, one or more synthetic queries using the query template and one or more other structured documents, the generating comprising: identifying a portion of a particular structured document that includes the structure specified by the query template; and generating a synthetic query using text contained in the portion of the structure of the particular structured document specified by the query template; and storing, by the one or more computers, the one or more synthetic queries in a query store. | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: identifying, by one or more computers, a seed query for a structured document based on a performance of the seed query with respect to the structured document; identifying, by the one or more computers, a structure of a portion of the structured document that includes at least one term of the seed query; generating, by the one or more computers, a query template that specifies the structure and a portion of the structure from which text should be extracted; generating, by the one or more computers, one or more synthetic queries using the query template and one or more other structured documents, the generating comprising: identifying a portion of a particular structured document that includes the structure specified by the query template; and generating a synthetic query using text contained in the portion of the structure of the particular structured document specified by the query template; and storing, by the one or more computers, the one or more synthetic queries in a query store. 16. The non-transitory computer storage medium of claim 15 , wherein the query template includes a generative rule that specifies the portion of the structure from which text should be extracted. | 0.757463 |
9,875,671 | 1 | 7 | 1. A computer-implemented method comprising: providing an application programming interface running in a web browser on a computer to receive a call from an event handler to process a detected user navigation event on a web page, wherein content navigation rules (CNRs) characterize nodes of a document-object-model (DOM) of the web page as a sequence of one or more logical paths through the web page when rendered by the computer, and wherein the CNRs are associated with respective augmented user interface (AUI) functionalities that are tailored to different types of users; in response to receiving the call, requesting a user preference file from a remote server; receiving, from the remote server, the user preference file and an AUI component API identified in the user preference file; and in response to receiving the user preference file: processing the detected user navigation event by: identifying a CNR corresponding to the detected navigation event; and calling, in the web browser, an AUI component application via the received AUI component API to invoke an AUI on the computer, the AUI having the respective AUI functionality associated with the identified CNR. | 1. A computer-implemented method comprising: providing an application programming interface running in a web browser on a computer to receive a call from an event handler to process a detected user navigation event on a web page, wherein content navigation rules (CNRs) characterize nodes of a document-object-model (DOM) of the web page as a sequence of one or more logical paths through the web page when rendered by the computer, and wherein the CNRs are associated with respective augmented user interface (AUI) functionalities that are tailored to different types of users; in response to receiving the call, requesting a user preference file from a remote server; receiving, from the remote server, the user preference file and an AUI component API identified in the user preference file; and in response to receiving the user preference file: processing the detected user navigation event by: identifying a CNR corresponding to the detected navigation event; and calling, in the web browser, an AUI component application via the received AUI component API to invoke an AUI on the computer, the AUI having the respective AUI functionality associated with the identified CNR. 7. The method of claim 1 , wherein the AUI component application includes one of a native screen reader, a native screen magnifier, a native speech recognizer, a browser plug-in version of a screen reader, a browser plug-in version of a screen magnifier, a browser plug-in version of a speech recognizer, a web based screen reader, a web based screen magnifier and a web based speech recognizer. | 0.5 |
9,082,409 | 1 | 4 | 1. A method for executing voice applications to perform a voice-based function, the method comprising: receiving a first request for a document; retrieving the document in response to the first request; parsing the document to create a parse tree, the parse tree including an XML node; creating script code from the parse tree; translating the script code to bytecode segments; replacing the XML node with script code, thereby consuming part of the parse tree to create a reduced parse tree; storing the reduced parse tree in a cache for subsequent retrieval in response to a second request for the document, the reduced parse tree configured for use to perform the voice-based function; storing the bytecode segments in a cache for subsequent execution to perform the voice-based function receiving the second request to retrieve the document: in response to the second request, determining whether bytecode corresponding to the document is stored in a cache; and responsive to determining that bytecode corresponding to the document is already stored in the cache: bypassing the retrieving, parsing, creating, replacing, translating and storing steps associated with the second request; and executing the cached bytecode. | 1. A method for executing voice applications to perform a voice-based function, the method comprising: receiving a first request for a document; retrieving the document in response to the first request; parsing the document to create a parse tree, the parse tree including an XML node; creating script code from the parse tree; translating the script code to bytecode segments; replacing the XML node with script code, thereby consuming part of the parse tree to create a reduced parse tree; storing the reduced parse tree in a cache for subsequent retrieval in response to a second request for the document, the reduced parse tree configured for use to perform the voice-based function; storing the bytecode segments in a cache for subsequent execution to perform the voice-based function receiving the second request to retrieve the document: in response to the second request, determining whether bytecode corresponding to the document is stored in a cache; and responsive to determining that bytecode corresponding to the document is already stored in the cache: bypassing the retrieving, parsing, creating, replacing, translating and storing steps associated with the second request; and executing the cached bytecode. 4. The method of claim 1 , further comprising: in response to the second request, determining whether a reduced parse tree corresponding to the document is already stored in a cache; and responsive to determining that a reduced parse tree corresponding to the document is already stored in a cache: translating the script code to bytecode segments; and executing the cached bytecode segments. | 0.5 |
8,799,262 | 7 | 8 | 7. The configurable web crawler of claim 1 , wherein the crawling rules further specify crawling behavior for one or more domain-specific crawl behavior to be applied during a crawl to one or more identified domains; the one or more processing units configured to, only if allowed by the specified general crawl behavior, the domain-specific crawl behavior, and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and to process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a domain-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified domain-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules. | 7. The configurable web crawler of claim 1 , wherein the crawling rules further specify crawling behavior for one or more domain-specific crawl behavior to be applied during a crawl to one or more identified domains; the one or more processing units configured to, only if allowed by the specified general crawl behavior, the domain-specific crawl behavior, and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and to process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a domain-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified domain-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules. 8. The configurable web crawler of claim 7 , wherein the user-specified web crawl configuration further comprises user-specified throttling rules, the throttling rules comprising at least a plurality of a user-specified page pause time, a user-specified number of page crawler threads, and a user-specified maximum number of threads allocated per crawled domain; and wherein the default crawl behavior further comprises pausing at least the user-specified page pause time before fetching the next page resource, spawning up to the user-specified number of page crawler threads to perform the crawl, and for any given crawled domain, spawning up to the user-specified maximum number of threads allocated per crawled domain. | 0.5 |
9,317,594 | 10 | 14 | 10. The method of claim 1 , wherein the data file is further classified within a lower node of the hierarchical structure based on a social organization characteristic of the classified data file, an individual descriptive characteristic of the classified data file, or an operational characteristic of the classified data file, wherein the social organization characteristic indicates a social position associated with a creator of the classified data file, wherein the individual descriptive characteristic indicates a personal characteristic of the creator of the classified data file, and wherein the operational characteristic indicates characteristics of message exchange associated with the classified data file. | 10. The method of claim 1 , wherein the data file is further classified within a lower node of the hierarchical structure based on a social organization characteristic of the classified data file, an individual descriptive characteristic of the classified data file, or an operational characteristic of the classified data file, wherein the social organization characteristic indicates a social position associated with a creator of the classified data file, wherein the individual descriptive characteristic indicates a personal characteristic of the creator of the classified data file, and wherein the operational characteristic indicates characteristics of message exchange associated with the classified data file. 14. The method of claim 10 , wherein the social organization characteristic includes a geographical location associated with the classified data file; a time associated with the classified data file; a social role associated with the classified data file; an indication of whether the creator of the classified data file has a leader status, a follower status, or a marginal status; a social influence associated with the classified data file; a community size associated with the classified data file; a community density associated with the classified data file; a dispersion of a community associated with the classified data file; or a community character associated with the classified data file. | 0.5 |
8,137,105 | 1 | 8 | 1. A computer implemented method for reviewing vocabulary comprising: using a computer and a graphical user interface on a display connected to the computer, and responsive to a user selecting a chapter from a plurality of chapters in a Chinese-English textbook, a question language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, and an answer language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, displaying a plurality of vocabulary words from the chapter, displaying a question containing a vocabulary word in the question language; responsive to the user inputting an answer in the answer language, determining if the answer is a correct answer; responsive to the vocabulary word or the answer being in Simplified Chinese, translating the vocabulary word or the answer into Traditional Chinese by accessing a Simplified Chinese/Traditional Chinese conversion table; wherein a determination if the answer is a correct answer is performed by determining whether the vocabulary word and the answer both match an entry in a Traditional Chinese/Pin Yin/English dictionary encoded in Unicode. | 1. A computer implemented method for reviewing vocabulary comprising: using a computer and a graphical user interface on a display connected to the computer, and responsive to a user selecting a chapter from a plurality of chapters in a Chinese-English textbook, a question language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, and an answer language from English, Simplified Chinese, Traditional Chinese, or Pin Yin, displaying a plurality of vocabulary words from the chapter, displaying a question containing a vocabulary word in the question language; responsive to the user inputting an answer in the answer language, determining if the answer is a correct answer; responsive to the vocabulary word or the answer being in Simplified Chinese, translating the vocabulary word or the answer into Traditional Chinese by accessing a Simplified Chinese/Traditional Chinese conversion table; wherein a determination if the answer is a correct answer is performed by determining whether the vocabulary word and the answer both match an entry in a Traditional Chinese/Pin Yin/English dictionary encoded in Unicode. 8. The method of claim 1 further comprising: changing the font size of the Chinese characters displayed on a graphical user interface. | 0.719665 |
9,501,456 | 1 | 9 | 1. A method comprising: in a computing system having at least a processor, a memory and a display unit, detecting a location causing an error in a markup language document; displaying the location and the error in the markup language document on the display unit; analyzing the error in the markup language document and underlying causes of the error in the markup language document; computing a set of possible actions to remedy the error in the markup language document; displaying information about the error in the markup language document and its underlying causes on the display unit; displaying the set of possible actions to remedy the error in the markup language document on the display unit; receiving a user input selecting one of the possible actions to remedy the error in the markup language document; and replacing the location causing the error in the markup language document with the selected one of the possible actions to remedy the error in the markup language document, wherein the information about the error in the markup language document and its underlying causes comprises: a link to the error in the working XML file; a link to the corresponding definition(s) in an associated schema file; and links to relevant information in an applicable W3C specification. | 1. A method comprising: in a computing system having at least a processor, a memory and a display unit, detecting a location causing an error in a markup language document; displaying the location and the error in the markup language document on the display unit; analyzing the error in the markup language document and underlying causes of the error in the markup language document; computing a set of possible actions to remedy the error in the markup language document; displaying information about the error in the markup language document and its underlying causes on the display unit; displaying the set of possible actions to remedy the error in the markup language document on the display unit; receiving a user input selecting one of the possible actions to remedy the error in the markup language document; and replacing the location causing the error in the markup language document with the selected one of the possible actions to remedy the error in the markup language document, wherein the information about the error in the markup language document and its underlying causes comprises: a link to the error in the working XML file; a link to the corresponding definition(s) in an associated schema file; and links to relevant information in an applicable W3C specification. 9. The method of claim 1 wherein computing the set of possible actions to remedy the error comprises: type-specific corrections of an offending value; brute-force attempts to remove invalid characters from a string; and computing and offering enumeration values defined for a simple type. | 0.727273 |
8,499,283 | 19 | 20 | 19. The non-transitory, tangible computer readable storage medium of claim 14 , wherein the normalized scripting-language-data comprises consolidated portions of scripting-language-data that are normalized into tokens; and wherein the inspection data is collected during the emulated execution of data suspected of being scripting-language-based. | 19. The non-transitory, tangible computer readable storage medium of claim 14 , wherein the normalized scripting-language-data comprises consolidated portions of scripting-language-data that are normalized into tokens; and wherein the inspection data is collected during the emulated execution of data suspected of being scripting-language-based. 20. The non-transitory, tangible computer readable storage medium of claim 19 , wherein the normalized scripting-language-data indicates functions that the scripting-language-data would execute when executed in a web browser. | 0.5 |
8,498,983 | 1 | 14 | 1. A computer-assisted method for assisting a user to search for documents or other file objects, comprising: receiving a query comprising a queried term from a user, wherein the queried term comprises a sequence of characters entered by the user; in response to each character being entered in the query, obtaining, by the computer system, a first search result comprising a plurality of documents and a first context term list comprising a first context term, wherein the first context term is selected from one or more of the plurality of documents, and displaying an interface object for the first context term to allow the user to indicate the degree of importance of the first context term to the query; displaying, by the computer system, the first search result and the first context term list in response to each character being entered in the query; allowing the user to select a first context term in the first context term list; obtaining and displaying, by the computer system, a second search result comprising a plurality of documents in a user interface in response to the selection of the first context term in the first context term list. | 1. A computer-assisted method for assisting a user to search for documents or other file objects, comprising: receiving a query comprising a queried term from a user, wherein the queried term comprises a sequence of characters entered by the user; in response to each character being entered in the query, obtaining, by the computer system, a first search result comprising a plurality of documents and a first context term list comprising a first context term, wherein the first context term is selected from one or more of the plurality of documents, and displaying an interface object for the first context term to allow the user to indicate the degree of importance of the first context term to the query; displaying, by the computer system, the first search result and the first context term list in response to each character being entered in the query; allowing the user to select a first context term in the first context term list; obtaining and displaying, by the computer system, a second search result comprising a plurality of documents in a user interface in response to the selection of the first context term in the first context term list. 14. The computer-assisted method of claim 1 , further comprising: obtaining document properties or property values related to the documents in the first search result by the computer system; displaying, in the user interface, the document properties or property values related to the documents in the first search result in response to each character being entered in the query; and allowing the user to select at least one of the document properties or property values, wherein the second search result is obtained based on the query, the first context term, and the at least one of the document properties or property values selected by the user. | 0.5 |
8,301,581 | 4 | 6 | 4. The method as defined in claim 1 , wherein the presence of the node is determined based on a membership for the node and a threshold. | 4. The method as defined in claim 1 , wherein the presence of the node is determined based on a membership for the node and a threshold. 6. The method as defined in claim 4 , wherein the membership in the node is based on at least one attribute of an individual person as stored in an enterprise directory. | 0.59375 |
9,928,232 | 8 | 14 | 8. A computing device for generating a word candidate to assist a user providing an input to the computing device, comprising: a processor; and a memory having a set of computer-executable instructions stored thereupon which, when executed by the processor, cause the computing device to receive, at the computing device, the input containing a plurality of words; determine a conditional count; determine an unconditional count; determine an adjustment factor for a pair of words of the plurality of words based on the unconditional count and the conditional count; generate a data structure defining a plurality of word clusters, individual word clusters of the plurality of word clusters include at least one word of the plurality of words; reconstruct the adjustment factor of the pair of words based on a number of common clusters between individual words of the pair of words; determine a candidate probability associated with the word candidate based, at least in part, on the reconstructed adjustment factor, wherein the word candidate is selected from individual words associated with the plurality of word clusters; generate an output containing the word candidate based, at least in part, on the candidate probability; and display the word candidate on a display screen of the computing device. | 8. A computing device for generating a word candidate to assist a user providing an input to the computing device, comprising: a processor; and a memory having a set of computer-executable instructions stored thereupon which, when executed by the processor, cause the computing device to receive, at the computing device, the input containing a plurality of words; determine a conditional count; determine an unconditional count; determine an adjustment factor for a pair of words of the plurality of words based on the unconditional count and the conditional count; generate a data structure defining a plurality of word clusters, individual word clusters of the plurality of word clusters include at least one word of the plurality of words; reconstruct the adjustment factor of the pair of words based on a number of common clusters between individual words of the pair of words; determine a candidate probability associated with the word candidate based, at least in part, on the reconstructed adjustment factor, wherein the word candidate is selected from individual words associated with the plurality of word clusters; generate an output containing the word candidate based, at least in part, on the candidate probability; and display the word candidate on a display screen of the computing device. 14. The computing device of claim 8 , wherein reconstructing the adjustment factor of the pair of words comprises: determining a cluster density for individual clusters of the plurality of clusters; determining an ordering of the plurality of clusters based on the cluster density for the individual clusters; and reconstructing the adjustment factor based on the ordering of the plurality of clusters and the number of common clusters between individual words of the pair of words. | 0.682895 |
7,571,169 | 12 | 20 | 12. A computer-readable storage medium having computer-executable instructions for interacting with a document, comprising: interpreting a published XSD (Extensible Markup Language (XML) Schema Definition), wherein the XSD defines rules relating to the XML file format for documents associated with an application having a rich set of features; and creating an element in an XML file, wherein the element is selected from a set of elements, including: a style element; a hints element that is interpreted according to a hints schema that includes information to assist an external application in displaying text of the of the document; a bookmark element; wherein the bookmark element includes an identifier attribute that associates a start bookmark element with an end bookmark element; wherein two bookmark elements are used in book marking the portion of the document; wherein each of the two bookmark elements include a opening tag and an ending tag; a document properties element; a text element that contains text of the document; wherein all of the text of the document is stored within text elements such that only the text of the document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; a text run element that includes the formatting information for the text within text elements; a font element; a formatting element; a section element; a paragraphs element; a table element; an outline element; and a proofing element and storing the element in the XML file. | 12. A computer-readable storage medium having computer-executable instructions for interacting with a document, comprising: interpreting a published XSD (Extensible Markup Language (XML) Schema Definition), wherein the XSD defines rules relating to the XML file format for documents associated with an application having a rich set of features; and creating an element in an XML file, wherein the element is selected from a set of elements, including: a style element; a hints element that is interpreted according to a hints schema that includes information to assist an external application in displaying text of the of the document; a bookmark element; wherein the bookmark element includes an identifier attribute that associates a start bookmark element with an end bookmark element; wherein two bookmark elements are used in book marking the portion of the document; wherein each of the two bookmark elements include a opening tag and an ending tag; a document properties element; a text element that contains text of the document; wherein all of the text of the document is stored within text elements such that only the text of the document is contained between start text tags and end text tags; wherein there are no intervening tags between each of the start text tags and each of the corresponding end text tags and wherein each of the start text tags do not include formatting information for the text between each of the start text tags and the end text tags; a text run element that includes the formatting information for the text within text elements; a font element; a formatting element; a section element; a paragraphs element; a table element; an outline element; and a proofing element and storing the element in the XML file. 20. The computer-readable medium of claim 12 , wherein the section information includes: page layout for a section, footer information, and header information. | 0.815116 |
9,679,251 | 6 | 8 | 6. The method according to claim 5 , wherein the at least one hardware processor further performs: obtaining a set complement of the largest composite sets of evidences G that supports negation of the target rule L; and computing a composite object ω 2 p indicative according to a deductive reasoning of a second plausibility value for the target rule L. | 6. The method according to claim 5 , wherein the at least one hardware processor further performs: obtaining a set complement of the largest composite sets of evidences G that supports negation of the target rule L; and computing a composite object ω 2 p indicative according to a deductive reasoning of a second plausibility value for the target rule L. 8. The method according to claim 6 , wherein the at least one hardware processor further performs adding a new object in form U→L, where the new object is the target rule L supported by the U, to the knowledge base, to expand the knowledge base to an expanded knowledge base; and the largest composite sets of evidences G is created from the expanded knowledge base that supports a logical truth T created on basis of the target rule L, subject to the relationship constraints κ which support the composite rule L 0 , to compute a third plausibility value for the target rule L. | 0.5 |
8,397,165 | 16 | 22 | 16. A non-transitory computer-readable storage medium encoded with instructions that cause one or more processors of a computing device to: provide a first annotation group and a second annotation group during execution of a module, wherein the first annotation group includes annotations at least some of which have one or more corresponding textual annotation details, and wherein the second annotation group includes annotations at least some of which have one or more corresponding textual annotation details; receive a first user input to select an annotation in the second annotation group; upon receiving the first user input, display the one or more corresponding textual annotation details of the annotations for the first annotation group; display, upon receiving the first user input, visual representations of the annotations for the second annotation group without displaying the one or more corresponding textual annotation details of the annotations of the second annotation group; receive a second user input to select a visual representation of the annotation in the second annotation group, wherein the visual representation of the annotation is displayed without one or more corresponding textual annotation details; and display, responsive to receiving the second user input, one or more textual annotation details corresponding to the selected annotation in the second annotation group. | 16. A non-transitory computer-readable storage medium encoded with instructions that cause one or more processors of a computing device to: provide a first annotation group and a second annotation group during execution of a module, wherein the first annotation group includes annotations at least some of which have one or more corresponding textual annotation details, and wherein the second annotation group includes annotations at least some of which have one or more corresponding textual annotation details; receive a first user input to select an annotation in the second annotation group; upon receiving the first user input, display the one or more corresponding textual annotation details of the annotations for the first annotation group; display, upon receiving the first user input, visual representations of the annotations for the second annotation group without displaying the one or more corresponding textual annotation details of the annotations of the second annotation group; receive a second user input to select a visual representation of the annotation in the second annotation group, wherein the visual representation of the annotation is displayed without one or more corresponding textual annotation details; and display, responsive to receiving the second user input, one or more textual annotation details corresponding to the selected annotation in the second annotation group. 22. The non-transitory computer-readable storage medium of claim 16 further encoded with instructions that cause one or more processors of the computing device to: receive a third user input to select an annotation of the second annotation group; and display the one or more corresponding textual event details of the annotations of the second annotation group, responsive to receiving the third user input. | 0.694903 |
9,208,219 | 9 | 10 | 9. A non-transitory storage medium having stored instructions which, when executed by a processor, cause the processor to perform actions with regard to a first dataset having a plurality of first dataset elements and which is operably accessible to the processor, each of the first dataset elements corresponding to a different document and each of the documents having one or more characteristics, the actions comprising: creating a n-tuple vector for each of a selected number of the first dataset element of the plurality of first dataset elements wherein each component of the n-tuple vector correlates to a characteristic of the relevant first dataset element; creating an m-tuple vector for each of two or more of the n-tuple vectors, wherein each of the m-tuple vectors includes as its components (a) the norm of its corresponding n-tuple vector, (b) the component sum of its corresponding n-tuple vector, and (c) a set of random projections of its corresponding n-tuple vector; selecting one of the dataset elements to be a target; selecting the m-tuple vector which corresponds to the target and at least one other of the m-tuple vectors as elements of a first candidate set; bisectionally performing a series of one-dimensional range searches starting with the first candidate set to create a second candidate set comprising one or more of the m-tuple vectors of the first candidate set; determining for each of the n-tuple vectors which corresponds to one of the m-tuple vectors of the second candidate set its distance from the target's n-tuple vector; and creating a second dataset comprising each of the first dataset elements which has a corresponding n-tuple vector which is within a selected distance from the target's n-tuple vector, wherein the actions further comprise selecting one of the one-dimensional searches to be based upon the component sum of the n-tuple vector which corresponds to the target, wherein the one-dimensional search that is based upon the component sum of the n-tuple vector which corresponds to the target includes setting a threshold related to a factor multiplied by the component sum of the n-tuple vector which corresponds to the target, and wherein the factor is determined based upon the selected distance from the target's n-tuple vector, the norm of the target's n-tuple vector, and the maximum element in the target's n-tuple vector. | 9. A non-transitory storage medium having stored instructions which, when executed by a processor, cause the processor to perform actions with regard to a first dataset having a plurality of first dataset elements and which is operably accessible to the processor, each of the first dataset elements corresponding to a different document and each of the documents having one or more characteristics, the actions comprising: creating a n-tuple vector for each of a selected number of the first dataset element of the plurality of first dataset elements wherein each component of the n-tuple vector correlates to a characteristic of the relevant first dataset element; creating an m-tuple vector for each of two or more of the n-tuple vectors, wherein each of the m-tuple vectors includes as its components (a) the norm of its corresponding n-tuple vector, (b) the component sum of its corresponding n-tuple vector, and (c) a set of random projections of its corresponding n-tuple vector; selecting one of the dataset elements to be a target; selecting the m-tuple vector which corresponds to the target and at least one other of the m-tuple vectors as elements of a first candidate set; bisectionally performing a series of one-dimensional range searches starting with the first candidate set to create a second candidate set comprising one or more of the m-tuple vectors of the first candidate set; determining for each of the n-tuple vectors which corresponds to one of the m-tuple vectors of the second candidate set its distance from the target's n-tuple vector; and creating a second dataset comprising each of the first dataset elements which has a corresponding n-tuple vector which is within a selected distance from the target's n-tuple vector, wherein the actions further comprise selecting one of the one-dimensional searches to be based upon the component sum of the n-tuple vector which corresponds to the target, wherein the one-dimensional search that is based upon the component sum of the n-tuple vector which corresponds to the target includes setting a threshold related to a factor multiplied by the component sum of the n-tuple vector which corresponds to the target, and wherein the factor is determined based upon the selected distance from the target's n-tuple vector, the norm of the target's n-tuple vector, and the maximum element in the target's n-tuple vector. 10. The non-transitory storage medium of claim 9 , wherein at least one of the random projections comprises at least one of a Gaussian random variable and a Rademacher random variable. | 0.619835 |
7,970,764 | 3 | 4 | 3. The system of claim 1 , wherein the at least one selected search term is adapted to be selected by an input device. | 3. The system of claim 1 , wherein the at least one selected search term is adapted to be selected by an input device. 4. The system of claim 3 , wherein the additional related search terms comprise a sub-subject matter associated with new search term. | 0.630556 |
8,332,251 | 1 | 3 | 1. A computer-implemented method, used in an Agile environment, for allocating resources across a plurality of stories in a project during a release and scheduling the stories across a plurality of iterations within the release, wherein 1) each story represents at least one task executable by an appropriate resource and 2) the release represents a deadline for delivering the stories and is divided into one or more iterations representative of a sequence of time periods within the release, the method comprising: receiving, at a computing device, (i) resource information representing a plurality of resources available for allocation to the stories, (ii) one or more story-level constraints corresponding to each story, and iii) one or more optimization criteria for a level different from a story level, including an objective function defined by the equation max ( ∑ k = 1 n F [ S k ] S [ S k ] ) wherein n represents the number of stories in one or more iterations, S k represents the kth story in the one or more iterations, function F represents a feature-points function, and function S represents a successful and on-time completion function; applying, using the computing device, a first-level optimization scheme to generate a plurality of story-level allocation scenarios, wherein applying the first-level optimization scheme comprises: assigning an iteration to each of the stories; allocating one or more of the plurality of resources to one or more of the stories; and satisfying the one or more story-level constraints associated with each story; and applying, using the computing device, a second-level optimization scheme to determine one or more optimized story-level allocation scenarios from the plurality of story-level allocation scenarios, by optimizing assignment of iterations and allocation of resources to the stories while satisfying the one or more optimization criteria. | 1. A computer-implemented method, used in an Agile environment, for allocating resources across a plurality of stories in a project during a release and scheduling the stories across a plurality of iterations within the release, wherein 1) each story represents at least one task executable by an appropriate resource and 2) the release represents a deadline for delivering the stories and is divided into one or more iterations representative of a sequence of time periods within the release, the method comprising: receiving, at a computing device, (i) resource information representing a plurality of resources available for allocation to the stories, (ii) one or more story-level constraints corresponding to each story, and iii) one or more optimization criteria for a level different from a story level, including an objective function defined by the equation max ( ∑ k = 1 n F [ S k ] S [ S k ] ) wherein n represents the number of stories in one or more iterations, S k represents the kth story in the one or more iterations, function F represents a feature-points function, and function S represents a successful and on-time completion function; applying, using the computing device, a first-level optimization scheme to generate a plurality of story-level allocation scenarios, wherein applying the first-level optimization scheme comprises: assigning an iteration to each of the stories; allocating one or more of the plurality of resources to one or more of the stories; and satisfying the one or more story-level constraints associated with each story; and applying, using the computing device, a second-level optimization scheme to determine one or more optimized story-level allocation scenarios from the plurality of story-level allocation scenarios, by optimizing assignment of iterations and allocation of resources to the stories while satisfying the one or more optimization criteria. 3. The computer-implemented method of claim 1 wherein the level different from the story level includes an iteration level, a release level, or a feature level. | 0.847909 |
9,183,535 | 16 | 18 | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. | 16. A non-transitory computer-readable storage medium storing executable computer program instructions for updating a user's social network model, the computer program instructions comprising instructions for: receiving a set of documents associated with a user; accessing the user's contact data, the contact data identifying a plurality of entities; analyzing the documents, using the contact data, to identify references to entities therein; identifying relationships among the referenced entities; determining a strength of a first relationship between a first entity and a second entity responsive to a volume of documents in which both the first entity and the second entity appear, wherein the first and second entities are a subset of the referenced entities; building a social network model for the user responsive to the identified relationships among the referenced entities and the strength of the first relationship; storing the social network model; receiving a new document associated with the user; identifying, in the new document, a reference to an ambiguous entity; performing the name disambiguation using the social network model to determine which of the at least two candidate entities from the social network model is an intended entity for the ambiguous entity; identifying other entities referenced by the new document; and updating the social network model by modifying relationship strengths in the social network model between the intended entity and the other entities referenced by the new document. 18. The non-transitory computer-readable storage medium of claim 16 , wherein the referenced entities comprise people. | 0.892336 |
8,549,072 | 1 | 9 | 1. A computer implemented method for providing information associated with a user of a social networking system, the method comprising: receiving a markup language document from an external website, wherein the markup language document includes markup language containing instructions for retrieving information associated with a user of a social networking system; processing the markup language contained in the received markup language document; responsive to processing the markup language document, sending a request to a social networking system for information associated with the user; receiving the requested information associated with the user from the social networking system in response to the request for the information; rendering a displayable web page based on the markup language, wherein the displayable web page includes information received from the social networking system server; and displaying the rendered web page on a display. | 1. A computer implemented method for providing information associated with a user of a social networking system, the method comprising: receiving a markup language document from an external website, wherein the markup language document includes markup language containing instructions for retrieving information associated with a user of a social networking system; processing the markup language contained in the received markup language document; responsive to processing the markup language document, sending a request to a social networking system for information associated with the user; receiving the requested information associated with the user from the social networking system in response to the request for the information; rendering a displayable web page based on the markup language, wherein the displayable web page includes information received from the social networking system server; and displaying the rendered web page on a display. 9. The computer implemented method of claim 1 , wherein the information rendered on the webpage comprises information received from the social networking system that is associated with one or more connections of the user, wherein the information rendered on the webpage is determined based on privacy settings. | 0.606599 |
8,786,607 | 9 | 16 | 9. A method of generating personal fonts, comprising: receiving an input of a character trace, which has at least one feature point, from a user; recognizing a representative character corresponding to an input character from the input character trace; generating a representative trace expressing a trace of the representative character; modifying a position of the at least one feature point on the trace of the input character by combining a weight value of the generated representative trace with the trace of the input character to generate the personal fonts; and analyzing the correspondence if the correspondence between constituent elements of the input character trace and the representative character is not provided by comparing the trace of the input character and the generated representative trace, wherein the method is performed using at least one processor. | 9. A method of generating personal fonts, comprising: receiving an input of a character trace, which has at least one feature point, from a user; recognizing a representative character corresponding to an input character from the input character trace; generating a representative trace expressing a trace of the representative character; modifying a position of the at least one feature point on the trace of the input character by combining a weight value of the generated representative trace with the trace of the input character to generate the personal fonts; and analyzing the correspondence if the correspondence between constituent elements of the input character trace and the representative character is not provided by comparing the trace of the input character and the generated representative trace, wherein the method is performed using at least one processor. 16. The method of claim 9 , further comprising displaying a modified trace of the input character on a display screen. | 0.804636 |
9,798,776 | 5 | 6 | 5. The computer-implemented method of claim 1 , further comprising: retrieving, from a storage device, at least one search query template including a sequence of the search categories. | 5. The computer-implemented method of claim 1 , further comprising: retrieving, from a storage device, at least one search query template including a sequence of the search categories. 6. The computer-implemented method of claim 5 , further comprising: retrieving a first and second search query template including the sequence of the search categories, the second search query template being retrieved after determining that a character sub string of the sequence of character substrings does not correspond to a particular search category of the sequence of the search categories in the first search query template. | 0.5 |
8,554,696 | 15 | 20 | 15. A non-transitory, tangible computer-readable medium having computer-executable code, when executed by a computer operable to: access an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. | 15. A non-transitory, tangible computer-readable medium having computer-executable code, when executed by a computer operable to: access an inverted index comprising a plurality of inverted index lists, each inverted index list corresponding to a term, each inverted index list comprising a term identifier of the term and one or more document identifiers indicating one or more documents of a document set in which the term appears; generating a plurality of ordered pairs from the inverted index, each ordered pair comprising a term identifier and a document identifier of an inverted index list, the ordered pairs being organized primarily based on the document identifiers of the ordered pairs; and generate a term identifier index according to the inverted index, the term identifier index comprising a plurality of sections, each section corresponding to a document, each section comprising one or more term identifiers of one or more terms that appear in the document, the generating the term identifier index according to the inverted index comprising organizing the term identifiers of the ordered pairs in the sections of the term identifier index, wherein organizing the term identifiers of the ordered pairs comprises: removing a selected ordered pair from a data structure; generating a next ordered pair from the inverted index, the next ordered pair comprising a term identifier equivalent to a term identifier of the selected ordered pair; and placing the next ordered pair into the data structure. 20. The medium of claim 15 , further operable to: generate an ontology affinity matrix comprising a plurality of entries, each entry corresponding to an affinity of a term pair comprising a first term and a second term, each entry comprising a count value indicating a number of times the term pair appears together in a document of the document set; and divide each count value of the ontology affinity matrix by one of a group consisting of a number of documents the first term appears in, a number of documents the second term appears in, and the number of documents the first term appears in plus the number of documents the second term appears in. | 0.5 |
7,673,227 | 1 | 5 | 1. An architecture comprising: a processor; a memory coupled to the processor; and one or more modules stored in the memory and executable via the processor, the one or more modules including: a user interface to present an xml document having text-based body elements and at least one table configured with spreadsheet functions, wherein the user interface is configured to overlay an entry field on a particular cell in the table to facilitate user entry of a formula into the particular cell; a table appearance manager to: manage how the table appears in the user interface such that the table resembles a table when not being edited and adds spreadsheet elements to the table when being edited; and apply one or more common document behaviors selectable via the user interface to both the text-based body elements and across boundaries of the table to text within the table; and a spreadsheet functionality manager to manage the spreadsheet functions for the table that is presented within the xml document of a particular application. | 1. An architecture comprising: a processor; a memory coupled to the processor; and one or more modules stored in the memory and executable via the processor, the one or more modules including: a user interface to present an xml document having text-based body elements and at least one table configured with spreadsheet functions, wherein the user interface is configured to overlay an entry field on a particular cell in the table to facilitate user entry of a formula into the particular cell; a table appearance manager to: manage how the table appears in the user interface such that the table resembles a table when not being edited and adds spreadsheet elements to the table when being edited; and apply one or more common document behaviors selectable via the user interface to both the text-based body elements and across boundaries of the table to text within the table; and a spreadsheet functionality manager to manage the spreadsheet functions for the table that is presented within the xml document of a particular application. 5. The architecture of claim 1 , wherein the user interface presents multiple tables, and the spreadsheet functionality manager is configured to track references made from one table to another table. | 0.767523 |
9,792,897 | 1 | 6 | 1. A device configured to identify phonemes within audible signal data, the device comprising: one or more audio sensors configured to receive the audible signal data; a spectral feature characterization module configured to generate a first feature stream and a plurality of targeted feature streams from the received audible signal data, wherein the first feature stream is generated primarily in order to provide audio information indicative of non-problematic phonemes, wherein each of the plurality of targeted feature streams is generated in order to provide audio information indicative of a corresponding problematic phoneme; an ensemble phoneme recognition neural network configured to assess which of a plurality of phonemes is present within the received audible signal data based on inputs including the first feature stream and a plurality of detection indicator values, wherein each of the plurality of detection indicator values characterizes a respective probability that a corresponding problematic phoneme is present within the received audible signal data; a phoneme-specific experts system having a plurality of problematic phoneme-specific expert neural networks (PPENNs) each configured to generate a respective one of the plurality of detection indicator values from a corresponding one of the plurality of targeted feature streams, wherein each of the plurality of targeted feature streams is associated with a respective problematic phoneme; and synthesizing, by the ensemble phoneme recognition neural network, one or more phoneme candidates as recognized within the received audible signal data based on the first feature stream and the plurality of detection indicator values. | 1. A device configured to identify phonemes within audible signal data, the device comprising: one or more audio sensors configured to receive the audible signal data; a spectral feature characterization module configured to generate a first feature stream and a plurality of targeted feature streams from the received audible signal data, wherein the first feature stream is generated primarily in order to provide audio information indicative of non-problematic phonemes, wherein each of the plurality of targeted feature streams is generated in order to provide audio information indicative of a corresponding problematic phoneme; an ensemble phoneme recognition neural network configured to assess which of a plurality of phonemes is present within the received audible signal data based on inputs including the first feature stream and a plurality of detection indicator values, wherein each of the plurality of detection indicator values characterizes a respective probability that a corresponding problematic phoneme is present within the received audible signal data; a phoneme-specific experts system having a plurality of problematic phoneme-specific expert neural networks (PPENNs) each configured to generate a respective one of the plurality of detection indicator values from a corresponding one of the plurality of targeted feature streams, wherein each of the plurality of targeted feature streams is associated with a respective problematic phoneme; and synthesizing, by the ensemble phoneme recognition neural network, one or more phoneme candidates as recognized within the received audible signal data based on the first feature stream and the plurality of detection indicator values. 6. The device of claim 1 , wherein each of the one or more phoneme candidates satisfies a recognition threshold value. | 0.867416 |
8,924,335 | 38 | 39 | 38. The method of claim 35 , wherein the modified display characteristic is based on another field in the user interface. | 38. The method of claim 35 , wherein the modified display characteristic is based on another field in the user interface. 39. The method of claim 38 , wherein the modified display characteristic is based on a requirement defined in accord with one or more other rules and/or a user interface generated based thereon; one or more transactional data relating to the user interface; and a context in which the user interface is any of transmitted, displayed and/or viewed by a user. | 0.639394 |
4,630,235 | 3 | 4 | 3. The translator of claim 1 wherein said access means recalls said selected translation arrangement and said means for indicating indicates said selected translation arrangement to the user of said translator subsequent to the recalling of said selected source arrangement by said access means and the indicating of said selected source arrangement by said means for indicating. | 3. The translator of claim 1 wherein said access means recalls said selected translation arrangement and said means for indicating indicates said selected translation arrangement to the user of said translator subsequent to the recalling of said selected source arrangement by said access means and the indicating of said selected source arrangement by said means for indicating. 4. The translator of claim 3 wherein said means for indicating comprises a visual display. | 0.5 |
8,296,179 | 17 | 18 | 17. The method of claim 15 , wherein the price of each advertisement is computed by multiplying a maximum price that the advertiser is willing to pay for the advertisement by the value of the advertisement for the given user, where the value of the advertisement for the user is stored in a value matrix, thereby forming a vector of prices for each of the advertisements for the given user, the vector being sorted in descending order with higher ranking advertisements being presented first. | 17. The method of claim 15 , wherein the price of each advertisement is computed by multiplying a maximum price that the advertiser is willing to pay for the advertisement by the value of the advertisement for the given user, where the value of the advertisement for the user is stored in a value matrix, thereby forming a vector of prices for each of the advertisements for the given user, the vector being sorted in descending order with higher ranking advertisements being presented first. 18. The method of claim 17 , wherein the price is variable and is determined as a price value vector by taking the price that the advertiser is willing to pay to present the advertisement to a given user multiplied by the value for that user. | 0.5 |
8,732,447 | 6 | 7 | 6. The method of claim 1 , wherein the contextual meta data that defines a state of the objects that are open on the computing device identifies one or more persons using the computing device while the operating system object is instantiated. | 6. The method of claim 1 , wherein the contextual meta data that defines a state of the objects that are open on the computing device identifies one or more persons using the computing device while the operating system object is instantiated. 7. The method of claim 6 , further comprising receiving a subsequent request to instantiate the operating system object when the operating system object is closed, and calling secondary objects that are identified in the contextual meta data. | 0.576923 |
8,412,599 | 3 | 4 | 3. The method of claim 1 , further comprising receiving, at the one or more computer systems, a hold indication for all or a portion of the information representing the timesheet from a current approver in a sequence of approvers. | 3. The method of claim 1 , further comprising receiving, at the one or more computer systems, a hold indication for all or a portion of the information representing the timesheet from a current approver in a sequence of approvers. 4. The method of claim 3 , further comprising generating, with the one or more processors associated with the one or more computer systems, one or more notifications indicative of a reason for the hold to an approver or reviewer based on a designated approver or reviewer established in a routing setup. | 0.5 |
9,875,304 | 1 | 9 | 1. A method for identifying mood in content, comprising: generating a static visual representation of the content based on frequency data sampled from the content; filtering the static visual representation to capture intensity differences represented in the static visual representation and generating a filtered representation of the content; encoding the filtered representation to create a digitized representation of the content; identifying characteristics within the digitized representation that correspond to a first set of one or more moods among a set of moods; and generating a three-dimensional shape that corresponds to the first set of one or more moods. | 1. A method for identifying mood in content, comprising: generating a static visual representation of the content based on frequency data sampled from the content; filtering the static visual representation to capture intensity differences represented in the static visual representation and generating a filtered representation of the content; encoding the filtered representation to create a digitized representation of the content; identifying characteristics within the digitized representation that correspond to a first set of one or more moods among a set of moods; and generating a three-dimensional shape that corresponds to the first set of one or more moods. 9. The method for identifying mood in content as recited in claim 1 , further comprising identifying a third set of one or more moods among the set of moods based on the digitized representation. | 0.810311 |
9,854,330 | 26 | 28 | 26. A system, comprising: a television to generate a fingerprint data, the fingerprint data being any one of an audio fingerprint data and a video fingerprint data; a relevancy-matching server to: match primary data generated using the fingerprint data with targeted data based on a relevancy factor comprising at least one of a category of the primary data, a behavioral history of a user, a category of a sandboxed application, and other information associated with the user in accordance with searching a storage for at least one of a matching item and a related item based on the relevancy factor, wherein the primary data is any one of a content identification data and a content identification history, and search the storage for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data; and a mobile device associated with the television to: process an embedded object within the sandboxed application executing thereon, constrain an executable environment in a security sandbox, and execute the embedded object through the sandboxed application in the executable environment, the execution of the embedded object causing rendering of the targeted data therethrough, wherein the television executes a sandbox-reachable service thereon, and is configured to automatically announce the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device, wherein the discovery module identifies the sandbox-reachable service offered through the television based on receiving the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television, wherein the sandboxed application reaching the sandbox-reachable service establishes bidirectional communication between the mobile device and the television, and, thereby, association between the mobile device and the television, wherein the primary data is available across the sandbox-reachable service and the sandboxed application based on the established bidirectional communication between the mobile device and the television, and wherein the identification data of the television comprises at least one of a GUID, an alphanumeric name, a hardware address associated with the television, a public address associated with an automatic content identification service of the television, and a private address associated with the automatic content identification service of the television when the shared computer network is determined to be commonly associated with the mobile device and the television. | 26. A system, comprising: a television to generate a fingerprint data, the fingerprint data being any one of an audio fingerprint data and a video fingerprint data; a relevancy-matching server to: match primary data generated using the fingerprint data with targeted data based on a relevancy factor comprising at least one of a category of the primary data, a behavioral history of a user, a category of a sandboxed application, and other information associated with the user in accordance with searching a storage for at least one of a matching item and a related item based on the relevancy factor, wherein the primary data is any one of a content identification data and a content identification history, and search the storage for at least one of the targeted data, a reference to the targeted data and a metadata of the targeted data; and a mobile device associated with the television to: process an embedded object within the sandboxed application executing thereon, constrain an executable environment in a security sandbox, and execute the embedded object through the sandboxed application in the executable environment, the execution of the embedded object causing rendering of the targeted data therethrough, wherein the television executes a sandbox-reachable service thereon, and is configured to automatically announce the sandbox-reachable service to a discovery module executing at least one of: on a pairing server external to the mobile device and as part of an extension of the security sandbox executing on the mobile device, wherein the discovery module identifies the sandbox-reachable service offered through the television based on receiving the automatic announcement to enable the sandboxed application of the mobile device reach the sandbox-reachable service by communicating an identification data of the television via the sandbox-reachable service when a shared computer network is determined to be commonly associated with the mobile device and the television, wherein the sandboxed application reaching the sandbox-reachable service establishes bidirectional communication between the mobile device and the television, and, thereby, association between the mobile device and the television, wherein the primary data is available across the sandbox-reachable service and the sandboxed application based on the established bidirectional communication between the mobile device and the television, and wherein the identification data of the television comprises at least one of a GUID, an alphanumeric name, a hardware address associated with the television, a public address associated with an automatic content identification service of the television, and a private address associated with the automatic content identification service of the television when the shared computer network is determined to be commonly associated with the mobile device and the television. 28. The system of claim 26 , further comprising: a content identification server to: process the fingerprint data from the television, and communicate the primary data from the fingerprint data to any of a number of devices with access to at least one of: the identification data of the television and an identification data of the automatic content identification service of the television. | 0.5 |
8,306,962 | 15 | 16 | 15. The system of claim 13 , wherein the one or more processors are further operable when executing the instructions to: access a plurality of advertisement templates for constructing advertisements to be presented to users, each advertisement template being associated with at least one of the one or more advertising groups; for each advertising group, construct one or more advertisements from the advertisement templates associated with the advertising group based on the labels annotating the keywords in the advertising group. | 15. The system of claim 13 , wherein the one or more processors are further operable when executing the instructions to: access a plurality of advertisement templates for constructing advertisements to be presented to users, each advertisement template being associated with at least one of the one or more advertising groups; for each advertising group, construct one or more advertisements from the advertisement templates associated with the advertising group based on the labels annotating the keywords in the advertising group. 16. The system of claim 15 , wherein: each advertisement template of the plurality of advertisement templates comprises one or more dynamic elements, and for each advertising group of the plurality of advertising groups, construct one or more advertisements comprises: select one or more of the advertisement templates applicable to the advertising group; and for each of the selected advertisement templates, substitute the dynamic elements in the selected advertisement template with one or more of the labels annotating the keywords in the advertising group to obtain one of the advertisements for the advertising group; and associate a Uniform Resource Location (URL) of a landing page with the advertisement, the URL comprising the labels annotating the keywords in the advertising group. | 0.5 |
7,865,825 | 1 | 6 | 1. A method for configuring and publishing text to multiple applications, comprising: providing a block of text to be published; selecting at least one application that will use the block of text; defining at least one business entity to which the block of text pertains, wherein each business entity comprises an item of data associated with a business, wherein each business entity can be shared by a plurality of different applications, and wherein each business entity can be used by a single application, but shared across multiple instances of the single application; defining criteria under which the block of text will be used by each selected application based upon an entry in a standard text publisher table, the entry including an identifier for the selected application and a role corresponding to the selected application, the role being authorized to publish to the selected application; repeating the above steps for each additional block of text to be published; and publishing at least one of the blocks of text to at least one selected application; wherein providing each block of text to be published comprises: authoring the block of text; storing the block of text in a standard text table; providing at least one translation of the block of text, if required; and storing each translation of the block of text in a standard text translation table, wherein each translation of the block of text stored in the standard text translation table is linked to the block of text stored in the standard text table. | 1. A method for configuring and publishing text to multiple applications, comprising: providing a block of text to be published; selecting at least one application that will use the block of text; defining at least one business entity to which the block of text pertains, wherein each business entity comprises an item of data associated with a business, wherein each business entity can be shared by a plurality of different applications, and wherein each business entity can be used by a single application, but shared across multiple instances of the single application; defining criteria under which the block of text will be used by each selected application based upon an entry in a standard text publisher table, the entry including an identifier for the selected application and a role corresponding to the selected application, the role being authorized to publish to the selected application; repeating the above steps for each additional block of text to be published; and publishing at least one of the blocks of text to at least one selected application; wherein providing each block of text to be published comprises: authoring the block of text; storing the block of text in a standard text table; providing at least one translation of the block of text, if required; and storing each translation of the block of text in a standard text translation table, wherein each translation of the block of text stored in the standard text translation table is linked to the block of text stored in the standard text table. 6. The method of claim 1 , wherein each business entity can comprise a combination of other business entities. | 0.77551 |
8,423,354 | 1 | 5 | 1. A speech recognition dictionary creating support device comprising: a speech data storage section storing speech data; a prosodic information extracting section extracting prosodic information including at least a speech power value from the speech data; a speech data dividing section extracting an utterance section having a period with a power value equal to or larger than a predetermined threshold value lasting a preset time or longer from the speech data based on the prosodic information, and dividing the utterance section into sections, each of which has a power value equal to or lamer than a predetermined threshold value continuing for a given time or longer, to generate divided speech data; a phoneme sequence acquiring section executing a phoneme recognition process on the divided speech data to acquire phoneme sequence data for each divided speech data; a clustering section executing a clustering process on the phoneme sequence data to generate clusters each of which is a set of classified phoneme sequence data; an evaluation value calculating section calculating an evaluation value for each of the clusters based on the prosodic information for the divided speech data corresponding to the phoneme sequence data constituting the cluster; a candidate cluster selecting section selecting clusters for which the evaluation value is equal to or larger than a given value, as candidate clusters; and a listening target data selecting section determining one of the phoneme sequence data from the phoneme sequence data constituting the cluster for each of the candidate clusters to be a representative phoneme sequence and selecting the divided speech data corresponding to the representative phoneme sequence, as listening target speech data, and wherein the evaluation value calculating section includes dictionary data for a morpheme analysis process, and extracts a phrase classified as a predetermined word class from the dictionary data, calculates an appearance probability, in the extracted phrase, of a common phoneme subsequence constituting in the cluster, and calculates the evaluation value for the cluster based on the appearance probability. | 1. A speech recognition dictionary creating support device comprising: a speech data storage section storing speech data; a prosodic information extracting section extracting prosodic information including at least a speech power value from the speech data; a speech data dividing section extracting an utterance section having a period with a power value equal to or larger than a predetermined threshold value lasting a preset time or longer from the speech data based on the prosodic information, and dividing the utterance section into sections, each of which has a power value equal to or lamer than a predetermined threshold value continuing for a given time or longer, to generate divided speech data; a phoneme sequence acquiring section executing a phoneme recognition process on the divided speech data to acquire phoneme sequence data for each divided speech data; a clustering section executing a clustering process on the phoneme sequence data to generate clusters each of which is a set of classified phoneme sequence data; an evaluation value calculating section calculating an evaluation value for each of the clusters based on the prosodic information for the divided speech data corresponding to the phoneme sequence data constituting the cluster; a candidate cluster selecting section selecting clusters for which the evaluation value is equal to or larger than a given value, as candidate clusters; and a listening target data selecting section determining one of the phoneme sequence data from the phoneme sequence data constituting the cluster for each of the candidate clusters to be a representative phoneme sequence and selecting the divided speech data corresponding to the representative phoneme sequence, as listening target speech data, and wherein the evaluation value calculating section includes dictionary data for a morpheme analysis process, and extracts a phrase classified as a predetermined word class from the dictionary data, calculates an appearance probability, in the extracted phrase, of a common phoneme subsequence constituting in the cluster, and calculates the evaluation value for the cluster based on the appearance probability. 5. The speech recognition dictionary creating support device according to claim 1 , wherein the listening target data selecting section determines phoneme sequence data with a longest phoneme sequence in the candidate cluster to be the representative phoneme sequence. | 0.768166 |
9,158,825 | 12 | 13 | 12. A non-transitory computer-readable storage medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to perform a method of search on a data backup system comprising: receiving a search query; performing a search of indexed information stored in the data backup system based on the search query; determining how much non-indexed information is stored in the data backup system as related to the search query; and returning results of the performing and the determining, wherein returning the results comprises: displaying search results of the indexed information; displaying a relevancy of the search results; displaying additional information related to the search, the additional information comprising an identification of non-indexed inaccessible information; and displaying a set of indexing options associated with the non-indexed information. | 12. A non-transitory computer-readable storage medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to perform a method of search on a data backup system comprising: receiving a search query; performing a search of indexed information stored in the data backup system based on the search query; determining how much non-indexed information is stored in the data backup system as related to the search query; and returning results of the performing and the determining, wherein returning the results comprises: displaying search results of the indexed information; displaying a relevancy of the search results; displaying additional information related to the search, the additional information comprising an identification of non-indexed inaccessible information; and displaying a set of indexing options associated with the non-indexed information. 13. The computer-readable storage medium of claim 12 , wherein determining how much non-indexed information is stored in the data backup system as related to the search query comprises: querying a target image set related to the search query; and determining an amount of non-indexed information of the target image set. | 0.5 |
7,739,307 | 1 | 2 | 1. A method of storing digital assets, the digital assets comprising at least three different types of digital assets selected from the group consisting of still images, video recordings, movies, audio recordings, graphics, promos, voiceovers, and text, the method comprising: arranging metadata of a first type of digital asset in accordance with a document type definition (DTD) comprising declared elements and attributes for at least three different types of digital assets, the at least three different types of digital assets including still images, video recordings and at least one of audio recordings, movies, graphics, promos, voiceovers, and text, the DTD further comprising declared elements and attributes for rights management of the at least three different types of digital assets, the rights management elements and attributes comprising metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier; the DTD defining metadata for still images and metadata attributes for the still images metadata, the still images metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions; the DTD also defining metadata for video recordings and metadata attributes for the video recordings metadata, the video recordings metadata attributes comprising at least one of: a definition for title, a definition for version, a definition for author, a definition for caption, or a definition for ownership rights; the DTD further defining metadata for audio recordings and metadata attributes for the audio recordings metadata, the audio recordings metadata attributes comprising at least one of: a definition for music; a definition for track title; a definition for duration; a definition for compact disc (CD) number; a definition for CD title; or a definition for rights issues regarding use of an audio recording; arranging metadata of a second type of digital asset in accordance with the DTD, the second type different from the first type; arranging metadata of a third type of digital asset in accordance with the DTD, the third type different from the first type and the second type; storing a first digital asset of the first type in a database, the first type comprising a still image; storing a second digital asset of the second type in the same database as the first digital asset, the second type comprising a video recording; and storing a third digital asset of the third type in the same database as the first and second digital assets, the third type comprising an audio recording; wherein: the method is performed by a computer system comprising: a server comprising the database storing the first, second, and third different types of digital assets; and a computer readable storage medium comprising the DTD, the computer readable storage medium accessible by the server. | 1. A method of storing digital assets, the digital assets comprising at least three different types of digital assets selected from the group consisting of still images, video recordings, movies, audio recordings, graphics, promos, voiceovers, and text, the method comprising: arranging metadata of a first type of digital asset in accordance with a document type definition (DTD) comprising declared elements and attributes for at least three different types of digital assets, the at least three different types of digital assets including still images, video recordings and at least one of audio recordings, movies, graphics, promos, voiceovers, and text, the DTD further comprising declared elements and attributes for rights management of the at least three different types of digital assets, the rights management elements and attributes comprising metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier; the DTD defining metadata for still images and metadata attributes for the still images metadata, the still images metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions; the DTD also defining metadata for video recordings and metadata attributes for the video recordings metadata, the video recordings metadata attributes comprising at least one of: a definition for title, a definition for version, a definition for author, a definition for caption, or a definition for ownership rights; the DTD further defining metadata for audio recordings and metadata attributes for the audio recordings metadata, the audio recordings metadata attributes comprising at least one of: a definition for music; a definition for track title; a definition for duration; a definition for compact disc (CD) number; a definition for CD title; or a definition for rights issues regarding use of an audio recording; arranging metadata of a second type of digital asset in accordance with the DTD, the second type different from the first type; arranging metadata of a third type of digital asset in accordance with the DTD, the third type different from the first type and the second type; storing a first digital asset of the first type in a database, the first type comprising a still image; storing a second digital asset of the second type in the same database as the first digital asset, the second type comprising a video recording; and storing a third digital asset of the third type in the same database as the first and second digital assets, the third type comprising an audio recording; wherein: the method is performed by a computer system comprising: a server comprising the database storing the first, second, and third different types of digital assets; and a computer readable storage medium comprising the DTD, the computer readable storage medium accessible by the server. 2. The method of claim 1 further comprising storing the metadata of the first, second, and third types of digital assets in the same database as the first, second, and third digital assets. | 0.844828 |
9,547,420 | 1 | 24 | 1. A computer-implemented method of suggesting text via a computing device, comprising: receiving character input in a text entry element of an interface of a computing device; analyzing the character input to determine a plurality of suggestions, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determining a two-dimensional spatial layout of at least a portion of the plurality of suggestions, a location in the spatial layout being determined based, at least in part, upon a grouping of the suggestions and a confidence score of the suggestions, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; displaying the at least the portion of the plurality of suggestions according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detecting a user selection of a specified selection of the suggestions displayed according to the spatial layout; and modifying the character input in the text entry element according to the specified selection. | 1. A computer-implemented method of suggesting text via a computing device, comprising: receiving character input in a text entry element of an interface of a computing device; analyzing the character input to determine a plurality of suggestions, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determining a two-dimensional spatial layout of at least a portion of the plurality of suggestions, a location in the spatial layout being determined based, at least in part, upon a grouping of the suggestions and a confidence score of the suggestions, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; displaying the at least the portion of the plurality of suggestions according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detecting a user selection of a specified selection of the suggestions displayed according to the spatial layout; and modifying the character input in the text entry element according to the specified selection. 24. The method of claim 1 , wherein a suggestion is a word suggestion based on the character input, and is designated as one of the correction type, the common base portion type, or the completion type. | 0.722527 |
10,108,679 | 1 | 9 | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 1. A method of analyzing data, comprising: generating, by an entity, a query based at least in part on a topic of interest; executing the query on a plurality of data sources; selecting, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; monitoring, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; extracting data from the data source when at least the update to the stored data matches the query, the newly added data matches the query, or the combination thereof; determining an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; determining a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; dynamically adjusting the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; analyzing, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; establishing a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided the data to the data source, based on the analysis of the extracted data; transmitting, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and receiving, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 9. The method of claim 1 , in which the two-way communication channel comprises at least one of short message service (SMS), click-to-voice, interactive voice response (IVR), e-mail, phone, Internet protocol, message board, social media, digital communication, or a combination thereof. | 0.585507 |
10,120,850 | 15 | 17 | 15. A method for providing an active overlay image for interacting with and manipulating a digital image, the method comprising: providing a textual or graphical overlay of one or more annotated fields superimposed on a display of the digital image, wherein said one or more annotated fields correlate to one or more image informational items; said one or more image informational items comprising parameters and values relating to the display of the digital image; activating one or more of said one or more annotated fields, wherein said one or more activated fields are selectable to accept direct input of a value for said correlating one or more image informational items; defining a bounding region around said textual or graphical overlay of the digital image, wherein placement of a cursor within said bounding region provides an indication to an application program and results in a display of a visual indicia to a user; and wherein said indication initiates a feature of said application program that is selectable using the cursor to manipulate the digital image. | 15. A method for providing an active overlay image for interacting with and manipulating a digital image, the method comprising: providing a textual or graphical overlay of one or more annotated fields superimposed on a display of the digital image, wherein said one or more annotated fields correlate to one or more image informational items; said one or more image informational items comprising parameters and values relating to the display of the digital image; activating one or more of said one or more annotated fields, wherein said one or more activated fields are selectable to accept direct input of a value for said correlating one or more image informational items; defining a bounding region around said textual or graphical overlay of the digital image, wherein placement of a cursor within said bounding region provides an indication to an application program and results in a display of a visual indicia to a user; and wherein said indication initiates a feature of said application program that is selectable using the cursor to manipulate the digital image. 17. A method in accordance with claim 15 wherein said initiated feature of said application program is a context menu operation. | 0.597484 |
10,038,786 | 1 | 9 | 1. A computer-implemented method, comprising: determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood, by the processor, based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; tracking, by the processor, changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; performing, by the processor, the at least one action associated with the real-time textual conversation, wherein performing the at least one action comprises any of: displaying, by the processor, information associated with the at least one action to a supervisor monitoring the real-time textual conversation and providing, by the processor, the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation. | 1. A computer-implemented method, comprising: determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood, by the processor, based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; tracking, by the processor, changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; performing, by the processor, the at least one action associated with the real-time textual conversation, wherein performing the at least one action comprises any of: displaying, by the processor, information associated with the at least one action to a supervisor monitoring the real-time textual conversation and providing, by the processor, the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation. 9. The method of claim 1 , wherein determination of the at least one action is performed further based on a statistical analysis of one or more completed textual conversations. | 0.696552 |
9,208,148 | 1 | 2 | 1. A computer, comprising: at least one processor; and a storage system that stores one or more programs, when executed by the at least one processor, cause the at least one processor to perform a translation method, the method comprising: obtaining a word from a word list stored in a database connected to the computer; searching for position codes corresponding to the obtained word in a file; determining if the position codes corresponding to the obtained word overlap with the position codes corresponding to other words, wherein a character length of each other word is longer than the character length of the obtained word; deleting overlapped position codes from the position codes corresponding to the obtained word, in response to a determination that the position codes corresponding to the obtained word overlaps with the position codes corresponding to other words; saving remaining position codes corresponding to the obtained word into the word list; and converting the file between simplified Chinese and traditional Chinese according to the position codes of each word in the word list, in response to a determination that all of the words in the word list have been obtained. | 1. A computer, comprising: at least one processor; and a storage system that stores one or more programs, when executed by the at least one processor, cause the at least one processor to perform a translation method, the method comprising: obtaining a word from a word list stored in a database connected to the computer; searching for position codes corresponding to the obtained word in a file; determining if the position codes corresponding to the obtained word overlap with the position codes corresponding to other words, wherein a character length of each other word is longer than the character length of the obtained word; deleting overlapped position codes from the position codes corresponding to the obtained word, in response to a determination that the position codes corresponding to the obtained word overlaps with the position codes corresponding to other words; saving remaining position codes corresponding to the obtained word into the word list; and converting the file between simplified Chinese and traditional Chinese according to the position codes of each word in the word list, in response to a determination that all of the words in the word list have been obtained. 2. The computer of claim 1 , wherein the word list comprises simplified Chinese words and traditional Chinese words, each simplified Chinese word corresponds to a traditional Chinese word in the word list. | 0.5 |
7,849,094 | 11 | 13 | 11. A non-transitory computer accessible recording medium storing a program to be executed by a computer of an image processing device provided with a communication unit configured to communicate with an information processing device, and a web server unit configured to generate a webpage which can be browsed by a web browser executed in the information processing device and transmit the generated webpage to the information processing device, the program causes the computer, when executed, to perform steps of: receiving a webpage request from the information processing device; determining whether the webpage request includes a user selection of a specific language for the webpage from a plurality of languages, each of the plurality of languages corresponding to a different language character code set of a plurality of language character code sets; in response to determining that the webpage request includes a user selection of a specific language, operating in a first mode in which the text of the webpage is incorporated using characters of a first character code set corresponding to the specific language selected from among the plurality of languages; and in response to determining that the webpage request does not include a user selection of a specific language, operating in a second mode comprising: acquiring language information of the web browser; inserting a designation of a second character code set corresponding to the language information of the web browser in the webpage, wherein the second character code set further corresponds to a first language; and incorporating text of a second language into the webpage using a character set common to the plurality of language character code sets. | 11. A non-transitory computer accessible recording medium storing a program to be executed by a computer of an image processing device provided with a communication unit configured to communicate with an information processing device, and a web server unit configured to generate a webpage which can be browsed by a web browser executed in the information processing device and transmit the generated webpage to the information processing device, the program causes the computer, when executed, to perform steps of: receiving a webpage request from the information processing device; determining whether the webpage request includes a user selection of a specific language for the webpage from a plurality of languages, each of the plurality of languages corresponding to a different language character code set of a plurality of language character code sets; in response to determining that the webpage request includes a user selection of a specific language, operating in a first mode in which the text of the webpage is incorporated using characters of a first character code set corresponding to the specific language selected from among the plurality of languages; and in response to determining that the webpage request does not include a user selection of a specific language, operating in a second mode comprising: acquiring language information of the web browser; inserting a designation of a second character code set corresponding to the language information of the web browser in the webpage, wherein the second character code set further corresponds to a first language; and incorporating text of a second language into the webpage using a character set common to the plurality of language character code sets. 13. The non-transitory computer accessible recording medium according to claim 11 , wherein the image processing device further includes: a printing unit configured to print an image based on a file received from the image processing device via the communication unit; and a log information storage configured to store a log file comprising information defining a process by which the file is printed by the printing unit, and wherein the program further causes the computer to perform steps of: acquiring the log information from the log information storage, and incorporating the log information in the text of the webpage. | 0.5 |
9,524,751 | 9 | 11 | 9. An apparatus for multimedia content generation, comprising: a user terminal including a screen, which is configured to receive from a user, a text that will serve as audio narration in a video clip, to automatically collect from one or more databases, responsive to the received text that will serve as audio narration in the video clip, a collection of media items to be selectively included in the video clip, to present to the user, on the screen, in a graphic user interface (GUI), the received text that will serve as audio narration in the video clip and the collection of media items and to receive from the user, through the GUI, instructions, which associate one or more selected media items from the automatically collected collection of media items, with corresponding elements of the received text; and a processor, which is configured to automatically generate the video clip, such that the selected media items appear in the video clip in the order of the corresponding elements in the received text and in synchronization with the corresponding elements of the received text in accordance with the instructions, which associate the one or more selected media items with corresponding elements of the received text. | 9. An apparatus for multimedia content generation, comprising: a user terminal including a screen, which is configured to receive from a user, a text that will serve as audio narration in a video clip, to automatically collect from one or more databases, responsive to the received text that will serve as audio narration in the video clip, a collection of media items to be selectively included in the video clip, to present to the user, on the screen, in a graphic user interface (GUI), the received text that will serve as audio narration in the video clip and the collection of media items and to receive from the user, through the GUI, instructions, which associate one or more selected media items from the automatically collected collection of media items, with corresponding elements of the received text; and a processor, which is configured to automatically generate the video clip, such that the selected media items appear in the video clip in the order of the corresponding elements in the received text and in synchronization with the corresponding elements of the received text in accordance with the instructions, which associate the one or more selected media items with corresponding elements of the received text. 11. The apparatus according to claim 9 , wherein the instructions received from the user associate each selected media item with a respective element of the text selected from a group of elements consisting of a word, a part of a word, a space between words and a punctuation mark. | 0.522109 |
7,836,110 | 1 | 4 | 1. A method for generating a media presentation file containing composite media for display, the method comprising: generating a hierarchy of templates by at least one parent template receiving at least one child template comprised of a candidate template element received based upon a request and a search query for candidate template elements; interpreting one or more requests for at least one of media or templates in a framework template based on a user query input, wherein the framework template is comprised of the hierarchy of templates, wherein each template is comprised of corresponding slots for at least one of the candidate media elements and candidate template elements; executing one or more search queries based on the one or more requests for media or templates to locate and download candidates comprised of at least one of candidate media elements or candidate template elements; evaluating the candidates received from each of the one or more search queries to select winning media candidates comprised of selected candidate media elements and candidate template elements using design rules to change evaluation parameters associated with the candidates; and generating a media presentation file based on the defined presentation of composite media. | 1. A method for generating a media presentation file containing composite media for display, the method comprising: generating a hierarchy of templates by at least one parent template receiving at least one child template comprised of a candidate template element received based upon a request and a search query for candidate template elements; interpreting one or more requests for at least one of media or templates in a framework template based on a user query input, wherein the framework template is comprised of the hierarchy of templates, wherein each template is comprised of corresponding slots for at least one of the candidate media elements and candidate template elements; executing one or more search queries based on the one or more requests for media or templates to locate and download candidates comprised of at least one of candidate media elements or candidate template elements; evaluating the candidates received from each of the one or more search queries to select winning media candidates comprised of selected candidate media elements and candidate template elements using design rules to change evaluation parameters associated with the candidates; and generating a media presentation file based on the defined presentation of composite media. 4. The method of claim 1 , wherein the evaluation parameters comprise at least one of a statistical weight, previous use statistics, user ratings, candidate supplier rankings, or developer rankings. | 0.679612 |
8,495,062 | 1 | 3 | 1. A computer-implemented method for generating a search term comprising: in a computer system: a. defining a profile based on a selection made by a user; b. getting a text object, wherein the text object contains a plurality of text items, at least one of the plurality of text items comprising a text item pointed to by a Universal Resource Locator (URL); c. selecting at least one, but not all of the text items based on the profile; d. parsing only the selected text items to generate the search term; and e. creating a search based on the search term and a selection of a search engine made by the user. | 1. A computer-implemented method for generating a search term comprising: in a computer system: a. defining a profile based on a selection made by a user; b. getting a text object, wherein the text object contains a plurality of text items, at least one of the plurality of text items comprising a text item pointed to by a Universal Resource Locator (URL); c. selecting at least one, but not all of the text items based on the profile; d. parsing only the selected text items to generate the search term; and e. creating a search based on the search term and a selection of a search engine made by the user. 3. The method of claim 1 , wherein at least one of the plurality of text items is selected from the group comprising: a title, a header, a footer, an abstract, a description, text with a specific font, text with a specific font size, text with a specific color, text identified by bullets, numeric text, alpha-text, bold text, italicized text, and underlined text. | 0.52231 |
9,275,272 | 1 | 10 | 1. A method comprising, by a computing device: receiving an image associated with an online social network, wherein the image portrays at least a first person; determining a social-graph affinity for one or more users of the online social network; determining, for each of the one or more users, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: the social-graph affinity determined for each user; and a facial-representation associated with each user, wherein the facial-representation associated with each user is compared with the image; sending, to a client system, one or more tag suggestions for the first person portrayed in the image based on the determined facial-recognition scores, wherein each tag suggestion corresponds to a particular user of the one or more users; and tagging the image with a particular user corresponding to a particular tag suggestion responsive to receiving a selection of the particular tag suggestion from the client system. | 1. A method comprising, by a computing device: receiving an image associated with an online social network, wherein the image portrays at least a first person; determining a social-graph affinity for one or more users of the online social network; determining, for each of the one or more users, a facial-recognition score with respect to the first person portrayed in the image, wherein the facial-recognition score is based at least in part on: the social-graph affinity determined for each user; and a facial-representation associated with each user, wherein the facial-representation associated with each user is compared with the image; sending, to a client system, one or more tag suggestions for the first person portrayed in the image based on the determined facial-recognition scores, wherein each tag suggestion corresponds to a particular user of the one or more users; and tagging the image with a particular user corresponding to a particular tag suggestion responsive to receiving a selection of the particular tag suggestion from the client system. 10. The method of claim 1 , further comprising: receiving, from the client system, a request from a first user to view the image; and sending, to the client system, the image for display to the first user. | 0.767045 |
9,542,182 | 1 | 4 | 1. A method for providing for standardization of variable names in an integrated development environment, the method comprising: scanning, by one or more computer processors, a project source code for variable names, the project source code managed by a development team in an integrated development environment, wherein a variable name is determined based, at least in part, on whether the variable name includes one or more mutations to a root word of a standard variable name, and at least one of one or more inheritance relationships for the standard variable name, and one or more general rules for variable names; determining, by the one or more computer processors, the project source code contains a non-standard variable name, wherein the non-standard variable name is a variable name that is not stored as a standard variable name determined by the development team; identifying a location of the non-standard variable name in the project source code, the location identified to the development team by a notification and wherein the notification includes at least a highlight of the non-standard variable name; determining, by the one or more computer processors, whether the non-standard variable name is added to a database, wherein adding the non-standard variable name in the database indicates approval of the non-standard variable name; determining, by the one or more computer processors, the project source code contains one or more standard variable names; responsive to determining the project source code contains one or more standard variable names, storing, by the one or more computer processors, the one or more standard variable names in the database; and using, by the one or more computer processors, the database to standardize new source code by auto-completion of one or more variable names while the new source code is being written. | 1. A method for providing for standardization of variable names in an integrated development environment, the method comprising: scanning, by one or more computer processors, a project source code for variable names, the project source code managed by a development team in an integrated development environment, wherein a variable name is determined based, at least in part, on whether the variable name includes one or more mutations to a root word of a standard variable name, and at least one of one or more inheritance relationships for the standard variable name, and one or more general rules for variable names; determining, by the one or more computer processors, the project source code contains a non-standard variable name, wherein the non-standard variable name is a variable name that is not stored as a standard variable name determined by the development team; identifying a location of the non-standard variable name in the project source code, the location identified to the development team by a notification and wherein the notification includes at least a highlight of the non-standard variable name; determining, by the one or more computer processors, whether the non-standard variable name is added to a database, wherein adding the non-standard variable name in the database indicates approval of the non-standard variable name; determining, by the one or more computer processors, the project source code contains one or more standard variable names; responsive to determining the project source code contains one or more standard variable names, storing, by the one or more computer processors, the one or more standard variable names in the database; and using, by the one or more computer processors, the database to standardize new source code by auto-completion of one or more variable names while the new source code is being written. 4. The method of claim 1 , further comprising: determining, by the one or more computer processors, the non-standard variable name is no longer in the project source code; and removing the notification from the project source code. | 0.524691 |
7,877,421 | 1 | 9 | 1. A method executed in a computer for deriving a transformation for transforming first data conforming with a source data schema to second data conforming to a target data schema, the method comprising: providing an ontology model including classes and properties of classes; providing the source data schema; providing the target data schema, wherein the target data schema is different from the source data schema; identifying a first primary data construct within the source data schema; identifying a first secondary data construct within the first primary data construct; identifying a second primary data construct within the target data schema; identifying a second secondary data construct within the second primary data construct; generating a first mapping for mapping the first primary data construct to a corresponding class of the ontology model; generating a second mapping for mapping the first secondary data construct to a property of the corresponding class of the ontology model; generating a third mapping for mapping the second primary data to a corresponding class of the ontology model; generating a fourth mapping for mapping the second secondary data construct to a property of the corresponding class of the ontology model; and deriving the transformation, wherein the transformation is based on the first mapping, the second mapping, the third mapping, and the fourth mapping. | 1. A method executed in a computer for deriving a transformation for transforming first data conforming with a source data schema to second data conforming to a target data schema, the method comprising: providing an ontology model including classes and properties of classes; providing the source data schema; providing the target data schema, wherein the target data schema is different from the source data schema; identifying a first primary data construct within the source data schema; identifying a first secondary data construct within the first primary data construct; identifying a second primary data construct within the target data schema; identifying a second secondary data construct within the second primary data construct; generating a first mapping for mapping the first primary data construct to a corresponding class of the ontology model; generating a second mapping for mapping the first secondary data construct to a property of the corresponding class of the ontology model; generating a third mapping for mapping the second primary data to a corresponding class of the ontology model; generating a fourth mapping for mapping the second secondary data construct to a property of the corresponding class of the ontology model; and deriving the transformation, wherein the transformation is based on the first mapping, the second mapping, the third mapping, and the fourth mapping. 9. The method of claim 1 wherein generating the first mapping and generating the second mapping are performed automatically, based on matching at least partial names between the primary data construct and a class of the ontology model, and between the secondary data construct and a property of the class, respectively. | 0.671811 |
10,127,329 | 1 | 2 | 1. A method for processing an extensible markup language (XML) file, the method comprising: determining, by a computer processor, whether an XML file includes one or more complex elements, and whether the XML file is generated based on a schema that includes one or more split attributes and one or more hierarchy attributes; responsive to determining the XML file includes one or more complex elements, the computer processor determining whether a first element of the one or more complex elements of the XML file includes one or more split attributes, wherein the one or more split attributes include one or more characters indicating the first element of the XML file to be split, and determining whether the first element includes one or more hierarchy attributes, wherein the one or more hierarchy attributes include one or more characters indicating a relative processing priority of the first element of the one or more complex elements of the XML file; responsive to determining the first element of the one or more complex elements of the XML file includes one or more split attributes that include the one or more characters indicating the first element to be split, splitting at run-time, by the computer processor, the first element of the XML file into a subset of the XML file, based on the one or more split attributes and the one or more characters indicating the first element of the XML file to be split, as identified within the first element of the XML file; responsive to determining the first element of the one or more complex elements of the XML file includes one or more hierarchy attributes, submitting the subset of the XML file first element for processing, based on the one or more characters indicating the relative processing priority within the one or more hierarchy attributes; and distributing, by the computer processor, the subset of the first element of the XML file to a computing node of a plurality of computing nodes of a distributed computer processing system. | 1. A method for processing an extensible markup language (XML) file, the method comprising: determining, by a computer processor, whether an XML file includes one or more complex elements, and whether the XML file is generated based on a schema that includes one or more split attributes and one or more hierarchy attributes; responsive to determining the XML file includes one or more complex elements, the computer processor determining whether a first element of the one or more complex elements of the XML file includes one or more split attributes, wherein the one or more split attributes include one or more characters indicating the first element of the XML file to be split, and determining whether the first element includes one or more hierarchy attributes, wherein the one or more hierarchy attributes include one or more characters indicating a relative processing priority of the first element of the one or more complex elements of the XML file; responsive to determining the first element of the one or more complex elements of the XML file includes one or more split attributes that include the one or more characters indicating the first element to be split, splitting at run-time, by the computer processor, the first element of the XML file into a subset of the XML file, based on the one or more split attributes and the one or more characters indicating the first element of the XML file to be split, as identified within the first element of the XML file; responsive to determining the first element of the one or more complex elements of the XML file includes one or more hierarchy attributes, submitting the subset of the XML file first element for processing, based on the one or more characters indicating the relative processing priority within the one or more hierarchy attributes; and distributing, by the computer processor, the subset of the first element of the XML file to a computing node of a plurality of computing nodes of a distributed computer processing system. 2. The method of claim 1 , wherein determining the XML file as a split candidate, further comprises: comparing, by the computer processor, a size of the XML file to a pre-determined threshold size; and in response to the size of the XML file exceeding the pre-determined threshold size, determining the XML file as a split candidate. | 0.614583 |
9,965,459 | 8 | 14 | 8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a source document to be processed for contextual information relating to the source document; provide, for display on a representation of the source document on a user interface, a first input mechanism for a user; identify, based on a first user interaction with the first input mechanism, a first named entity included in the source document; identify, based on a second user interaction with the first input mechanism, a context associated with the source document by using context terms, of the source document, that are different than the first named entity; provide the first named entity as a search query; identify a first reference document based on providing the first named entity as the search query, the first reference document being associated with a result of the search query, and the first reference document being different from the source document; identify a second named entity included in the source document; identify a second reference document associated with the second named entity; analyze the first reference document and the second reference document; classify the first named entity as a primary entity based on analyzing the first reference document and the second reference document; classify the second named entity as a secondary entity based on analyzing the first reference document and the second reference document; perform a semantic similarity analysis using the context associated with the source document and based on classifying the first named entity as the primary entity and the second named entity as the secondary entity; provide, for display on the user interface, a second input mechanism for the user to cause contextual information to be provided; and identify contextual information, based on performing the semantic similarity analysis and based on a third user interaction with the second input mechanism, the contextual information including one or more reference text sections having a threshold semantic similarity score with respect to the secondary entity and the context associated with the source document, and not being included in the source document. | 8. A computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a source document to be processed for contextual information relating to the source document; provide, for display on a representation of the source document on a user interface, a first input mechanism for a user; identify, based on a first user interaction with the first input mechanism, a first named entity included in the source document; identify, based on a second user interaction with the first input mechanism, a context associated with the source document by using context terms, of the source document, that are different than the first named entity; provide the first named entity as a search query; identify a first reference document based on providing the first named entity as the search query, the first reference document being associated with a result of the search query, and the first reference document being different from the source document; identify a second named entity included in the source document; identify a second reference document associated with the second named entity; analyze the first reference document and the second reference document; classify the first named entity as a primary entity based on analyzing the first reference document and the second reference document; classify the second named entity as a secondary entity based on analyzing the first reference document and the second reference document; perform a semantic similarity analysis using the context associated with the source document and based on classifying the first named entity as the primary entity and the second named entity as the secondary entity; provide, for display on the user interface, a second input mechanism for the user to cause contextual information to be provided; and identify contextual information, based on performing the semantic similarity analysis and based on a third user interaction with the second input mechanism, the contextual information including one or more reference text sections having a threshold semantic similarity score with respect to the secondary entity and the context associated with the source document, and not being included in the source document. 14. The computer-readable medium of claim 8 , where the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: calculate a relevance score for the first named entity and a relevance score for the second named entity; and where the one or more instructions, that cause the one or more processors to classify the first named entity as the primary entity, cause the one or more processors to: classify the first named entity as the primary entity based on the first named entity having a higher relevance score than the second named entity. | 0.679185 |
8,401,847 | 9 | 12 | 9. The program for speech recognition system according to claim 8 , wherein the speech recognition section performs speech recognition once again for speech data corresponding to an uncorrected portion of the text data that has not been subjected to correction when the additional registration section makes a new additional registration. | 9. The program for speech recognition system according to claim 8 , wherein the speech recognition section performs speech recognition once again for speech data corresponding to an uncorrected portion of the text data that has not been subjected to correction when the additional registration section makes a new additional registration. 12. The program for speech recognition system according to claim 9 , further causing the computer to function as: a speaker recognition section that identifies the speaker type based on the speech data; and a dictionary selecting section that selects a speech recognition dictionary corresponding to the speaker type identified by the speaker recognition section from among a plurality of speech recognition dictionaries that have been previously prepared corresponding to the speaker type as a speech recognition dictionary to be used in the speech recognition section. | 0.528926 |
5,495,603 | 19 | 20 | 19. The computer file management system of claim 18 wherein said file attributes include a plurality of file identifiers and a plurality of file characteristics and wherein each said rule declaration specifies a value for at least one of said plurality of file characteristics. | 19. The computer file management system of claim 18 wherein said file attributes include a plurality of file identifiers and a plurality of file characteristics and wherein each said rule declaration specifies a value for at least one of said plurality of file characteristics. 20. The computer file management system of claim 19 wherein said plurality of file identifiers includes a file name, a file directory and a file storage group and said plurality of file characteristics includes a file size designation and one or more file type designations. | 0.5 |
9,355,193 | 9 | 10 | 9. The method of claim 6 , further comprising: ascertaining, by the system, an identification of a user that requested the data model; activating, by the system, at least a portion of the associated functionalities related to the data model based on the identification of the user; and outputting, by the system, the data model with at least the portion of the associated functionalities activated, wherein the activation enables at least the portion of the associated functionalities to be viewed. | 9. The method of claim 6 , further comprising: ascertaining, by the system, an identification of a user that requested the data model; activating, by the system, at least a portion of the associated functionalities related to the data model based on the identification of the user; and outputting, by the system, the data model with at least the portion of the associated functionalities activated, wherein the activation enables at least the portion of the associated functionalities to be viewed. 10. The method of claim 9 , wherein the activating comprises determining, by the system, the user has access rights to at least the portion of the associated functionalities based on the identification of the user. | 0.5 |
8,751,234 | 1 | 4 | 1. A method for determining contextual information at a communication device comprising a processing unit interconnected with a memory device, a communication interface and a display device, said method comprising: receiving, at said processing unit, textual information from calendar data associated with a calendar event; processing, at said processing unit, said textual information to automatically extract contextual data embedded in said textual information in response to said receiving; automatically retrieving, by said processing unit, supplementary contextual data based on said contextual data from a remote data source via said communication interface in response to said processing; automatically rendering said supplementary contextual data at said display device in association with said calendar event from which the textual information was received and said contextual data in response to receiving said supplementary contextual data; and determining a time for automatically rendering said supplementary contextual data at said display device in association with said contextual data, using said supplementary context data. | 1. A method for determining contextual information at a communication device comprising a processing unit interconnected with a memory device, a communication interface and a display device, said method comprising: receiving, at said processing unit, textual information from calendar data associated with a calendar event; processing, at said processing unit, said textual information to automatically extract contextual data embedded in said textual information in response to said receiving; automatically retrieving, by said processing unit, supplementary contextual data based on said contextual data from a remote data source via said communication interface in response to said processing; automatically rendering said supplementary contextual data at said display device in association with said calendar event from which the textual information was received and said contextual data in response to receiving said supplementary contextual data; and determining a time for automatically rendering said supplementary contextual data at said display device in association with said contextual data, using said supplementary context data. 4. The method of claim 1 , wherein said automatically rendering said supplementary contextual data at said display device in association with said contextual data in response to receiving said supplementary contextual data comprises rendering said supplementary contextual data at least one of adjacent and proximal to said contextual data. | 0.5 |
8,078,602 | 20 | 22 | 20. A method comprising the steps of: (A) obtaining consumer navigation data from computer programs running on multiple user computers, said navigation data comprising data identifying a plurality of web pages viewed at said user computers; (B) obtaining behavioral data from said multiple user computers, said behavioral data relating to said plurality of web pages identified by said consumer navigation data; (C) for each of the plurality of web pages identified by the navigation data, using said navigation data and said behavioral data to determine corresponding implied consumer preference data; (D) building a search engine index using at least the consumer navigation data and the implied consumer preference data, said step of building comprising, for each particular web page of the plurality of web pages identified by the navigation data: (d1) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and (d2) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page; and (E) in response to a search request based on a search keyword, retrieving results from the search engine index, said results identifying a plurality of web pages, and (F) providing the results ordered, at least in part, by a ranking of the plurality of web pages relative to the search keyword. | 20. A method comprising the steps of: (A) obtaining consumer navigation data from computer programs running on multiple user computers, said navigation data comprising data identifying a plurality of web pages viewed at said user computers; (B) obtaining behavioral data from said multiple user computers, said behavioral data relating to said plurality of web pages identified by said consumer navigation data; (C) for each of the plurality of web pages identified by the navigation data, using said navigation data and said behavioral data to determine corresponding implied consumer preference data; (D) building a search engine index using at least the consumer navigation data and the implied consumer preference data, said step of building comprising, for each particular web page of the plurality of web pages identified by the navigation data: (d1) parsing a copy of the particular web page to determine the occurrence of one or more keywords in the particular web page; and (d2) ranking the particular web page relative to at least some of the one or more keywords, said ranking being based at least in part on results of the parsing and on implied consumer preference data associated with the particular web page; and (E) in response to a search request based on a search keyword, retrieving results from the search engine index, said results identifying a plurality of web pages, and (F) providing the results ordered, at least in part, by a ranking of the plurality of web pages relative to the search keyword. 22. The system of claim 20 , wherein the consumer navigation data include addresses of web pages viewed at a user computer. | 0.6925 |
6,061,697 | 7 | 10 | 7. An SGML type document managing apparatus for allowing users to create, edit, and use an SGML type document collaboratively, comprising: means for storing history information of a document element being copied, moved, exchanged, appended, or deleted in an SGML format, which can indicate a change of a structure of the SGML type document; and means for outputting the stored history information in a machine-independent format. | 7. An SGML type document managing apparatus for allowing users to create, edit, and use an SGML type document collaboratively, comprising: means for storing history information of a document element being copied, moved, exchanged, appended, or deleted in an SGML format, which can indicate a change of a structure of the SGML type document; and means for outputting the stored history information in a machine-independent format. 10. The SGML type document managing apparatus as set forth in claim 7, wherein the output history information is formed by embedding an original SGML type document in a frame of history information, and describes a revision history as a transition of elements before and after revisions. | 0.570359 |
8,812,537 | 3 | 4 | 3. The method of claim 1 , wherein the database command comprises a database selection command, and wherein transacting further comprises: querying the database system with the selection command; and retrieving command-specified data based on the querying. | 3. The method of claim 1 , wherein the database command comprises a database selection command, and wherein transacting further comprises: querying the database system with the selection command; and retrieving command-specified data based on the querying. 4. The method of claim 3 , further comprising: providing the command-specific data to at least one target. | 0.554622 |
5,537,485 | 23 | 24 | 23. The method according to claim 22, wherein said step of performing at least one predetermined thresholding test comprises: performing an area versus contrast thresholding test to determine, for each signal for which features are extracted, whether that signal corresponds to a false positive microcalcification cluster, and if so, removing from said cluster image that pixel identifying the location of said false positive microcalcification cluster by setting the value of that pixel in the cluster image to a predetermined value. | 23. The method according to claim 22, wherein said step of performing at least one predetermined thresholding test comprises: performing an area versus contrast thresholding test to determine, for each signal for which features are extracted, whether that signal corresponds to a false positive microcalcification cluster, and if so, removing from said cluster image that pixel identifying the location of said false positive microcalcification cluster by setting the value of that pixel in the cluster image to a predetermined value. 24. This method according to claim 23, wherein said of performing at least one predetermined thresholding test identifying comprises: performing a contrast versus background test to determine for each signal for which features are extracted, whether that signal corresponds to a false positive signal, and if so, removing from said cluster image that pixel identifying the location of said false positive signal by setting the value of that pixel in the cluster image to a predetermined value. | 0.5 |
9,740,690 | 11 | 15 | 11. A computer system, comprising: a memory storing executable instructions; a processor, when configured by the executable instructions, is operable to: provide a developer interface to define a flexible sentence syntax that controls how an application service, among multiple application services, of a social networking system expresses one or more edges in a social graph of the social networking system, wherein the edges represent one or more user actions occurring in the social networking system and wherein the multiple application services respectively correspond to different flexible sentence syntaxes; generate, on the developer interface, a selectable token associated with a sentence element in the flexible sentence syntax; insert the sentence element into the flexible sentence syntax by selecting the selectable token that is associated with the sentence element to incorporate in the flexible sentence syntax; and according to the flexible sentence syntax, a target sentence corresponding to a new edge in a social graph of the social networking system. | 11. A computer system, comprising: a memory storing executable instructions; a processor, when configured by the executable instructions, is operable to: provide a developer interface to define a flexible sentence syntax that controls how an application service, among multiple application services, of a social networking system expresses one or more edges in a social graph of the social networking system, wherein the edges represent one or more user actions occurring in the social networking system and wherein the multiple application services respectively correspond to different flexible sentence syntaxes; generate, on the developer interface, a selectable token associated with a sentence element in the flexible sentence syntax; insert the sentence element into the flexible sentence syntax by selecting the selectable token that is associated with the sentence element to incorporate in the flexible sentence syntax; and according to the flexible sentence syntax, a target sentence corresponding to a new edge in a social graph of the social networking system. 15. The computer system of claim 11 , wherein the processor, when configured by the executable instructions, is operable to customize the flexible sentence syntax by inserting an arbitrary text string. | 0.813197 |
8,239,406 | 4 | 9 | 4. The method of claim 2 , wherein the data structure comprises a tree, the tree comprising at least one level. | 4. The method of claim 2 , wherein the data structure comprises a tree, the tree comprising at least one level. 9. The method of claim 4 , wherein the tree includes a header, the header including at least one of the following: a number of predicates in the tree, whether the tree is a special type, at least one counter, and combinations thereof. | 0.708955 |
8,924,216 | 15 | 18 | 15. Apparatus comprising: at least one processor; and at least one storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for synchronizing an audio medical dictation and a manual transcription of the audio medical dictation, the method comprising: establishing a repetition frequency at which to query playback of the audio medical dictation; while the audio medical dictation is being played back and manually transcribed, repeatedly obtaining, at the established repetition frequency, a current time position of a corresponding currently played sound datum in the audio medical dictation, and a currently transcribed text datum in the manual transcription at the current time position; generating a corrected time position for the currently transcribed text datum by applying to the current time position a time correction value in accordance with a transcription delay; and generating at least one association datum indicative of a synchronization association between the corrected time position and the currently transcribed text datum. | 15. Apparatus comprising: at least one processor; and at least one storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for synchronizing an audio medical dictation and a manual transcription of the audio medical dictation, the method comprising: establishing a repetition frequency at which to query playback of the audio medical dictation; while the audio medical dictation is being played back and manually transcribed, repeatedly obtaining, at the established repetition frequency, a current time position of a corresponding currently played sound datum in the audio medical dictation, and a currently transcribed text datum in the manual transcription at the current time position; generating a corrected time position for the currently transcribed text datum by applying to the current time position a time correction value in accordance with a transcription delay; and generating at least one association datum indicative of a synchronization association between the corrected time position and the currently transcribed text datum. 18. The apparatus of claim 15 , wherein the method further comprises storing the at least one association datum separately from the manual transcription in a synchronization file. | 0.69244 |
7,899,818 | 10 | 14 | 10. A system for providing search results, comprising: a processor; and memory storing instructions that, when executed by the processor, cause the processor to: perform a first search based on a keyword; generate for display a first list of results associated with the keyword based on the search; analyze searchable content of each of the results in the first list of results to identify terms in the searchable content that are useful in grouping sets of the first list of results; provide the identified terms in a list of selectable terms to be displayed with the first list of results, the terms being selectable independently of multi-character or single-character textual input; receive a selection of a user-selected term from the list of selectable terms, the list including selectable objects placed on a user interface adjacent to the terms on the list, the user-selected term being selected by selecting a selectable object adjacent to the term, said selecting being done independently of multi-character or single-character textual input, the selection causing results having content related to the user-selected term to be excluded from a second list of results; and in response to receiving the selection of the user-selected term, perform a second search based at least upon the keyword and the user-selected term and generate for display the second list of results that excludes results having content related to the user-selected term, wherein the second list of results is further able to include results not included in the first list of results. | 10. A system for providing search results, comprising: a processor; and memory storing instructions that, when executed by the processor, cause the processor to: perform a first search based on a keyword; generate for display a first list of results associated with the keyword based on the search; analyze searchable content of each of the results in the first list of results to identify terms in the searchable content that are useful in grouping sets of the first list of results; provide the identified terms in a list of selectable terms to be displayed with the first list of results, the terms being selectable independently of multi-character or single-character textual input; receive a selection of a user-selected term from the list of selectable terms, the list including selectable objects placed on a user interface adjacent to the terms on the list, the user-selected term being selected by selecting a selectable object adjacent to the term, said selecting being done independently of multi-character or single-character textual input, the selection causing results having content related to the user-selected term to be excluded from a second list of results; and in response to receiving the selection of the user-selected term, perform a second search based at least upon the keyword and the user-selected term and generate for display the second list of results that excludes results having content related to the user-selected term, wherein the second list of results is further able to include results not included in the first list of results. 14. The system of claim 10 , wherein the first and second lists of results comprise web pages. | 0.863768 |
8,396,901 | 17 | 18 | 17. The apparatus according to claim 12 further comprising: a converter for converting the XML encoded dataset into one or more pre-processed content fields. | 17. The apparatus according to claim 12 further comprising: a converter for converting the XML encoded dataset into one or more pre-processed content fields. 18. The apparatus according to claim 17 , wherein said converter for converting an XML encoded dataset associated with each identified hierarchical structure further comprises: storage for storing said one or more pre-processed content fields in an SQL content table, said record in said content table having a node identifier field containing the corresponding node identifier, a block identifier field and a content field. | 0.5 |
9,659,564 | 1 | 4 | 1. A non-standard speech detection system that is capable of analyzing human voice to detect the speech style of an individual for verifying identity of the individual according to his speech style, the system comprising: at least one voice recording unit for recording personal standard speeches of the individual in his/her normal life; at least one voice database wherein the personal standard speeches recorded by the voice recording unit are stored as voice recordings; at least one acoustic examination module for determining acoustic speech characteristics of the individual from the voice recordings stored in the voice database; at least one speech recognition module for determining behavioral characteristics and speech content characteristics of the individual from the voice recordings stored in the voice database and capable of making speech analysis by converting the voice recordings into text; at least one analysis module for creating a personal standard speech style model by examining the acoustic speech characteristics and the behavioral speech characteristics of the individual determined by the acoustic examination module and the speech content characteristics of the individual determined by the speech recognition module; at least one personal standard speech style model database wherein the personal standard speech style models created by the analysis module are recorded in a personalized way; at least one evaluation module for comparing a new voice input with the recorded personal standard speech style models; at least one transmission unit capable of transmitting result reached after the comparison of the evaluation module to related units, wherein the speech content characteristics of the individual include sentence patterns, words and phrases, language model n-gram parameters, and semantic parameters obtained from the text, wherein the evaluation module evaluates whether speech content characteristics, acoustic speech characteristics, and behavioral speech characteristics of the new voice input match the personal standard speech style model of the individual and verifies identity of a caller producing the new voice if a match occurs, wherein the behavioral speech characteristics of the individual include speech behavioral characteristic parameters of the individual, interruption interval for another party to the conversation, and speech overlap with the other party, and wherein the speech behavioral characteristic parameters include speaking speed, monotony, hesitance, and loudness of voice. | 1. A non-standard speech detection system that is capable of analyzing human voice to detect the speech style of an individual for verifying identity of the individual according to his speech style, the system comprising: at least one voice recording unit for recording personal standard speeches of the individual in his/her normal life; at least one voice database wherein the personal standard speeches recorded by the voice recording unit are stored as voice recordings; at least one acoustic examination module for determining acoustic speech characteristics of the individual from the voice recordings stored in the voice database; at least one speech recognition module for determining behavioral characteristics and speech content characteristics of the individual from the voice recordings stored in the voice database and capable of making speech analysis by converting the voice recordings into text; at least one analysis module for creating a personal standard speech style model by examining the acoustic speech characteristics and the behavioral speech characteristics of the individual determined by the acoustic examination module and the speech content characteristics of the individual determined by the speech recognition module; at least one personal standard speech style model database wherein the personal standard speech style models created by the analysis module are recorded in a personalized way; at least one evaluation module for comparing a new voice input with the recorded personal standard speech style models; at least one transmission unit capable of transmitting result reached after the comparison of the evaluation module to related units, wherein the speech content characteristics of the individual include sentence patterns, words and phrases, language model n-gram parameters, and semantic parameters obtained from the text, wherein the evaluation module evaluates whether speech content characteristics, acoustic speech characteristics, and behavioral speech characteristics of the new voice input match the personal standard speech style model of the individual and verifies identity of a caller producing the new voice if a match occurs, wherein the behavioral speech characteristics of the individual include speech behavioral characteristic parameters of the individual, interruption interval for another party to the conversation, and speech overlap with the other party, and wherein the speech behavioral characteristic parameters include speaking speed, monotony, hesitance, and loudness of voice. 4. The non-Standard speech detection system according to claim 1 , wherein the related pre-determined places include financial and e-commerce institutions that require verification of the caller. | 0.765625 |
8,463,782 | 1 | 6 | 1. A computer-implemented method comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating, by one or more computers, the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. | 1. A computer-implemented method comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating, by one or more computers, the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. 6. The method of claim 1 , wherein determining a correlation value from the first value and the second value comprises calculating the correlation value by dividing the first value by the second value. | 0.808206 |
9,412,392 | 1 | 9 | 1. A method for processing voice commands, performed at a electronic device capable of communicating with remote computing equipment over a communications path, the method comprising: in response to user input, recording at least a portion of a voice command on the electronic device; storing contextual information of the electronic device when the electronic device is recording the at least a portion of the voice command; and after recording the at least a portion of the voice command and storing the contextual information of the electronic device, uploading the at least a portion of the recorded voice command and the stored contextual information from the electronic device to the remote computing equipment over the communications path. | 1. A method for processing voice commands, performed at a electronic device capable of communicating with remote computing equipment over a communications path, the method comprising: in response to user input, recording at least a portion of a voice command on the electronic device; storing contextual information of the electronic device when the electronic device is recording the at least a portion of the voice command; and after recording the at least a portion of the voice command and storing the contextual information of the electronic device, uploading the at least a portion of the recorded voice command and the stored contextual information from the electronic device to the remote computing equipment over the communications path. 9. The method of claim 1 , wherein the contextual information comprises a location of the electronic device when the electronic device is recording the at least a portion of the voice command. | 0.545024 |
6,035,268 | 16 | 26 | 16. The method of claim 1, further comprising the step, prior to said identifying step, of applying a set of heuristic rules to said stored character string to identify a character-transition in said first segment of said stored character string, said identification of a character-transition reducing the number of possible character combinations forming words in said stored character string. | 16. The method of claim 1, further comprising the step, prior to said identifying step, of applying a set of heuristic rules to said stored character string to identify a character-transition in said first segment of said stored character string, said identification of a character-transition reducing the number of possible character combinations forming words in said stored character string. 26. The method of claim 16, wherein said step of applying the set of heuristic rules further comprises locating identifying Kanji-Katakana character-transitions in said stored character string, and identifying a character-transition that occurs at said located Kanji-Katakana character-transition. | 0.506645 |
9,251,246 | 7 | 8 | 7. A computer program product for defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving a data stream of non-dimensional data objects; applying a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects, a probability that one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. | 7. A computer program product for defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving a data stream of non-dimensional data objects; applying a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects, a probability that one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. 8. The computer program product of claim 7 , further comprising program code that is readable and executable by the processor to: graphically display the multiple context-based conformed dimensional data gravity wells according to a combined virtual mass of the multiple parsed synthetic context-based objects and the multiple parsed conformed dimensional objects, wherein a first context-based conformed dimensional data gravity well holds a more virtually massive combination of parsed data objects than a second context-based conformed dimensional data gravity well, and wherein the first context-based conformed dimensional data gravity well extends farther away from the context-based conformed dimensional data gravity wells membrane than the second context-based conformed dimensional data gravity well. | 0.747033 |
7,826,101 | 1 | 4 | 1. A document management apparatus for connection through a network to an image forming device, a document file server, and a workflow server, respectively, the document management apparatus comprising: an information acquisition unit configured to acquire, from the image forming device through the network, image data of a paper document including a signature block at a predetermined position of the paper document, and a user ID that identifies a user who requests the image forming device to read the image data from the paper document; an extraction unit configured to receive, from the document file server through the network, a document file which is acquired from a document file accumulation unit of the document file server in response to a document file ID that identifies the document file and is included in the image data of the paper document, and transmitted to the document management apparatus by the document file server, to extract revision data that is added to the paper document, based on difference data indicating differences obtained by matching of the image data of the paper document with image data of the document file, and to determine propriety of approval of the revision data based on an item of the extracted revision data corresponding to the predetermined position of the paper document; and a registration unit configured to transmit, to the workflow server through the network, a request of registration of approval information indicating the propriety of approval of the revision data, the request of registration including the approval information, the user ID and the document file ID, wherein the extraction unit is configured to request the document file server to register, into the document file accumulation unit, the document file, the revision data and the user ID that are associated with the document file, by using the document ID contained in the image data of the paper document, and wherein the workflow server is configured to register, in response to the request of registration received from the registration unit, state information indicating a progress of approval of the document file associated with the document ID. | 1. A document management apparatus for connection through a network to an image forming device, a document file server, and a workflow server, respectively, the document management apparatus comprising: an information acquisition unit configured to acquire, from the image forming device through the network, image data of a paper document including a signature block at a predetermined position of the paper document, and a user ID that identifies a user who requests the image forming device to read the image data from the paper document; an extraction unit configured to receive, from the document file server through the network, a document file which is acquired from a document file accumulation unit of the document file server in response to a document file ID that identifies the document file and is included in the image data of the paper document, and transmitted to the document management apparatus by the document file server, to extract revision data that is added to the paper document, based on difference data indicating differences obtained by matching of the image data of the paper document with image data of the document file, and to determine propriety of approval of the revision data based on an item of the extracted revision data corresponding to the predetermined position of the paper document; and a registration unit configured to transmit, to the workflow server through the network, a request of registration of approval information indicating the propriety of approval of the revision data, the request of registration including the approval information, the user ID and the document file ID, wherein the extraction unit is configured to request the document file server to register, into the document file accumulation unit, the document file, the revision data and the user ID that are associated with the document file, by using the document ID contained in the image data of the paper document, and wherein the workflow server is configured to register, in response to the request of registration received from the registration unit, state information indicating a progress of approval of the document file associated with the document ID. 4. The document management method of claim 1 wherein the document file is a document file concerning a meeting, and the document management apparatus further comprises a collation-request transmission unit transmitting a request for collation of the meeting, which contains at least user identification information that identifies a user, to a meeting management unit which manages information concerning the meeting. | 0.5 |
8,566,301 | 13 | 14 | 13. The method of claim 1 , wherein the media is displayed within a web-browsing application on an electronic device accessing the document. | 13. The method of claim 1 , wherein the media is displayed within a web-browsing application on an electronic device accessing the document. 14. The method of claim 13 , wherein the media is displayed in an application associated with the web-browsing application. | 0.5 |
9,224,402 | 3 | 5 | 3. The method of claim 1 , wherein said at least one set of second harmonic model component values is removed in a plurality of iterations so that during each one of said plurality of iterations the following is performed until a remaining harmonic component cost function is below a threshold: analyzing new harmonic model of previous harmonic model residual to produce new set of harmonic model component values, removing said new set of harmonic component values from said previous harmonic model residual to produce a new harmonic model residual for further iterations. | 3. The method of claim 1 , wherein said at least one set of second harmonic model component values is removed in a plurality of iterations so that during each one of said plurality of iterations the following is performed until a remaining harmonic component cost function is below a threshold: analyzing new harmonic model of previous harmonic model residual to produce new set of harmonic model component values, removing said new set of harmonic component values from said previous harmonic model residual to produce a new harmonic model residual for further iterations. 5. The method of claim 3 , wherein said new harmonic modeling uses at least one estimated energy envelope signal. | 0.5 |
7,756,398 | 1 | 2 | 1. A recording medium storing a data structure, the data structure comprising: at least one text subtitle stream, each text subtitle stream including a style segment defining at least one region style and a plurality of presentation segments, each presentation segment containing at least one region of text and the region of text defined by one of the at least one region style, wherein the style segment includes palette information, and each presentation segment further contains a palette update flag which indicates whether to use the palette information defined in the style segment or to use new palette information defined in an associated presentation segment. | 1. A recording medium storing a data structure, the data structure comprising: at least one text subtitle stream, each text subtitle stream including a style segment defining at least one region style and a plurality of presentation segments, each presentation segment containing at least one region of text and the region of text defined by one of the at least one region style, wherein the style segment includes palette information, and each presentation segment further contains a palette update flag which indicates whether to use the palette information defined in the style segment or to use new palette information defined in an associated presentation segment. 2. The recording medium of claim 1 , wherein when the palette update flag indicates the use of the new palette information defined in the associated presentation segment, the region of text defined by the at least one region style remaining constant from an immediately previous presentation segment but for an associated palette information. | 0.5 |
8,793,133 | 19 | 20 | 19. A system comprising: a display device; a memory; and a computing device operatively coupled to the display device and memory, and configured to: cause a user interface to render on the display an electronic representation of a document, where a first portion of the document is pre-associated with a first voice model and a remaining portion of the document is not pre-associated with a voice model, with pre-associated and non-pre-associated text being displayed with different indicia to indicate the portions that pre-associated and non-pre-associated text; receive a user-based selection of text corresponding to at least part of the first portion of the document; apply, in response to the user-based selection of the at least part of the first portion, a first set of indicia to the user-selected first portion in the document; and overwrite the at least part of the pre-association of the first voice model, by the one or more computers, with a second voice model for the first portion of words. | 19. A system comprising: a display device; a memory; and a computing device operatively coupled to the display device and memory, and configured to: cause a user interface to render on the display an electronic representation of a document, where a first portion of the document is pre-associated with a first voice model and a remaining portion of the document is not pre-associated with a voice model, with pre-associated and non-pre-associated text being displayed with different indicia to indicate the portions that pre-associated and non-pre-associated text; receive a user-based selection of text corresponding to at least part of the first portion of the document; apply, in response to the user-based selection of the at least part of the first portion, a first set of indicia to the user-selected first portion in the document; and overwrite the at least part of the pre-association of the first voice model, by the one or more computers, with a second voice model for the first portion of words. 20. The system of claim 19 , wherein the computing device is further configured: narrate words in the remaining first portion using the second voice model; and narrate at least some of at least part of the first portion of the document using the first voice model. | 0.685714 |
9,195,714 | 1 | 8 | 1. A method, comprising: performing, by one or more computers, initiating, based on receiving a source document, a routine for identifying one or more candidate duplicate documents of the source document from a document corpus, said identifying comprising: receiving the source document, wherein a document type of the source document is the same as a document type of at least some of a plurality of reference documents in the document corpus; determining a plurality of different queries from content of the source document; executing the plurality of different queries on the document corpus in response to receiving the source document, wherein the plurality of different queries differ from one another by at least one search term, wherein individual queries of the plurality of different queries produce a respective list of documents that identifies at least some of the plurality of reference documents of the document corpus, wherein the respective reference documents of the respective lists of documents are scored at least in part with respect to the source document; based, at least in part, on scores for the reference documents from at least two of the respective lists, selecting one or more of the reference documents having a respective score that meets a score threshold as potential duplicates of the same received source document that initiated the routine; and storing an identification of the one or more potential duplicate documents. | 1. A method, comprising: performing, by one or more computers, initiating, based on receiving a source document, a routine for identifying one or more candidate duplicate documents of the source document from a document corpus, said identifying comprising: receiving the source document, wherein a document type of the source document is the same as a document type of at least some of a plurality of reference documents in the document corpus; determining a plurality of different queries from content of the source document; executing the plurality of different queries on the document corpus in response to receiving the source document, wherein the plurality of different queries differ from one another by at least one search term, wherein individual queries of the plurality of different queries produce a respective list of documents that identifies at least some of the plurality of reference documents of the document corpus, wherein the respective reference documents of the respective lists of documents are scored at least in part with respect to the source document; based, at least in part, on scores for the reference documents from at least two of the respective lists, selecting one or more of the reference documents having a respective score that meets a score threshold as potential duplicates of the same received source document that initiated the routine; and storing an identification of the one or more potential duplicate documents. 8. The method of claim 1 , wherein the score threshold is a relative score threshold applied to a collection of the identified reference documents. | 0.846875 |
5,467,425 | 7 | 8 | 7. The method of claim 5, further comprising the step of (6a) immediately following step (6), searching all memory locations representing all of said n-grams which are not previously classified to determine an additional complement count for each of one or more additional putative classes, said one or more additional putative classes being the classes that can possibly exist based upon the last (n-x) words of all of the n-grams not previously classified, x being equal to 2 the first time step (6a) is executed and increased by one each additional execution of step (6a), each putative class having one or more of the not previously classified n-grams having the same last (n-x) words, said additional complement count to be stored in an additional complement count memory location; | 7. The method of claim 5, further comprising the step of (6a) immediately following step (6), searching all memory locations representing all of said n-grams which are not previously classified to determine an additional complement count for each of one or more additional putative classes, said one or more additional putative classes being the classes that can possibly exist based upon the last (n-x) words of all of the n-grams not previously classified, x being equal to 2 the first time step (6a) is executed and increased by one each additional execution of step (6a), each putative class having one or more of the not previously classified n-grams having the same last (n-x) words, said additional complement count to be stored in an additional complement count memory location; 8. The method of claim 7, further comprising the step of (6b) immediately following step (6a), comparing the additional complement count for a given putative class of said one or more additional putative classes with a value located in an additional predetermined memory location representing an additional threshold value, if said additional complement count is greater than said additional threshold value identify said additional complement count with a second additional class count memory location representing said additional complement count for said given putative class, said given putative class is determined to be a class if its complement count is greater than said additional threshold value; | 0.5 |
9,679,568 | 1 | 11 | 1. A computer-implemented method comprising: providing, by a dialog engine of a computing device, an answer to a question; after providing the answer to the question, receiving, by the dialog engine, a voice input; determining, by the dialog engine, that the received voice input is classified as feedback that indicates satisfaction or dissatisfaction with the provided answer to the question; identifying, by the dialog engine, a predetermined feedback score that reflects an extent to which, in response to other questions, other users express satisfaction or dissatisfaction when speaking a particular term that is included in the received voice input; adjusting, based at least on the predetermined feedback score that is associated with a transcription of the received voice input, a confidence score that, based on prior selections of the provided answer to the question by other users, indicates an estimation of relevance of the provided answer to the question; and in response to a subsequent receipt of the question, selecting, by the answer generation engine, the answer or a different answer based at least on the adjusted confidence score. | 1. A computer-implemented method comprising: providing, by a dialog engine of a computing device, an answer to a question; after providing the answer to the question, receiving, by the dialog engine, a voice input; determining, by the dialog engine, that the received voice input is classified as feedback that indicates satisfaction or dissatisfaction with the provided answer to the question; identifying, by the dialog engine, a predetermined feedback score that reflects an extent to which, in response to other questions, other users express satisfaction or dissatisfaction when speaking a particular term that is included in the received voice input; adjusting, based at least on the predetermined feedback score that is associated with a transcription of the received voice input, a confidence score that, based on prior selections of the provided answer to the question by other users, indicates an estimation of relevance of the provided answer to the question; and in response to a subsequent receipt of the question, selecting, by the answer generation engine, the answer or a different answer based at least on the adjusted confidence score. 11. The method of claim 1 , wherein the subsequent receipt of the question is based on a question that originated with a user that is different than the user that originated the received voice input. | 0.823894 |
8,861,891 | 1 | 3 | 1. A method for segmenting an image, comprising: registering an annotated template image to an acquired reference image using only rigid transformations to define a transformation function relating the annotated template image to the acquired reference image; refining the defined transformation function by registering the annotated template image to the acquired reference image using only the rigid transformations and scaling in which scale is held equal for x, y, and z axes; further refining the refined transformation function by registering the annotated template image to the acquired reference image using only multi-affine transformations, wherein the step of further refining using only multi-affine transformations is divided into multiple registration steps wherein at each successive step thereof, registration is iterated by including additional transformation centers such that a number of transformation centers used during each successive registration step progressively increases; and still further refining the twice refined transformation function by registering the annotated template image to the acquired reference image using deformation transformations. | 1. A method for segmenting an image, comprising: registering an annotated template image to an acquired reference image using only rigid transformations to define a transformation function relating the annotated template image to the acquired reference image; refining the defined transformation function by registering the annotated template image to the acquired reference image using only the rigid transformations and scaling in which scale is held equal for x, y, and z axes; further refining the refined transformation function by registering the annotated template image to the acquired reference image using only multi-affine transformations, wherein the step of further refining using only multi-affine transformations is divided into multiple registration steps wherein at each successive step thereof, registration is iterated by including additional transformation centers such that a number of transformation centers used during each successive registration step progressively increases; and still further refining the twice refined transformation function by registering the annotated template image to the acquired reference image using deformation transformations. 3. The method of claim 1 , wherein further refining the refined transformation function by registering the annotated template image to the acquired reference image using only rigid, rigid and scaling, and multi-affine transformations includes: refining the transformation function by registering the annotated template image to the acquired reference image using only two points of rotation; refining the transformation function by registering the annotated template image to the acquired reference image using only three points of rotation after the refining using only the two points of rotation; and refining the transformation function by registering the annotated template image to the acquired reference image using four or more points of rotation after the refining using only the three points of rotation. | 0.5 |
8,712,188 | 2 | 8 | 2. A method as in claim 1 , wherein binarizing each subimage comprises: performing Otsu's thresholding algorithm to determine a threshold for binarization; detecting if a subimage is blank; detecting when a subimage includes light text on a dark background; and detecting if a subimage has varying background and foreground. | 2. A method as in claim 1 , wherein binarizing each subimage comprises: performing Otsu's thresholding algorithm to determine a threshold for binarization; detecting if a subimage is blank; detecting when a subimage includes light text on a dark background; and detecting if a subimage has varying background and foreground. 8. A method as in claim 2 , wherein detecting when a subimage includes light text on a dark background comprises: determining probabilities of finding pixels lower than and higher than the threshold for binarization; detecting that the subimage includes light text on a dark background when the probability of finding pixels lower than the threshold is higher than the probability of finding pixels higher than the threshold. | 0.5 |
9,201,928 | 9 | 10 | 9. The computer-implemented method of claim 5 , wherein determining a quality score for the review based on the product review data comprises: determining a first sentiment score for the review, the first sentiment score indicative of a type and a magnitude of a sentiment expressed in the review; determining a second sentiment score for the product review data, the second sentiment score indicative of a type and a magnitude of a sentiment expression in the product review data; and determining the quality score based at least in part on the first sentiment score and the second sentiment score. | 9. The computer-implemented method of claim 5 , wherein determining a quality score for the review based on the product review data comprises: determining a first sentiment score for the review, the first sentiment score indicative of a type and a magnitude of a sentiment expressed in the review; determining a second sentiment score for the product review data, the second sentiment score indicative of a type and a magnitude of a sentiment expression in the product review data; and determining the quality score based at least in part on the first sentiment score and the second sentiment score. 10. The computer-implemented method of claim 9 , wherein the quality score is determined based at least in part on a difference between the first sentiment score and the second sentiment score. | 0.5 |
10,027,796 | 1 | 7 | 1. A computer-implemented method of creating a smart reminder, comprising: receiving a user input on a device; processing the user input, comprising: identifying one or more entities associated with the user input, wherein at least one entity is associated with a person; and identifying an action by semantically evaluating the user input to determine a user intention; based at least in part on the processed user input, automatically generating the smart reminder to perform the action; detecting at least one triggering event associated with the smart reminder, wherein detecting the triggering event comprises detecting the person; and based on detecting the at least one triggering event, providing the smart reminder on a display of the device. | 1. A computer-implemented method of creating a smart reminder, comprising: receiving a user input on a device; processing the user input, comprising: identifying one or more entities associated with the user input, wherein at least one entity is associated with a person; and identifying an action by semantically evaluating the user input to determine a user intention; based at least in part on the processed user input, automatically generating the smart reminder to perform the action; detecting at least one triggering event associated with the smart reminder, wherein detecting the triggering event comprises detecting the person; and based on detecting the at least one triggering event, providing the smart reminder on a display of the device. 7. The method of claim 1 , wherein the at least one triggering event is an incoming text from the person, and wherein the smart reminder is displayed in response to detecting the incoming text. | 0.741287 |
6,134,540 | 21 | 25 | 21. A method implemented in a query system, the method comprising: providing a query engine having a capability to build objects in a memory based upon a view type referenced in a query received from an application; and applying query rewrite optimizations to the query referencing the view type, wherein the query rewrite optimizations determine which portions of the query to push down to a database at a second tier for resolution and which portions of the query are to be processed by the query engine at a first tier to build objects from the view types. | 21. A method implemented in a query system, the method comprising: providing a query engine having a capability to build objects in a memory based upon a view type referenced in a query received from an application; and applying query rewrite optimizations to the query referencing the view type, wherein the query rewrite optimizations determine which portions of the query to push down to a database at a second tier for resolution and which portions of the query are to be processed by the query engine at a first tier to build objects from the view types. 25. The method of claim 21 wherein the step of applying query rewrite optimizations further comprises: analyzing the query to determine if the query requests a handle on an object, or if the query references a method, or if the query raises a collation sequence issue. | 0.668317 |
6,163,852 | 10 | 12 | 10. An apparatus for receiving data from a synchronous random access memory, comprising: a data input for receiving a stream of data from the synchronous random access memory, which adheres to the SyncLink interface standard; a data clock input for receiving a data clock signal from the synchronous random access memory for clocking the stream of data; a first memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the first memory register including a plurality of separately-clocked data words; a second memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the second memory register including a plurality of separately-clocked data words; a first system register for receiving data from the first memory register, the first system register being clocked by a system clock signal, which is slower than the data clock signal; a second system register, that is clocked by the system clock signal, for receiving data from the second memory register; and a controller for coordinating actions of the first and second memory registers as well as the first and second system registers so that data is loaded into the second memory register by the data clock signal while data is being loaded into the first system register by the system clock signal and, during alternate cycles, so that data is loaded into the first memory register by the data clock signal while data is being loaded into the second system register by the system clock signal, and wherein the controller is configured to sequentially clock the stream of data into successive words in the plurality of separately-clocked data words in the first memory register and the second memory register. | 10. An apparatus for receiving data from a synchronous random access memory, comprising: a data input for receiving a stream of data from the synchronous random access memory, which adheres to the SyncLink interface standard; a data clock input for receiving a data clock signal from the synchronous random access memory for clocking the stream of data; a first memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the first memory register including a plurality of separately-clocked data words; a second memory register, that is clocked by the data clock signal, for receiving data from the stream of data, the second memory register including a plurality of separately-clocked data words; a first system register for receiving data from the first memory register, the first system register being clocked by a system clock signal, which is slower than the data clock signal; a second system register, that is clocked by the system clock signal, for receiving data from the second memory register; and a controller for coordinating actions of the first and second memory registers as well as the first and second system registers so that data is loaded into the second memory register by the data clock signal while data is being loaded into the first system register by the system clock signal and, during alternate cycles, so that data is loaded into the first memory register by the data clock signal while data is being loaded into the second system register by the system clock signal, and wherein the controller is configured to sequentially clock the stream of data into successive words in the plurality of separately-clocked data words in the first memory register and the second memory register. 12. The method of claim 10, wherein the plurality of separately-clocked data words in the first memory register and the plurality of separately-clocked data words from the second memory register are coupled to a plurality of word disable signals from the controller that work in concert with the data clock signal to provide the sequential clocking, the plurality of word disable signals being generated by the controller in response to changes in the data clock signal. | 0.748394 |
9,697,239 | 10 | 11 | 10. The system of claim 7 , wherein the operations further comprise: converting text of a database request into the sequence of tokens and an unknown word; and generating the execution tree based on the sequence of tokens and the unknown word, a node of the execution tree being associated with the unknown word. | 10. The system of claim 7 , wherein the operations further comprise: converting text of a database request into the sequence of tokens and an unknown word; and generating the execution tree based on the sequence of tokens and the unknown word, a node of the execution tree being associated with the unknown word. 11. The system of claim 10 , wherein the operations further comprise executing one or more nodes of the execution tree associated with inserting a token into the token database. | 0.5 |
7,970,598 | 12 | 16 | 12. A method for conversing in a plurality of languages, comprising: establishing a plurality of real-time conference areas wherein each real-time conference area supports a language and is operated in parallel with the other conference areas such that each conference area contains the same messages in the same order, said plurality of real-time conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to the other conference areas; posting a first message from a first user onto a first of said plurality of real-time conference areas for access by a plurality of computer users currently connected to said first of said plurality of real-time conference areas based on a specified preference for a first language, said first message in said first language and originating from a spoken communication; automatically determining that said first message posted to said first real-time conference area is untranslated; automatically translating said first message into a second language after determining said first message is untranslated; automatically posting said translated message to a second of said real-time conference areas for access by a plurality of computer users currently connected to said second of said plurality of real-time conference areas based on a specified preference for said second language; posting a response to said translated message onto said second of said plurality of real-time conference areas for access by said plurality of users currently connected to said second of said plurality of real-time conference areas, said response in said second language and originating from a spoken communication; automatically determining that said response posted to said second real-time conference area is untranslated; automatically translating said response into said first language after determining said response is untranslated; and automatically posting said translated response in said first language onto said first real-time conference area for access by said plurality of computer users currently connect to said first real-time conference area. | 12. A method for conversing in a plurality of languages, comprising: establishing a plurality of real-time conference areas wherein each real-time conference area supports a language and is operated in parallel with the other conference areas such that each conference area contains the same messages in the same order, said plurality of real-time conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to the other conference areas; posting a first message from a first user onto a first of said plurality of real-time conference areas for access by a plurality of computer users currently connected to said first of said plurality of real-time conference areas based on a specified preference for a first language, said first message in said first language and originating from a spoken communication; automatically determining that said first message posted to said first real-time conference area is untranslated; automatically translating said first message into a second language after determining said first message is untranslated; automatically posting said translated message to a second of said real-time conference areas for access by a plurality of computer users currently connected to said second of said plurality of real-time conference areas based on a specified preference for said second language; posting a response to said translated message onto said second of said plurality of real-time conference areas for access by said plurality of users currently connected to said second of said plurality of real-time conference areas, said response in said second language and originating from a spoken communication; automatically determining that said response posted to said second real-time conference area is untranslated; automatically translating said response into said first language after determining said response is untranslated; and automatically posting said translated response in said first language onto said first real-time conference area for access by said plurality of computer users currently connect to said first real-time conference area. 16. The method of claim 12 wherein automatically translating said first message into a second language comprises forwarding said first message to a translation queue, removing said first message from said queue and translating said first message, and formatting said translated message for posting at said second real-time conference area. | 0.741616 |
7,694,226 | 1 | 3 | 1. A method for operating an electronic system adapted to process content data files to form a work of communication; receiving instructions from an author of the work of communication including a designation of a set of content data files and a selection of an output form for the work of communication; accessing the designated content data files; determining narrative content from the content data files based upon the selected output form; determining context indicators from the content data files based upon a contextual framework of rules for identifying context indicators; determining inference queries based upon the context indicators and a knowledge base for a person associated with the work of communication; obtaining context data files from a source of content data files using the inference queries; and, prioritizing obtained context data files based upon the significance of the context data file relative to the associated person and providing content data files that have an assigned priority that is greater than a threshold priority for integration with the determined narrative content to form a work of communication; wherein said context data files comprise content data files that are not limited to the designated set of content data files. | 1. A method for operating an electronic system adapted to process content data files to form a work of communication; receiving instructions from an author of the work of communication including a designation of a set of content data files and a selection of an output form for the work of communication; accessing the designated content data files; determining narrative content from the content data files based upon the selected output form; determining context indicators from the content data files based upon a contextual framework of rules for identifying context indicators; determining inference queries based upon the context indicators and a knowledge base for a person associated with the work of communication; obtaining context data files from a source of content data files using the inference queries; and, prioritizing obtained context data files based upon the significance of the context data file relative to the associated person and providing content data files that have an assigned priority that is greater than a threshold priority for integration with the determined narrative content to form a work of communication; wherein said context data files comprise content data files that are not limited to the designated set of content data files. 3. The method of claim 1 , wherein the step of determining narrative content comprises determining narrative content from the set of content data files based upon the type of work of communication that has been designated. | 0.814691 |
7,735,026 | 21 | 25 | 21. The computer program product of claim 17 further comprising instructions to select an interface that includes a screen saver interface option to open a dialogue box having an option to provide a link to a dialogue box comprising screen saver options. | 21. The computer program product of claim 17 further comprising instructions to select an interface that includes a screen saver interface option to open a dialogue box having an option to provide a link to a dialogue box comprising screen saver options. 25. The computer program product of claim 21 , further comprising instructions to select an interface that includes a screen saver interface option to select from at least one available poet personality. | 0.5 |
7,962,555 | 13 | 14 | 13. The system of claim 8 , wherein said program code for determining whether said sub-thread is off-topic comprises: program code for determining tag rankings of said user-defined tags, said system generated tags, and said moderator-promoted tags; program code for determining a conjunctiveness score of said selected post with respect to its parent topic post in said discussion thread responsive to tags associated with said selected post, said parent topic post and said tag rankings; and program code for determining that said sub-thread is off-topic in the event that said conjunctiveness score is below a predetermined threshold. | 13. The system of claim 8 , wherein said program code for determining whether said sub-thread is off-topic comprises: program code for determining tag rankings of said user-defined tags, said system generated tags, and said moderator-promoted tags; program code for determining a conjunctiveness score of said selected post with respect to its parent topic post in said discussion thread responsive to tags associated with said selected post, said parent topic post and said tag rankings; and program code for determining that said sub-thread is off-topic in the event that said conjunctiveness score is below a predetermined threshold. 14. The system of claim 13 , wherein said program code for determining said tag rankings is responsive to frequency of use of said tags in said parent topic post. | 0.5 |
7,606,794 | 4 | 9 | 4. The method of claim 1 wherein: said metadata indicates a plurality of candidate non-traditional abstract links to include in an abstract for said particular resource; the step of selecting a subset of candidate items from said plurality of candidate items includes selecting a subset of the candidate non-traditional abstract links from the plurality of candidate non-traditional abstract links; and the step of generating abstracts of each of said plurality of matching resources includes generating an abstract, for said particular resource, that includes the subset of candidate non-traditional abstract links that were selected based on the search query. | 4. The method of claim 1 wherein: said metadata indicates a plurality of candidate non-traditional abstract links to include in an abstract for said particular resource; the step of selecting a subset of candidate items from said plurality of candidate items includes selecting a subset of the candidate non-traditional abstract links from the plurality of candidate non-traditional abstract links; and the step of generating abstracts of each of said plurality of matching resources includes generating an abstract, for said particular resource, that includes the subset of candidate non-traditional abstract links that were selected based on the search query. 9. The method of claim 4 wherein the plurality of candidate non-traditional abstract links includes a value added service link which, when activated, causes information to be sent to a service that is controlled by a party other than the party that controls the particular resource, wherein the information is either (a) extracted from the particular resource or (b) about the party that controls the particular resource. | 0.544372 |
7,864,989 | 28 | 29 | 28. The apparatus according to claim 21 , wherein said plurality of formulas are derived using logistic regression. | 28. The apparatus according to claim 21 , wherein said plurality of formulas are derived using logistic regression. 29. The apparatus according to claim 28 , further comprising: a similarity measurement unit for learning parameters for said plurality of formulas using logistic regression. | 0.5 |
9,565,146 | 29 | 34 | 29. A method for controlling a messenger in a first terminal, the method comprising: if a specific chat phrase associated with an answer phrase among a plurality of chat phrases in a messenger chat window is deleted when the answer phrase to the specific chat phrase in the messenger chat window is received, transmitting, to a second terminal, an acknowledgement signal including a specific value indicating deletion of the specific chat phrase; receiving a related image of the deleted specific chat phrase from the second terminal; detecting the deleted specific chat phrase from received messenger information including the answer phrase; and displaying the detected specific chat phrase and the answer phrase in the messenger chat window. | 29. A method for controlling a messenger in a first terminal, the method comprising: if a specific chat phrase associated with an answer phrase among a plurality of chat phrases in a messenger chat window is deleted when the answer phrase to the specific chat phrase in the messenger chat window is received, transmitting, to a second terminal, an acknowledgement signal including a specific value indicating deletion of the specific chat phrase; receiving a related image of the deleted specific chat phrase from the second terminal; detecting the deleted specific chat phrase from received messenger information including the answer phrase; and displaying the detected specific chat phrase and the answer phrase in the messenger chat window. 34. The method of claim 29 , further comprising: if an answer phrase to a specific chat phrase among a plurality of chat phrases in the messenger chat window is entered, displaying the entered answer phrase in a position near the specific chat phrase; transmitting, to the second terminal, messenger information including the specific chat phrase, index information of the specific chat phrase, the answer phrase to the specific chat phrase, and a phone number of the second terminal; and upon receiving from the second terminal an acknowledgement signal including a specific value indicating the deletion of the specific chat phrase, transmitting to the second terminal an image obtained by capturing the specific chat phrase, the answer phrase to the specific chat phrase, and preceding and subsequent phrases of the specific chat phrase. | 0.5 |
7,953,600 | 49 | 57 | 49. A system for speech synthesis comprising: a processor; and a storage medium having program instructions written thereon for execution on the processor, the program instructions including program instructions for: a front end module configured to receive symbolic input descriptive of an utterance to be synthesized, a back end module configured to select a portion of the utterance to be constructed from a speech unit of a speech corpus, the speech unit recorded from a human speaker, the speech unit lacking transitions at one or both of the speech unit's edges, a synthesis module configured to synthesize a transition for use at an edge of the speech unit by use of Rule-Based Speech Synthesis (RBSS) rules, and a concatenation engine of the back end module configured to concatenate the speech unit with the synthesized transition in production of a speech waveform for the utterance. | 49. A system for speech synthesis comprising: a processor; and a storage medium having program instructions written thereon for execution on the processor, the program instructions including program instructions for: a front end module configured to receive symbolic input descriptive of an utterance to be synthesized, a back end module configured to select a portion of the utterance to be constructed from a speech unit of a speech corpus, the speech unit recorded from a human speaker, the speech unit lacking transitions at one or both of the speech unit's edges, a synthesis module configured to synthesize a transition for use at an edge of the speech unit by use of Rule-Based Speech Synthesis (RBSS) rules, and a concatenation engine of the back end module configured to concatenate the speech unit with the synthesized transition in production of a speech waveform for the utterance. 57. The system of claim 49 wherein the concatenation engine is further configured to concatenate the speech unit and the synthesized transition with one or more other speech units synthesized by RBSS rules. | 0.59127 |
8,700,593 | 18 | 28 | 18. A search system for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the search system comprising: a result pipeline extending through the search system; a deterministic finite automaton (DFA) engine to store first sub-expressions that comprise strings, the DFA engine having an input to receive the input string of characters from a data pipeline, and having an output to provide a first token onto the result pipeline in response to a match with one of the first sub-expressions; a non-deterministic finite automaton (NFA) engine to store second sub-expressions having selected quantified character classes, the NFA engine having an input to selectively receive the input string of characters from the data pipeline, and having an output to provide a second token onto the result pipeline in response to a match with one of the second sub-expressions; and a token stitcher, having an input to receive the tokens from the result pipeline, to combine the tokens to generate a latch signal indicating whether the input string of characters matches the regular expression, wherein the regular expression comprises an unbounded sub-expression, and the unbounded sub-expression is delegated to the token stitcher for processing without utilizing resources of the DFA or NFA engine and wherein the DFA and NFA engines and the token stitcher are implemented by at least one processor-based computing device. | 18. A search system for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the search system comprising: a result pipeline extending through the search system; a deterministic finite automaton (DFA) engine to store first sub-expressions that comprise strings, the DFA engine having an input to receive the input string of characters from a data pipeline, and having an output to provide a first token onto the result pipeline in response to a match with one of the first sub-expressions; a non-deterministic finite automaton (NFA) engine to store second sub-expressions having selected quantified character classes, the NFA engine having an input to selectively receive the input string of characters from the data pipeline, and having an output to provide a second token onto the result pipeline in response to a match with one of the second sub-expressions; and a token stitcher, having an input to receive the tokens from the result pipeline, to combine the tokens to generate a latch signal indicating whether the input string of characters matches the regular expression, wherein the regular expression comprises an unbounded sub-expression, and the unbounded sub-expression is delegated to the token stitcher for processing without utilizing resources of the DFA or NFA engine and wherein the DFA and NFA engines and the token stitcher are implemented by at least one processor-based computing device. 28. The search system of claim 18 , wherein the token stitcher comprises: a program memory having a plurality of storage locations, each for storing a program for a corresponding token; a flag bank having a plurality of storage locations, each for storing a flag for a corresponding sub-expression; and a token stitcher engine coupled to the program memory and the flag bank, wherein the token stitcher engine is configured to selectively execute the programs in response to the tokens provided on the result pipeline. | 0.5 |
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