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1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. | 1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. 36. The method according to claim 1 , which comprises outputting the at least one application description with a plurality of application blocks. | 0.632526 |
20. The method of claim 1 , applying the second set of rules resulting in assigning respective scores to respective groups of segments, the computer determining whether the on-line bank account is a business account or utilized for business purposes based at least in part upon the respective scores for respective groups of segments. | 20. The method of claim 1 , applying the second set of rules resulting in assigning respective scores to respective groups of segments, the computer determining whether the on-line bank account is a business account or utilized for business purposes based at least in part upon the respective scores for respective groups of segments. 22. The method of claim 20 , the second set of rules comprising multiple rules that are applied to each group of segments such that multiple scores are assigned to each group of segments. | 0.773023 |
1. A method of text entry, said method comprising: selecting, by a processor of a computer system, segments of text from text documents including web pages, wherein each of the selected segments of text adheres to at least one of one or more patterns of text, wherein each of the one or more patterns specifies one or more of a range of numbers of words in phrases of text and a range of numbers of letters in words of text, and wherein at least one of the one or more patterns specifies a minimum number of words in phrases of text; said processor indexing the selected segments of text to generate a plurality of indexed segments of text that includes one or more indexed segments of text; said processor determining, an attribute of text entered by a user into an application; said processor determining an attribute of each attribute segment of the one or more indexed selected segments of text, wherein said determining the attribute of each attribute segment comprises determining a geographical location of an origin of each attribute segment; said processor matching the text entered by the user to a single portion of each attribute segment of the one or more indexed segments of text, each attribute segment consisting of the single portion and a remaining portion, wherein said matching the text entered by the user to the single portion of each attribute segment is based upon the determined geographical location of the origin of each attribute segment and a location of a computing device into which the text is entered by the user; after said matching, said processor receiving a selection of a single attribute segment selected by the user from the one or more indexed segments of text; and said processor entering into the application the remaining portion of the selected single attribute segment. | 1. A method of text entry, said method comprising: selecting, by a processor of a computer system, segments of text from text documents including web pages, wherein each of the selected segments of text adheres to at least one of one or more patterns of text, wherein each of the one or more patterns specifies one or more of a range of numbers of words in phrases of text and a range of numbers of letters in words of text, and wherein at least one of the one or more patterns specifies a minimum number of words in phrases of text; said processor indexing the selected segments of text to generate a plurality of indexed segments of text that includes one or more indexed segments of text; said processor determining, an attribute of text entered by a user into an application; said processor determining an attribute of each attribute segment of the one or more indexed selected segments of text, wherein said determining the attribute of each attribute segment comprises determining a geographical location of an origin of each attribute segment; said processor matching the text entered by the user to a single portion of each attribute segment of the one or more indexed segments of text, each attribute segment consisting of the single portion and a remaining portion, wherein said matching the text entered by the user to the single portion of each attribute segment is based upon the determined geographical location of the origin of each attribute segment and a location of a computing device into which the text is entered by the user; after said matching, said processor receiving a selection of a single attribute segment selected by the user from the one or more indexed segments of text; and said processor entering into the application the remaining portion of the selected single attribute segment. 2. The method of claim 1 , said method further comprising: after said matching, said processor determining a priority ordering for the one or more segments of the indexed selected segments of text; before said receiving the selection of the single segment, said processor displaying the one or more segments of the indexed selected segments of text to the user based upon the priority ordering. | 0.694272 |
8. A computer-implemented method, comprising: receiving a request for electronic messages associated with a specified label; and identifying electronic messages labeled using the specified label, including electronic messages having an associated verbal label corresponding to the specified label, wherein the verbal label comprises audio data representing audio input by a user, wherein the verbal label is used to identify the electronic messages and wherein the verbal label is unified with a preexisting text label for the user, wherein unifying the verbal label with the preexisting text label includes: performing speech recognition on the audio input by the user or the audio data representing the audio input from the user, matching the preexisting text label for the user to the audio input from the user or the audio data representing the audio input from the user, and labeling the electronic messages having the associated verbal label with the matching preexisting text label for the user. | 8. A computer-implemented method, comprising: receiving a request for electronic messages associated with a specified label; and identifying electronic messages labeled using the specified label, including electronic messages having an associated verbal label corresponding to the specified label, wherein the verbal label comprises audio data representing audio input by a user, wherein the verbal label is used to identify the electronic messages and wherein the verbal label is unified with a preexisting text label for the user, wherein unifying the verbal label with the preexisting text label includes: performing speech recognition on the audio input by the user or the audio data representing the audio input from the user, matching the preexisting text label for the user to the audio input from the user or the audio data representing the audio input from the user, and labeling the electronic messages having the associated verbal label with the matching preexisting text label for the user. 15. The method of claim 8 , wherein text labels in the identified messages are an N-best match to a request input by voice, where N is a number greater than one. | 0.581407 |
12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document. | 12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document. 19. A method according to claim 12 wherein generating the template document includes displaying the stored template document on a display screen and receiving an input to incorporate the chosen field into the stored template document. | 0.744723 |
7. A method comprising: maintaining a profile for a user of a social networking system, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; generating a feed that comprises a plurality of stories, wherein each of the stories comprises a description of an action performed by or related to another user of the social networking system with whom the user has established a connection; obtaining a plurality of questions associated with one or more information items, each question having a response probability indicating a likelihood of receiving a response to a question when presented, each question related to one or more stories in the feed; selecting an unknown information item from the set of unknown information items based at least in part on data acquisition values associated with each of the unknown information items; selecting a question associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more questions associated with the selected unknown information item and content of the feed; incorporating the selected question into one of the stories of the feed to which the selected question is related; and sending the feed for display to the user. | 7. A method comprising: maintaining a profile for a user of a social networking system, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; generating a feed that comprises a plurality of stories, wherein each of the stories comprises a description of an action performed by or related to another user of the social networking system with whom the user has established a connection; obtaining a plurality of questions associated with one or more information items, each question having a response probability indicating a likelihood of receiving a response to a question when presented, each question related to one or more stories in the feed; selecting an unknown information item from the set of unknown information items based at least in part on data acquisition values associated with each of the unknown information items; selecting a question associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more questions associated with the selected unknown information item and content of the feed; incorporating the selected question into one of the stories of the feed to which the selected question is related; and sending the feed for display to the user. 8. The method of claim 7 , further comprising: receiving a response to the selected question from the user; and storing the response to the selected question in the user profile as data associated with the selected unknown information item. | 0.538774 |
14. A non-transitory computer-readable medium storing instructions that, when executed by a processor on a computing device, cause the computing device to at least: receive a first transcription comprising first text and second text, wherein the first transcription was created by transcribing first audio data using a speech recognition engine configured to filter the first transcription by automatically replacing one or more words with corresponding numbers or digits formatted as a telephone number; receive a first value associated with the first text and a second confidence value associated with the second text; and cause presentation of the first text with a first graphical element indicating the first value and presentation of the second text with a second graphical element indicating the second value. | 14. A non-transitory computer-readable medium storing instructions that, when executed by a processor on a computing device, cause the computing device to at least: receive a first transcription comprising first text and second text, wherein the first transcription was created by transcribing first audio data using a speech recognition engine configured to filter the first transcription by automatically replacing one or more words with corresponding numbers or digits formatted as a telephone number; receive a first value associated with the first text and a second confidence value associated with the second text; and cause presentation of the first text with a first graphical element indicating the first value and presentation of the second text with a second graphical element indicating the second value. 15. The non-transitory computer-readable medium of claim 14 , wherein the first graphical element indicates a volume level associated with a portion of the first audio data corresponding to the first text and is presented substantially simultaneously with the presentation of the first text. | 0.526235 |
13. A method, comprising: using at least one or more processors to retrieve a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria; using a citation graph to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; using the at least one or more processors to determine an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allow for determination of expertise on any query term in real-time; using the at least one or more processors to rank the cited objects of the plurality of citations using the influence and relative expertise of the subjects; using the at least one or more processors to select objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. | 13. A method, comprising: using at least one or more processors to retrieve a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria; using a citation graph to determine an influence of each of the subjects and the objects, the citation graph including the plurality of citations each describing an opinion of an object by subject, the citation graph including nodes or entities that are 1) subjects that have an opinion or making citations, and 2) objects cited by citations relative to subjects that have opinions or make citations; using the at least one or more processors to determine an expertise of a subject as a measure of the subject's expertise in a topic relative to a larger population of multiple subjects and allow for determination of expertise on any query term in real-time; using the at least one or more processors to rank the cited objects of the plurality of citations using the influence and relative expertise of the subjects; using the at least one or more processors to select objects as the search result for the user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. 15. The method of claim 13 , further comprising: accepting and enforcing a plurality of criteria on citation searching, retrieving and ranking, each of which is either be explicitly described by a user or best guessed by the system based on internal statistical data. | 0.806358 |
1. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where executed by a processor, the computer usable code causes a computer to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. | 1. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the non-transitory computer readable storage medium, where executed by a processor, the computer usable code causes a computer to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. 3. The computer program product of claim 1 , wherein the consumer generated content is to include at least one of forum content, review content, blog content and social networking content. | 0.534021 |
1. A method comprising: receiving, by a processing device, an input of a word that is to be learned by a user; performing, by the processing device, a search for a definition of the word using a search engine, wherein performing the search for the definition of the word comprises: generating a search query for the definition of the word; and sending the search query to the search engine, wherein the search engine comprises a public search engine accessible via a network; receiving, by the processing device, one or more search results based on the search query; selecting the definition of the word from the one or more search results; prompting, by the processing device, the user to rewrite the definition; receiving, by the processing device, a user input of a new definition for the word; prompting, by the processing device, the user to select a vocabulary learning mode from a group of vocabulary learning modes comprising a story mode, an etymology mode or an image mode; receiving, by the processing device, a selection of a vocabulary learning mode from the group of vocabulary learning modes; providing, by the processing device, a user interface and one or more tools for generation of a card for study of the word, wherein the one or more tools are based on the selected vocabulary learning mode; generating the card by the processing device; and saving the card by the processing device. | 1. A method comprising: receiving, by a processing device, an input of a word that is to be learned by a user; performing, by the processing device, a search for a definition of the word using a search engine, wherein performing the search for the definition of the word comprises: generating a search query for the definition of the word; and sending the search query to the search engine, wherein the search engine comprises a public search engine accessible via a network; receiving, by the processing device, one or more search results based on the search query; selecting the definition of the word from the one or more search results; prompting, by the processing device, the user to rewrite the definition; receiving, by the processing device, a user input of a new definition for the word; prompting, by the processing device, the user to select a vocabulary learning mode from a group of vocabulary learning modes comprising a story mode, an etymology mode or an image mode; receiving, by the processing device, a selection of a vocabulary learning mode from the group of vocabulary learning modes; providing, by the processing device, a user interface and one or more tools for generation of a card for study of the word, wherein the one or more tools are based on the selected vocabulary learning mode; generating the card by the processing device; and saving the card by the processing device. 7. The method of claim 1 , wherein the selected vocabulary learning mode of the group of vocabulary learning modes is the image mode, and wherein the one or more tools comprise drawing tools for drawing a picture, the method further comprising: receiving user input to draw a digital image. | 0.680892 |
5. The text processing system of claim 4 wherein the integrator forwards said outputs to the first language dependent module and the second language dependent module as a function of associated identifiers. | 5. The text processing system of claim 4 wherein the integrator forwards said outputs to the first language dependent module and the second language dependent module as a function of associated identifiers. 6. The text processing system of claim 5 wherein the first language dependent module and the second language dependent module are adapted to perform morphological analysis. | 0.90556 |
10. A system comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory provide operations comprising: selecting a context from a plurality of contexts associated with a plurality of hierarchical software constructs, the context defining a class of content modules included in a construct of the plurality of hierarchical software constructs; retrieving context data for each content module of a plurality of content modules for each software construct of a plurality of hierarchical software constructs, the context data including a primary context identifier identifying a primary context in which the content module was created or modified, at least one secondary context identifier identifying additional secondary contexts in which the content module is permitted to be included, a restriction identifier identifying a class of contexts in which the content module may be used, and a reference count value indicating a number of times the content module is referenced in the plurality of hierarchical software constructs; determining, based on the primary and the at least one secondary context identifiers, whether each content module is permitted in the selected context; determining the reference count value as the number of times the content module is used in the plurality of hierarchical software constructs; storing the reference count value in association with the context data; identifying the content of the content module as valuable content if the reference count value exceeds a threshold value; generating a collection of content modules from the class of content modules based on the selected context, the collection including the plurality of content modules permitted in the selected context based on the determination; and storing the collection. | 10. A system comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory provide operations comprising: selecting a context from a plurality of contexts associated with a plurality of hierarchical software constructs, the context defining a class of content modules included in a construct of the plurality of hierarchical software constructs; retrieving context data for each content module of a plurality of content modules for each software construct of a plurality of hierarchical software constructs, the context data including a primary context identifier identifying a primary context in which the content module was created or modified, at least one secondary context identifier identifying additional secondary contexts in which the content module is permitted to be included, a restriction identifier identifying a class of contexts in which the content module may be used, and a reference count value indicating a number of times the content module is referenced in the plurality of hierarchical software constructs; determining, based on the primary and the at least one secondary context identifiers, whether each content module is permitted in the selected context; determining the reference count value as the number of times the content module is used in the plurality of hierarchical software constructs; storing the reference count value in association with the context data; identifying the content of the content module as valuable content if the reference count value exceeds a threshold value; generating a collection of content modules from the class of content modules based on the selected context, the collection including the plurality of content modules permitted in the selected context based on the determination; and storing the collection. 16. The system of claim 10 , further comprising: determining, based on the context data, the number of contexts associated with the content of the content module; and identifying the content of the content module as valuable content if the number of contexts associated with the content of the content module exceeds a threshold value. | 0.5 |
45. The method recited in claim 28 wherein said signal to be identified includes a video signal said video signal includes a color signal, wherein the step of extracting the feature string includes the step of determining the time interval between predetermined changes in the color signals. | 45. The method recited in claim 28 wherein said signal to be identified includes a video signal said video signal includes a color signal, wherein the step of extracting the feature string includes the step of determining the time interval between predetermined changes in the color signals. 46. The method recited in claim 45 wherein the step of determining changes in the color signal includes the step of comparing a function of the color signal with the average of the color signal and determining the time intervals when the function of the color signal exceeds the average of the color signal and the time intervals when the function of the color signal is less than the average of the color signal to extract the feature string. | 0.740646 |
8. The method of claim 7 , wherein said compiling the graphical program comprises inferring strict types for the textual language program portion. | 8. The method of claim 7 , wherein said compiling the graphical program comprises inferring strict types for the textual language program portion. 9. The method of claim 8 , wherein said inferring strict types for the textual language program portion comprises using generic data types for variables in the textual language program portion. | 0.936058 |
4. The method of claim 1 wherein the informing step includes asking the user for confirmation that the alphanumeric character and/or word is an alphanumeric character and/or word that the user intended to be determined in the determining step. | 4. The method of claim 1 wherein the informing step includes asking the user for confirmation that the alphanumeric character and/or word is an alphanumeric character and/or word that the user intended to be determined in the determining step. 7. The method of claim 4 wherein the user is in a passenger compartment of a motor vehicle, and a likelihood that the user is asked for the confirmation is inversely related to a sound level and/or a noise level in the passenger compartment. | 0.9032 |
7. The method of claim 1 , wherein obtaining updated statistics from a further store comprises: determining whether sufficiently updated statistics for compiling the first query are available from a second store or a third store comprising statistics associated with the table in the database; if sufficiently updated statistics for compiling the first query are not available from the second store or the third store, collecting the updated statistics from the database, storing the updated statistics in the second store, and retrieving the updated statistics for compiling the first query from the second store. | 7. The method of claim 1 , wherein obtaining updated statistics from a further store comprises: determining whether sufficiently updated statistics for compiling the first query are available from a second store or a third store comprising statistics associated with the table in the database; if sufficiently updated statistics for compiling the first query are not available from the second store or the third store, collecting the updated statistics from the database, storing the updated statistics in the second store, and retrieving the updated statistics for compiling the first query from the second store. 8. The method of claim 7 , wherein retrieving the updated statistics for compiling the first query from the second store comprises loading the updated statistics from the second store into the first store, and retrieving the updated statistics from the first store. | 0.789798 |
8. The computer-readable memory device of claim 1 , wherein the one more teaching animations comprises a video of a model hand properly executing the manual gesture on nondescript text. | 8. The computer-readable memory device of claim 1 , wherein the one more teaching animations comprises a video of a model hand properly executing the manual gesture on nondescript text. 9. The computer-readable memory device of claim 8 , the method further comprising: looping the play of the teaching animation for a predefined number of cycles; detecting the manual gesture applied to a portion of the display area in which the one or more launched teaching animations are playing; and incident to detecting the manual gesture, interrupting the looping of the teaching animation and hiding the display area. | 0.892331 |
11. A computer program product comprising a computer usable medium having a physical data storage unit with control logic stored therein for causing a computer to reverse engineer a program application for processing markup language documents, to reconstruct a markup language template used to generate the program application, said control logic comprising: first computer readable program code means for causing a computer to locate a start of a markup language data structure in code of the program application created using the markup language template; second computer readable program code means for causing a computer to read program lines of the program application containing the markup language data structure; third computer readable program code means for causing a computer to extract, from the program lines of the program application, (i) content fragments of markup language, and (ii) data indicating the end of a template line of the markup language template, comprised of extracted content fragments; and fourth computer readable program code means for causing a computer to assemble the markup language template by (i) concatenating the extracted content fragments, in the order of their occurrence in the program lines, into template lines, and (ii) reading out the concatenated template lines in the markup language template in accordance with the extracted data indicating the end of each template line, wherein the markup language template contains (i) a plurality of indicators present in markup language documents which are processed by the program application, and (ii) correlations between the plurality of indicators and respective descriptions of the plurality of indicators. | 11. A computer program product comprising a computer usable medium having a physical data storage unit with control logic stored therein for causing a computer to reverse engineer a program application for processing markup language documents, to reconstruct a markup language template used to generate the program application, said control logic comprising: first computer readable program code means for causing a computer to locate a start of a markup language data structure in code of the program application created using the markup language template; second computer readable program code means for causing a computer to read program lines of the program application containing the markup language data structure; third computer readable program code means for causing a computer to extract, from the program lines of the program application, (i) content fragments of markup language, and (ii) data indicating the end of a template line of the markup language template, comprised of extracted content fragments; and fourth computer readable program code means for causing a computer to assemble the markup language template by (i) concatenating the extracted content fragments, in the order of their occurrence in the program lines, into template lines, and (ii) reading out the concatenated template lines in the markup language template in accordance with the extracted data indicating the end of each template line, wherein the markup language template contains (i) a plurality of indicators present in markup language documents which are processed by the program application, and (ii) correlations between the plurality of indicators and respective descriptions of the plurality of indicators. 15. The computer program product according to claim 11 , further comprising: fifth computer readable program code means for causing a computer to extract from the program application start data indicating the start of a first portion of the data structure containing a first group of content fragments corresponding to lines of the markup language template which were repeated; sixth computer readable program code means for causing a computer to extract end data indicating the end of the first portion of the data structure; and seventh computer readable program code means for causing a computer to repeat in the reconstructed markup template all of the lines read out in connection with the first portion of the data structure. | 0.5 |
17. A method comprising: receiving a first set of data, wherein the first set of data comprises a plurality of data fields; analyzing a particular data field of the plurality of data fields to determine a particular property type of the data field; using the particular property type, at least in part, to generate a database schema; storing the first set of data in a secondary data store using the database schema; wherein the method is performed using one or more processors. | 17. A method comprising: receiving a first set of data, wherein the first set of data comprises a plurality of data fields; analyzing a particular data field of the plurality of data fields to determine a particular property type of the data field; using the particular property type, at least in part, to generate a database schema; storing the first set of data in a secondary data store using the database schema; wherein the method is performed using one or more processors. 19. The method of claim 17 , wherein the first set of data is formatted in a JavaScript Object Notation (JSON) format. | 0.887264 |
7. A system for validating EDI documents comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: provide an inventory of all rules, the inventory including a common set of rules for a plurality of entities; dynamically adjust the inventory of all rules based upon entity specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; create a rules analyzer to analyze content of the plurality of companion guides and to build an organizer of companion guide rules; employ the organizer of companion guide rules to add companion guide rules to the inventory of all rules; create a profiles engine to create a respective, current rule set for each of said plurality of entities; create a companion guide profile for each of the plurality of entities where each companion guide profile indicates that entity's companion guide rules and provides pointers to the rules in the inventory of all rules that are associated with the respective, current rule set of that entity, and create a runtime checker engine to validate an EDI document by comparing the EDI document to the respective, current rule set associated with a corresponding one of the plurality of entities, by forwarding the EDI document to the corresponding one of the plurality of entities if the EDI document matches its current rule set, wherein the EDI document is validated and by returning the EDI document to a sender if the EDI document does not match the respective, current rule set, wherein the EDI document is invalidated. | 7. A system for validating EDI documents comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: provide an inventory of all rules, the inventory including a common set of rules for a plurality of entities; dynamically adjust the inventory of all rules based upon entity specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; create a rules analyzer to analyze content of the plurality of companion guides and to build an organizer of companion guide rules; employ the organizer of companion guide rules to add companion guide rules to the inventory of all rules; create a profiles engine to create a respective, current rule set for each of said plurality of entities; create a companion guide profile for each of the plurality of entities where each companion guide profile indicates that entity's companion guide rules and provides pointers to the rules in the inventory of all rules that are associated with the respective, current rule set of that entity, and create a runtime checker engine to validate an EDI document by comparing the EDI document to the respective, current rule set associated with a corresponding one of the plurality of entities, by forwarding the EDI document to the corresponding one of the plurality of entities if the EDI document matches its current rule set, wherein the EDI document is validated and by returning the EDI document to a sender if the EDI document does not match the respective, current rule set, wherein the EDI document is invalidated. 11. The system of claim 7 , wherein when creating a profiles engine to create a respective, current rule set for each of said plurality of entities, wherein the memory further store computer usable program code executed by the processor to: create the respective, current rule set for each of the plurality of entities the first time a corresponding companion guide profile is accessed during validating the EDI document associated with that entity, wherein the respective, current rule set is used subsequently each additional time that the corresponding companion guide profile is accessed. | 0.642427 |
7. The method of claim 1 wherein the one or more instructions are interpreted by a transcoding engine component of a computing device configured for transcoding web pages to a target format. | 7. The method of claim 1 wherein the one or more instructions are interpreted by a transcoding engine component of a computing device configured for transcoding web pages to a target format. 8. The method of claim 7 wherein the web site comprises an e-commerce web site and some of the web pages are for conducting a transaction. | 0.907108 |
12. A system including memory and one or more processors operable to execute instructions, stored in the memory, including instructions to: receive a sequence of one or more characters entered into a search field on a computing device, wherein the sequence of characters represents a first partial query; provide a first list of query completions for the first partial query for display on the computing device; receive one or more additional characters entered into the search field upon display of the first list, wherein the sequence of characters and the additional characters cumulatively represent a second partial query; obtain a second list of query completions for the second partial query; identify, for each of one or more query completions in the second list, an initial ranking score for the query completion for the second partial query; identify one or more query completions in the second list that appear in the first list; calculate demotion scores for the identified query completions, wherein a demotion score for a particular identified query completion is a function of both: the initial ranking score for the particular identified query completion, and a value that is based on a period of time between when the first list was displayed and when the additional characters were entered; use the demotion scores to demote one or more of the identified query completions to a lesser position within the second list, thereby forming a refined second list; and provide the refined second list of query completions for the second list of query completions for display on the computing device. | 12. A system including memory and one or more processors operable to execute instructions, stored in the memory, including instructions to: receive a sequence of one or more characters entered into a search field on a computing device, wherein the sequence of characters represents a first partial query; provide a first list of query completions for the first partial query for display on the computing device; receive one or more additional characters entered into the search field upon display of the first list, wherein the sequence of characters and the additional characters cumulatively represent a second partial query; obtain a second list of query completions for the second partial query; identify, for each of one or more query completions in the second list, an initial ranking score for the query completion for the second partial query; identify one or more query completions in the second list that appear in the first list; calculate demotion scores for the identified query completions, wherein a demotion score for a particular identified query completion is a function of both: the initial ranking score for the particular identified query completion, and a value that is based on a period of time between when the first list was displayed and when the additional characters were entered; use the demotion scores to demote one or more of the identified query completions to a lesser position within the second list, thereby forming a refined second list; and provide the refined second list of query completions for the second list of query completions for display on the computing device. 17. The system of claim 12 , further comprising instructions to: receive one or more further characters entered into the search field upon display of the refined second list, wherein the second partial query and the further characters represent a third partial query; obtain a third list of query completions for the third partial query; identify one or more query completions in the third list that appear in the refined second list; calculate demotion scores for the identified query completions in the third list, wherein a demotion score for a given identified query completion in the third list is based at least in part on a second period of time between when the refined second list was displayed and when the further characters were entered; use the demotion scores for the identified completions in the third list to demote one or more of the identified query completions to a lesser position in the third list, thereby forming a refined third list; and provide the refined third list of query completions for display on the computing device. | 0.5 |
1. A computer-implemented system, comprising: an annotation component configured to receive, from a client device via a network, a first annotation of a data source, wherein the first annotation comprises an association of a first global term with data for the data source; a data store configured to store the first annotation; an interface component configured to render the data based on the first annotation in response to a request for the data and further configured to receive a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; and an analysis component configured to determine, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary. | 1. A computer-implemented system, comprising: an annotation component configured to receive, from a client device via a network, a first annotation of a data source, wherein the first annotation comprises an association of a first global term with data for the data source; a data store configured to store the first annotation; an interface component configured to render the data based on the first annotation in response to a request for the data and further configured to receive a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; and an analysis component configured to determine, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary. 7. The computer-implemented system of claim 1 , wherein the computer implemented system is accessed by a client over a public network, including the world wide web. | 0.864086 |
22. A non-transitory computer readable storage medium having stored thereon instructions that when executed by one or more processors, cause the one or more processors to perform: determining augmentations in response to identifying a context of a user device, each of augmentations associated with one of physical venues including a certain physical venue; grouping the augmentations into clusters, each cluster representing one of the physical venues; deriving information for the clusters, the information indicative of conceptual representations of the clusters reflecting the augmentations grouped in the clusters, wherein the information includes concept descriptions of the augmentations grouped in the clusters, the concept descriptions based on properties of the augmentations grouped in the clusters, and wherein the concept descriptions are indicative of at least a look of the conceptual representations as determined by the properties of the augmentations; and rendering the clusters based on the information, wherein the rendering the clusters based on the information comprises rendering a certain cluster of the clusters associated with the certain physical venue based on a combination of augmentations grouped into the certain cluster, wherein the certain cluster further comprises at least one lower-level cluster rendered based on the properties of a subset of the combination of augmentations grouped into the certain cluster. | 22. A non-transitory computer readable storage medium having stored thereon instructions that when executed by one or more processors, cause the one or more processors to perform: determining augmentations in response to identifying a context of a user device, each of augmentations associated with one of physical venues including a certain physical venue; grouping the augmentations into clusters, each cluster representing one of the physical venues; deriving information for the clusters, the information indicative of conceptual representations of the clusters reflecting the augmentations grouped in the clusters, wherein the information includes concept descriptions of the augmentations grouped in the clusters, the concept descriptions based on properties of the augmentations grouped in the clusters, and wherein the concept descriptions are indicative of at least a look of the conceptual representations as determined by the properties of the augmentations; and rendering the clusters based on the information, wherein the rendering the clusters based on the information comprises rendering a certain cluster of the clusters associated with the certain physical venue based on a combination of augmentations grouped into the certain cluster, wherein the certain cluster further comprises at least one lower-level cluster rendered based on the properties of a subset of the combination of augmentations grouped into the certain cluster. 25. The non-transitory computer readable storage medium of claim 22 , wherein the rendered clusters comprise a simplified representation of the augmentations in a given cluster. | 0.670624 |
17. A computer program product for differential dynamic content delivery, the computer program product comprising: a non-transitory recording medium; means, recorded on the recording medium, for providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for identifying a recording period within a presentation session; means, recorded on the recording medium, for recording, during the recording period, a first presentation control instruction; means, recorded on the recording medium, for selecting from the session structured document a first classified structural element in dependence upon the recorded first presentation control instruction and in dependence upon user classifications of a first user participant in the presentation; means, recorded on the recording medium, for presenting the first classified structural element to the first user on a first display device; selecting from the session structured document a second classified structural element in dependence upon a second presentation control instruction and in dependence upon user classifications of a second user participant in the presentation; and presenting the second classified structural element to the second user on a second display device. | 17. A computer program product for differential dynamic content delivery, the computer program product comprising: a non-transitory recording medium; means, recorded on the recording medium, for providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; means, recorded on the recording medium, for identifying a recording period within a presentation session; means, recorded on the recording medium, for recording, during the recording period, a first presentation control instruction; means, recorded on the recording medium, for selecting from the session structured document a first classified structural element in dependence upon the recorded first presentation control instruction and in dependence upon user classifications of a first user participant in the presentation; means, recorded on the recording medium, for presenting the first classified structural element to the first user on a first display device; selecting from the session structured document a second classified structural element in dependence upon a second presentation control instruction and in dependence upon user classifications of a second user participant in the presentation; and presenting the second classified structural element to the second user on a second display device. 19. The computer program product of claim 17 wherein means, recorded on the recording medium, for identifying a recording period within a presentation session further comprises means, recorded on the recording medium, for logging on by the first user during the presentation session. | 0.527679 |
4. A method according to claim 1 , further comprising: automatically assigning query tags from the query tag database to user queries from a new call routing application. | 4. A method according to claim 1 , further comprising: automatically assigning query tags from the query tag database to user queries from a new call routing application. 6. A method according to claim 4 , wherein the new call routing application is in a vertical domain represented in the user query corpuses, and wherein the assigned query tags are obtained by intersecting the query tags in the query tag database with the user queries in the user query corpuses in the vertical domain of the new call routing application. | 0.841584 |
24. The computer-readable medium of claim 15 , further comprising training the first and second Bayesian networks based on real movement trajectories during multiple iterations of the gesture. | 24. The computer-readable medium of claim 15 , further comprising training the first and second Bayesian networks based on real movement trajectories during multiple iterations of the gesture. 25. The computer-readable medium of claim 24 , wherein the training the first and second Bayesian networks comprises aligning accelerometer timeseries data for each real movement trajectory. | 0.936262 |
62. The computerized information and display apparatus of claim 61 , further configured to, based at least on the data uniquely identifying the portable radio frequency device, cause enablement of one or more functions within the transport device. | 62. The computerized information and display apparatus of claim 61 , further configured to, based at least on the data uniquely identifying the portable radio frequency device, cause enablement of one or more functions within the transport device. 66. The computerized information and display apparatus of claim 62 , wherein the radio frequency apparatus comprises at least one computer program configured to, when executed, decode at least a portion of an encoded transmission from the portable radio frequency device in order to obtain the data uniquely identifying the portable radio frequency device, the encoding of the transmission performed at least in part to hide or make secret at least a portion of the data uniquely identifying the portable radio frequency device. | 0.940107 |
1. A computing device having a screen and computer-readable storage media having instructions stored thereon that, if executed by the computing device, cause the computing device to perform a method comprising: presenting one or more controls on the screen, at least one of the controls being a moving-input control; receiving a handwriting stroke made to the screen; generating a bounded rectangle around at least a first portion of the handwriting stroke made to the screen; comparing an area within the bounded rectangle to an area associated with the moving-input control to determine if the area within the bounded rectangle overlaps the area associated with the moving-input control; selecting, without user interaction independent of the handwriting stroke received and while in a mode permitting the handwriting stroke to be interpreted as text, the moving-input control when the area within the bounded rectangle overlaps the area associated with the moving-input control; and interpreting the handwriting stroke as input to the selected moving-input control. | 1. A computing device having a screen and computer-readable storage media having instructions stored thereon that, if executed by the computing device, cause the computing device to perform a method comprising: presenting one or more controls on the screen, at least one of the controls being a moving-input control; receiving a handwriting stroke made to the screen; generating a bounded rectangle around at least a first portion of the handwriting stroke made to the screen; comparing an area within the bounded rectangle to an area associated with the moving-input control to determine if the area within the bounded rectangle overlaps the area associated with the moving-input control; selecting, without user interaction independent of the handwriting stroke received and while in a mode permitting the handwriting stroke to be interpreted as text, the moving-input control when the area within the bounded rectangle overlaps the area associated with the moving-input control; and interpreting the handwriting stroke as input to the selected moving-input control. 7. The device of claim 1 , wherein the bounded rectangle is generated using a bounding-type algorithm. | 0.636364 |
1. A method for dynamic document retention in a multi-owner environment that includes a document management system, comprising: registering, by a processor, in a retention service, a plurality of document owners as owners of a same document; registering, by the processor, in a plug-in registry, as registered retention policies, different document retention policies related to the same document, the different document retention policies being managed, defined, and provided by the plurality of document owners; triggering, by the processor, a retrieval, from at least one of the plurality of document owners, of an update to at least one of the registered retention policies, which is registered in the plug-in registry, wherein the update includes at least whether the same document is still needed by the at least one of the plurality of document owners or whether the same document may be deleted; modifying, by the processor, in the retention service, when the update is that the same document may be deleted, document owners registered as owners of the same document by deleting the at least one of the plurality of owners as a registered owner of the same document, and adjusting downward a document-owner-count for the same document that counts the document owners; and performing, by the processor, a first determination, based on the document-owner-count, as to whether there is at least one document owner of the same document, and when the first determination is that there is not at least one owner of the same document, deleting or archiving or moving to a recycle bin, by the processor, the same document, otherwise performing, by the processor, a second determination as to whether each of the owner-defined document retention policies which are registered for the at least one document owner of the same document separately confirms that the same document can be deleted or archived or moved to the recycle bin, and when the second determination is that each of the owner-defined document retention policies which are registered for the at least one document owner of the same document does confirm that the same document can be deleted or archived or moved to the recycle bin, deleting or archiving or moving to the recycle bin, by the processor, the same document, otherwise performing, by the processor, a third determination as to whether an override document retention policy assigned to the same document requires the same document to be archived or deleted or moved to the recycle bin, and when the third determination is that an override document retention policy assigned to the same document does require the same document to be archived or deleted or moved to the recycle bin, deleting, archiving, or moving to the recycle bin, by the processor, the same document, wherein: the retention service and the plug-in registry are part of a document management system, and the document retention policies managed, defined, and provided by the plurality of document owners may be responsive to events occurring internal to the document management system, to events occurring external to the document management system, and to timing. | 1. A method for dynamic document retention in a multi-owner environment that includes a document management system, comprising: registering, by a processor, in a retention service, a plurality of document owners as owners of a same document; registering, by the processor, in a plug-in registry, as registered retention policies, different document retention policies related to the same document, the different document retention policies being managed, defined, and provided by the plurality of document owners; triggering, by the processor, a retrieval, from at least one of the plurality of document owners, of an update to at least one of the registered retention policies, which is registered in the plug-in registry, wherein the update includes at least whether the same document is still needed by the at least one of the plurality of document owners or whether the same document may be deleted; modifying, by the processor, in the retention service, when the update is that the same document may be deleted, document owners registered as owners of the same document by deleting the at least one of the plurality of owners as a registered owner of the same document, and adjusting downward a document-owner-count for the same document that counts the document owners; and performing, by the processor, a first determination, based on the document-owner-count, as to whether there is at least one document owner of the same document, and when the first determination is that there is not at least one owner of the same document, deleting or archiving or moving to a recycle bin, by the processor, the same document, otherwise performing, by the processor, a second determination as to whether each of the owner-defined document retention policies which are registered for the at least one document owner of the same document separately confirms that the same document can be deleted or archived or moved to the recycle bin, and when the second determination is that each of the owner-defined document retention policies which are registered for the at least one document owner of the same document does confirm that the same document can be deleted or archived or moved to the recycle bin, deleting or archiving or moving to the recycle bin, by the processor, the same document, otherwise performing, by the processor, a third determination as to whether an override document retention policy assigned to the same document requires the same document to be archived or deleted or moved to the recycle bin, and when the third determination is that an override document retention policy assigned to the same document does require the same document to be archived or deleted or moved to the recycle bin, deleting, archiving, or moving to the recycle bin, by the processor, the same document, wherein: the retention service and the plug-in registry are part of a document management system, and the document retention policies managed, defined, and provided by the plurality of document owners may be responsive to events occurring internal to the document management system, to events occurring external to the document management system, and to timing. 12. The method of claim 1 , wherein: the triggering of the retrieval of the update to at least one of the registered retention policies, as a push mechanism, is by the at least one of the plurality of document owners. | 0.578891 |
1. A computer implemented method comprising: obtaining metadata for a document, wherein the metadata includes a sequence of terms; assigning a tag to each term in the sequence of terms based at least in part on grammatical relationships between the terms, resulting in a corresponding sequence of tags; determining that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags; in response to the determination, storing the sequence of terms as a query suggestion within a database of query suggestions; in response to the determination, further calculating a suggestion score for the query suggestion based on one or more data points, and wherein storing the query suggestion includes storing the suggestion score with the query suggestion; receiving a partial search query; selecting one or more query suggestions in the database for the partial search query based at least in part on the suggestion scores; and sending the selected query suggestions in response to receiving the partial search query; wherein obtaining metadata for the document comprises segmenting the metadata for the document into a plurality of sequences of terms, wherein at least two of the plurality of sequences include at least some identical terms in different orders; and wherein assigning a tag comprises assigning a tag to each term in a given sequence of terms in the plurality of sequences of terms. | 1. A computer implemented method comprising: obtaining metadata for a document, wherein the metadata includes a sequence of terms; assigning a tag to each term in the sequence of terms based at least in part on grammatical relationships between the terms, resulting in a corresponding sequence of tags; determining that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags; in response to the determination, storing the sequence of terms as a query suggestion within a database of query suggestions; in response to the determination, further calculating a suggestion score for the query suggestion based on one or more data points, and wherein storing the query suggestion includes storing the suggestion score with the query suggestion; receiving a partial search query; selecting one or more query suggestions in the database for the partial search query based at least in part on the suggestion scores; and sending the selected query suggestions in response to receiving the partial search query; wherein obtaining metadata for the document comprises segmenting the metadata for the document into a plurality of sequences of terms, wherein at least two of the plurality of sequences include at least some identical terms in different orders; and wherein assigning a tag comprises assigning a tag to each term in a given sequence of terms in the plurality of sequences of terms. 4. The computer implemented method of claim 1 , further comprising obtaining a document score for the document, wherein the document score is based at least in part on a relative ranking of the document among a plurality of documents, and wherein the suggestion score is calculated based at least in part on the document score. | 0.664622 |
13. The computer-readable storage device of claim 11 , wherein the computer-executable instructions, when executed by the processor, further cause the processor to perform acts comprising: executing the factor graph on a dataset having elements of at least one unlabeled property to determine a label for the at least one unlabeled property for each element. | 13. The computer-readable storage device of claim 11 , wherein the computer-executable instructions, when executed by the processor, further cause the processor to perform acts comprising: executing the factor graph on a dataset having elements of at least one unlabeled property to determine a label for the at least one unlabeled property for each element. 14. The computer-readable storage device of claim 13 , wherein the executing operation comprises: minimizing an energy function to determine the label for the at least one unlabeled property for each element. | 0.809032 |
14. The apparatus of claim 13 , wherein said processor and said memory with the program code are configured to cause said apparatus to identify and store a background color out of a library of reference colors for the identified picture by comparing said identified word with color words, wherein each background color out of the library of reference colors is uniquely identified by at least one color word to facilitate identification of said topic of the communication event by said apparatus later retrieving and displaying said at least one stored picture with said stored background color. | 14. The apparatus of claim 13 , wherein said processor and said memory with the program code are configured to cause said apparatus to identify and store a background color out of a library of reference colors for the identified picture by comparing said identified word with color words, wherein each background color out of the library of reference colors is uniquely identified by at least one color word to facilitate identification of said topic of the communication event by said apparatus later retrieving and displaying said at least one stored picture with said stored background color. 16. The apparatus of claim 14 , wherein said processor and said memory with the program with code are configured to cause said apparatus to display said stored picture with said identified background color. | 0.886175 |
17. A computer-implemented method for modeling a context representation in a business application, comprising the steps performed by a computer of: storing at least one collection of references to a plurality of entities in a database; determining, by a processor, a subset of the plurality of entities that are relevant to a current context, the current context comprising a combination of at least a user context and a session context, the user context comprising at least one of a role, project, or personal preference, and the session context comprising at least one of a last action or a manipulated business entity; assigning an activation attribute to at least one context entity included in the determined subset, the at least one context entity having a temporal validity, and the activation attribute indicating an importance level of the at least one context entity in the current context; and modeling the context representation using the activation attribute assigned to the at least one context entity, wherein the modeling comprises using a semantic net data structure comprising nodes and relationships between the nodes, wherein modeling the context representation includes considering for the context representation an entity related to the at least one context entity, and wherein the importance of the related entity is derived from the activation attribute of the at least one context entity referring to the related entity, and wherein the derived importance is determined in accordance with the sum of the products of the activation attribute values of the referring at least one context entity and a weighting factor assigned to the relation type linking the at least one context entity and the referred entity. | 17. A computer-implemented method for modeling a context representation in a business application, comprising the steps performed by a computer of: storing at least one collection of references to a plurality of entities in a database; determining, by a processor, a subset of the plurality of entities that are relevant to a current context, the current context comprising a combination of at least a user context and a session context, the user context comprising at least one of a role, project, or personal preference, and the session context comprising at least one of a last action or a manipulated business entity; assigning an activation attribute to at least one context entity included in the determined subset, the at least one context entity having a temporal validity, and the activation attribute indicating an importance level of the at least one context entity in the current context; and modeling the context representation using the activation attribute assigned to the at least one context entity, wherein the modeling comprises using a semantic net data structure comprising nodes and relationships between the nodes, wherein modeling the context representation includes considering for the context representation an entity related to the at least one context entity, and wherein the importance of the related entity is derived from the activation attribute of the at least one context entity referring to the related entity, and wherein the derived importance is determined in accordance with the sum of the products of the activation attribute values of the referring at least one context entity and a weighting factor assigned to the relation type linking the at least one context entity and the referred entity. 25. The computer-implemented method according to claim 17 , further comprising: increasing the value of the activation attribute if the at least one context entity is used in connection with a user interaction. | 0.513379 |
13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; and a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document. | 13. A computer-implemented structure for storing XML data in a relational database, the computer implemented structure comprising a first table structure, the first table structure comprising: a document identifier stored in a volatile or non-volatile computer usable storage medium corresponding to an XML document; and a path string for a node within the XML document stored in the volatile or non-volatile computer usable storage medium, wherein the path string comprises a full path for the node from a root node of the XML document. 15. The computer-implemented structure of claim 13 in which the path string comprises a full path for the node. | 0.775197 |
19. A physical computer-readable medium having instructions stored thereon which, when executed by a computer, cause the computer to perform an information retrieval method comprising: performing at least one input evaluation function for generating a plurality of extracted inputs from at least one user supplied input; decomposing a plurality of resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech; generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and including a subject, an attribute and a bond therebetween, the knowledge correlation function comprising iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool; determining a plurality of most significant resources based upon the answer space; ranking in significance the plurality of most significant resources to thereby generate the ranked plurality of resources; and displaying the ranked plurality of resources. | 19. A physical computer-readable medium having instructions stored thereon which, when executed by a computer, cause the computer to perform an information retrieval method comprising: performing at least one input evaluation function for generating a plurality of extracted inputs from at least one user supplied input; decomposing a plurality of resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech; generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and including a subject, an attribute and a bond therebetween, the knowledge correlation function comprising iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool; determining a plurality of most significant resources based upon the answer space; ranking in significance the plurality of most significant resources to thereby generate the ranked plurality of resources; and displaying the ranked plurality of resources. 28. The physical computer-readable medium according to claim 19 wherein the most significant resources are strongly associated with resources used to create the answer space. | 0.584978 |
7. A text-to-speech system comprising: at least one computer programmed to perform speech synthesis for creating an audio recording from a text source comprising a story including a first character and a second character, wherein the at least one computer is programmed to: automatically identify based, at least in part, on a content of the text source, at least one first spoken passage as being spoken by the first character, at least one second passage as being spoken by the second character, and at least one non-spoken passage within the text source from which speech is to be synthesized to create the audio recording; automatically assign a first voice configuration for the first character to the at least one first spoken passage, a second voice configuration for the second character to the at least one second spoken passage, and a third voice configuration to the at least one non-spoken passage; automatically identify at least one third spoken passage having a measure of certainty regarding an identity of the character speaking the at least one third spoken passage being less than a threshold value; automatically assign to the at least one third spoken passage, a voice configuration for a character assigned to a spoken passage preceding the at least one third spoken passage; and create the audio recording by converting the text source to speech by selectively applying the first voice configuration to the at least one first spoken passage, applying the second voice configuration to the at least one second spoken passage, and applying the third voice configuration to the at least one non-spoken passage. | 7. A text-to-speech system comprising: at least one computer programmed to perform speech synthesis for creating an audio recording from a text source comprising a story including a first character and a second character, wherein the at least one computer is programmed to: automatically identify based, at least in part, on a content of the text source, at least one first spoken passage as being spoken by the first character, at least one second passage as being spoken by the second character, and at least one non-spoken passage within the text source from which speech is to be synthesized to create the audio recording; automatically assign a first voice configuration for the first character to the at least one first spoken passage, a second voice configuration for the second character to the at least one second spoken passage, and a third voice configuration to the at least one non-spoken passage; automatically identify at least one third spoken passage having a measure of certainty regarding an identity of the character speaking the at least one third spoken passage being less than a threshold value; automatically assign to the at least one third spoken passage, a voice configuration for a character assigned to a spoken passage preceding the at least one third spoken passage; and create the audio recording by converting the text source to speech by selectively applying the first voice configuration to the at least one first spoken passage, applying the second voice configuration to the at least one second spoken passage, and applying the third voice configuration to the at least one non-spoken passage. 8. The text-to-speech system of claim 7 , wherein the at least one computer is programmed to automatically determine a speaker gender for at least one fourth spoken passage based, at least in part on gender specific pronouns identified in the text source. | 0.658058 |
70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer. | 70. A computer system for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, the computer system including a computer program product, the computer program product comprising: program instructions that group selected words into a cognitive cluster to be treated as a single word; program instructions that assign an emphasis value to each word and cognitive cluster in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word and cognitive cluster; program instructions that process the first tagged file, including deriving emphasis values for recognizability and comprehensibility, to generate a second tagged file of derived emphasis values; program instructions that process the second tagged file, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; a printer or an electronic display device; and program instructions that present the electronic document to the viewer on the electronic display device or to the printer. 89. The computer system for presenting an electronic document of claim 70 wherein the computer program product further comprises program instructions that enable editing of the derived recognizability value and the derived comprehensibility value for each word or a portion of the electronic document. | 0.620873 |
6. The method of claim 1 , wherein the at least one query is defined using a pattern query language. | 6. The method of claim 1 , wherein the at least one query is defined using a pattern query language. 7. The method of claim 6 , wherein the pattern query language includes functionality to search for at least one software pattern in the target system. | 0.967457 |
1. A method for harmonizing business process tasks, the method comprising: comparing by a processing unit descriptors associated with each of a plurality of business process tasks of different and separate processes of a service oriented architecture, wherein the descriptors associated with each of the tasks comprise a task name, a text description of the task, a predicate task that provides an input to the task in the service oriented architecture, and a subsequent task receives an output generated from the task in the service oriented architecture; identifying by the processing unit a first task of the plurality of business process tasks that is within a first process of the service oriented architecture, and a second task of the plurality of business process tasks that is within a second process of the service oriented architecture that is different and separate from the first process, as a candidate task pair for consolidation as a function of determining that they have a text term in common in their task names or in their text descriptions; comparing by the processing unit the inputs received from the predicate tasks of each of the candidate pair tasks and the outputs generated by each of the candidate pair tasks to their subsequent tasks; confirming by the processing unit consolidation of the candidate pair tasks if the compared inputs to the first and second task are similar and the compared outputs of the first and second task are similar; consolidating by the processing unit the confirmed candidate pair tasks by merging the confirmed candidate pair tasks into a new merged task or replacing a one of the first and the second tasks with a replacement other of the first and the second tasks; and generating by the processing unit an output from the consolidated candidate pair tasks as a common harmonized output for the subsequent tasks of the first and the second tasks. | 1. A method for harmonizing business process tasks, the method comprising: comparing by a processing unit descriptors associated with each of a plurality of business process tasks of different and separate processes of a service oriented architecture, wherein the descriptors associated with each of the tasks comprise a task name, a text description of the task, a predicate task that provides an input to the task in the service oriented architecture, and a subsequent task receives an output generated from the task in the service oriented architecture; identifying by the processing unit a first task of the plurality of business process tasks that is within a first process of the service oriented architecture, and a second task of the plurality of business process tasks that is within a second process of the service oriented architecture that is different and separate from the first process, as a candidate task pair for consolidation as a function of determining that they have a text term in common in their task names or in their text descriptions; comparing by the processing unit the inputs received from the predicate tasks of each of the candidate pair tasks and the outputs generated by each of the candidate pair tasks to their subsequent tasks; confirming by the processing unit consolidation of the candidate pair tasks if the compared inputs to the first and second task are similar and the compared outputs of the first and second task are similar; consolidating by the processing unit the confirmed candidate pair tasks by merging the confirmed candidate pair tasks into a new merged task or replacing a one of the first and the second tasks with a replacement other of the first and the second tasks; and generating by the processing unit an output from the consolidated candidate pair tasks as a common harmonized output for the subsequent tasks of the first and the second tasks. 3. The method of claim 1 , wherein the consolidating the confirmed candidate pair tasks comprises replacing the one of the confirmed candidate pair with the replacement other of the confirmed candidate pair if a one of the compared inputs from the predicate tasks are analogous but not the same, and the compared outputs generated to the subsequent tasks are analogous but not the same. | 0.655711 |
2. The computer-executed method of claim 1 further comprising: prior to forming the fused path expression from the two or more path expressions, identifying the two or more path expressions by: identifying a set of one or more operators from the particular query; wherein each operator of the set of one or more operators is associated with a particular operator from the particular query; and identifying the two or more path expressions as path expressions that are each associated with at least one operator of the set of one or more operators. | 2. The computer-executed method of claim 1 further comprising: prior to forming the fused path expression from the two or more path expressions, identifying the two or more path expressions by: identifying a set of one or more operators from the particular query; wherein each operator of the set of one or more operators is associated with a particular operator from the particular query; and identifying the two or more path expressions as path expressions that are each associated with at least one operator of the set of one or more operators. 17. The computer-executed method of claim 2 , wherein the two or more path expressions comprise all of the path expressions that are associated with the set of one or more operators. | 0.925097 |
7. The system of claim 6 , further comprising: a culture specific value database including a plurality of cultural modules each configured to at least one of augment and alter one or more of the social perception scores associated with one or more of the particular behaviors and the summation of the social perception scores, wherein: the scoring processor is configured to determine the social perception score for each of the individual elements of each one of the communicative acts based on the particular behaviors identified in each one of the communicative acts, the behavior recognition patterns stored in the database, and a preselected one of the plurality of cultural modules from the culture specific value database. | 7. The system of claim 6 , further comprising: a culture specific value database including a plurality of cultural modules each configured to at least one of augment and alter one or more of the social perception scores associated with one or more of the particular behaviors and the summation of the social perception scores, wherein: the scoring processor is configured to determine the social perception score for each of the individual elements of each one of the communicative acts based on the particular behaviors identified in each one of the communicative acts, the behavior recognition patterns stored in the database, and a preselected one of the plurality of cultural modules from the culture specific value database. 9. The system of claim 7 , further comprising a discourse parser configured to receive the communicative acts and to decompose each of the communicative acts into the individual elements for analysis by the scoring processor. | 0.850269 |
9. A computer-implemented method for executing a search query, the method comprising: receiving a search query including a textual expression, wherein the textual expression is written in a language that at least occasionally lacks discrete boundaries between words or autonomous language units; referencing a structured vocabulary knowledge base to determine whether the textual expression comprises a keyword or synonym associated with the structured vocabulary knowledge base, wherein the structured vocabulary knowledge base is for storing vocabulary information associated with a language having multiple orthographic forms or scripts, and wherien the structured vocabulary knowledge base is generated prior to receiving the search query by a repeatable method comprising: assigning an identifier to a semantic concept that is usable as a keyword or key phrase; identifying a main written form for the semantic concept, wherein the main written form is based on at least one of the multiple written forms; for at least one of the multiple written forms associated with the complex language, associating at least one synonymous written form with the semantic concept, wherein the synonymous written form is at least partially distinct from the main written form; and storing the identifier, the main written form, and the at least one synonymous written form in a data storage component associated with the vocabulary knowledge base; if the textual expression does not comprise a keyword, key phrase or synonym associated with the structured vocabulary knowledge base, performing segmentation on the textual expression, wherein the segmentation includes systematically splitting the textual expression into two or more segments, and identifying at least one keyword from the vocabulary knowledge based on the textual expression and the two or more segments; performing the search query using the at least one identified keyword; and providing for display results of the search query. | 9. A computer-implemented method for executing a search query, the method comprising: receiving a search query including a textual expression, wherein the textual expression is written in a language that at least occasionally lacks discrete boundaries between words or autonomous language units; referencing a structured vocabulary knowledge base to determine whether the textual expression comprises a keyword or synonym associated with the structured vocabulary knowledge base, wherein the structured vocabulary knowledge base is for storing vocabulary information associated with a language having multiple orthographic forms or scripts, and wherien the structured vocabulary knowledge base is generated prior to receiving the search query by a repeatable method comprising: assigning an identifier to a semantic concept that is usable as a keyword or key phrase; identifying a main written form for the semantic concept, wherein the main written form is based on at least one of the multiple written forms; for at least one of the multiple written forms associated with the complex language, associating at least one synonymous written form with the semantic concept, wherein the synonymous written form is at least partially distinct from the main written form; and storing the identifier, the main written form, and the at least one synonymous written form in a data storage component associated with the vocabulary knowledge base; if the textual expression does not comprise a keyword, key phrase or synonym associated with the structured vocabulary knowledge base, performing segmentation on the textual expression, wherein the segmentation includes systematically splitting the textual expression into two or more segments, and identifying at least one keyword from the vocabulary knowledge based on the textual expression and the two or more segments; performing the search query using the at least one identified keyword; and providing for display results of the search query. 17. The method of claim 9 wherein the search query is received via a network connection. | 0.66866 |
25. The medium of claim 18 , wherein at least one constraint for preserving statistical consistency specified by the constraint specification is based on an equivalence between a field of the second dataset and a field of the first dataset. | 25. The medium of claim 18 , wherein at least one constraint for preserving statistical consistency specified by the constraint specification is based on an equivalence between a field of the second dataset and a field of the first dataset. 26. The medium of claim 25 , wherein the field of the first dataset and the field of the second dataset are keys in a join operation. | 0.954323 |
1. A method for revealing a document's marked structure, comprising the steps of: inputting a file that is representative of said document; parsing said file to identify marked content, said parsing step comprising the steps of: providing a look up table; parsing said file into markers; building a vector of all markers, said vector comprising the function and location of each of said markers; and establishing links between a vector that holds the tags from a newly read in document to all those tags that are currently held in a look up table, while the document is being parsed, wherein said vector is made of marked content in said document, and locations within a document information stream, when said document is read; accessing said marked content, said accessing step comprising the step of: accessing a glossary for each marker to determine what each marker is and what each marker does; and presenting said document on a display and providing instructions indicating marked structure in said document; wherein an interface is provided such that a person reviewing said document is instructed in the operation and recreation of said document from a casual on-screen review of said document. | 1. A method for revealing a document's marked structure, comprising the steps of: inputting a file that is representative of said document; parsing said file to identify marked content, said parsing step comprising the steps of: providing a look up table; parsing said file into markers; building a vector of all markers, said vector comprising the function and location of each of said markers; and establishing links between a vector that holds the tags from a newly read in document to all those tags that are currently held in a look up table, while the document is being parsed, wherein said vector is made of marked content in said document, and locations within a document information stream, when said document is read; accessing said marked content, said accessing step comprising the step of: accessing a glossary for each marker to determine what each marker is and what each marker does; and presenting said document on a display and providing instructions indicating marked structure in said document; wherein an interface is provided such that a person reviewing said document is instructed in the operation and recreation of said document from a casual on-screen review of said document. 3. The method of claim 1, further comprising the step of: clicking on marked text in said document to access a library that contains more information. | 0.858879 |
4. The method of claim 2 , further comprising applying the picture to a model representing the three-dimensional text. | 4. The method of claim 2 , further comprising applying the picture to a model representing the three-dimensional text. 5. The method of claim 4 , further comprising examining the model and applying a dilation algorithm to the picture. | 0.951137 |
1. A method for advertising in electronic commerce comprising: creating an electronic advertisement while connected to a computer network, wherein creating the electronic advertisement comprises: accessing a server included in said computer network; selecting at least one advertising service from a plurality of advertising services provided in a menu of advertising services, each of said advertising services including: an advertisement format specific to the advertising service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services, and an associated cost; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; and paying at least a portion of the associated cost via said server while connected to said computer network. | 1. A method for advertising in electronic commerce comprising: creating an electronic advertisement while connected to a computer network, wherein creating the electronic advertisement comprises: accessing a server included in said computer network; selecting at least one advertising service from a plurality of advertising services provided in a menu of advertising services, each of said advertising services including: an advertisement format specific to the advertising service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services, and an associated cost; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; and paying at least a portion of the associated cost via said server while connected to said computer network. 7. The method of claim 1 , further including: generating an electronic order associated with said advertising services purchased; and obtaining payment authorization for said electronic order. | 0.735671 |
54. The method according to claim 51 , wherein the metric is a metric distance between two IOs defined as a matrix of size n 1 ×n 2 : {ρ(T 1 ,r 1 ,T 2 ,r 2 )} n 1× n 2 , where T 1 , T 2 are rooted trees, representing the intrinsic structure of compared IOs, r 1 , r 2 are two nodes (from T 1 and T 2 respectively), designated as temporary roots, n 1 , n 2 denote the number of nodes in the structures of the first and second IO respectively; therewith ρ(T 1 ,r 1 ,T 2 ,r 2 )=(c(T 1 ,r 1 ,T 2 ,r 2 )) α , where c(T 1 ,r 1 ,T 2 ,r 2 ) is the similarity measure equal to the power (number of nodes) of the largest subtree common for two compared IO trees, isomorphically transformed relative to the designated temporary roots r 1 and r 2 respectively, and α is a numeric parameter assuming values α<−1. | 54. The method according to claim 51 , wherein the metric is a metric distance between two IOs defined as a matrix of size n 1 ×n 2 : {ρ(T 1 ,r 1 ,T 2 ,r 2 )} n 1× n 2 , where T 1 , T 2 are rooted trees, representing the intrinsic structure of compared IOs, r 1 , r 2 are two nodes (from T 1 and T 2 respectively), designated as temporary roots, n 1 , n 2 denote the number of nodes in the structures of the first and second IO respectively; therewith ρ(T 1 ,r 1 ,T 2 ,r 2 )=(c(T 1 ,r 1 ,T 2 ,r 2 )) α , where c(T 1 ,r 1 ,T 2 ,r 2 ) is the similarity measure equal to the power (number of nodes) of the largest subtree common for two compared IO trees, isomorphically transformed relative to the designated temporary roots r 1 and r 2 respectively, and α is a numeric parameter assuming values α<−1. 55. The method according to claim 54 , wherein the metric distance principal value ρ main (T 1 ,T 2 )=ρ(T 1 ,R 1 ,T 2 ,R 2 ) is defined as a value of the metric function for two untransformed trees. | 0.821657 |
14. A system comprising: a memory device that stores instructions; and at least one processor that executes the instructions and is configured to: receive one or more characteristics of a client requesting access to protected content, the protected content comprising data; determine a risk profile for the client based on the client characteristics, the risk profile reflecting a likelihood that the client is unauthorized to access the protected content; select first challenge characteristics or second challenge characteristics of a challenge/response test based on the risk profile; generate a challenge/response test based on the selected challenge characteristics by: determining a challenge phrase comprising a plurality of characters; and dividing the challenge phrase into at least two character subsets selected from the plurality of characters comprising the challenge phrase; and provide the at least two character subsets for consecutive display on the client at a predetermined frequency, wherein the first challenge characteristics and the second challenge characteristics each reflect distortion levels used to distort characters of the challenge/response test, and the first challenge characteristics reflect less character distortion than the second challenge characteristics. | 14. A system comprising: a memory device that stores instructions; and at least one processor that executes the instructions and is configured to: receive one or more characteristics of a client requesting access to protected content, the protected content comprising data; determine a risk profile for the client based on the client characteristics, the risk profile reflecting a likelihood that the client is unauthorized to access the protected content; select first challenge characteristics or second challenge characteristics of a challenge/response test based on the risk profile; generate a challenge/response test based on the selected challenge characteristics by: determining a challenge phrase comprising a plurality of characters; and dividing the challenge phrase into at least two character subsets selected from the plurality of characters comprising the challenge phrase; and provide the at least two character subsets for consecutive display on the client at a predetermined frequency, wherein the first challenge characteristics and the second challenge characteristics each reflect distortion levels used to distort characters of the challenge/response test, and the first challenge characteristics reflect less character distortion than the second challenge characteristics. 18. The system of claim 14 , wherein the first challenge characteristics and the second challenge characteristics each reflect colors used for characters and background of the challenge/response test, and the first challenge characteristics reflect less contrast between the characters and background than the second challenge characteristics. | 0.526403 |
1. A processor-implemented method for generating and utilizing a synthetic context-based object to locate a user-specific data store, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein data within the non-contextual data object has no meaning until said data is matched to a specific context object from a context object database, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, and wherein the context object that is associated with the non-contextual data object is selected from a plurality of context objects stored in the context object database; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object, wherein said at least one specific data store is from a heterogeneous data structure wherein the heterogeneous data structure contains data stores that are in different formats; matching, by the processor, the at least one specific data store to the synthetic context-based object in response to the at least one specific data store and the synthetic context-based object each containing the non-contextual data object and the context object; determining, by the processor, a subject-matter of interest for a specific user; associating, by the processor, the subject-matter of interest to a specific synthetic context-based object, wherein the specific synthetic context-based object is associated with data that describes the subject-matter of interest for the specific user; further determining, by the processor, the subject-matter of interest for the specific user by data mining a database that describes current interests of the specific user; constructing, by the processor, multiple avatars that represent multiple subject-matters of interest; displaying, by the processor, the multiples avatars on a user interface; further determining, by the processor, the subject-matter of interest for the specific user by receiving a selection of a specific avatar from the specific user, wherein the specific avatar is associated with the subject-matter of interest for the specific user; receiving, from the specific user, a request for data from at least one data store that is associated with the subject-matter of interest that has been determined for the specific user; directing, by the processor, the request to the specific synthetic context-based object that is associated with data that describes the subject-matter of interest for the specific user based on the at least one s ecific data store and the synthetic context-based object each containing the non-contextual data object and the context object and based on the specific avatar that is selected by the user; locating, via the specific synthetic context-based object, said at least one specific data store that is associated with the subject-matter of interest; and returning, by the processor, data from said at least one specific data store that is associated with the subject-matter of interest to the specific user. | 1. A processor-implemented method for generating and utilizing a synthetic context-based object to locate a user-specific data store, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein data within the non-contextual data object has no meaning until said data is matched to a specific context object from a context object database, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, and wherein the context object that is associated with the non-contextual data object is selected from a plurality of context objects stored in the context object database; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object, wherein said at least one specific data store is from a heterogeneous data structure wherein the heterogeneous data structure contains data stores that are in different formats; matching, by the processor, the at least one specific data store to the synthetic context-based object in response to the at least one specific data store and the synthetic context-based object each containing the non-contextual data object and the context object; determining, by the processor, a subject-matter of interest for a specific user; associating, by the processor, the subject-matter of interest to a specific synthetic context-based object, wherein the specific synthetic context-based object is associated with data that describes the subject-matter of interest for the specific user; further determining, by the processor, the subject-matter of interest for the specific user by data mining a database that describes current interests of the specific user; constructing, by the processor, multiple avatars that represent multiple subject-matters of interest; displaying, by the processor, the multiples avatars on a user interface; further determining, by the processor, the subject-matter of interest for the specific user by receiving a selection of a specific avatar from the specific user, wherein the specific avatar is associated with the subject-matter of interest for the specific user; receiving, from the specific user, a request for data from at least one data store that is associated with the subject-matter of interest that has been determined for the specific user; directing, by the processor, the request to the specific synthetic context-based object that is associated with data that describes the subject-matter of interest for the specific user based on the at least one s ecific data store and the synthetic context-based object each containing the non-contextual data object and the context object and based on the specific avatar that is selected by the user; locating, via the specific synthetic context-based object, said at least one specific data store that is associated with the subject-matter of interest; and returning, by the processor, data from said at least one specific data store that is associated with the subject-matter of interest to the specific user. 5. The processor-implemented method of claim 1 , further comprising: determining the subject-matter of interest for the specific user by data mining a database that describes where the specific user resides. | 0.860215 |
333. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 333. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 337. The method of claim 333 , wherein the resume comprises a curriculum vitae. | 0.614379 |
1. A method for automatic parsing of a markup language (ML) document, comprising: receiving a request from an ML producer to write an ML document including ML data in a text format at an ML file manager; passing the ML data in the text format from the ML file manager to an ML parser, wherein the ML parser translates the ML data in the text format into a parsed binary format; writing the ML data in the text format as a text format ML document to a data storage device by the ML file manager; receiving the ML data in the parsed binary format at the ML file manager from the ML parser; and writing the ML data in the parsed binary format as a parsed binary format ML document to the data storage device by the ML file manager; wherein the ML data in the text format and the ML data in the parsed binary format are stored in a single multi-format data object on the data storage device comprising a one-to-one relationship between the ML data of the ML document in the text format and the ML data of the ML document in the parsed binary format, read and write operations are performed on both the text format and the parsed binary format by accessing the single multi-format data object, and additional ML documents are managed by the ML file manager as separate multi-format data objects each comprising text format and parsed binary format ML data in the one-to-one relationship per object. | 1. A method for automatic parsing of a markup language (ML) document, comprising: receiving a request from an ML producer to write an ML document including ML data in a text format at an ML file manager; passing the ML data in the text format from the ML file manager to an ML parser, wherein the ML parser translates the ML data in the text format into a parsed binary format; writing the ML data in the text format as a text format ML document to a data storage device by the ML file manager; receiving the ML data in the parsed binary format at the ML file manager from the ML parser; and writing the ML data in the parsed binary format as a parsed binary format ML document to the data storage device by the ML file manager; wherein the ML data in the text format and the ML data in the parsed binary format are stored in a single multi-format data object on the data storage device comprising a one-to-one relationship between the ML data of the ML document in the text format and the ML data of the ML document in the parsed binary format, read and write operations are performed on both the text format and the parsed binary format by accessing the single multi-format data object, and additional ML documents are managed by the ML file manager as separate multi-format data objects each comprising text format and parsed binary format ML data in the one-to-one relationship per object. 2. The method of claim 1 wherein the request to write the ML document is received via a file system as an option passed with a file open command. | 0.678281 |
3. A system according to claim 1 , further comprising: a coefficient determination module to determine a variable coefficient, wherein the distance of the at least one overlapping cluster is multiplied by the variable coefficient during the reorientation. | 3. A system according to claim 1 , further comprising: a coefficient determination module to determine a variable coefficient, wherein the distance of the at least one overlapping cluster is multiplied by the variable coefficient during the reorientation. 4. A system according to claim 3 , wherein the distances of the remaining overlapping clusters remain unchanged. | 0.813333 |
5. A computer automated subject estimation method in a convolution neural network comprising: performing, on an input of a word-string vector sequence corresponding to dialog text transcribed from a dialog, topic-dependent convolution process including a convolution operation dependent on a topic by using a processor; performing, on the input, topic-independent convolution process including a convolution operation not dependent on the topic by using the processor; performing pooling process on outputs of (i) the topic-dependent convolution process and (ii) the topic-independent convolution process by using processor; and performing full connection process on outputs of the pooling process and estimating a subject label of the dialog by using the processor. | 5. A computer automated subject estimation method in a convolution neural network comprising: performing, on an input of a word-string vector sequence corresponding to dialog text transcribed from a dialog, topic-dependent convolution process including a convolution operation dependent on a topic by using a processor; performing, on the input, topic-independent convolution process including a convolution operation not dependent on the topic by using the processor; performing pooling process on outputs of (i) the topic-dependent convolution process and (ii) the topic-independent convolution process by using processor; and performing full connection process on outputs of the pooling process and estimating a subject label of the dialog by using the processor. 6. The computer automated subject estimation method according to claim 5 , wherein, in the performing of the topic-dependent convolution process, a convolution operation between the word-string vector sequence and first weights triggered by a specific word indicating a topic on which the topic-dependent convolution process is dependent is performed; wherein, in the performing of the topic-independent convolution process, a convolution operation between the word-string vector sequence and second weights triggered by a word indicating a topic other than the topic on which the topic-dependent convolution process is dependent is performed; wherein, in the performing of the pooling process, a computational operation for extracting maximum values in a time direction from the outputs of the topic-dependent convolution process and the outputs of the topic-independent convolution process is performed; and wherein, in the performing of the full connection process, after weighted addition using a connection weight is performed on the outputs of the pooling process, a result of the weighted addition is represented with a probability distribution to perform the full connection process. | 0.526608 |
1. A method comprising: detecting, by a computing device, a user input for a telestration on an image being displayed on a display device; determining, by the computing device, a plurality of image portions of the image based on the telestration, wherein the plurality of image portions are determined by a boundary around each image portion based on the telestration; determining, by the computing device, a set of tags for the plurality of image portions, wherein the set of tags are determined based on image recognition of content in the plurality of image portions; determining, by the computing device, an operator based on the telestration, wherein the operator characterizes an operation to perform for the plurality of image portions; determining, by the computing device, a search query based on applying the operator to the set of tags; and causing, by the computing device, a search to be performed using the search query. | 1. A method comprising: detecting, by a computing device, a user input for a telestration on an image being displayed on a display device; determining, by the computing device, a plurality of image portions of the image based on the telestration, wherein the plurality of image portions are determined by a boundary around each image portion based on the telestration; determining, by the computing device, a set of tags for the plurality of image portions, wherein the set of tags are determined based on image recognition of content in the plurality of image portions; determining, by the computing device, an operator based on the telestration, wherein the operator characterizes an operation to perform for the plurality of image portions; determining, by the computing device, a search query based on applying the operator to the set of tags; and causing, by the computing device, a search to be performed using the search query. 14. The method of claim 1 , further comprising receiving a submit command, wherein the submit command causes submitting of the search query to determine a search result. | 0.724911 |
1. A computer-implemented method performed by a computerized device, comprising: obtaining a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; selecting a set of candidate invariants comprising at least one intermediate node of the DAG; determining, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model; and utilizing the subset for model checking of the unbounded model. | 1. A computer-implemented method performed by a computerized device, comprising: obtaining a proof of a property with respect to a bounded model having a bounded number of cycles, wherein the bounded model comprising an initial axiom and a transition relation axiom, wherein the proof of the property is a Directed Acyclic Graph (DAG), wherein each non-leaf node of the DAG is deducible from its child nodes, wherein a root of the DAG is the property, and wherein leaves of the DAG are associated with an axiom of the bounded model; selecting a set of candidate invariants comprising at least one intermediate node of the DAG; determining, without using the proof and using a Boolean satisfiability problem solver, a subset of the set of candidates, wherein the subset comprises invariants which are held in an unbounded model during each cycle after the bound, wherein the unbounded model is an unbounded version of the bounded model; and utilizing the subset for model checking of the unbounded model. 8. The computer-implemented method of claim 1 , wherein said selecting comprises selecting substantially all nodes as invariant candidates. | 0.741228 |
3. The method of claim 2 , wherein automatically generating a plurality of first feature bins further comprises, prior to generating the plurality of first feature bins: performing peak detection on the probability distribution of values of the first feature, and wherein generating the plurality of first feature bins based on the probability distribution for the values of the first feature comprises generating the plurality of first feature bins based on the peaks. | 3. The method of claim 2 , wherein automatically generating a plurality of first feature bins further comprises, prior to generating the plurality of first feature bins: performing peak detection on the probability distribution of values of the first feature, and wherein generating the plurality of first feature bins based on the probability distribution for the values of the first feature comprises generating the plurality of first feature bins based on the peaks. 4. The method of claim 3 , wherein generating the plurality of first feature bins based on the peaks comprises: performing k-means clustering at the detected peaks. | 0.842849 |
8. A search apparatus implemented in a computer, said apparatus comprising a processor programmed to: receive a search query comprising a plurality of keywords; determine each mathematical combination of the plurality of keywords; divide the search query into a number of sub-queries, in which each sub-query comprising at least one of said keywords and in which each mathematical combination is represented as a separate sub-query; compare each sub-query to an inhibited combinations list; exclude sub-queries that are identified as inhibited combinations; after excluding sub-queries that are identified as inhibited combinations, submit remaining sub-queries to different search engines such that private information from the search query is less discernible at any one of said search engines than if more of the keywords of the search query were provided to that individual search engine; and re-search a plurality of search results returned from the different search engines in response to the submission of said sub-queries, said re-searching being performed using all the keywords of the search query. | 8. A search apparatus implemented in a computer, said apparatus comprising a processor programmed to: receive a search query comprising a plurality of keywords; determine each mathematical combination of the plurality of keywords; divide the search query into a number of sub-queries, in which each sub-query comprising at least one of said keywords and in which each mathematical combination is represented as a separate sub-query; compare each sub-query to an inhibited combinations list; exclude sub-queries that are identified as inhibited combinations; after excluding sub-queries that are identified as inhibited combinations, submit remaining sub-queries to different search engines such that private information from the search query is less discernible at any one of said search engines than if more of the keywords of the search query were provided to that individual search engine; and re-search a plurality of search results returned from the different search engines in response to the submission of said sub-queries, said re-searching being performed using all the keywords of the search query. 11. The search apparatus of claim 8 , in which said processor is further programmed to calculate a co-occurrence probability for the keywords of each sub-query and to exclude from use as a sub-query any combination of keywords having a co-occurrence probability below a threshold, in which the co-occurrence probability is a ratio of percentage chance that multiple keywords will be used in a same search result. | 0.718033 |
7. A shank and retainer assembly for a bone screw wherein: a) the shank has a lower threaded portion for implantation in a bone of a patient and an upper portion; the shank upper portion includes a first partial sphere; and b) the retainer compress a second partial sphere whereby mating of the first and second partial sphere during mating forms a combined substantially ball shaped pivot structure. | 7. A shank and retainer assembly for a bone screw wherein: a) the shank has a lower threaded portion for implantation in a bone of a patient and an upper portion; the shank upper portion includes a first partial sphere; and b) the retainer compress a second partial sphere whereby mating of the first and second partial sphere during mating forms a combined substantially ball shaped pivot structure. 8. The assembly according to claim 7 , wherein the first partial sphere includes a concave region and the second partial sphere includes a convex region that mates with the concave region. | 0.952441 |
1. A method comprising: receiving, by a processing device, a request for a user interface (UI) document comprising a first set of media items, wherein a set of identifiers is associated with the UI document, the set of identifiers comprising a page identifier for the UI document and one or more identifiers of the first set of media items; obtaining, by the processing device, an identifier list for a second set of media items in a social share included in the UI document; comparing the set of identifiers for the UI document with the identifier list for the social share to determine one or more media items in the second set of media items that are represented on the UI document; updating the identifier list by removing identifiers of the one or more determined media items that are represented on the UI document; and modifying the UI document to provide a representation associated with a first identifier from the updated identifier list for the second set of media items of the social share. | 1. A method comprising: receiving, by a processing device, a request for a user interface (UI) document comprising a first set of media items, wherein a set of identifiers is associated with the UI document, the set of identifiers comprising a page identifier for the UI document and one or more identifiers of the first set of media items; obtaining, by the processing device, an identifier list for a second set of media items in a social share included in the UI document; comparing the set of identifiers for the UI document with the identifier list for the social share to determine one or more media items in the second set of media items that are represented on the UI document; updating the identifier list by removing identifiers of the one or more determined media items that are represented on the UI document; and modifying the UI document to provide a representation associated with a first identifier from the updated identifier list for the second set of media items of the social share. 5. The method of claim 1 , further comprising: selecting the first identifier from the updated identifier list in view of a user associated with the request for the UI document. | 0.823552 |
41. The system of claim 39 wherein the determining of the relevant information further includes: determining, for each of multiple content categories, multiple comment groups that are a subset of the plurality of generated comment groups and that correspond to one or more definition terms for the content category; analyzing, for each of the multiple content categories, the textual comments included in the multiple comment groups corresponding to the content category to determine one or more relevant attributes for the content category that are distinct from the definition terms for the content category; and providing information about at least one of the determined relevant attributes for at least one of the multiple content categories. | 41. The system of claim 39 wherein the determining of the relevant information further includes: determining, for each of multiple content categories, multiple comment groups that are a subset of the plurality of generated comment groups and that correspond to one or more definition terms for the content category; analyzing, for each of the multiple content categories, the textual comments included in the multiple comment groups corresponding to the content category to determine one or more relevant attributes for the content category that are distinct from the definition terms for the content category; and providing information about at least one of the determined relevant attributes for at least one of the multiple content categories. 42. The system of claim 41 wherein at least some of the determined relevant attributes for at least some of the multiple content categories are terms included in contents of the plurality of textual comments, and wherein the at least one determined inter-relationship is between two or more comment groups associated with two or more of the multiple content categories. | 0.880308 |
5. The system of claim 1 , wherein the suggestion management component is configured to: determine a rationale for the first suggested activity, wherein the rationale includes information related to a value of the first suggested activity to a customer associated with the first suggested activity; and wherein the activity management component is configured to: output, to the first worker, the rationale for the first suggested activity with the first suggested activity. | 5. The system of claim 1 , wherein the suggestion management component is configured to: determine a rationale for the first suggested activity, wherein the rationale includes information related to a value of the first suggested activity to a customer associated with the first suggested activity; and wherein the activity management component is configured to: output, to the first worker, the rationale for the first suggested activity with the first suggested activity. 7. The system of claim 5 , wherein the suggestion management component is configured to: calculate a score for the first suggested activity based on calculating a first rank value for a first factor and calculating a second rank value for a second factor, wherein the rationale comprises information related to one or more of: the first rank value calculated for the first factor associated with the first suggested activity and the second rank value calculated for the second factor associated with the first suggested activity. | 0.942691 |
120. The system of claim 110 , wherein the matching resume that satisfies the job description includes the required skill or experience-related phrase for each said at least one job requirement, and the term of experience for the required skill or experience-related phrase in the resume is greater than or equal to the required term of experience. | 120. The system of claim 110 , wherein the matching resume that satisfies the job description includes the required skill or experience-related phrase for each said at least one job requirement, and the term of experience for the required skill or experience-related phrase in the resume is greater than or equal to the required term of experience. 121. The system of claim 120 , wherein at least one of said at least one job requirement includes at least one alternative job requirement, each said at least one alternative job requirement comprising an alternative required skill or experience-related phrase and an alternative required term of experience, and wherein the matching resume satisfies said at least one of said at least one job requirement when the resume includes either: the required skill or experience-related phrase for said at least one of said at least one job requirement, and the term of experience for the required skill or experience-related phrase in the resume is greater than or equal to the required term of experience; or the alternative required skill or experience-related phrase for any said at least one alternative job requirement, and the term of experience for the alternative required skill or experience-related phrase in the resume is greater than or equal to the alternative required term of experience. | 0.761036 |
29. A system for constructing at least one data structure encoding a preference graph that represents user preferences, the system comprising: at least one processor configured to receive a plurality of first-order user preferences indicative of user preferences among values of attributes of items in a plurality of items, receive at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, wherein the preference graph comprises a first node for a first item in the plurality of items and a second node for a second item in the plurality of items, and compute a weight for an edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item. | 29. A system for constructing at least one data structure encoding a preference graph that represents user preferences, the system comprising: at least one processor configured to receive a plurality of first-order user preferences indicative of user preferences among values of attributes of items in a plurality of items, receive at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, wherein the preference graph comprises a first node for a first item in the plurality of items and a second node for a second item in the plurality of items, and compute a weight for an edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item. 33. The system of claim 29 , wherein items in the plurality of items are represented as tuples, each tuple comprising values of the attributes of the corresponding item, and wherein the at least one processor is configured to receive the plurality of first-order preferences at least by: receiving a first-order preference for the first item over the second item by receiving an indication of a user preference for a first value of a first attribute of a first tuple representing the first item over a second value of the second attribute of a second tuple representing the second item. | 0.596238 |
37. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a tile for each node of hierarchical information; arrange tiles for nodes of a same hierarchical level into a planar layer; arrange the planar layers in a vertical stack; generate a three dimensional orthographic projection with the vertical stack of planar layers each having multiple tiles; render, in a user interface, the three dimensional orthographic projection of the vertical stack of planar layers, wherein the vertical stack of planar layers each has multiple tiles for presentation on a display; and move a first set of tiles from a planar layer to a top layer of the vertical stack when the tiles are selected. | 37. An article of manufacture comprising a storage medium containing instructions that when executed enable a system to: generate a tile for each node of hierarchical information; arrange tiles for nodes of a same hierarchical level into a planar layer; arrange the planar layers in a vertical stack; generate a three dimensional orthographic projection with the vertical stack of planar layers each having multiple tiles; render, in a user interface, the three dimensional orthographic projection of the vertical stack of planar layers, wherein the vertical stack of planar layers each has multiple tiles for presentation on a display; and move a first set of tiles from a planar layer to a top layer of the vertical stack when the tiles are selected. 39. The article of claim 37 , further comprising instructions that if executed enable the system to present node information when a tile is selected. | 0.681289 |
8. The method of claim 1 , further comprising: selecting the second endpoint; while the second endpoint is selected, detecting a finger slide across the touch sensitive display; and moving the second endpoint in accordance with the detected finger slide to a third location in the text. | 8. The method of claim 1 , further comprising: selecting the second endpoint; while the second endpoint is selected, detecting a finger slide across the touch sensitive display; and moving the second endpoint in accordance with the detected finger slide to a third location in the text. 9. The method of claim 8 , wherein the finger slide is detected starting on a portion of the touch-sensitive display that is remote from the second location. | 0.875742 |
1. A method for providing a generic robot architecture for robot control software, comprising: providing a hardware abstraction level configured for developing a plurality of hardware abstractions for defining, monitoring, and controlling a plurality of hardware modules available on a robot platform; providing a robot abstraction level configured for defining a plurality of robot attributes comprising at least one of the plurality of hardware abstractions; and providing a robot behavior level configured for defining a plurality of robot behaviors comprising at least one of the plurality of robot attributes; wherein: each robot attribute of the plurality is configured for substantially isolating the robot behaviors from the plurality of hardware abstractions; each hardware abstraction of the plurality is configured for substantially isolating the plurality of robot attributes from a corresponding hardware module of the plurality; at least two hardware abstractions are configured to provide substantially similar hardware information to at least one of the plurality of robot attributes; and the at least one of the plurality of robot attributes is configured to combine the hardware information from each of the at least two hardware abstractions to form attribute information for the at least one of the plurality of robot attributes and can disregard the hardware information from one of the at least two hardware abstractions in forming the attribute information. | 1. A method for providing a generic robot architecture for robot control software, comprising: providing a hardware abstraction level configured for developing a plurality of hardware abstractions for defining, monitoring, and controlling a plurality of hardware modules available on a robot platform; providing a robot abstraction level configured for defining a plurality of robot attributes comprising at least one of the plurality of hardware abstractions; and providing a robot behavior level configured for defining a plurality of robot behaviors comprising at least one of the plurality of robot attributes; wherein: each robot attribute of the plurality is configured for substantially isolating the robot behaviors from the plurality of hardware abstractions; each hardware abstraction of the plurality is configured for substantially isolating the plurality of robot attributes from a corresponding hardware module of the plurality; at least two hardware abstractions are configured to provide substantially similar hardware information to at least one of the plurality of robot attributes; and the at least one of the plurality of robot attributes is configured to combine the hardware information from each of the at least two hardware abstractions to form attribute information for the at least one of the plurality of robot attributes and can disregard the hardware information from one of the at least two hardware abstractions in forming the attribute information. 6. The method of claim 1 , wherein providing the robot abstraction level further comprises providing a plurality of environment abstractions wherein the plurality of environment abstractions provide environment information about an environment around the robot to an operator, to the robot behaviors, to another robot, or to combinations thereof. | 0.601395 |
1. An anchor assembly comprising: a anchor body with an anchor; an anchor head including a yoke extending from the anchor body and a shaft positioned across the yoke; a saddle mounting element located on said shaft; a saddle including a port that is received about said saddle mounting element wherein the saddle includes a mount adapted to secure the saddle to a spinal rod; and a fastener that can lock said saddle mounting element against said shaft in order to position said saddle relative to said anchor body. | 1. An anchor assembly comprising: a anchor body with an anchor; an anchor head including a yoke extending from the anchor body and a shaft positioned across the yoke; a saddle mounting element located on said shaft; a saddle including a port that is received about said saddle mounting element wherein the saddle includes a mount adapted to secure the saddle to a spinal rod; and a fastener that can lock said saddle mounting element against said shaft in order to position said saddle relative to said anchor body. 2. The anchor assembly of claim 1 wherein said saddle mounting element is a sphere having a bore that is received over said shaft. | 0.621145 |
12. A computing system, comprising: a processor and a memory containing instructions that when executed by the processor, cause the processor perform a method comprising: receiving a sequence of English characters from the corresponding keys on the keyboard to an input method editor (“IME”) application; receiving an input of a single text character of a language different than English to the IME application, wherein the single text character does not have a one-to-one correspondence with one of the keys of the keyboard or with a sequence of keys of the keyboard, wherein the single text character is a character of at least one of Chinese, Japanese, Korean, or Indic; subsequently, defining a custom reading for the language by mapping the received sequence of the English characters to the received single text character of the language different than English; determining if a number of custom readings associated with the IME application is above a threshold; and in response to determining that the number of custom readings is not above the threshold, storing the custom reading having the mapped sequence of the English characters and the single text character of the language different than English in a dictionary accessible by the IME application, the stored custom reading being accessible to convert a sequence of English characters to the single text character in response to receiving the sequence of the English characters from the keyboard without updating the IME application. | 12. A computing system, comprising: a processor and a memory containing instructions that when executed by the processor, cause the processor perform a method comprising: receiving a sequence of English characters from the corresponding keys on the keyboard to an input method editor (“IME”) application; receiving an input of a single text character of a language different than English to the IME application, wherein the single text character does not have a one-to-one correspondence with one of the keys of the keyboard or with a sequence of keys of the keyboard, wherein the single text character is a character of at least one of Chinese, Japanese, Korean, or Indic; subsequently, defining a custom reading for the language by mapping the received sequence of the English characters to the received single text character of the language different than English; determining if a number of custom readings associated with the IME application is above a threshold; and in response to determining that the number of custom readings is not above the threshold, storing the custom reading having the mapped sequence of the English characters and the single text character of the language different than English in a dictionary accessible by the IME application, the stored custom reading being accessible to convert a sequence of English characters to the single text character in response to receiving the sequence of the English characters from the keyboard without updating the IME application. 15. The computing system of claim 12 wherein: the sequence is a first sequence; the single text character is a single text character; the custom reading is a first custom reading; the method performed by the processor further includes: receiving a second sequence of English characters from the corresponding keys on the keyboard; receiving an input of a second single text character of the language different than English; and defining a second custom reading for the language by mapping the received second sequence of the English characters to the received second single text character of the language different than English. | 0.520447 |
13. A system as in claim 12 , wherein the report designer program is operable to use a graphical user interface to generate one or more reports. | 13. A system as in claim 12 , wherein the report designer program is operable to use a graphical user interface to generate one or more reports. 14. A system as in claim 13 , wherein the template is configured to define user-selectable formatting and layout of the report based on one or more sub-reports. | 0.92931 |
2. The apparatus of claim 1 further comprising a query monitor mechanism that stores successful queries for elements in the repository in a successful query database. | 2. The apparatus of claim 1 further comprising a query monitor mechanism that stores successful queries for elements in the repository in a successful query database. 3. The apparatus of claim 2 wherein if the query returns a plurality of query results, ranking the query results using data in the successful query database, and selecting the top ranked query result for insertion into the document. | 0.935777 |
16. An image processing system, comprising: a memory storing one or more routines; and a processing component configured to access previously or concurrently acquired projection data and to execute the one or more routines stored in the memory, wherein the one or more routines, when executed by the processing component: perform an iterative reconstruction of a set of projection data by solving an objective function comprising at least a dictionary-based term, wherein the dictionary-based term employs dictionary learning that employs one or more dictionaries comprising two-dimensional image patches oriented in different directions; generate a reconstructed image upon completion of the iterative reconstruction. | 16. An image processing system, comprising: a memory storing one or more routines; and a processing component configured to access previously or concurrently acquired projection data and to execute the one or more routines stored in the memory, wherein the one or more routines, when executed by the processing component: perform an iterative reconstruction of a set of projection data by solving an objective function comprising at least a dictionary-based term, wherein the dictionary-based term employs dictionary learning that employs one or more dictionaries comprising two-dimensional image patches oriented in different directions; generate a reconstructed image upon completion of the iterative reconstruction. 17. The image processing system of claim 16 , wherein the one or more dictionaries comprise three dictionaries, wherein each dictionary comprises two-dimensional image patches corresponding to a different orthogonal direction. | 0.626582 |
1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels. | 1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels. 9. A computer readable non-transitory storage medium comprising a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform the steps of claim 1 . | 0.846983 |
1. A method of performing speech synthesis, the method comprising: obtaining at a first time a plurality of phoneme sequences by applying a first part of a speech synthesizer to a text corpus to yield an obtained plurality of phoneme sequences, the first part of the speech synthesizer only identifying possible phoneme sequences to be used in synthesizing speech at a second time which is later than the first time; for each respective phoneme sequence of the obtained plurality of phoneme sequences, identifying joins that would be calculated to synthesize the respective phoneme sequence; and adding the identified joins to a cache for use in speech synthesis. | 1. A method of performing speech synthesis, the method comprising: obtaining at a first time a plurality of phoneme sequences by applying a first part of a speech synthesizer to a text corpus to yield an obtained plurality of phoneme sequences, the first part of the speech synthesizer only identifying possible phoneme sequences to be used in synthesizing speech at a second time which is later than the first time; for each respective phoneme sequence of the obtained plurality of phoneme sequences, identifying joins that would be calculated to synthesize the respective phoneme sequence; and adding the identified joins to a cache for use in speech synthesis. 3. The method of claim 1 , the method further comprising: building a plurality of caches of different sizes based on values or parameters. | 0.712056 |
1. A method comprising: receiving domain-specific training data of sentences describing a target entity in a context; extracting a speaker history and a visual context from the domain-specific training data; selecting attributes of the target entity based on at least one of the speaker history, the visual context, and speaker preferences; generating a text expression referring to the target entity based on at least one of the attributes, the speaker history, and the context; and outputting, via a processor, the text expression. | 1. A method comprising: receiving domain-specific training data of sentences describing a target entity in a context; extracting a speaker history and a visual context from the domain-specific training data; selecting attributes of the target entity based on at least one of the speaker history, the visual context, and speaker preferences; generating a text expression referring to the target entity based on at least one of the attributes, the speaker history, and the context; and outputting, via a processor, the text expression. 2. The method of claim 1 , wherein generating the text expression is further based on a dependency tree model. | 0.625526 |
7. A computer-implemented method comprising: receiving, from a client device and by a document system, a request for one or more documents; obtaining, by the document system and from a corpus of documents, a set of documents responsive to the request; obtaining, from a user profile associated with a source of the request, representations of a plurality of topics of interest to a user; selecting, by the document system and using an index, at least one document from the set of documents that is associated with a particular group of co-occurring topics that matches at least one group of topics in the plurality of topics of interest to the user; for the at least one selected document, obtaining a value corresponding to an inverse document frequency of the particular group of co-occurring topics in the corpus of documents, comprising: identifying a first number of documents in the corpus of documents that have been created during a limited time period that ranges from a prior time to a current time, wherein the first number of documents is less than a total number of documents in the corpus of documents; and identifying a second number of documents in the corpus of documents that have been created during the limited time period and that reference the particular group of co-occurring topics, wherein the second number of documents is less than the first number of documents, wherein the value corresponding to the inverse document frequency is based on a ratio of the first number of documents and the second number of documents; generating a score for the at least one document based at least in part on the value corresponding to the inverse document frequency that is based on the ratio of the first number of documents and the second number of documents; determining that the score for the at least one document satisfies a threshold score that indicates that the particular group of co-occurring topics of the at least one document is an infrequent group of co-occurring topics in the corpus of documents; and responsive to determining that the score for the at least one document satisfies the threshold score that indicates that the particular group of co-occurring topics of the at least one document is an infrequent group of co-occurring topics in the corpus of documents, transmitting information associated with the at least one document from the document system to the client device in response to the request, wherein the transmitted information includes information for rendering an interface that provides access to the at least one document. | 7. A computer-implemented method comprising: receiving, from a client device and by a document system, a request for one or more documents; obtaining, by the document system and from a corpus of documents, a set of documents responsive to the request; obtaining, from a user profile associated with a source of the request, representations of a plurality of topics of interest to a user; selecting, by the document system and using an index, at least one document from the set of documents that is associated with a particular group of co-occurring topics that matches at least one group of topics in the plurality of topics of interest to the user; for the at least one selected document, obtaining a value corresponding to an inverse document frequency of the particular group of co-occurring topics in the corpus of documents, comprising: identifying a first number of documents in the corpus of documents that have been created during a limited time period that ranges from a prior time to a current time, wherein the first number of documents is less than a total number of documents in the corpus of documents; and identifying a second number of documents in the corpus of documents that have been created during the limited time period and that reference the particular group of co-occurring topics, wherein the second number of documents is less than the first number of documents, wherein the value corresponding to the inverse document frequency is based on a ratio of the first number of documents and the second number of documents; generating a score for the at least one document based at least in part on the value corresponding to the inverse document frequency that is based on the ratio of the first number of documents and the second number of documents; determining that the score for the at least one document satisfies a threshold score that indicates that the particular group of co-occurring topics of the at least one document is an infrequent group of co-occurring topics in the corpus of documents; and responsive to determining that the score for the at least one document satisfies the threshold score that indicates that the particular group of co-occurring topics of the at least one document is an infrequent group of co-occurring topics in the corpus of documents, transmitting information associated with the at least one document from the document system to the client device in response to the request, wherein the transmitted information includes information for rendering an interface that provides access to the at least one document. 11. The method of claim 7 , wherein the score for the at least one document is generated based on a function of the value corresponding to the inverse document frequency. | 0.544364 |
14. A device configured to decode video data, the device comprising: a storage medium configured to store the video data; and one or more processors configured to: determine that a coding unit (CU) in a B slice is partitioned into one or more prediction units (PUs); and for at least one of the PUs of the CU: determine, based on a size characteristic of the PU, that the PU is restricted to uni-directional inter prediction; and parse, from a bitstream, an inter prediction mode indicator for the PU, wherein when the PU is restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate that the PU is either uni-directionally inter predicted based on a list 0 or uni-directionally inter predicted based on a list 1 , wherein when the PU is not restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate the PU is either uni-directionally inter predicted based on the list 0 , uni-directionally inter predicted based on the list 1 , or bi-directionally predicted. | 14. A device configured to decode video data, the device comprising: a storage medium configured to store the video data; and one or more processors configured to: determine that a coding unit (CU) in a B slice is partitioned into one or more prediction units (PUs); and for at least one of the PUs of the CU: determine, based on a size characteristic of the PU, that the PU is restricted to uni-directional inter prediction; and parse, from a bitstream, an inter prediction mode indicator for the PU, wherein when the PU is restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate that the PU is either uni-directionally inter predicted based on a list 0 or uni-directionally inter predicted based on a list 1 , wherein when the PU is not restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate the PU is either uni-directionally inter predicted based on the list 0 , uni-directionally inter predicted based on the list 1 , or bi-directionally predicted. 16. The device of claim 14 , wherein the one or more processors are configured to determine that the PU is restricted to uni-directional inter prediction if a height or a width of a video block associated with the PU is below a threshold. | 0.545808 |
1. An image processing apparatus comprising: a printing unit; a storage unit configured to store information on the image processing apparatus; a display control unit configured to display an operation screen in a display language associated with a log-in user who has logged in to the image processing apparatus; and a print control unit configured to control execution of manual report printing in which the information is printed by said printing unit as a report, based on an instruction input by using the operation screen displayed in the display language for the log-in user, wherein said print control unit performs the manual report printing in the display language for the log-in user. | 1. An image processing apparatus comprising: a printing unit; a storage unit configured to store information on the image processing apparatus; a display control unit configured to display an operation screen in a display language associated with a log-in user who has logged in to the image processing apparatus; and a print control unit configured to control execution of manual report printing in which the information is printed by said printing unit as a report, based on an instruction input by using the operation screen displayed in the display language for the log-in user, wherein said print control unit performs the manual report printing in the display language for the log-in user. 4. The image processing apparatus according to claim 1 , wherein said print control unit controls execution of automatic report printing in which the information is automatically printed by said printing unit as a report, and said printing unit performs the automatic report printing in a predetermined language. | 0.5 |
13. A method comprising: parse content input of a plurality of past electronic communications stored in an electronic communication database; identify a pattern between the parsed content input of a first of the plurality of past electronic communications and a second of the plurality of past electronic communications; generate a recipient rule based on the identified pattern between the first and the second of the plurality of past electronic communications; receive a save command from a user, wherein the save command is a command to save a user configuration of the recipient rule; store the recipient rule in a memory device; receiving content input for an electronic communication, wherein the electronic communication comprises at least one field of a plurality of fields, the plurality of fields comprising a subject line, a message body, and a recipient address field, and wherein the at least one of the plurality of fields of the electronic communication is populated with the content input; parsing the content input of the at least one field of the electronic communication; semantically analyzing the parsed content input of the at least one field of the electronic communication to identify a content qualifier of the recipient rule; and suggesting a potential recipient of the electronic communication based on the content qualifier of the recipient rule associated with the content input of the at least one field of the electronic communication. | 13. A method comprising: parse content input of a plurality of past electronic communications stored in an electronic communication database; identify a pattern between the parsed content input of a first of the plurality of past electronic communications and a second of the plurality of past electronic communications; generate a recipient rule based on the identified pattern between the first and the second of the plurality of past electronic communications; receive a save command from a user, wherein the save command is a command to save a user configuration of the recipient rule; store the recipient rule in a memory device; receiving content input for an electronic communication, wherein the electronic communication comprises at least one field of a plurality of fields, the plurality of fields comprising a subject line, a message body, and a recipient address field, and wherein the at least one of the plurality of fields of the electronic communication is populated with the content input; parsing the content input of the at least one field of the electronic communication; semantically analyzing the parsed content input of the at least one field of the electronic communication to identify a content qualifier of the recipient rule; and suggesting a potential recipient of the electronic communication based on the content qualifier of the recipient rule associated with the content input of the at least one field of the electronic communication. 14. The method of claim 13 , further comprising: comparing the parsed content input of the electronic communication with entries of a semantic database to determine a semantic meaning of at least a portion of the parsed content input, wherein the semantic database defines the recipient rule between the semantic meaning and the potential recipient; identifying an omission of the potential recipient from the recipient address field of the electronic communication; and adding the potential recipient to the recipient address field of the electronic communication according to a selection of an email user. | 0.611442 |
2. The method of claim 1 , further comprising determining the presence of the user-specific XML document based on a user identity for the user and the requested prescribed voice application operation. | 2. The method of claim 1 , further comprising determining the presence of the user-specific XML document based on a user identity for the user and the requested prescribed voice application operation. 3. The method of claim 2 , wherein the determining step includes accessing an external database, configured for storing data for respective users, for retrieval of the user-specific XML document. | 0.806261 |
5. The method of claim 1 , wherein the identifying a character location of the one or more potential errors proceeds sequentially through potential error character locations responsive to repeated user input associated with the string of characters. | 5. The method of claim 1 , wherein the identifying a character location of the one or more potential errors proceeds sequentially through potential error character locations responsive to repeated user input associated with the string of characters. 6. The method of claim 5 , wherein sequential error locations are visually indicated responsive to repeated user input associated with the string of characters. | 0.908546 |
1. An apparatus, comprising: a processing node, implemented by one or more processors, comprising a data reception module to receive an original query plan comprising query nodes that include one or more database operations; and an analysis module, implemented by the one or more processors, to couple to the processing node, the analysis module to; transform the original query plan into an equivalent executable compact query plan to store on a machine readable device; compute maximal source sub-queries associated with the compact query plan; and compute semi-join reductions of the maximal source sub-queries associated with the compact query plan to generate a derivative query plan, wherein the compact query plan comprises at least two source nodes including scan operations to source tables, the at least two source nodes coupled to at least one abstract node and at least one singleton node, wherein a child of the at least one abstract node comprises at least one of the source nodes or the at least one singleton node, but not another abstract node. | 1. An apparatus, comprising: a processing node, implemented by one or more processors, comprising a data reception module to receive an original query plan comprising query nodes that include one or more database operations; and an analysis module, implemented by the one or more processors, to couple to the processing node, the analysis module to; transform the original query plan into an equivalent executable compact query plan to store on a machine readable device; compute maximal source sub-queries associated with the compact query plan; and compute semi-join reductions of the maximal source sub-queries associated with the compact query plan to generate a derivative query plan, wherein the compact query plan comprises at least two source nodes including scan operations to source tables, the at least two source nodes coupled to at least one abstract node and at least one singleton node, wherein a child of the at least one abstract node comprises at least one of the source nodes or the at least one singleton node, but not another abstract node. 3. The apparatus of claim 1 , wherein the processing node comprises one of a server or a client. | 0.627181 |
10. A method of preventing cross-site scripting, the method comprising: parsing an HTML e-mail message to create a document object model (DOM) tree wherein the DOM tree includes a plurality of branches, the plurality of branches including at least one branch having only known elements; utilizing a model hook of an e-mail program to derive a normal element filter; applying the normal element filter to the DOM tree, the filter executing as a plug-in in a browser in a computing device; creating a modified DOM tree wherein the at least one branch having only known elements is excluded from the DOM tree and wherein the excluding of the at least one branch from the DOM tree is performed such that remaining branches of the DOM tree are still connected with one another; and applying a script analyzer filter to the modified DOM tree to create a final DOM tree having only unknown element types. | 10. A method of preventing cross-site scripting, the method comprising: parsing an HTML e-mail message to create a document object model (DOM) tree wherein the DOM tree includes a plurality of branches, the plurality of branches including at least one branch having only known elements; utilizing a model hook of an e-mail program to derive a normal element filter; applying the normal element filter to the DOM tree, the filter executing as a plug-in in a browser in a computing device; creating a modified DOM tree wherein the at least one branch having only known elements is excluded from the DOM tree and wherein the excluding of the at least one branch from the DOM tree is performed such that remaining branches of the DOM tree are still connected with one another; and applying a script analyzer filter to the modified DOM tree to create a final DOM tree having only unknown element types. 14. A method as recited in claim 10 further comprising: analyzing a template to determine where hooking points can be injected into the code. | 0.754438 |
15. The computer implemented method of claim 1 wherein identifying said one or more recognized elements further comprises performing a pattern search, said pattern search comprising locating known patterns in said resource from a database coupled to said proxy. | 15. The computer implemented method of claim 1 wherein identifying said one or more recognized elements further comprises performing a pattern search, said pattern search comprising locating known patterns in said resource from a database coupled to said proxy. 16. The computer implemented method of claim 15 wherein said pattern search is a search for links. | 0.936389 |
89. The apparatus of claim 88 , further comprising: means for automatically submitting a second query to the search engine, the second query based on the suggestion; wherein said suggestion is for an alternative spelling of a term within the first search input; and means for displaying, within the web browser application, a second results web page returned from the second query submitted to the search engine. | 89. The apparatus of claim 88 , further comprising: means for automatically submitting a second query to the search engine, the second query based on the suggestion; wherein said suggestion is for an alternative spelling of a term within the first search input; and means for displaying, within the web browser application, a second results web page returned from the second query submitted to the search engine. 90. The apparatus of claim 89 , wherein the first results web page is not displayed within the web browser application. | 0.883633 |
10. An influential users identifier for identifying influential users among a group of users associated with a communication network, wherein the identifier comprises: a ranking model selection module configured to select two or more ranking models and provide scores to the users in the group using said ranking models based on usage data of the users; a calculation module configured to calculate a weighing factor for each of the selected ranking models; and an aggregate score generation module configured to identify the influential users by: generating an aggregate score for each user using the weighing factor and the score provided by each one of the selected ranking models; and comparing the aggregate score with a predefined score. | 10. An influential users identifier for identifying influential users among a group of users associated with a communication network, wherein the identifier comprises: a ranking model selection module configured to select two or more ranking models and provide scores to the users in the group using said ranking models based on usage data of the users; a calculation module configured to calculate a weighing factor for each of the selected ranking models; and an aggregate score generation module configured to identify the influential users by: generating an aggregate score for each user using the weighing factor and the score provided by each one of the selected ranking models; and comparing the aggregate score with a predefined score. 12. The identifier according to claim 10 , wherein the aggregate score generation module is configured to: multiply the weighing factor of each model with the score provided by said model to a particular user so as to obtain a modified score; and add the modified scores obtained from two or more selected ranking models to obtain the aggregate score for each user. | 0.57026 |
1. An interactive toy that performs a method for interacting with a user, the method comprising: activating a phrase-detection state in which said toy is configured to receive a first plurality of audible sounds corresponding to text read aloud from a book; receiving, through a microphone embedded in the toy, the first plurality of audible sounds; processing a signal associated with the first plurality of audible sounds to detect one or more triggering phrases, wherein the one or more triggering phrases are a combination of words corresponding to text from the book; detecting a triggering phrase was read aloud by the user reading the book; upon detecting the triggering phrase, switching to a term-detection state in which said toy is configured to receive a second plurality of audible sounds; receiving, through the microphone, the second plurality of audible sounds; processing a signal associated with the second plurality of audible sounds to detect one or more single triggering terms, wherein the one or more single triggering terms are predetermined words or commands; detecting the one or more single triggering terms spoken by the user; and upon detecting the triggering term, activating a response sequence that supplements a story told in the book, wherein the response sequence is determined from a pre-programmed response program. | 1. An interactive toy that performs a method for interacting with a user, the method comprising: activating a phrase-detection state in which said toy is configured to receive a first plurality of audible sounds corresponding to text read aloud from a book; receiving, through a microphone embedded in the toy, the first plurality of audible sounds; processing a signal associated with the first plurality of audible sounds to detect one or more triggering phrases, wherein the one or more triggering phrases are a combination of words corresponding to text from the book; detecting a triggering phrase was read aloud by the user reading the book; upon detecting the triggering phrase, switching to a term-detection state in which said toy is configured to receive a second plurality of audible sounds; receiving, through the microphone, the second plurality of audible sounds; processing a signal associated with the second plurality of audible sounds to detect one or more single triggering terms, wherein the one or more single triggering terms are predetermined words or commands; detecting the one or more single triggering terms spoken by the user; and upon detecting the triggering term, activating a response sequence that supplements a story told in the book, wherein the response sequence is determined from a pre-programmed response program. 4. The method of claim 1 , wherein the response sequence is only activated when the triggering term is detected within a predetermined amount of time after activating the term-detection state. | 0.641554 |
1. A method for creating an audio file from a spoken utterance of a user, the method comprising: performing speech recognition on the spoken utterance to identify a verbally-added keyword or keyword combination from the spoken utterance; wherein the verbally-added keyword or keyword combination is associated with an audio effect to be performed on the spoken utterance to generate the audio file; and performing the audio effect on at least a portion of the spoken utterance to create the audio file. | 1. A method for creating an audio file from a spoken utterance of a user, the method comprising: performing speech recognition on the spoken utterance to identify a verbally-added keyword or keyword combination from the spoken utterance; wherein the verbally-added keyword or keyword combination is associated with an audio effect to be performed on the spoken utterance to generate the audio file; and performing the audio effect on at least a portion of the spoken utterance to create the audio file. 4. The method according to claim 1 , wherein the audio effect is to insert a sound or new audio file into the spoken utterance; and wherein, the performing the audio effect includes: inserting the sound or the new audio file into the spoken utterance to create the voice file. | 0.677757 |
1. A computer-implemented method performed by one or more processors, comprising: receiving, from a first device, a remote user status, wherein the remote user status is automatically determined based on an activity of the first device with an online application running on the first device; assigning the received remote user status to a current activity status of the first device to indicate the first device is active with the online application, wherein the current activity status identifies the online application; receiving, from a second device, a request to communicate with the first device; and providing, in response to the request, the first device's current activity status to the second device. | 1. A computer-implemented method performed by one or more processors, comprising: receiving, from a first device, a remote user status, wherein the remote user status is automatically determined based on an activity of the first device with an online application running on the first device; assigning the received remote user status to a current activity status of the first device to indicate the first device is active with the online application, wherein the current activity status identifies the online application; receiving, from a second device, a request to communicate with the first device; and providing, in response to the request, the first device's current activity status to the second device. 3. The method of claim 1 , further comprising: detecting an attempt at the first device to communicate with a second device; retrieving an activity status associated with the second device; and transmitting the retrieved activity status to the first device. | 0.654752 |
10. A computer program product for entity resolution between traditional and non-traditional datasets, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: create a deterministic model, comprising: defining an entity to be resolved; selecting two datasets for comparison, wherein a first of the two datasets is a traditional database comprising structured or semi-structured data, wherein a second of the two datasets is a non-traditional database comprising unstructured data; defining matching predicates for attributes of the two datasets to select a set of candidate matches; and defining at least one precedence rule for the candidate matches to select a subset of the candidate matches; run the deterministic model on the two datasets, the running comprising applying the matching predicates and the at least one precedence rule to data in the two datasets that correspond to the attributes; apply a cardinality rule to results of the running; output, via the processor, the matching candidates for which the cardinality rule is satisfied; create a probabilistic model, comprising: selecting records from the two datasets for comparison; implementing data derivation on the records, the data derivation resulting in standardized and bucketed data; defining blocking conditions for application to each of corresponding bucketed data; and defining a scoring rule for pairwise comparisons of the bucketed data; run the probabilistic model on the bucketed data; score results of the pairwise comparisons of the bucketed data; and combine the results of the deterministic model with the results of the probabilistic model. | 10. A computer program product for entity resolution between traditional and non-traditional datasets, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: create a deterministic model, comprising: defining an entity to be resolved; selecting two datasets for comparison, wherein a first of the two datasets is a traditional database comprising structured or semi-structured data, wherein a second of the two datasets is a non-traditional database comprising unstructured data; defining matching predicates for attributes of the two datasets to select a set of candidate matches; and defining at least one precedence rule for the candidate matches to select a subset of the candidate matches; run the deterministic model on the two datasets, the running comprising applying the matching predicates and the at least one precedence rule to data in the two datasets that correspond to the attributes; apply a cardinality rule to results of the running; output, via the processor, the matching candidates for which the cardinality rule is satisfied; create a probabilistic model, comprising: selecting records from the two datasets for comparison; implementing data derivation on the records, the data derivation resulting in standardized and bucketed data; defining blocking conditions for application to each of corresponding bucketed data; and defining a scoring rule for pairwise comparisons of the bucketed data; run the probabilistic model on the bucketed data; score results of the pairwise comparisons of the bucketed data; and combine the results of the deterministic model with the results of the probabilistic model. 12. The computer program product of claim 10 , wherein the attributes include geo-location indicators of a physical location of the entity; wherein the geo-location indicators reflect geographic coordinates of a current and temporary location of the entity that are retrieved from social media activity derived from one of the two datasets. | 0.61361 |
1. A method of recovering from an error in a speech recognition system, comprising: receiving, by a processor, a first command recognized from a first speech utterance by a first language model; receiving, by the processor, a second command recognized from the first speech utterance by a second language model; determining, by the processor, at least one of similarities and dissimilarities between the first command and the second command; determining, by the processor, a root cause by processing the first command and the second command with at least one rule of an error model based on the similarities and dissimilarities; and selectively executing a recovery process based on the root cause. | 1. A method of recovering from an error in a speech recognition system, comprising: receiving, by a processor, a first command recognized from a first speech utterance by a first language model; receiving, by the processor, a second command recognized from the first speech utterance by a second language model; determining, by the processor, at least one of similarities and dissimilarities between the first command and the second command; determining, by the processor, a root cause by processing the first command and the second command with at least one rule of an error model based on the similarities and dissimilarities; and selectively executing a recovery process based on the root cause. 6. The method of claim 1 further comprising retrieving the at least one rule of the error model based on the at least one of similarities and dissimilarities. | 0.645972 |
27. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristic of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristic of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein the emotion state of the speaker comprises at least one magnitude along a corresponding at least one of the one or more dimensions within the acoustic space. | 27. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristic of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristic of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein the emotion state of the speaker comprises at least one magnitude along a corresponding at least one of the one or more dimensions within the acoustic space. 48. The method according to claim 27 , wherein determining the emotion state of the speaker based on the comparison occurs within one minute of receiving the subject utterance of speech by the speaker. | 0.700951 |
22. A method of responding to a search query to a user with a computing system comprising: a) processing a query from a user concerning a first topic with the computing system; b) automatically determining a geographic region associated with said user with the computing system; c) automatically determining if said first topic query relates to one or more events occurring within said geographic region; wherein said determining is performed by analyzing published online content relating to said one or more events or updates to said event(s) with the computing system; d) automatically selecting first news content relating to said first topic with the computing system when said first topic query relates to said one or more events or updates to said event(s) occurring within said geographic region; and e) presenting search results to said user with the computing system for said query including optionally said first topic news content in response to said query directed to said first topic, wherein advertising is presented within said interface based on an expected mental state of said user predicted based on a state of an event identified in said first topic news content. | 22. A method of responding to a search query to a user with a computing system comprising: a) processing a query from a user concerning a first topic with the computing system; b) automatically determining a geographic region associated with said user with the computing system; c) automatically determining if said first topic query relates to one or more events occurring within said geographic region; wherein said determining is performed by analyzing published online content relating to said one or more events or updates to said event(s) with the computing system; d) automatically selecting first news content relating to said first topic with the computing system when said first topic query relates to said one or more events or updates to said event(s) occurring within said geographic region; and e) presenting search results to said user with the computing system for said query including optionally said first topic news content in response to said query directed to said first topic, wherein advertising is presented within said interface based on an expected mental state of said user predicted based on a state of an event identified in said first topic news content. 37. The method of claim 22 wherein said first topic news content is selected by analyzing a temporal rank of said news story relative to other stories from set of reference content sources that contain content for said one or more events or updates to said event(s). | 0.601493 |
1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech. | 1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech. 5. The method of claim 1 , wherein suppressing the further output of the text-to-speech engine comprises at least temporarily ceasing an audio output of the text-to-speech engine. | 0.709949 |
12. One or more processor-accessible storage media comprising processor-executable instructions that, when executed, direct a device to provide an interface comprising: an entry area to permit entry of a keyword string of one or more keywords, the keyword string being representative of a geographically-relevant object, wherein the geographically-relevant object is an object selected from a group of objects, the group of objects comprising map objects, image objects, and sensor objects; a module to identify, via the Web, geographical locations associated with the keyword string and to associate geographic-related information of the geographical location with the geographically-relevant object, by assigning a metadata tag derived from the keyword string to the geographically-relevant object wherein the metadata tag associates geographic-related information descriptors with the geographically-relevant object; and a correlating module, wherein the correlating module that correlates the geographic-related semantic information of the probable location with the geographically-relevant object, wherein the cluster function for computing a probable location from the multiple locations comprises: computing an initial center point as a statistical function that minimizes a sum of the square distances from the initial center point to each one of the multiple locations; removing spurious locations located greater than a predefined distance from a mean of the multiple locations; and computing the probable location for remaining ones of the multiple locations by minimizing a sum of the square distances from the probable location to each one of the remaining ones of the multiple locations. | 12. One or more processor-accessible storage media comprising processor-executable instructions that, when executed, direct a device to provide an interface comprising: an entry area to permit entry of a keyword string of one or more keywords, the keyword string being representative of a geographically-relevant object, wherein the geographically-relevant object is an object selected from a group of objects, the group of objects comprising map objects, image objects, and sensor objects; a module to identify, via the Web, geographical locations associated with the keyword string and to associate geographic-related information of the geographical location with the geographically-relevant object, by assigning a metadata tag derived from the keyword string to the geographically-relevant object wherein the metadata tag associates geographic-related information descriptors with the geographically-relevant object; and a correlating module, wherein the correlating module that correlates the geographic-related semantic information of the probable location with the geographically-relevant object, wherein the cluster function for computing a probable location from the multiple locations comprises: computing an initial center point as a statistical function that minimizes a sum of the square distances from the initial center point to each one of the multiple locations; removing spurious locations located greater than a predefined distance from a mean of the multiple locations; and computing the probable location for remaining ones of the multiple locations by minimizing a sum of the square distances from the probable location to each one of the remaining ones of the multiple locations. 15. The interface as recited in claim 12 , wherein the module further comprising an analysis unit to determine a probable location from the multiple possible locations and associate the geographic-related semantic information of the probable location to the geographically-relevant object. | 0.685466 |
10. A computer-implemented method for generating comparison output files indicating differences in annotations, the method comprising: create a first index for a first electronic file; identifying, by a processor, hidden characters for an insertion point and an end point of a first annotation in the first electronic file; identifying a first portion of the first index between the identified hidden characters; creating a second index for a second electronic file different than the first electronic file; comparing, by the processor, the identified first portion with the second electronic file, to determine whether the second electronic file contains a matching annotation corresponding to the first annotation; and generating, by the processor and based on the comparison, a comparison output file including information for displaying a modified appearance of characters in the first annotation to indicate that the second electronic file does not contain a matching annotation. | 10. A computer-implemented method for generating comparison output files indicating differences in annotations, the method comprising: create a first index for a first electronic file; identifying, by a processor, hidden characters for an insertion point and an end point of a first annotation in the first electronic file; identifying a first portion of the first index between the identified hidden characters; creating a second index for a second electronic file different than the first electronic file; comparing, by the processor, the identified first portion with the second electronic file, to determine whether the second electronic file contains a matching annotation corresponding to the first annotation; and generating, by the processor and based on the comparison, a comparison output file including information for displaying a modified appearance of characters in the first annotation to indicate that the second electronic file does not contain a matching annotation. 18. The computer-implemented method of claim 10 , further comprising: receiving the first electronic file for comparison, receiving the second electronic file for comparison, comparing the first electronic file with the second electronic file, and generating information for displaying, within the comparison output, differences between the first electronic file and the second electronic file. | 0.592415 |
16. The mobile device of claim 15 , wherein the one or more characters are Chinese characters of a Chinese language and each of the plurality of symbols is a Bopomofo symbol. | 16. The mobile device of claim 15 , wherein the one or more characters are Chinese characters of a Chinese language and each of the plurality of symbols is a Bopomofo symbol. 17. The mobile device of claim 16 , wherein the filtering engine disables the one or more symbols based on grammar rules of the Chinese language. | 0.932603 |
1. In a computing environment, a method for persisting data clippings categorized according to metadata associated with the clippings at the time of the creation of the clippings, the method comprising: detecting that a user has selected one or more items from a source file that is stored on a memory storage device, the items is captured for inclusion in a clipping; determining the format of each item included in the clipping, wherein at least one of the items includes a plurality of different formats where at least one of the plurality of different formats includes a greater amount of item formatting information than another format; identifying a file path for the source file from which the clipping was selected, the file path to access additional items from the source file; generating associated metadata about the selected clipping including the determined formats of each item in the selected clipping and an activatable hyperlink that, upon activation, is configured to access the source file using a stored file path linking the clipping to the source file; for each item of the clipping: determining that the items include a plurality of different formats, each different format including a greater or lesser amount of item formatting information in comparison to the other formats, such that a format with a greater or lesser amount of item formatting information than the format in which the item was initially captured for inclusion in the clipping is selectable by the user for inserting the item; persisting the item in the determined plurality of different formats based on item type along with the associated metadata, the item is configured for insertion into software application fields in any of the plurality of formats; and inserting the items into one or more data fields of a software application in a format different than the format in which the item was initially captured for inclusion in the clipping, the format is selected by the application and based on at least some of the associated metadata, the selected format for each item selected from among the plurality of formats the item was persisted in; receiving a user request to access one or more additional items from the source file; based on the received user request, activating the hyperlink to access the one or more additional items in the source file using the hyperlink provided in the associated metadata; and providing a user interface having a plurality of user-selectable views, wherein at least one of the user-selectable views displays a thumbnail in a user-preferred format corresponding to at least one of the clippings, and wherein at least one of the user-selectable views displays a list view including text corresponding to the clippings. | 1. In a computing environment, a method for persisting data clippings categorized according to metadata associated with the clippings at the time of the creation of the clippings, the method comprising: detecting that a user has selected one or more items from a source file that is stored on a memory storage device, the items is captured for inclusion in a clipping; determining the format of each item included in the clipping, wherein at least one of the items includes a plurality of different formats where at least one of the plurality of different formats includes a greater amount of item formatting information than another format; identifying a file path for the source file from which the clipping was selected, the file path to access additional items from the source file; generating associated metadata about the selected clipping including the determined formats of each item in the selected clipping and an activatable hyperlink that, upon activation, is configured to access the source file using a stored file path linking the clipping to the source file; for each item of the clipping: determining that the items include a plurality of different formats, each different format including a greater or lesser amount of item formatting information in comparison to the other formats, such that a format with a greater or lesser amount of item formatting information than the format in which the item was initially captured for inclusion in the clipping is selectable by the user for inserting the item; persisting the item in the determined plurality of different formats based on item type along with the associated metadata, the item is configured for insertion into software application fields in any of the plurality of formats; and inserting the items into one or more data fields of a software application in a format different than the format in which the item was initially captured for inclusion in the clipping, the format is selected by the application and based on at least some of the associated metadata, the selected format for each item selected from among the plurality of formats the item was persisted in; receiving a user request to access one or more additional items from the source file; based on the received user request, activating the hyperlink to access the one or more additional items in the source file using the hyperlink provided in the associated metadata; and providing a user interface having a plurality of user-selectable views, wherein at least one of the user-selectable views displays a thumbnail in a user-preferred format corresponding to at least one of the clippings, and wherein at least one of the user-selectable views displays a list view including text corresponding to the clippings. 5. The method of claim 1 wherein persisting the item in a plurality of formats based on item type along with the associated metadata includes persisting size information in association with at least some of the clippings. | 0.576822 |
19. A computer program product providing a tutoring agent comprising: a non-transitory computer useable medium having a computer readable program; wherein the computer readable program when executed on a computer causes the computer to: define one or more measurable science inquiry skills; measure the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; provide to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; and provide to the subject person guidance on how to better conduct scientific inquiry. | 19. A computer program product providing a tutoring agent comprising: a non-transitory computer useable medium having a computer readable program; wherein the computer readable program when executed on a computer causes the computer to: define one or more measurable science inquiry skills; measure the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; provide to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; and provide to the subject person guidance on how to better conduct scientific inquiry. 20. The computer program product of claim 19 , wherein the computer readable program when executed on the computer further causes the computer to generate a real-time communication to another person based upon the measurement of the one or more science inquiry skills, and, responsive to the real-time communication, the another person providing at least a portion of the real-time feedback to the subject person. | 0.59365 |
1. A method implemented by a computing device, the method comprising: identifying, by the computing device and for primary text located in a non-rectangular frame, one or more anchored text elements referenced in the primary text; and fitting, by the computing device, the one or more anchored text elements within the non-rectangular frame and at a bottom of the non-rectangular frame by iteratively repositioning the one or more anchored text elements, including: initially positioning the one or more anchored text elements at a top of the non-rectangular frame; and repositioning the one or more anchored text elements at a next computed position, including composing the one or more anchored text elements starting from the next computed position, until there are zero points of space between a bottom of the one or more anchored text elements and the bottom of the non-rectangular frame and until the one or more anchored text elements fit entirely within the non-rectangular frame. | 1. A method implemented by a computing device, the method comprising: identifying, by the computing device and for primary text located in a non-rectangular frame, one or more anchored text elements referenced in the primary text; and fitting, by the computing device, the one or more anchored text elements within the non-rectangular frame and at a bottom of the non-rectangular frame by iteratively repositioning the one or more anchored text elements, including: initially positioning the one or more anchored text elements at a top of the non-rectangular frame; and repositioning the one or more anchored text elements at a next computed position, including composing the one or more anchored text elements starting from the next computed position, until there are zero points of space between a bottom of the one or more anchored text elements and the bottom of the non-rectangular frame and until the one or more anchored text elements fit entirely within the non-rectangular frame. 2. A method as described in claim 1 , wherein the one or more anchored text elements each comprise a footnote or an endnote. | 0.636234 |
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