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1. A method comprising: receiving a set of keywords; determining a set of concepts corresponding to the set of keywords, wherein the determining the set of concepts comprises utilizing a general purpose knowledgebase and one or more of the set of concepts are associated with a score to indicate a probability that a term from the general purpose knowledgebase is a concept of a keyword of the set of keywords; obtaining context information corresponding to the set of keywords by: collecting snippets from search results obtained from a search engine; ranking a predetermined number of snippet words based at least in part on frequency of occurrence; and storing the predetermined number of highest ranked snippet words as the context information; determining a weight for a term based at least in part on the set of concepts and the context information; and performing hierarchical clustering to automatically generate a taxonomy based at least in part on the weight, the set of concepts and the context information. | 1. A method comprising: receiving a set of keywords; determining a set of concepts corresponding to the set of keywords, wherein the determining the set of concepts comprises utilizing a general purpose knowledgebase and one or more of the set of concepts are associated with a score to indicate a probability that a term from the general purpose knowledgebase is a concept of a keyword of the set of keywords; obtaining context information corresponding to the set of keywords by: collecting snippets from search results obtained from a search engine; ranking a predetermined number of snippet words based at least in part on frequency of occurrence; and storing the predetermined number of highest ranked snippet words as the context information; determining a weight for a term based at least in part on the set of concepts and the context information; and performing hierarchical clustering to automatically generate a taxonomy based at least in part on the weight, the set of concepts and the context information. 4. The method of claim 1 , wherein the obtaining the context information further comprises analyzing a set of the snippet words as a bag of words. | 0.86236 |
1. A method for associating a plurality of attributes and a plurality of values for a product within at least one natural language document to define attribute-value pairs, the method comprising: determining, by a computer, correlations between two or more attributes of the plurality of attributes; identifying at least one attribute phrase based on the correlations between the two or more attributes; determining correlations between two or more values of the plurality of values; identifying at least one value phrase based on the correlations between the two or more values; associating an attribute of the plurality of attributes or an attribute phrase of the at least one attribute phrase with a value of the plurality of values or a value phrase of the at least one value phrase based on syntactic dependency therebetween; and storing the attribute or attribute phrase and the associated value or value phrase as an attribute-value pair. | 1. A method for associating a plurality of attributes and a plurality of values for a product within at least one natural language document to define attribute-value pairs, the method comprising: determining, by a computer, correlations between two or more attributes of the plurality of attributes; identifying at least one attribute phrase based on the correlations between the two or more attributes; determining correlations between two or more values of the plurality of values; identifying at least one value phrase based on the correlations between the two or more values; associating an attribute of the plurality of attributes or an attribute phrase of the at least one attribute phrase with a value of the plurality of values or a value phrase of the at least one value phrase based on syntactic dependency therebetween; and storing the attribute or attribute phrase and the associated value or value phrase as an attribute-value pair. 2. The method of claim 1 , further comprising: determining correlations between another attribute of the plurality of attributes or another value phrase of the at least one value phrase and another value of the plurality of values or another value phrase of the at least one value phrase; associating the other attribute or the other attribute phrase with the other value or the other value phrase based on correlations therebetween; and storing the other attribute or other attribute phrase and the associated other value or other value phrase as another attribute-value pair. | 0.654719 |
10. A system comprising: at least one processor; and a computer storage medium encoding computer executable instructions that, when executed by the at least one processor perform a method comprising: receiving a message from a client for sending to a recipient; including a conversation identifier in the message; sending the message to the recipient; receiving a reply message that responds to the message, the reply message including the conversation identifier from the message; receiving a request for messages related to the conversation, wherein the request includes the conversation identifier; identifying the message and the reply message using the conversation identifier; in response to the request, sending information from the message and the reply message to the client; receiving an indication that the conversation is to be ignored; in response to receiving the selection to ignore the selected conversation, performing an ignore action on the conversation, wherein the ignore action comprises removing a plurality of previously displayed e-mail messages associated with the selected conversation from display; receiving a new message related to the conversation, wherein upon receiving the indication the new message will not be displayed; receiving a selection to change an ignore status; displaying a list of ignored conversations; receiving a selection of at least one ignored conversation from the list of ignored conversations; changing the ignore status of the at least one ignored conversation; and displaying the plurality of e-mail messages that were previously removed from display. | 10. A system comprising: at least one processor; and a computer storage medium encoding computer executable instructions that, when executed by the at least one processor perform a method comprising: receiving a message from a client for sending to a recipient; including a conversation identifier in the message; sending the message to the recipient; receiving a reply message that responds to the message, the reply message including the conversation identifier from the message; receiving a request for messages related to the conversation, wherein the request includes the conversation identifier; identifying the message and the reply message using the conversation identifier; in response to the request, sending information from the message and the reply message to the client; receiving an indication that the conversation is to be ignored; in response to receiving the selection to ignore the selected conversation, performing an ignore action on the conversation, wherein the ignore action comprises removing a plurality of previously displayed e-mail messages associated with the selected conversation from display; receiving a new message related to the conversation, wherein upon receiving the indication the new message will not be displayed; receiving a selection to change an ignore status; displaying a list of ignored conversations; receiving a selection of at least one ignored conversation from the list of ignored conversations; changing the ignore status of the at least one ignored conversation; and displaying the plurality of e-mail messages that were previously removed from display. 11. The system of claim 10 , wherein the conversation identifier is a Globally Unique Identifier (GUID). | 0.552048 |
14. The system of claim 10 , where the tag logic is further configured to determine if a document has linguistic tags, and where if the document does not have the linguistic tags the tag logic is configured to create linguistic tags for the document. | 14. The system of claim 10 , where the tag logic is further configured to determine if a document has linguistic tags, and where if the document does not have the linguistic tags the tag logic is configured to create linguistic tags for the document. 15. The system of claim 14 , where the value logic is configured to apply values to the linguistic tags in the document based, at least in part, on a source of the document. | 0.918424 |
14. The method of claim 1 , further comprising generating a prompt for additional input, based on the conclusion, the prompt included in a rendering of the structured document. | 14. The method of claim 1 , further comprising generating a prompt for additional input, based on the conclusion, the prompt included in a rendering of the structured document. 15. The method of claim 14 , further comprising: receiving input representing the content; and removing the prompt from the rendering of the structured document. | 0.899358 |
11. A system comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, cause the processor to: identify first text content on a first conversation medium; identify a plurality of available templates, each of the plurality of available templates including second text content; identify a plurality of available target sites, each of the plurality of available target sites including third text content; identify a first combination including a first template of the available templates, and a first target site of the available target sites; identify a second combination including a second template of the available templates, and a second target site of the available target sites; determine a first score based on a comparison of the second and third text contents of the first combination, against the first text content of the conversation; determine a second score based on a comparison of the second and third text contents of the second combination, against the first text content of the conversation; select one of the first or second combinations based on the first and second scores; and provide the second text of a selected template of the first and second templates corresponding to the selected combination, and a link to a selected target site of the first and second target sites corresponding to the selected combination, in the first conversation medium. | 11. A system comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, cause the processor to: identify first text content on a first conversation medium; identify a plurality of available templates, each of the plurality of available templates including second text content; identify a plurality of available target sites, each of the plurality of available target sites including third text content; identify a first combination including a first template of the available templates, and a first target site of the available target sites; identify a second combination including a second template of the available templates, and a second target site of the available target sites; determine a first score based on a comparison of the second and third text contents of the first combination, against the first text content of the conversation; determine a second score based on a comparison of the second and third text contents of the second combination, against the first text content of the conversation; select one of the first or second combinations based on the first and second scores; and provide the second text of a selected template of the first and second templates corresponding to the selected combination, and a link to a selected target site of the first and second target sites corresponding to the selected combination, in the first conversation medium. 19. The system of claim 11 , wherein the second text content of the selected template includes at least one of introductory words, themes, or prompts to take action. | 0.760116 |
6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. | 6. A computer program product comprising one or more computer-readable physical storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, the computing system is caused to perform a method for identifying validation errors in a visual representation of a graphical model, the graphical model comprising one or more objects that include interrelationship, at least some of the objects capable of being visualized on a display, the method comprising: reading a constraint that comprises one or more rules that the graphical model must adhere to in order to comply with the declarative constraint, the one or more rules specifying how the graphical model should function, and the one or more rules specifying properties, parameters, and relationships that objects of the graphical model should adhere to; imposing the constraint on the graphical model; identifying an object in the graphical model that does not conform with one or more rules of the constraint imposed on the graphical model; reading a declarative definition of the graphical model to ascertain a declarative relationship between the non-conforming object of the graphical model and its visual representation that is rendered on a display, the declarative definition including shapes, types, connectors, and decorators; interpreting the declarative relationship between the non-conforming object of the graphical model and its visual representation to formulate underlying code that when executed causes the computing system to provide a visually distinct attribute related to the visual representation on the display; and causing the computing system to execute the underlying code. 13. The computer program product in accordance with claim 6 , wherein the one or more computer-readable physical storage media is one of physical memory media and physical storage media. | 0.744334 |
1. A method for persistently linking sources to text copied from the sources, the method comprising: a processor displaying a first electronic document, said displaying comprising displaying first text appearing in the first electronic document; said processor obtaining, from a web page differing from the first electronic document, both selected text and an address of a source electronic document that comprises the selected text in a temporary computer object; said processor generating the temporary computer object that includes the selected text and persistently links the selected text with the source electronic document object, said generating the temporary computer object comprising generating a header in the temporary computer object, said generating the header in the temporary computer object comprising: copying a first tag, a second tag, and the obtained address of the source electronic document into the header of the temporary computer object, wherein the first tag marks the beginning of the header and the second tag marks the end of the header, wherein the address of the source electronic document is disposed between the first tag and the second tag in the header, wherein the header consists of the first tag, an identifier of the temporary computer object, an attribute pertaining to the address of the source electronic document, the address of the source electronic document paired in the header with the attribute, additional information pertaining to the source electronic document, and the second tag, and wherein the additional information consists of an author of the source electronic document, a date of creation of the source electronic document, and an owner of the intellectual property rights of the source electronic document; said processor copying the obtained selected text into the temporary computer object; said processor copying a third tag into the temporary computer object, wherein the third tag marks the end of the temporary computer object, and wherein the selected text is disposed between the header of the temporary computer object and the third tag, wherein the selected text in the temporary computer object is persistently linked with the source electronic document via the address of the source electronic document in the temporary computer object; said processor storing the temporary computer object in the first electronic document after the first text, wherein the temporary computer object in the first electronic document persistently links the selected text with the source electronic document that comprises the selected text. | 1. A method for persistently linking sources to text copied from the sources, the method comprising: a processor displaying a first electronic document, said displaying comprising displaying first text appearing in the first electronic document; said processor obtaining, from a web page differing from the first electronic document, both selected text and an address of a source electronic document that comprises the selected text in a temporary computer object; said processor generating the temporary computer object that includes the selected text and persistently links the selected text with the source electronic document object, said generating the temporary computer object comprising generating a header in the temporary computer object, said generating the header in the temporary computer object comprising: copying a first tag, a second tag, and the obtained address of the source electronic document into the header of the temporary computer object, wherein the first tag marks the beginning of the header and the second tag marks the end of the header, wherein the address of the source electronic document is disposed between the first tag and the second tag in the header, wherein the header consists of the first tag, an identifier of the temporary computer object, an attribute pertaining to the address of the source electronic document, the address of the source electronic document paired in the header with the attribute, additional information pertaining to the source electronic document, and the second tag, and wherein the additional information consists of an author of the source electronic document, a date of creation of the source electronic document, and an owner of the intellectual property rights of the source electronic document; said processor copying the obtained selected text into the temporary computer object; said processor copying a third tag into the temporary computer object, wherein the third tag marks the end of the temporary computer object, and wherein the selected text is disposed between the header of the temporary computer object and the third tag, wherein the selected text in the temporary computer object is persistently linked with the source electronic document via the address of the source electronic document in the temporary computer object; said processor storing the temporary computer object in the first electronic document after the first text, wherein the temporary computer object in the first electronic document persistently links the selected text with the source electronic document that comprises the selected text. 4. The method of claim 1 , wherein the first text is a first portion of an electronic message, wherein said displaying the first electronic document comprises displaying a cursor at a cursor position after the first text for receiving an additional portion of the message at the cursor position, and wherein said storing the temporary computer object in the first electronic document comprises storing the temporary computer object at the cursor position in the first electronic document, wherein the stored temporary computer object is the additional portion of the message at the cursor position. | 0.529046 |
1. A skew detection apparatus, comprising: a data storage device to store a document; a hardware processor to: generate a first estimate of a skew angle based on an alignment of peripheral boundary points of the document or an alignment of peripheral boundary points of foreground content of the document; generate a second estimate of the skew angle based on an orientation of foreground or background content in an interior of the document; generate a combined estimate of the skew angle, based on at least one of the first and second estimates; and determine a confidence value of the combined estimate of the skew angle, wherein to determine the confidence value, the hardware processor is to: determine an angle of a line joining two pixels for each side of the image; calculate a side confidence value for each angle; combine the angles by clustering them into groups; calculate a group confidence value for each group based on a sum of the side confidence values of the angles in the group; select the group having a highest group confidence value; and estimate the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value. | 1. A skew detection apparatus, comprising: a data storage device to store a document; a hardware processor to: generate a first estimate of a skew angle based on an alignment of peripheral boundary points of the document or an alignment of peripheral boundary points of foreground content of the document; generate a second estimate of the skew angle based on an orientation of foreground or background content in an interior of the document; generate a combined estimate of the skew angle, based on at least one of the first and second estimates; and determine a confidence value of the combined estimate of the skew angle, wherein to determine the confidence value, the hardware processor is to: determine an angle of a line joining two pixels for each side of the image; calculate a side confidence value for each angle; combine the angles by clustering them into groups; calculate a group confidence value for each group based on a sum of the side confidence values of the angles in the group; select the group having a highest group confidence value; and estimate the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value. 2. The skew detection apparatus of claim 1 , wherein a skew detection function of the apparatus can be manually enabled and/or disabled by user-input. | 0.675944 |
13. A method comprising: under control of one or more computing devices configured with executable instructions, receiving a first audio signal generated by a microphone of a device residing in an environment; identifying, from the audio signal, a voice command uttered by a user in the environment; causing the device to perform a first operation specified by the voice command; identifying, from a subsequent audio signal generated by the microphone of the device, subsequent speech uttered within the environment at least partly while the device performs the first operation, the subsequent speech requesting that the device perform a second operation related to the first operation; determining whether that the user uttered the subsequent speech or whether that another user in the environment uttered the subsequent speech; interpreting the subsequent speech as a valid voice command at least partly in response to determining that the user uttered the subsequent speech; and refraining from interpreting the subsequent speech as a valid voice command at least partly in response to determining that another user in the environment uttered the subsequent speech. | 13. A method comprising: under control of one or more computing devices configured with executable instructions, receiving a first audio signal generated by a microphone of a device residing in an environment; identifying, from the audio signal, a voice command uttered by a user in the environment; causing the device to perform a first operation specified by the voice command; identifying, from a subsequent audio signal generated by the microphone of the device, subsequent speech uttered within the environment at least partly while the device performs the first operation, the subsequent speech requesting that the device perform a second operation related to the first operation; determining whether that the user uttered the subsequent speech or whether that another user in the environment uttered the subsequent speech; interpreting the subsequent speech as a valid voice command at least partly in response to determining that the user uttered the subsequent speech; and refraining from interpreting the subsequent speech as a valid voice command at least partly in response to determining that another user in the environment uttered the subsequent speech. 20. A method as recited in claim 13 , wherein the attempting comprises comparing past voice commands uttered by the user to one or more characteristics associated with the subsequent speech. | 0.703514 |
4. A method according to claim 1 , wherein the word substitution model derives probabilities by a log-linear combination of one or more feature functions. | 4. A method according to claim 1 , wherein the word substitution model derives probabilities by a log-linear combination of one or more feature functions. 5. A method according to claim 4 , wherein the word substitution model includes interpolation parameters. | 0.953953 |
3. A computer-implemented method for adding knowledge to a knowledge base, the knowledge base including a plurality of known entity objects and a plurality of known relation objects represented in a machine-readable format of the knowledge base, the knowledge base also including a plurality of known facts, each known fact including one of the known relation objects and at least one of the known entity objects, the method comprising: identifying known strings of text from textual information based on corresponding known facts in the knowledge base that relate each of the known strings of text to one or more of the known entity objects or one or more of the known relation objects; identifying candidate strings of text from the textual information based on correspondence of each of the candidate strings of text to at least one of a plurality of entity classes represented in the knowledge base; generating candidate entity objects in the machine-readable format of the knowledge base based on the candidate strings of text; based on natural language processing of the textual information, identifying relationships among the strings of text corresponding to the known entity objects, the known relation objects, and the candidate entity objects; generating candidate facts using the known entity objects, the known relation objects, and the candidate entity objects and based on the relationships among the known and candidate strings of text in the textual information; identifying temporal information in the textual information, the temporal information being a natural language representation of time; generating a temporal constraint from the temporal information for at least one of the candidate facts using the machine-readable format of the knowledge base, the temporal constraint representing a time or a period of time during which the corresponding candidate fact is valid; and adding at least some of the candidate facts to the knowledge base. | 3. A computer-implemented method for adding knowledge to a knowledge base, the knowledge base including a plurality of known entity objects and a plurality of known relation objects represented in a machine-readable format of the knowledge base, the knowledge base also including a plurality of known facts, each known fact including one of the known relation objects and at least one of the known entity objects, the method comprising: identifying known strings of text from textual information based on corresponding known facts in the knowledge base that relate each of the known strings of text to one or more of the known entity objects or one or more of the known relation objects; identifying candidate strings of text from the textual information based on correspondence of each of the candidate strings of text to at least one of a plurality of entity classes represented in the knowledge base; generating candidate entity objects in the machine-readable format of the knowledge base based on the candidate strings of text; based on natural language processing of the textual information, identifying relationships among the strings of text corresponding to the known entity objects, the known relation objects, and the candidate entity objects; generating candidate facts using the known entity objects, the known relation objects, and the candidate entity objects and based on the relationships among the known and candidate strings of text in the textual information; identifying temporal information in the textual information, the temporal information being a natural language representation of time; generating a temporal constraint from the temporal information for at least one of the candidate facts using the machine-readable format of the knowledge base, the temporal constraint representing a time or a period of time during which the corresponding candidate fact is valid; and adding at least some of the candidate facts to the knowledge base. 6. The method of claim 3 , wherein a subset of the candidate facts associates two of the known entity objects with one of the known relation objects, the method further comprising filtering the subset of the candidate facts to remove preexisting facts already represented in the knowledge base. | 0.886012 |
21. A computer system comprising a processor, a memory, and a computer readable hardware storage device, said storage device containing program code configured to be executed by the processor via the memory to implement a method of text entry, said method comprising: said processor receiving, via a text entry program that provides a type-ahead feature for multiple applications, first text entered by a user, said received first text comprising a plurality of words; said processor entering, via the text entry program, the received first text into a first application; after said entering the received first text, said processor matching, via the text entry program, the received first text to one portion of each indexed segment of text of a plurality of indexed segments of text, said matching being based on matching rules, each indexed segment of text consisting of the one portion and a remaining portion; in response to said matching, said processor displaying to the user the plurality of indexed segments of text; said processor receiving from the user a selection of an indexed segment of text of the displayed plurality of indexed segments of text; in response to said receiving the selection from the user of the indexed segment of text of the displayed plurality of indexed segments of text, said processor entering into the first application, via the text entry program, the remaining portion of the selected indexed segment of text to auto-complete the received first text entered into the first application which results in auto-completed text in the first application, wherein the auto-completed text in the first application consists of (i) the received first text entered into the first application before said matching and (ii) the remaining portion of the selected indexed segment of text entered into the first application in response to said receiving the selection, and wherein the auto-completed text in the first application matches the selected indexed segment of text; said processor receiving second text entered by the user; said processor matching the second text to a portion of the first text, said first text consisting of the second text and a remaining portion of the first text, said remaining portion being a finite portion of the first text; said processor entering, via the text entry program, the received second text into a second application, said first and second applications being different applications; and after said entering the received second text into the second application, said processor entering, via the text entry program, into the second application the remaining portion of the first text to auto-complete the received second text entered into the second application which results in auto-completed text in the second application, wherein the auto-completed text in the second application consists of (i) the received second text entered into the second application and (ii) the remaining portion of the first text, and wherein the auto-completed text in the second application matches the first text. | 21. A computer system comprising a processor, a memory, and a computer readable hardware storage device, said storage device containing program code configured to be executed by the processor via the memory to implement a method of text entry, said method comprising: said processor receiving, via a text entry program that provides a type-ahead feature for multiple applications, first text entered by a user, said received first text comprising a plurality of words; said processor entering, via the text entry program, the received first text into a first application; after said entering the received first text, said processor matching, via the text entry program, the received first text to one portion of each indexed segment of text of a plurality of indexed segments of text, said matching being based on matching rules, each indexed segment of text consisting of the one portion and a remaining portion; in response to said matching, said processor displaying to the user the plurality of indexed segments of text; said processor receiving from the user a selection of an indexed segment of text of the displayed plurality of indexed segments of text; in response to said receiving the selection from the user of the indexed segment of text of the displayed plurality of indexed segments of text, said processor entering into the first application, via the text entry program, the remaining portion of the selected indexed segment of text to auto-complete the received first text entered into the first application which results in auto-completed text in the first application, wherein the auto-completed text in the first application consists of (i) the received first text entered into the first application before said matching and (ii) the remaining portion of the selected indexed segment of text entered into the first application in response to said receiving the selection, and wherein the auto-completed text in the first application matches the selected indexed segment of text; said processor receiving second text entered by the user; said processor matching the second text to a portion of the first text, said first text consisting of the second text and a remaining portion of the first text, said remaining portion being a finite portion of the first text; said processor entering, via the text entry program, the received second text into a second application, said first and second applications being different applications; and after said entering the received second text into the second application, said processor entering, via the text entry program, into the second application the remaining portion of the first text to auto-complete the received second text entered into the second application which results in auto-completed text in the second application, wherein the auto-completed text in the second application consists of (i) the received second text entered into the second application and (ii) the remaining portion of the first text, and wherein the auto-completed text in the second application matches the first text. 25. The computer system of claim 21 , said method further comprising: said processor receiving selection rules for selecting text; said processor selecting text in accordance with the received selection rules; and before said receiving first text entered by the user, said processor indexing the selected text to generate multiple indexed segments of text which include the plurality of indexed segments of text. | 0.50339 |
1. A method comprising: receiving from a user, an utterance in a first language that is to be translated by a speech translation system from the first language to a second language; receiving, an indication to add a new word in the first language to a first recognition lexicon of the first language of a first automatic speech recognition module of the speech translation system; determining for the new word, by a processor, word class information, a pronunciation in the first language, a translation in the second language, and a pronunciation in the second language in response to receiving the indication to add the new word; adding the new word the determined word class information and the determined pronunciation in the first language to the first recognition lexicon of the first language of the first automatic speech recognition module; and adding the new word, the determined word class information, the determined translation in the second language and the pronunciation of the translation in the second language, to a first machine translation module associated with the first language of the speech translation system. | 1. A method comprising: receiving from a user, an utterance in a first language that is to be translated by a speech translation system from the first language to a second language; receiving, an indication to add a new word in the first language to a first recognition lexicon of the first language of a first automatic speech recognition module of the speech translation system; determining for the new word, by a processor, word class information, a pronunciation in the first language, a translation in the second language, and a pronunciation in the second language in response to receiving the indication to add the new word; adding the new word the determined word class information and the determined pronunciation in the first language to the first recognition lexicon of the first language of the first automatic speech recognition module; and adding the new word, the determined word class information, the determined translation in the second language and the pronunciation of the translation in the second language, to a first machine translation module associated with the first language of the speech translation system. 7. The method of claim 1 , further comprising: displaying simultaneously in text, on a user interface display of the speech translation system, at least (i) recognized speech in the utterance in the first language, and (ii) the translation into the second language of the speech in the utterance; storing, by the speech translation system, a bilingual sentence-pair selected by the user via the user interface display, as a speech translation favorite, wherein the bilingual sentence pair comprises a sentence in the first language uttered by the user in a first dialog and a translation of the sentence from the first language into the second language; and playing the translation of the sentence into the second language upon selection by the user to play the translation of the sentence into the second language in a second dialog that is after the first dialog, without the user having to speak the sentence in the second dialog. | 0.614015 |
14. The computer program product of claim 10 , wherein the user interaction with the one or more content items associated with the digital magazine includes a length of time to interact with a content item based at least in part on prior interactions between the user and content items associated with the digital magazine previously presented to the user. | 14. The computer program product of claim 10 , wherein the user interaction with the one or more content items associated with the digital magazine includes a length of time to interact with a content item based at least in part on prior interactions between the user and content items associated with the digital magazine previously presented to the user. 15. The computer program product of claim 14 , wherein the length of time to interact with the content item is further based at least in part on one or more attributes of the client device. | 0.945172 |
7. The computer-implemented method of claim 1 , wherein creating the graphical data structure comprises incorporating factor nodes as computational units into the graphical data structure, each factor node having at least one associated computational message. | 7. The computer-implemented method of claim 1 , wherein creating the graphical data structure comprises incorporating factor nodes as computational units into the graphical data structure, each factor node having at least one associated computational message. 8. The computer-implemented method of claim 7 , wherein the statistics for the at least one of the variable nodes are updated by using messaging passing that includes computing the computational messages and passing results of the computations to variable nodes in the graphical data structure. | 0.87989 |
1. A method of translating printed text using a handheld display device having an image sensor, a transceiver and an opaque touch-sensitive screen, said method comprising the steps of: overlaying said device on part of said printed substrate; imaging an area of a printed substrate containing printed text in a first language and generating image data using the image sensor; determining interaction data using said image data, said interaction data identifying a page description corresponding to the printed substrate; sending the interaction data to a computer system, thereby causing the computer system to identify the page description and retrieve display data corresponding to said printed text translated into a second language; receiving the display data from the computer system; displaying, on said opaque touch-sensitive screen, display information based on said display data, said display information comprising displayed text corresponding to said printed text translated into said second language, said displayed text being aligned with the printed text underlying said screen, such that the opaque touch-sensitive screen has real-time virtual transparency through the screen to the printed content underlying said screen from a user's perspective to provide a virtual window to the printed content underlying said screen. | 1. A method of translating printed text using a handheld display device having an image sensor, a transceiver and an opaque touch-sensitive screen, said method comprising the steps of: overlaying said device on part of said printed substrate; imaging an area of a printed substrate containing printed text in a first language and generating image data using the image sensor; determining interaction data using said image data, said interaction data identifying a page description corresponding to the printed substrate; sending the interaction data to a computer system, thereby causing the computer system to identify the page description and retrieve display data corresponding to said printed text translated into a second language; receiving the display data from the computer system; displaying, on said opaque touch-sensitive screen, display information based on said display data, said display information comprising displayed text corresponding to said printed text translated into said second language, said displayed text being aligned with the printed text underlying said screen, such that the opaque touch-sensitive screen has real-time virtual transparency through the screen to the printed content underlying said screen from a user's perspective to provide a virtual window to the printed content underlying said screen. 15. The method of claim 1 further comprising the step of: printing onto said substrate using a printer integrated with said handheld display device. | 0.57925 |
9. The system of claim 7 , further comprising a pull model parser comprising a subset of the extractor, the parser, the metadata retriever, a syntax analyzer, the semantic analyzer and a style analyzer. | 9. The system of claim 7 , further comprising a pull model parser comprising a subset of the extractor, the parser, the metadata retriever, a syntax analyzer, the semantic analyzer and a style analyzer. 10. The system of claim 9 , the extractor, the parser, the metadata retriever, the syntax analyzer, the semantic analyzer and the style analyzer are stand alone units. | 0.806402 |
4. The method of claim 3 , wherein when the user response indicates a preference to use the original command, the substitute command is stored as a secondary command for the user-defined speech command, wherein both the original command and the substitute command are able to be used to initiate a set of actions associated with the user-defined speech command. | 4. The method of claim 3 , wherein when the user response indicates a preference to use the original command, the substitute command is stored as a secondary command for the user-defined speech command, wherein both the original command and the substitute command are able to be used to initiate a set of actions associated with the user-defined speech command. 5. The method of claim 4 , wherein the at least one processor is further programmed to perform: when presenting a prompt relating to the user-defined speech command, presenting the substitute as a trigger for the user-defined speech command instead of presenting the original command. | 0.7397 |
11. The electronic device of claim 10 , wherein generating the dictionary comprises storing, as language objects of the dictionary, words found in messages associated with the message thread. | 11. The electronic device of claim 10 , wherein generating the dictionary comprises storing, as language objects of the dictionary, words found in messages associated with the message thread. 12. The electronic device of claim 11 , wherein the language objects are associated with frequency objects containing frequency values for the language objects. | 0.832242 |
1. A computer-implemented method for providing, via a computer processor, at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the method comprising: extracting, via the computer processor, the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping, via the computer processor, the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating, via the computer processor, the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. | 1. A computer-implemented method for providing, via a computer processor, at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the method comprising: extracting, via the computer processor, the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping, via the computer processor, the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating, via the computer processor, the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. 25. The computer-implemented method of claim 1 , wherein the structured data object comprises a business object of an enterprise resource planning (ERP) software. | 0.597056 |
9. A system for differential dynamic content delivery, the system comprising a computer processor operatively coupled to a computer memory, the computer memory including computer program instructions that, upon being executed by the processor, cause the system to carry out the steps of: providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; providing a session copy of a user profile including a user classification; creating a presentation control instruction, including: receiving from a user participating in the presentation a key phrase and optional parameters for invoking a presentation action; parsing the key phrase and parameters against a voice response grammar into a presentation control instruction; and the presentation control instruction includes a presentation action identifier and optional parameters; receiving, from a presenter, a user classification instruction to change a user classification in the session copy of a user profile; changing the user classification in the session copy of a user profile in dependence upon the presenter's instruction; selecting from the session structured document a classified structural element in dependence upon a user classification in the session copy of a user profile of a user in the presentation, the presentation action identifier, and the parameters received as part of the presentation control instruction; and presenting the selected structural element to the user. | 9. A system for differential dynamic content delivery, the system comprising a computer processor operatively coupled to a computer memory, the computer memory including computer program instructions that, upon being executed by the processor, cause the system to carry out the steps of: providing a session document for a presentation, wherein the session document includes a session grammar and a session structured document; providing a session copy of a user profile including a user classification; creating a presentation control instruction, including: receiving from a user participating in the presentation a key phrase and optional parameters for invoking a presentation action; parsing the key phrase and parameters against a voice response grammar into a presentation control instruction; and the presentation control instruction includes a presentation action identifier and optional parameters; receiving, from a presenter, a user classification instruction to change a user classification in the session copy of a user profile; changing the user classification in the session copy of a user profile in dependence upon the presenter's instruction; selecting from the session structured document a classified structural element in dependence upon a user classification in the session copy of a user profile of a user in the presentation, the presentation action identifier, and the parameters received as part of the presentation control instruction; and presenting the selected structural element to the user. 10. The system of claim 9 wherein only the presenter is authorized to change a user classification in the session copy of the user profile. | 0.646083 |
8. A computer system for protecting one or more server computers by identifying a resource on a client computer comprising: one or more hardware processors; a memory coupled to the one or more hardware processors and storing one or more instructions, which when executed by the one or more hardware processors cause the one or more hardware processors to: supplement a set of web code with a set of instrumentation code, which when executed on the client computer collects a set of information that describes a document object model created by the client computer after the client computer executes the set of web code; send the set of web code and the set of instrumentation code to the client computer; receive the set of information from the client computer; identify the resource on the client computer based on the set of information that describes the document object model. | 8. A computer system for protecting one or more server computers by identifying a resource on a client computer comprising: one or more hardware processors; a memory coupled to the one or more hardware processors and storing one or more instructions, which when executed by the one or more hardware processors cause the one or more hardware processors to: supplement a set of web code with a set of instrumentation code, which when executed on the client computer collects a set of information that describes a document object model created by the client computer after the client computer executes the set of web code; send the set of web code and the set of instrumentation code to the client computer; receive the set of information from the client computer; identify the resource on the client computer based on the set of information that describes the document object model. 10. The computer system of claim 8 , wherein the one or more instructions, when executed, cause the one or more hardware processors to determine that the resource is a malicious resource, and in response, terminate one or more requests for one or more sets of data from the client computer without sending the one or more sets of data to the client computer. | 0.600709 |
36. An apparatus, comprising: means for receiving a query expression specifying a set of information to be retrieved; means for checking for the presence of a cache file related to a database file, the database file including at least the specified set of information, wherein the cache file comprises one or more subsets of information from the database file and one or more query expressions, wherein each one of the one or more subsets of information is stored in the cache file in association with a different one of the one or more query expressions, and wherein each one of the one or more subsets of information is a result of parsing the database file according to a corresponding one of the one or query expressions; means for, in response to determining that the cache file is present: determining whether the specified set of information is present in the cache file; means for, in response to determining that the specified set of information is present in the cache file; determining whether the cache file is valid based, wherein said determining whether the cache file is valid comprises examining, on a currency token stored in association with the cache file, wherein the currency token indicates an attribute of the database file at a time when the database file was parsed according to one or more query expressions that are stored in the cache file; means for, in response to determining that the cache file is valid: retrieving the specified set of information from an entry in the cache file, wherein the entry is associated with one of the one or more query expression. | 36. An apparatus, comprising: means for receiving a query expression specifying a set of information to be retrieved; means for checking for the presence of a cache file related to a database file, the database file including at least the specified set of information, wherein the cache file comprises one or more subsets of information from the database file and one or more query expressions, wherein each one of the one or more subsets of information is stored in the cache file in association with a different one of the one or more query expressions, and wherein each one of the one or more subsets of information is a result of parsing the database file according to a corresponding one of the one or query expressions; means for, in response to determining that the cache file is present: determining whether the specified set of information is present in the cache file; means for, in response to determining that the specified set of information is present in the cache file; determining whether the cache file is valid based, wherein said determining whether the cache file is valid comprises examining, on a currency token stored in association with the cache file, wherein the currency token indicates an attribute of the database file at a time when the database file was parsed according to one or more query expressions that are stored in the cache file; means for, in response to determining that the cache file is valid: retrieving the specified set of information from an entry in the cache file, wherein the entry is associated with one of the one or more query expression. 37. The apparatus of claim 36 , wherein the means for determining whether the specified set of information is present in the cache file comprises means for determining whether the received query expression is present in the cache file. | 0.580259 |
18. One or more processor readable storage devices having processor readable code embodied on the processor readable storage devices, the processor readable code for programming one or more processors to perform a method comprising: receiving a first input at a user interface of a computing device for a first field of a natural language expression, the first input indicates a first data value for the first field; accessing options for a second field of the natural language expression that are determined based on the first data value and data stored in data group; displaying the second field and the options for the second field; receiving a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field; accessing options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group; displaying the third field and the options for the third field; receiving a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language; and accessing and reporting a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. | 18. One or more processor readable storage devices having processor readable code embodied on the processor readable storage devices, the processor readable code for programming one or more processors to perform a method comprising: receiving a first input at a user interface of a computing device for a first field of a natural language expression, the first input indicates a first data value for the first field; accessing options for a second field of the natural language expression that are determined based on the first data value and data stored in data group; displaying the second field and the options for the second field; receiving a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field; accessing options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group; displaying the third field and the options for the third field; receiving a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language; and accessing and reporting a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. 20. One or more processor readable storage devices according to claim 18 , wherein the method further comprises: monitoring performance of a software system; and collecting and storing performance data of the software system based on the monitoring, the stored performance data is the data group. | 0.776254 |
7. A system for managing interactions with a person, comprising non-transitory computer storage media storing programming instructions executable by at least one processor for: receiving data representing an input from a person; using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions related to the input; accepting an intent from the intent analyst through the analyst user interface; providing the information and the intent to a training subsystem; accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent; accepting from the training ASR statistics generated responsive to the information; and training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof. | 7. A system for managing interactions with a person, comprising non-transitory computer storage media storing programming instructions executable by at least one processor for: receiving data representing an input from a person; using a processor, automatically presenting information relating to the input to an intent analyst through a graphical analyst user interface, the information presented in the graphical analyst user interface comprising at least one of: an output produced responsive to the received data, location information corresponding to the person, historical information corresponding to the person, characteristics of the person, and prior interactions related to the input; accepting an intent from the intent analyst through the analyst user interface; providing the information and the intent to a training subsystem; accepting from the training subsystem a training model used by a training automated speech recognizer (ASR), the training ASR generated responsive to the information and the intent; accepting from the training ASR statistics generated responsive to the information; and training, via the statistics, a second model used by a real-time ASR in order to improve performance thereof. 9. The system of claim 7 , wherein the training comprises testing performance of the real-time ASR and continuing training responsive to the performance not exceeding a performance threshold. | 0.642317 |
35. The computer program product of claim 31 , wherein embedding the character set information comprises embedding the character set information in a vendor-specific information element. | 35. The computer program product of claim 31 , wherein embedding the character set information comprises embedding the character set information in a vendor-specific information element. 37. The computer program product of claim 35 , wherein the vendor-specific information element comprises at least an element ID field, a length field, an organizationally unique identifier field, and a data field. | 0.875969 |
7. A non-transitory computer-readable storage medium storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to: receive a query that includes one or more terms; identify, using the one or more terms, search results; determine an attribute identifier that identifies an attribute to be used in ranking the search results, the attribute being different from a measure of relevance of the search results to the query; calculate a combined score for each search result, included in the search results, based on an attribute value associated with the attribute and a value corresponding to the measure of relevance of the search result to the query; rank the search results based on the combined score calculated for each search result to obtain a first ranking of search results; divide, based on a threshold measure of relevancy, the first ranking of search results into a first subset of ranked search results and a second subset of ranked search results; rank search results included in the first subset of ranked search results and search results included in the second subset of ranked search results based on the attribute value to obtain a second ranking of search results, each of the search results included in the first subset of ranked search results being ranked relative only to other ones of the search results included in the first subset of ranked search results, and each of the search results included in the second subset of ranked search results being ranked relative only to other ones of the search results included in the second subset of ranked search results; and provide the second ranking of search results. | 7. A non-transitory computer-readable storage medium storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to: receive a query that includes one or more terms; identify, using the one or more terms, search results; determine an attribute identifier that identifies an attribute to be used in ranking the search results, the attribute being different from a measure of relevance of the search results to the query; calculate a combined score for each search result, included in the search results, based on an attribute value associated with the attribute and a value corresponding to the measure of relevance of the search result to the query; rank the search results based on the combined score calculated for each search result to obtain a first ranking of search results; divide, based on a threshold measure of relevancy, the first ranking of search results into a first subset of ranked search results and a second subset of ranked search results; rank search results included in the first subset of ranked search results and search results included in the second subset of ranked search results based on the attribute value to obtain a second ranking of search results, each of the search results included in the first subset of ranked search results being ranked relative only to other ones of the search results included in the first subset of ranked search results, and each of the search results included in the second subset of ranked search results being ranked relative only to other ones of the search results included in the second subset of ranked search results; and provide the second ranking of search results. 9. The non-transitory computer-readable storage medium of claim 7 , wherein the attribute identifier includes one or more of: a price; a rating; an image size; an image resolution; a video length; an audio length; a text length; a file size; a date; a time; or an expiration date. | 0.551813 |
1. A method for retrieving a solution document in response to an inquiry from among a system of distributed data bases, the system having at least a first and a second computer, each computer having a data base of solution documents, the method comprising the steps of: receiving at least one inquiry into the first computer, the inquiry having a subject; searching the data base of the first computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the first computer related to the subject of the inquiry, retrieving the solution document from the first computer; responsive to finding no solution document in the data base of the first computer related to the subject of the inquiry, performing the steps of: generating in the first computer, a document from at least one inquiry in the first computer for which no solution document was found, the document containing for each such inquiry the subject of the inquiry, and an identity of the computer in which the inquiry originated; transmitting the document to the second computer; extracting in the second computer any inquiries from the document; for each extracted inquiry, searching the data base of the second computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the second computer, retrieving the solution document from the second computer and exporting the solution document to the computer in which the inquiry originated; and, responsive to finding no solution document in the data base of the second computer, notifying the computer in which the inquiry originated that no solution document has been found. | 1. A method for retrieving a solution document in response to an inquiry from among a system of distributed data bases, the system having at least a first and a second computer, each computer having a data base of solution documents, the method comprising the steps of: receiving at least one inquiry into the first computer, the inquiry having a subject; searching the data base of the first computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the first computer related to the subject of the inquiry, retrieving the solution document from the first computer; responsive to finding no solution document in the data base of the first computer related to the subject of the inquiry, performing the steps of: generating in the first computer, a document from at least one inquiry in the first computer for which no solution document was found, the document containing for each such inquiry the subject of the inquiry, and an identity of the computer in which the inquiry originated; transmitting the document to the second computer; extracting in the second computer any inquiries from the document; for each extracted inquiry, searching the data base of the second computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the second computer, retrieving the solution document from the second computer and exporting the solution document to the computer in which the inquiry originated; and, responsive to finding no solution document in the data base of the second computer, notifying the computer in which the inquiry originated that no solution document has been found. 7. The method of claim 1, wherein the computers are coupled by an electronic communications network, and where the steps of transmitting the document, and exporting the solution document further comprise the step of: transmitting the document between the computers using the electronic communications network. | 0.821603 |
1. One or more computer-readable memories having stored thereon executable instructions to perform a method of facilitating access to a resource, the method comprising: abducing a first set of one or more assertions from information that comprises an access request for a first principal to access the resource, a system that performs said abducing not having in possession said first set of one or more assertions, said abducing being performed by acts comprising: receiving a first answer set and a second answer set, said first answer set comprising said first set of one or more assertions, said second answer set comprising a second set of one or more assertions, said first set of said one or more assertions and said second set of said one or more assertions each satisfying a condition that either said first set of one or more assertions or said second set of one or more assertions will, when presented to a guard of the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; and determining that said first answer set is not subsumed by said second answer set; receiving a template that specifies said first set of one or more assertions; obtaining a first token that satisfies a first one of said first set of one or more assertions; presenting, to said guard, (a) a set of one or more tokens that comprises said first token, and (b) said access request; receiving access to said resource from said guard; and accessing said resource. | 1. One or more computer-readable memories having stored thereon executable instructions to perform a method of facilitating access to a resource, the method comprising: abducing a first set of one or more assertions from information that comprises an access request for a first principal to access the resource, a system that performs said abducing not having in possession said first set of one or more assertions, said abducing being performed by acts comprising: receiving a first answer set and a second answer set, said first answer set comprising said first set of one or more assertions, said second answer set comprising a second set of one or more assertions, said first set of said one or more assertions and said second set of said one or more assertions each satisfying a condition that either said first set of one or more assertions or said second set of one or more assertions will, when presented to a guard of the resource, cause said guard to find that a query evaluates to true under a policy implemented by said guard; and determining that said first answer set is not subsumed by said second answer set; receiving a template that specifies said first set of one or more assertions; obtaining a first token that satisfies a first one of said first set of one or more assertions; presenting, to said guard, (a) a set of one or more tokens that comprises said first token, and (b) said access request; receiving access to said resource from said guard; and accessing said resource. 2. The one or more computer-readable memories of claim 1 , wherein said obtaining comprises: consulting a token store that contains said first token; determining that said first token satisfies said first one of said first set of one or more assertions; and retrieving said first token from said token store. | 0.626521 |
14. The printing equipment according to claim 13 , wherein the apparatus for printing documents further comprises: a processing module configured to process the color document to obtain printing step information in the case that the printing step information for the color document is not complete. | 14. The printing equipment according to claim 13 , wherein the apparatus for printing documents further comprises: a processing module configured to process the color document to obtain printing step information in the case that the printing step information for the color document is not complete. 16. The printing equipment according to claim 14 , wherein the apparatus for printing documents further comprises: a color correction module configured to execute the color correction to the color document. | 0.771253 |
1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. | 1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. 13. The method of claim 1 , wherein at least a portion of the first metadata that represents the meaning with the at least a portion of the first vehicle service data represents one or more strings of the symbols of the natural human language selected from at least one of the defined taxonomies. | 0.572459 |
2. A method of representing a database query expression for use during execution of the query expression by a computer, wherein the database query expression includes a plurality of predicates related to one another by at least one logical relation, the method comprising: generating a plurality of operands from the database query expression, wherein each operand in the plurality of operands is representative of a predicate in the plurality of predicates; mapping each operand among the plurality of operands into an operand map; and generating a hierarchical data structure based upon the generated plurality of operands, wherein the data structure includes a plurality of nodes, wherein each node includes an operand identifier that identifies at least one operand from the plurality of operands based upon the operand map, wherein each node defines a first logical relation between those predicates in the database query expression that are represented by operands identified by the operand identifier for such node, and wherein the plurality of nodes are arranged relative to one another in the data structure within multiple hierarchical levels to define at least a second logical relation among predicates in the database query expression. | 2. A method of representing a database query expression for use during execution of the query expression by a computer, wherein the database query expression includes a plurality of predicates related to one another by at least one logical relation, the method comprising: generating a plurality of operands from the database query expression, wherein each operand in the plurality of operands is representative of a predicate in the plurality of predicates; mapping each operand among the plurality of operands into an operand map; and generating a hierarchical data structure based upon the generated plurality of operands, wherein the data structure includes a plurality of nodes, wherein each node includes an operand identifier that identifies at least one operand from the plurality of operands based upon the operand map, wherein each node defines a first logical relation between those predicates in the database query expression that are represented by operands identified by the operand identifier for such node, and wherein the plurality of nodes are arranged relative to one another in the data structure within multiple hierarchical levels to define at least a second logical relation among predicates in the database query expression. 5. The method of claim 2 , wherein the plurality of operands, the operand map, and the data structure represent a disjunctive normal form of the database query expression. | 0.633949 |
1. A computer-implemented method comprising: receiving an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to the respective domain relation of each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. | 1. A computer-implemented method comprising: receiving an expression in a database query language, the expression having a programming language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes, and wherein a particular alternative subtype of the two or more alternative subtypes is a recursively defined subtype; generating respective domain relations using definitions of each of the alternative subtypes within the expression, wherein each domain relation for each alternative subtype has domain tuples belonging to the alternative subtype, including generating a recursively defined domain relation for the recursively defined alternative subtype and performing one or more iterations of recursive evaluation for the recursively defined domain relation to generate one or more new domain tuples belonging to the recursively defined domain relation; generating respective domain id relations for each of the domain relations, wherein each domain id relation for each domain relation of each alternative subtype defines uniquely identified tuples that each assign a unique domain identifier to each of the domain tuples belonging to the respective domain relation of each alternative subtype, including performing, for each domain tuple of one or more new domain tuples generated for the recursively defined domain relation, operations comprising: determining that the elements of the new domain tuple are not represented in a cache of keys; and in response, generating a new domain identifier for the new domain tuple and adding a new domain id tuple to the domain id relation, the new domain id tuple having all elements of the new domain tuple and the new domain identifier; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and defines union tuples that each have a domain identifier of a domain tuple and a branch identifier of a subtype to which the domain tuple belongs; assigning unique union identifiers for union tuples belonging to the union relation; and generating respective injector relations for each of the alternative subtypes, wherein each injector relation for each alternative subtype defines, for a particular domain tuple of an alternative subtype, an injector tuple having elements from the particular domain tuple and a union identifier corresponding to the particular domain tuple. 4. The method of claim 1 , further comprising: receiving a query that references a variable having the algebraic data type; and computing one or more tuples that satisfy the query, wherein each of the one or more tuples that satisfies the query is an injector tuple defined by a respective injector relation of one of the alternative subtypes for the algebraic data type. | 0.537527 |
13. A system for cleansing anomalies from sequence-based data at query time in a computing environment, comprising: means for loading sequence-based data into a database managed by a database management system (DBMS) of a computing system, said loading being performed at a load time of said sequence-based data that precedes a query time of said sequence-based data; means for receiving a cleansing rule at a cleansing rules engine of said computing system; means for automatically converting, by said cleansing rules engine, said cleansing rule to a template, said template including logic to compensate for one or more anomalies in said sequence-based data; means for receiving, at said query time and by a query rewrite engine of said computing system, a user query to retrieve said sequence-based data; means for automatically rewriting, at said query time and by said query rewrite engine, said user query to provide a rewritten query, wherein said means for automatically rewriting includes means for applying said logic included in said template to compensate for said one or more anomalies, and wherein said means for automatically rewriting further includes means for performing at least one of: an expanded rewrite algorithm and a join-back algorithm to generate said rewritten query, said means for performing including: means for reducing said sequence-based data to a subset of said sequence-based data, said subset to be used by a generation of cleansed data; and means for executing, subsequent to said reducing, logic included in said user query on said cleansed data; and means for executing, at said query time, said rewritten query by said DBMS, wherein an answer provided by said means for executing said rewritten query is identical to a result provided by a means for executing said user query on a set of data generated by an application of said cleansing rule to all of said sequence-based data, and wherein said means for reducing said sequence-based data to said subset and said means for executing said logic included in said user query provide an assurance that said answer provided by said executing said rewritten query is identical to said result of said executing said user query on said set of data generated by said application of said cleansing rule to all of said sequence-based data. | 13. A system for cleansing anomalies from sequence-based data at query time in a computing environment, comprising: means for loading sequence-based data into a database managed by a database management system (DBMS) of a computing system, said loading being performed at a load time of said sequence-based data that precedes a query time of said sequence-based data; means for receiving a cleansing rule at a cleansing rules engine of said computing system; means for automatically converting, by said cleansing rules engine, said cleansing rule to a template, said template including logic to compensate for one or more anomalies in said sequence-based data; means for receiving, at said query time and by a query rewrite engine of said computing system, a user query to retrieve said sequence-based data; means for automatically rewriting, at said query time and by said query rewrite engine, said user query to provide a rewritten query, wherein said means for automatically rewriting includes means for applying said logic included in said template to compensate for said one or more anomalies, and wherein said means for automatically rewriting further includes means for performing at least one of: an expanded rewrite algorithm and a join-back algorithm to generate said rewritten query, said means for performing including: means for reducing said sequence-based data to a subset of said sequence-based data, said subset to be used by a generation of cleansed data; and means for executing, subsequent to said reducing, logic included in said user query on said cleansed data; and means for executing, at said query time, said rewritten query by said DBMS, wherein an answer provided by said means for executing said rewritten query is identical to a result provided by a means for executing said user query on a set of data generated by an application of said cleansing rule to all of said sequence-based data, and wherein said means for reducing said sequence-based data to said subset and said means for executing said logic included in said user query provide an assurance that said answer provided by said executing said rewritten query is identical to said result of said executing said user query on said set of data generated by said application of said cleansing rule to all of said sequence-based data. 14. The system of claim 13 , wherein said means for automatically rewriting includes said means for performing said expanded rewrite algorithm, and wherein said means for performing said expanded rewrite algorithm further includes: means for performing a loop for each context reference X of one or more context references included in a pattern of said cleansing rule (C) on a relational table R, said means for performing said loop including: means for setting a correlation condition cr to a list of one or more conjuncts, said one or more conjuncts comprising at least one of: one or more explicit conjuncts included in a condition of said cleansing rule C and referring to said context reference X and one or more implied conjuncts, each implied conjunct being on a cluster key of said relational table R or a sequence key of said relational table R, wherein said correlation condition cr is a correlation condition between said context reference X and T, said T being a target reference included in said pattern, means for retaining in said one or more conjuncts of said correlation condition cr only position-preserving conjuncts, if said context reference X is a position-based context reference, means for binding s to said target reference T, wherein said s is a query condition on said relational table R and is included in said user query (Q), means for running a transitivity analysis between said correlation condition cr and said query condition s, means for determining d, said d being a set including any conjunct of a condition generated through said transitivity analysis that refers only to said context reference X, and means for adding set d to a context condition cc if set d is not empty, and otherwise for setting said context condition cc to an empty set and breaking out of said loop, wherein said context condition cc defines a context set for context reference X; and means for generating, if said context condition cc is not said empty set, an expanded rewrite Q e as said rewritten query, and otherwise for setting said expanded rewrite Q e to a null value. | 0.502734 |
1. A method of managing electronic documents shared across networked satellite nodes remotely located from one another, the method comprising: storing a first plurality of electronic documents in a common electronic document repository, wherein the first plurality of electronic documents includes electronic documents owned by at least two different owners remotely located from one another; storing ownership information at a master node for the first plurality of electronic documents stored in the common electronic document repository, wherein the ownership information indicates that at least one of the electronic documents of the first plurality of electronic documents is owned by a first owner of the at least two different owners and at least one of the electronic documents of the first plurality of electronic documents is owned by a second owner of the at least two different owners, the second owner different from and remotely located with respect to the first owner; and storing ownership information at the master node for a second plurality of electronic documents which are locally stored by at least one satellite node at a respective location remote from the common electronic document repository, wherein the second plurality of electronic documents are not stored in the common electronic document repository, and wherein the ownership information stored at the master node for the first and the second plurality of electronic documents indicates for each electronic document a logical entity that has authority to authorize changes to the respective electronic document. | 1. A method of managing electronic documents shared across networked satellite nodes remotely located from one another, the method comprising: storing a first plurality of electronic documents in a common electronic document repository, wherein the first plurality of electronic documents includes electronic documents owned by at least two different owners remotely located from one another; storing ownership information at a master node for the first plurality of electronic documents stored in the common electronic document repository, wherein the ownership information indicates that at least one of the electronic documents of the first plurality of electronic documents is owned by a first owner of the at least two different owners and at least one of the electronic documents of the first plurality of electronic documents is owned by a second owner of the at least two different owners, the second owner different from and remotely located with respect to the first owner; and storing ownership information at the master node for a second plurality of electronic documents which are locally stored by at least one satellite node at a respective location remote from the common electronic document repository, wherein the second plurality of electronic documents are not stored in the common electronic document repository, and wherein the ownership information stored at the master node for the first and the second plurality of electronic documents indicates for each electronic document a logical entity that has authority to authorize changes to the respective electronic document. 4. The method of claim 1 , further comprising: receiving a request at the master node for a specific electronic document from a first satellite node; determining a location of the requested specific electronic document; and providing the first satellite node with a copy of the specific electronic document that is stored locally by a second satellite node remote from the first satellite node and remote from the common electronic document repository. | 0.537726 |
12. The non-transitory computer-readable medium of claim 9 , wherein classifying is based upon, at least in part, non-intrusive classification of message quality. | 12. The non-transitory computer-readable medium of claim 9 , wherein classifying is based upon, at least in part, non-intrusive classification of message quality. 13. The non-transitory computer-readable medium of claim 12 , wherein classifying is performed per each time frame. | 0.944942 |
35. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: attaining data representing features of a font capable of representing one or more glyphs; and determining a rating for pairing the font and at least one other font using a machine learning system and the data representing the features of the font, wherein at least one of the features or at least one category of a set of categories is identified to represent the font by the machine learning using the features of the font, and wherein the machine learning system produces a vector of numerical values, each numerical value represents one of the features or one of the categories in the set of categories. | 35. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising: attaining data representing features of a font capable of representing one or more glyphs; and determining a rating for pairing the font and at least one other font using a machine learning system and the data representing the features of the font, wherein at least one of the features or at least one category of a set of categories is identified to represent the font by the machine learning using the features of the font, and wherein the machine learning system produces a vector of numerical values, each numerical value represents one of the features or one of the categories in the set of categories. 42. The non-transitory computer readable media of claim 35 , wherein at least one category is not pairable with another of the categories. | 0.544683 |
1. A computer implemented method for stress testing a service oriented architecture based application, the computer implemented method comprising: recording a business process flow; extracting an XML document from the recorded business process flow; creating an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generating a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and executing the test script. | 1. A computer implemented method for stress testing a service oriented architecture based application, the computer implemented method comprising: recording a business process flow; extracting an XML document from the recorded business process flow; creating an XML document file for the extracted XML document, an XML document descriptor file comprising XPath queries for data elements in the XML document file, a configuration file comprising user input parameters obtained from the recorded business process flow, and a test input data file; generating a test script using input of the XML document file, the XML document descriptor file, and the configuration file and inserting data values from the test input data file into a template defined by the XML document file at locations specified by the XPath queries; and executing the test script. 6. The computer implemented method of claim 1 , wherein the XML document descriptor file includes labels comprising names of the data elements in the XML document file. | 0.734229 |
6. The method of claim 1 , wherein displaying the evaluation result comprises displaying a pop-up window containing the evaluation result close to the arithmetic expression. | 6. The method of claim 1 , wherein displaying the evaluation result comprises displaying a pop-up window containing the evaluation result close to the arithmetic expression. 7. The method of claim 6 , wherein displaying the evaluation result further comprises replacing, when the pop-up window is touched, the arithmetic expression with the evaluation result. | 0.825235 |
1. A computer-implemented word processing presentation method, comprising: obtaining an unformatted data structure containing a series of characters representing content for a word processing document; accessing a series of first records in a data structure associated with the unformatted data structure file, wherein each first record contains data correlating a location of one or more characters in the unformatted data structure to a location for the one or more characters in the word processing document; generating a display of the word processing document by applying the correlating data from the series of records to the series of characters in the unformatted data structure; receiving a command to delete particular characters from the word processing document, wherein the particular characters are included in the unformatted data structure; and in response to receiving the command to delete characters, generating a record in the series of records that indicates that the particular characters are deleted from the word processing document while leaving the particular characters in the unformatted data structure unchanged. | 1. A computer-implemented word processing presentation method, comprising: obtaining an unformatted data structure containing a series of characters representing content for a word processing document; accessing a series of first records in a data structure associated with the unformatted data structure file, wherein each first record contains data correlating a location of one or more characters in the unformatted data structure to a location for the one or more characters in the word processing document; generating a display of the word processing document by applying the correlating data from the series of records to the series of characters in the unformatted data structure; receiving a command to delete particular characters from the word processing document, wherein the particular characters are included in the unformatted data structure; and in response to receiving the command to delete characters, generating a record in the series of records that indicates that the particular characters are deleted from the word processing document while leaving the particular characters in the unformatted data structure unchanged. 8. The method of claim 1 , further comprising accessing a series of second records in a data structure associated with the unformatted data structure, and wherein each second record contains data correlating one or more characters in the unformatted data structure to a paragraph format for the one or more characters in the word processing document. | 0.544744 |
10. A system comprising: one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a graph representing public social data comprising identity data and social link data, wherein the graph comprises nodes and directed edges, each edge connecting a pair of nodes, wherein each node represents an identity extracted from the public social data and each edge represents a social link extracted from the public social data from one identity to another different identity, wherein each edge is a “me” edge if the edge represents a “me” social link between identities claimed b a link author as belonging to the same person or real-life entity, and a “friend” edge represents a “friend” social link between identities claimed by a link author as belonging to different persons or entities; and wherein each edge has a weight; quantifying a connection strength between an ordered pair of nodes X and Y in the graph by determining: a distance, the distance being a smallest number of edges on any path from X to Y; a friend distance, the friend distance being a smallest number of friend edges on any path from X to Y; and an affinity score, the affinity score being a function of weights of edges along a path from X to Y; and determining a total affinity between a source node S and a target node T as a sum of affinity scores along all possible paths of a length that does not exceed an upper limit K. | 10. A system comprising: one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a graph representing public social data comprising identity data and social link data, wherein the graph comprises nodes and directed edges, each edge connecting a pair of nodes, wherein each node represents an identity extracted from the public social data and each edge represents a social link extracted from the public social data from one identity to another different identity, wherein each edge is a “me” edge if the edge represents a “me” social link between identities claimed b a link author as belonging to the same person or real-life entity, and a “friend” edge represents a “friend” social link between identities claimed by a link author as belonging to different persons or entities; and wherein each edge has a weight; quantifying a connection strength between an ordered pair of nodes X and Y in the graph by determining: a distance, the distance being a smallest number of edges on any path from X to Y; a friend distance, the friend distance being a smallest number of friend edges on any path from X to Y; and an affinity score, the affinity score being a function of weights of edges along a path from X to Y; and determining a total affinity between a source node S and a target node T as a sum of affinity scores along all possible paths of a length that does not exceed an upper limit K. 13. The system of claim 10 , wherein the operations further comprise cleaning the graph by removing any nodes having a number of friend edges or me edges that exceeds a predetermined threshold. | 0.739946 |
54. The system of claim 40 , wherein the processor is further configured to: identify as a selected resume one of said at least one matching resume; and display the selected resume on a display screen having a left side and a right side, the left side showing a parsed representation of the selected resume, and the right side showing a marked-up representation of the selected resume. | 54. The system of claim 40 , wherein the processor is further configured to: identify as a selected resume one of said at least one matching resume; and display the selected resume on a display screen having a left side and a right side, the left side showing a parsed representation of the selected resume, and the right side showing a marked-up representation of the selected resume. 55. The system of claim 54 , wherein the marked-up representation includes at least one occurrence of the required skill or experience-related phrase for each said at least one job requirement, and wherein to display the selected resume, the processor is further configured to: mark each said at least one occurrence of the required skill or experience-related phrase for each said at least one job requirement. | 0.869281 |
21. An apparatus comprising: a computing device, the computing device to: transform between at least first and at least second non-transitory stored binary digital signal quantities respectively representing at least a first and at least a second expression, said represented expressions to have a common view for non-common expression types of said represented expressions and to have a non-common view for common expression types of said represented expressions, said represented expressions to comprise at least one of the following expression types: a hierarchical edge and/or node labeled tree or a symbol string. | 21. An apparatus comprising: a computing device, the computing device to: transform between at least first and at least second non-transitory stored binary digital signal quantities respectively representing at least a first and at least a second expression, said represented expressions to have a common view for non-common expression types of said represented expressions and to have a non-common view for common expression types of said represented expressions, said represented expressions to comprise at least one of the following expression types: a hierarchical edge and/or node labeled tree or a symbol string. 27. The apparatus of claim 21 , wherein said computing device to employ operations with respect to said first represented expression subsequent to said transformation. | 0.610771 |
1. A method for using program listings information to locate programs of interest to a user, the method comprising: receiving a plurality of program listings with user equipment, wherein at least one of the program listings is associated with two or more simple categories; and generating at least one combination category with the user equipment, the generating comprising: identifying the two or more simple categories associated with the at least one program listing; and combining at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category, wherein the combination category comprises more than one of the identified simple categories. | 1. A method for using program listings information to locate programs of interest to a user, the method comprising: receiving a plurality of program listings with user equipment, wherein at least one of the program listings is associated with two or more simple categories; and generating at least one combination category with the user equipment, the generating comprising: identifying the two or more simple categories associated with the at least one program listing; and combining at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category, wherein the combination category comprises more than one of the identified simple categories. 6. The method of claim 1 , wherein each of the plurality of program listings has associated metadata, the method further comprising automatically assigning each of the plurality of program listings at least one of a plurality of simple categories based on the associated metadata. | 0.63297 |
22. The method of claim 20, wherein said step of identifying rectangular boundaries comprises the steps of: (a) locating associated pixels at horizontal and vertical extremes of each group of black pixels associated with a first black pixel; and (b) determining a rectangular boundary about each group, the rectangular boundary representing the horizontal and vertical extremes. | 22. The method of claim 20, wherein said step of identifying rectangular boundaries comprises the steps of: (a) locating associated pixels at horizontal and vertical extremes of each group of black pixels associated with a first black pixel; and (b) determining a rectangular boundary about each group, the rectangular boundary representing the horizontal and vertical extremes. 23. The method of claim 22, wherein the rasterized data defining the image is a bitmap rasterized with respect to a pair of orthogonal image axes, and said boundary determining step determines a rectangular box, the major axes of which are parallel to the image axes. | 0.822446 |
13. A method for specifying an animatronics unit comprising: determining a force-based software model for the animatronics unit; determining a kinematics-based software model for the animatronics unit; receiving animation data for animating the kinematics-based software model, wherein the animation data comprises artistically determined motions by a user; animating the force-based software model in response to the animation data; displaying animation of the force-based software model determined in response to the animation data; and determining a physical implementation of the animatronics unit in response to animation of the kinematics-based software model, comprising: a) determining an initial physical implementation of the animatronics unit; and b) determining the physical implementation of the animatronics unit in response to animation of the kinematics-based software model and to the initial physical implementation; wherein the initial physical implementation comprises an initial implementation of a component of the animatronics unit having a first dimension; wherein the physical implementation comprises an implementation of the component of the animatronics unit having a second dimension instead of the first dimension. | 13. A method for specifying an animatronics unit comprising: determining a force-based software model for the animatronics unit; determining a kinematics-based software model for the animatronics unit; receiving animation data for animating the kinematics-based software model, wherein the animation data comprises artistically determined motions by a user; animating the force-based software model in response to the animation data; displaying animation of the force-based software model determined in response to the animation data; and determining a physical implementation of the animatronics unit in response to animation of the kinematics-based software model, comprising: a) determining an initial physical implementation of the animatronics unit; and b) determining the physical implementation of the animatronics unit in response to animation of the kinematics-based software model and to the initial physical implementation; wherein the initial physical implementation comprises an initial implementation of a component of the animatronics unit having a first dimension; wherein the physical implementation comprises an implementation of the component of the animatronics unit having a second dimension instead of the first dimension. 14. The method of claim 13 wherein the initial physical implementation comprises an initial implementation of a component of the animatronics unit having a first performance characteristic; wherein the physical implementation comprises an implementation of the component of the animatronics unit having a second performance characteristic instead of the first performance characteristic. | 0.637097 |
12. A system operating in a communication network, comprising: a computer comprising a memory to store a program code, and a processor to execute the program code to: receive a request from a user of the computer to preview an e-document template; invoke a content of the e-document template, wherein the content include a placeholder for a variable; determine a correspondence language of the user; identify, by the computer, a markup language element for the placeholder in the e-document template; determine, by the computer, a descriptive name for the identified markup language element by invoking metadata information pertaining to the place holder, and based on the metadata information, deriving the descriptive name associated with the identified markup language element for the placeholder in the correspondence language of the user; replace the markup language element for the placeholder with the selected descriptive name; and render a preview of the e-document template. | 12. A system operating in a communication network, comprising: a computer comprising a memory to store a program code, and a processor to execute the program code to: receive a request from a user of the computer to preview an e-document template; invoke a content of the e-document template, wherein the content include a placeholder for a variable; determine a correspondence language of the user; identify, by the computer, a markup language element for the placeholder in the e-document template; determine, by the computer, a descriptive name for the identified markup language element by invoking metadata information pertaining to the place holder, and based on the metadata information, deriving the descriptive name associated with the identified markup language element for the placeholder in the correspondence language of the user; replace the markup language element for the placeholder with the selected descriptive name; and render a preview of the e-document template. 17. The system of claim 12 , wherein the markup language element is an HTML element for the placeholder rendered within HTML tags. | 0.605915 |
1. A method for content indexing of streaming hierarchical document content, the method comprising: identifying a hierarchical node from a streaming hierarchical document, the streaming hierarchical document streamed in document order from an stored intact hierarchical document, the streaming hierarchical document comprising two or more namespace indicators, the hierarchical node associated with a first namespace indicator of the two or more namespace indicators; generating a first portion of a hierarchical pattern forest for the first namespace indicator using a first set of structured index path expressions, the hierarchical pattern forest comprising at least one of a tree and a twig generated from one or more structured index path expressions of the first set of structured index path expressions; comparing the hierarchical node to nodes of the first portion of the hierarchical pattern forest; matching the hierarchical node with an index node in one of a tree and a twig of the first portion of the hierarchical pattern forest, the index node having a path from an ancestor node to the index node that matches axis steps of at least one of the structured index path expressions for the first namespace indicator; storing an index entry for the hierarchical node in response to the determined match; identifying a second hierarchical node associated with a second namespace indicator; and generating a second portion of the hierarchical pattern forest for the second namespace indicator using a second set of structured index path expressions. | 1. A method for content indexing of streaming hierarchical document content, the method comprising: identifying a hierarchical node from a streaming hierarchical document, the streaming hierarchical document streamed in document order from an stored intact hierarchical document, the streaming hierarchical document comprising two or more namespace indicators, the hierarchical node associated with a first namespace indicator of the two or more namespace indicators; generating a first portion of a hierarchical pattern forest for the first namespace indicator using a first set of structured index path expressions, the hierarchical pattern forest comprising at least one of a tree and a twig generated from one or more structured index path expressions of the first set of structured index path expressions; comparing the hierarchical node to nodes of the first portion of the hierarchical pattern forest; matching the hierarchical node with an index node in one of a tree and a twig of the first portion of the hierarchical pattern forest, the index node having a path from an ancestor node to the index node that matches axis steps of at least one of the structured index path expressions for the first namespace indicator; storing an index entry for the hierarchical node in response to the determined match; identifying a second hierarchical node associated with a second namespace indicator; and generating a second portion of the hierarchical pattern forest for the second namespace indicator using a second set of structured index path expressions. 2. The method of claim 1 , wherein each twig represents a structured index path expression that has a descendent-or-self axis for a first step. | 0.974386 |
16. Non-transitory computer storage which stores executable code capable of causing a computing system to perform a process that comprises: scanning a sentence for at least one sign of a possible writing problem relating to nominalization; in response to detecting an occurrence of said sign, determining whether the sign is part of a word or word group that is present in a database of false positives; and at least partly in response to determining that the sign is not part of a word or word group that is present in the database of false positives, determining an edit that can be made to the sentence to improve readability of the sentence, the edit comprising changing the sentence to remove a nominalization, wherein the edit comprises deleting a verb closest to the occurrence of the sign. | 16. Non-transitory computer storage which stores executable code capable of causing a computing system to perform a process that comprises: scanning a sentence for at least one sign of a possible writing problem relating to nominalization; in response to detecting an occurrence of said sign, determining whether the sign is part of a word or word group that is present in a database of false positives; and at least partly in response to determining that the sign is not part of a word or word group that is present in the database of false positives, determining an edit that can be made to the sentence to improve readability of the sentence, the edit comprising changing the sentence to remove a nominalization, wherein the edit comprises deleting a verb closest to the occurrence of the sign. 18. The non-transitory computer storage of claim 16 , wherein scanning the sentence comprises searching for a word ending in “ion,” “ions,” “al,” “ant,” “ance,” “ancy,” “ent,” “enc,” “ency,” “ity,” “ing,” “sis,” “ise,” or “ure.” | 0.725296 |
20. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, from a search interface presented at a user device, a request for advertisements, the request specifying a set of query suggestions, wherein the set of query suggestions has been identified for a partial query received from the search interface presented by the user device in response to a time delay between characters having been entered in a query input field of the search interface; accessing an index that includes a ranking of the query suggestions, wherein the ranking was performed prior to receiving the request for advertisements and is based, at least in part, on a probability of each query suggestion being selected by a user that input the partial query, and is based at least in part on a length of each query suggestion, wherein the query suggestions have been ranked (i) by the probability of each query suggestion being selected by the user, such that the query suggestion is ranked higher when the query suggestion has a higher probability of being selected by the user, and (ii) by the length of each query suggestion, such that a shorter query suggestion is ranked higher among multiple query suggestions that each have a similar probability of being selected by the user; selecting a proper subset of the query suggestions, the proper subset including at least a highest ranked query suggestion based on the ranking, a second query suggestion, and a third query suggestion, wherein each query suggestion of the proper subset of the query suggestions has been classified with a corresponding topic; identifying a topic of the highest ranked query suggestion, a topic of the second query suggestion, and a topic of the third query suggestion; identifying a first advertisement based on the highest ranked query suggestion; determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion, wherein the second query suggestion of the proper subset is different from the highest ranked query suggestion; determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion, wherein the third query suggestion of the proper subset is different from the highest ranked query suggestion and the second query suggestion; identifying a second advertisement based on the third query suggestion as a result of determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion and determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion; providing, to the user device, data that causes presentation of the identified first and second advertisements at the user device; and dynamically updating the search interface presented by the user device to include the first advertisement and the second advertisement. | 20. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, from a search interface presented at a user device, a request for advertisements, the request specifying a set of query suggestions, wherein the set of query suggestions has been identified for a partial query received from the search interface presented by the user device in response to a time delay between characters having been entered in a query input field of the search interface; accessing an index that includes a ranking of the query suggestions, wherein the ranking was performed prior to receiving the request for advertisements and is based, at least in part, on a probability of each query suggestion being selected by a user that input the partial query, and is based at least in part on a length of each query suggestion, wherein the query suggestions have been ranked (i) by the probability of each query suggestion being selected by the user, such that the query suggestion is ranked higher when the query suggestion has a higher probability of being selected by the user, and (ii) by the length of each query suggestion, such that a shorter query suggestion is ranked higher among multiple query suggestions that each have a similar probability of being selected by the user; selecting a proper subset of the query suggestions, the proper subset including at least a highest ranked query suggestion based on the ranking, a second query suggestion, and a third query suggestion, wherein each query suggestion of the proper subset of the query suggestions has been classified with a corresponding topic; identifying a topic of the highest ranked query suggestion, a topic of the second query suggestion, and a topic of the third query suggestion; identifying a first advertisement based on the highest ranked query suggestion; determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion, wherein the second query suggestion of the proper subset is different from the highest ranked query suggestion; determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion, wherein the third query suggestion of the proper subset is different from the highest ranked query suggestion and the second query suggestion; identifying a second advertisement based on the third query suggestion as a result of determining that the topic of the third query suggestion matches the topic of the highest ranked query suggestion and determining that the topic of the second query suggestion does not match the topic of the highest ranked query suggestion; providing, to the user device, data that causes presentation of the identified first and second advertisements at the user device; and dynamically updating the search interface presented by the user device to include the first advertisement and the second advertisement. 27. The non-transitory computer storage medium of claim 20 , wherein the instructions further cause the data processing apparatus to: receive query data defining the partial query, the partial query being query input from the user device and having one or more characters ordered in an input sequence that defines an order in which the one or more characters were input as the query input; and identify the set of query suggestions based on the partial query. | 0.522421 |
9. A method of classifying a payment document, comprising: receiving an image of a payment document captured by a mobile device; extracting at least one feature from the image; comparing the at least one extracted feature with at least one known feature of a payment document type to determine a likelihood that the payment document matches the at least one payment document type, wherein comparing further includes comparing a plurality of extracted features with a plurality of known features in a series, starting with an extracted feature which requires the least computation time of the plurality of extracted features; and classifying the payment document as at least one payment document type based on the likelihood that the payment document matches the at least one payment document type. | 9. A method of classifying a payment document, comprising: receiving an image of a payment document captured by a mobile device; extracting at least one feature from the image; comparing the at least one extracted feature with at least one known feature of a payment document type to determine a likelihood that the payment document matches the at least one payment document type, wherein comparing further includes comparing a plurality of extracted features with a plurality of known features in a series, starting with an extracted feature which requires the least computation time of the plurality of extracted features; and classifying the payment document as at least one payment document type based on the likelihood that the payment document matches the at least one payment document type. 12. The method of claim 9 , wherein the at least one feature includes one or more connected components of the image of the payment document. | 0.611574 |
1. A method comprising: receiving a search query, wherein the search query comprises a first input modality and a second input modality, the first input modality being distinct from the second input modality; retrieving first modality search results for the search query using the first input modality of the search query; outputting, on a display and all at once, the first modality search results; retrieving, from a database, partial second modality search results based on the first modality search results and the second input modality as the second input modality is being entered; outputting, on the display, the partial second modality search results incrementally as the second input modality is still being entered; retrieving, from the database, final second modality search results based on the first modality search results and the second input modality upon the second input modality being completely entered; and outputting, on the display, the final second modality search results. | 1. A method comprising: receiving a search query, wherein the search query comprises a first input modality and a second input modality, the first input modality being distinct from the second input modality; retrieving first modality search results for the search query using the first input modality of the search query; outputting, on a display and all at once, the first modality search results; retrieving, from a database, partial second modality search results based on the first modality search results and the second input modality as the second input modality is being entered; outputting, on the display, the partial second modality search results incrementally as the second input modality is still being entered; retrieving, from the database, final second modality search results based on the first modality search results and the second input modality upon the second input modality being completely entered; and outputting, on the display, the final second modality search results. 8. The method of claim 1 , further comprising: identifying potentially important information absent in the search query based on one of user preferences and user history; and outputting suggestions associated with the potentially important information on the display. | 0.687721 |
7. The server of claim 6 , wherein each semantic equivalence is associated with the identifier. | 7. The server of claim 6 , wherein each semantic equivalence is associated with the identifier. 9. The server of claim 7 , wherein the identifier is associated with computer code parsing the information gathered by each heterogeneous information source. | 0.957709 |
2. A method in accordance with claim 1 , further comprising: prompting the user through the telephone connection to provide the first sound input; prompting the user through the telephone connection to provide the selected first variable value for the first prompted variable; sending the electronic message from the communication system to one or more recipients. | 2. A method in accordance with claim 1 , further comprising: prompting the user through the telephone connection to provide the first sound input; prompting the user through the telephone connection to provide the selected first variable value for the first prompted variable; sending the electronic message from the communication system to one or more recipients. 4. A method in accordance with claim 2 , wherein the step of determining from the second sound input comprises processing the second sound input with an automatic speech recognition (ASR) module. | 0.858935 |
1. A computer-implemented method for generating a cardinality estimate, comprising: identifying a predicate in a query, wherein the predicate is split into a plurality of equivalence classes; generating a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identifying spanning trees in the plurality of undirected equivalence graphs; determining a minimum spanning tree of the identified spanning trees; calculating a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and selecting a query plan corresponding to the cardinality estimate, wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by a processor. | 1. A computer-implemented method for generating a cardinality estimate, comprising: identifying a predicate in a query, wherein the predicate is split into a plurality of equivalence classes; generating a plurality of undirected equivalence graphs from the plurality of equivalence classes, wherein the undirected equivalence graphs include a plurality of weighted edges representing a join predicate between two tables, and wherein the equivalence classes are determined based on sets of common attributes that are included in tables joined in the query; identifying spanning trees in the plurality of undirected equivalence graphs; determining a minimum spanning tree of the identified spanning trees; calculating a cardinality estimate based on the minimum spanning tree based on multiplying each predicate, in a set of identified predicates in the spanning tress, by a selectivity associated with each edge corresponding to the predicate, wherein a quality of the selectivity indicates a relationship between two tables joined in the query, and wherein the relationship indicates at least one of a key or attribute relationship between the two tables; and selecting a query plan corresponding to the cardinality estimate, wherein the cardinality estimate for the selected query plan is associated with a lower consumption of resources amongst a plurality of query plans in an execution of a query by a processor. 6. The computer-implemented method of claim 1 , further comprising: determining a confidence level of the selectivity of at least one of the edges, wherein the confidence level is the weight of at least one of the edges. | 0.739271 |
1. A mobile terminal, comprising: a voice receiving unit; a display unit; an input unit; and a controller configured to: convert the voice input received via the voice receiving unit into text; control the display unit to display the text in which a word of the text is emphatically displayed if a voice recognition rate of the word is less than a preset reference value; receive a first touch selection signal indicating an emphasized word is touch selected for correction; control the display unit to display a plurality of candidate words to replace the selected word; receive a second touch signal indicating a candidate word is selected from the plurality of candidate words; and replace the selected word with the candidate word and stop displaying the plurality of candidate words when the second touch signal is received, wherein the controller is further configured to: simultaneously display the converted text in a first direction and display the plurality of candidate words in a list in a second direction perpendicular to the first direction; display a slide bar with the selected word being positioned with respect to a first position on the slide bar; receive a touch and slide action on the slide bar; and display candidate words at different positions on the slide bar based on the touch and slide action, and wherein as the touch and slide action slides away from the position of the selected word, candidate words having a lower similarity to the selected word are displayed, and as the touch and slide action slides toward the position of the selected word, candidate words having a higher similarity to the selected words are displayed. | 1. A mobile terminal, comprising: a voice receiving unit; a display unit; an input unit; and a controller configured to: convert the voice input received via the voice receiving unit into text; control the display unit to display the text in which a word of the text is emphatically displayed if a voice recognition rate of the word is less than a preset reference value; receive a first touch selection signal indicating an emphasized word is touch selected for correction; control the display unit to display a plurality of candidate words to replace the selected word; receive a second touch signal indicating a candidate word is selected from the plurality of candidate words; and replace the selected word with the candidate word and stop displaying the plurality of candidate words when the second touch signal is received, wherein the controller is further configured to: simultaneously display the converted text in a first direction and display the plurality of candidate words in a list in a second direction perpendicular to the first direction; display a slide bar with the selected word being positioned with respect to a first position on the slide bar; receive a touch and slide action on the slide bar; and display candidate words at different positions on the slide bar based on the touch and slide action, and wherein as the touch and slide action slides away from the position of the selected word, candidate words having a lower similarity to the selected word are displayed, and as the touch and slide action slides toward the position of the selected word, candidate words having a higher similarity to the selected words are displayed. 7. The mobile terminal of claim 1 , wherein the controller is further configured to control the display unit to discriminately display the selected words from other words displayed on the display. | 0.717448 |
17. A computer-readable medium, which does not consist of a modulated data signal or carrier wave, having computer executable instructions stored therein for generating a text message based on an arbitrary speech input, said instructions comprising: training a statistical language model and a corresponding text message database directly from one or more sets of real-world text messages, said language model including a lexicon limited to terms extracted from the one or more sets of real-world text messages; receiving an arbitrary speech input from a user; applying the statistical language model and lexicon to the arbitrary speech input to generate one or more probabilistic speech recognition hypotheses without requiring any user input to correct potential speech recognition errors; for each speech recognition hypothesis, identifying a group of one or more probabilistically matching text messages from the text message database, each probabilistically matching text message including a probability of match; ranking the probabilistically matching text messages based on the corresponding probability of match; evaluating the ranking of the text messages to select a single ranked text message to paraphrase the arbitrary speech input; and transmitting the selected text message to a recipient. | 17. A computer-readable medium, which does not consist of a modulated data signal or carrier wave, having computer executable instructions stored therein for generating a text message based on an arbitrary speech input, said instructions comprising: training a statistical language model and a corresponding text message database directly from one or more sets of real-world text messages, said language model including a lexicon limited to terms extracted from the one or more sets of real-world text messages; receiving an arbitrary speech input from a user; applying the statistical language model and lexicon to the arbitrary speech input to generate one or more probabilistic speech recognition hypotheses without requiring any user input to correct potential speech recognition errors; for each speech recognition hypothesis, identifying a group of one or more probabilistically matching text messages from the text message database, each probabilistically matching text message including a probability of match; ranking the probabilistically matching text messages based on the corresponding probability of match; evaluating the ranking of the text messages to select a single ranked text message to paraphrase the arbitrary speech input; and transmitting the selected text message to a recipient. 18. The computer-readable medium of claim 17 wherein one or more of the text messages in the text message database includes one or more variables, and wherein one or more of the variables of any text message selected for transmission are populated by using a context free grammar model to identify specific words to populate those variables from the arbitrary speech input. | 0.5 |
1. A communication device to be connected with a data server via a network, the communication device comprising: one or more processors; a memory that stores a computer program including instructions executed by the one or more processors; and a first information memory that stores first specific data representing specific information described in a first language, wherein the instructions cause the one or more processors, when executed by the one or more processors, to function as: a first acquiring unit configured to acquire second specific data stored in the data server from the data server, the second specific data representing the specific information described in a second language different from the first language; and a first supplying unit configured to: supply first image data obtained using the first specific data within the first information memory to a display unit in a case where the specific information described in the first language is requested, the first image data representing a first image including the specific information described in the first language, supply second image data obtained using the acquired second specific data to the display unit in a case where the specific information described in the second language is requested, the second image data representing a second image including the specific information described in the second language; and a storage control unit configured to store the acquired second specific data in a second information memory, wherein in the case where the specific information described in the second language is requested after the acquired second specific data is stored in the second information memory, the first supplying unit is configured to supply the second image data obtained using the second specific data within the second information memory, the acquired second specific data includes first character string data representing a first character string and second character string data representing a second character string, if third character string data is necessary instead of the second character string data in the case where the specific information described in the second language is requested after the acquired second specific data is stored in the second information memory, the first acquiring unit is configured to acquire the third character string data from the data server without acquiring the first character string data from the data server, and the first supplying unit is configured to supply the second image data obtained using the first character string data included in the second specific data within the second information memory and the acquired third character string data. | 1. A communication device to be connected with a data server via a network, the communication device comprising: one or more processors; a memory that stores a computer program including instructions executed by the one or more processors; and a first information memory that stores first specific data representing specific information described in a first language, wherein the instructions cause the one or more processors, when executed by the one or more processors, to function as: a first acquiring unit configured to acquire second specific data stored in the data server from the data server, the second specific data representing the specific information described in a second language different from the first language; and a first supplying unit configured to: supply first image data obtained using the first specific data within the first information memory to a display unit in a case where the specific information described in the first language is requested, the first image data representing a first image including the specific information described in the first language, supply second image data obtained using the acquired second specific data to the display unit in a case where the specific information described in the second language is requested, the second image data representing a second image including the specific information described in the second language; and a storage control unit configured to store the acquired second specific data in a second information memory, wherein in the case where the specific information described in the second language is requested after the acquired second specific data is stored in the second information memory, the first supplying unit is configured to supply the second image data obtained using the second specific data within the second information memory, the acquired second specific data includes first character string data representing a first character string and second character string data representing a second character string, if third character string data is necessary instead of the second character string data in the case where the specific information described in the second language is requested after the acquired second specific data is stored in the second information memory, the first acquiring unit is configured to acquire the third character string data from the data server without acquiring the first character string data from the data server, and the first supplying unit is configured to supply the second image data obtained using the first character string data included in the second specific data within the second information memory and the acquired third character string data. 2. The communication device as in claim 1 , wherein the first acquiring unit is configured to acquire the second specific data from the data server when the specific information described in the second language is requested. | 0.653469 |
24. A system for controlling a radio device, comprising: a gesture pad configured to modify an operation of the radio device, wherein the gesture pad distinguishes between a plurality of fingers used for a gesture, recognizes the orientation of the distinguished finger, and performs a function that is dependent on the distinguished finger and its orientation. | 24. A system for controlling a radio device, comprising: a gesture pad configured to modify an operation of the radio device, wherein the gesture pad distinguishes between a plurality of fingers used for a gesture, recognizes the orientation of the distinguished finger, and performs a function that is dependent on the distinguished finger and its orientation. 26. The system of claim 24 , further comprising a voice control component configured to modify a first operation of the radio device, wherein the first operation comprises one of: jumping to a current broadcast point; jumping to a point in a buffered content; indicating a preference for an output audio content of the radio; saving a copy of an audio content; or modifying an input signal type, wherein the input signal type comprises AM, FM, HD, Satellite, Wi-Fi, Saved, CD, MP3, iPod, or Flash. | 0.5 |
13. A computer implemented method comprising: receiving by a search engine, operating on a computing device, from a content searching or consuming application, a search expression having a first and a second proximally associated atomic sub-expression, the search engine and the content searching or consuming application being operated on one or more different or same computing devices; receiving content nominally associated with the search expression, or access information of the content, by the search engine; generating, by the search engine, one or more scores for one or more structures of the content indicative of relative relevance of the content or one or more portions of the content to the search expression, wherein the generating of a score for a structure is based at least in part on a distance function and a scoring function, wherein the structure have sub-structures structurally describing at least a portion of the content, and having content nodes and/or text strings, wherein the sub-structures are hierarchically organized with the one or more portions of the content in a sub-structure at a level respectively assigned one or more positions according to a geometry established for that level, wherein the distance function measures distances between sub-structures within the structure, and the scoring function is positionally sensitive, yielding different scores for different occurrence positions of either or both of the proximally associated first and second atomic sub-expressions in the sub-structures; and conditionally providing or not providing the content or one or more portions of the content, or access information of the content or one or more portions of the content, to the content searching or consuming application, by the search engine, based at least in part on the generated one or more scores; wherein the generating of a score for a structure further includes at each level, linearly iterating over one or more portions of the content at the level to capture potential of a portion to influence other portions of the level, and influence received by a portion from the other portions of the level. | 13. A computer implemented method comprising: receiving by a search engine, operating on a computing device, from a content searching or consuming application, a search expression having a first and a second proximally associated atomic sub-expression, the search engine and the content searching or consuming application being operated on one or more different or same computing devices; receiving content nominally associated with the search expression, or access information of the content, by the search engine; generating, by the search engine, one or more scores for one or more structures of the content indicative of relative relevance of the content or one or more portions of the content to the search expression, wherein the generating of a score for a structure is based at least in part on a distance function and a scoring function, wherein the structure have sub-structures structurally describing at least a portion of the content, and having content nodes and/or text strings, wherein the sub-structures are hierarchically organized with the one or more portions of the content in a sub-structure at a level respectively assigned one or more positions according to a geometry established for that level, wherein the distance function measures distances between sub-structures within the structure, and the scoring function is positionally sensitive, yielding different scores for different occurrence positions of either or both of the proximally associated first and second atomic sub-expressions in the sub-structures; and conditionally providing or not providing the content or one or more portions of the content, or access information of the content or one or more portions of the content, to the content searching or consuming application, by the search engine, based at least in part on the generated one or more scores; wherein the generating of a score for a structure further includes at each level, linearly iterating over one or more portions of the content at the level to capture potential of a portion to influence other portions of the level, and influence received by a portion from the other portions of the level. 29. The method of claim 13 , wherein the search expression comprises a plurality of recursively embedded sub-expressions, including a sub-expression having the first and second proximally associated atomic sub-expressions. | 0.617874 |
16. One or more non-transitory processor-readable media storing code representing instructions to cause one or more processors to: receive data associated with a characteristic of a plurality of students from an educational delivery system; select a control group of students from the plurality of students and an experimental group of students from the plurality of students based on the data such that a value of the characteristic associated with each student from the control group of students is substantially identical to a value of the characteristic associated with each student from the experimental group of students; deliver a first educational material to the control group of students, the first educational material including a first content associated with a plurality of learning objectives, which is arranged to define at least a first learning path; and deliver a second educational material to the experimental group of students, the second educational material including a second content associated with the plurality of learning objectives, which is arranged to define at least a second learning path. | 16. One or more non-transitory processor-readable media storing code representing instructions to cause one or more processors to: receive data associated with a characteristic of a plurality of students from an educational delivery system; select a control group of students from the plurality of students and an experimental group of students from the plurality of students based on the data such that a value of the characteristic associated with each student from the control group of students is substantially identical to a value of the characteristic associated with each student from the experimental group of students; deliver a first educational material to the control group of students, the first educational material including a first content associated with a plurality of learning objectives, which is arranged to define at least a first learning path; and deliver a second educational material to the experimental group of students, the second educational material including a second content associated with the plurality of learning objectives, which is arranged to define at least a second learning path. 17. The one or more non-transitory processor-readable media of claim 16 , wherein the characteristic includes at least one of a demographic characteristic, a geographical location, a score of an assessment associated with a learning objective from the plurality of learning objectives, a time to complete the assessment, a number of attempts to complete the assessment or an indicator of knowledge of the learning objective based on prior educational experience. | 0.739595 |
19. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: receive, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; determine whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; parse the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; generate a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; generate a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and send, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user. | 19. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: receive, from a client system of a user of the social-networking system, instructions for generating a post in a news feed associated with the user on the social-networking system, wherein the post comprises unstructured text from the user; determine whether the unstructured text of the post comprises a request for a recommendation from other users of the social-networking system; parse the unstructured text to identify one or more first entities and one or more first entity types referenced in the unstructured text; generate a structured query based upon the one or more first entities and the one or more first entity types referenced in the unstructured text of the post; generate a plurality of search results corresponding to a plurality of second entities matching the structured query, wherein each of the second entities has an entity type matching at least one of the first entity types; and send, to the client system of the user responsive to receiving the instructions for generating the post, instructions for presenting one or more of the plurality of search results, wherein the search results are presented in association with the post by the user in the news feed associated with the user. 34. The system of claim 19 , wherein the processors are further operable when executing instructions to: receive one or more comments from one or more users; and present the one or more comments in association with the news feed. | 0.59086 |
3. The method of claim 2 , wherein: the set of data fields includes a field selected from a competitive local exchange carrier field, a joint-poles-on-job count field, a poles-on-intent count field, and a pole address field. | 3. The method of claim 2 , wherein: the set of data fields includes a field selected from a competitive local exchange carrier field, a joint-poles-on-job count field, a poles-on-intent count field, and a pole address field. 5. The method of managing intents of claim 3 , wherein: the first asset owner is a first telecommunications company and wherein the intent database indicates work performed on poles of the first telecommunications company by a competing telecommunications company. | 0.860474 |
1. A system for correcting errors in an audio transcription comprising: an audio recorder that comprises an analog audio recorder; a transcription generator that comprises an analog-to-digital audio converter; a recording of speech; a collection of link data; transcription text of said speech; an audio player; a system of cross linking; a text editor including a text display with a cursor; a playback controller located on the text editor screen, wherein the playback controller includes a slider capable of allowing a user to jump to any part of a recording by simply dragging the slider; and a first button that causes the text cursor to jump to a corresponding playback position, a second button that disables a text tracking function of the audio transcription, and an optional third button that controls speed of a playback. | 1. A system for correcting errors in an audio transcription comprising: an audio recorder that comprises an analog audio recorder; a transcription generator that comprises an analog-to-digital audio converter; a recording of speech; a collection of link data; transcription text of said speech; an audio player; a system of cross linking; a text editor including a text display with a cursor; a playback controller located on the text editor screen, wherein the playback controller includes a slider capable of allowing a user to jump to any part of a recording by simply dragging the slider; and a first button that causes the text cursor to jump to a corresponding playback position, a second button that disables a text tracking function of the audio transcription, and an optional third button that controls speed of a playback. 11. The system for correcting errors in an audio transcription of claim 1 comprises a voice-to-text generator associated with at least one of the text editor and the transcription generator. | 0.577465 |
1. A system to locate and deny theft of personal information in a computer network, the system comprising: a. a search engine bot arranged to scan and write to memory existing or newly uncovered locations where personal data are being traded in the computer network; b. a conversation bot interactive with the search engine bot and arranged to solicit a transaction of stolen personal information through a natural language human conversation enticement; c. a notification bot interactive with the search engine bot to provide notification of the existence of a stolen personal information provider discovered through the conversation bot; and d. a computer, wherein one or more of the search engine bot, the conversation bot and the notification bot are embodied in one or more computer programs stored in a computer readable medium and are executed by the computer, wherein the search engine bot is further configured to update the memory with found keywords, responses, locations, patterns, terminology, conversational timing emulation, and criminal phraseology and pattern analyses. | 1. A system to locate and deny theft of personal information in a computer network, the system comprising: a. a search engine bot arranged to scan and write to memory existing or newly uncovered locations where personal data are being traded in the computer network; b. a conversation bot interactive with the search engine bot and arranged to solicit a transaction of stolen personal information through a natural language human conversation enticement; c. a notification bot interactive with the search engine bot to provide notification of the existence of a stolen personal information provider discovered through the conversation bot; and d. a computer, wherein one or more of the search engine bot, the conversation bot and the notification bot are embodied in one or more computer programs stored in a computer readable medium and are executed by the computer, wherein the search engine bot is further configured to update the memory with found keywords, responses, locations, patterns, terminology, conversational timing emulation, and criminal phraseology and pattern analyses. 3. The system as claimed in claim 1 further comprising a module for locating one or more computer-based locations where the personal information may be acquired. | 0.583088 |
13. The machine-readable storage medium of claim 12 , wherein the first SQL query statement is translated by a query translator implemented using ANTLR (Another Tool for Language Recognition) compatible techniques. | 13. The machine-readable storage medium of claim 12 , wherein the first SQL query statement is translated by a query translator implemented using ANTLR (Another Tool for Language Recognition) compatible techniques. 14. The machine-readable storage medium of claim 13 , wherein the data type of the wildcard parameter is predicted based on a property type of a corresponding property associated with the first SQL query statement. | 0.922632 |
1. A method performed in a Translation Memory Apparatus for translating an input sequence of data items in a first format to an output sequence of data items in a second format using a store comprising a plurality of example sequences in the first format each paired with its translation in the second format, comprising: (a) a processor of the apparatus choosing a base example sequence from the store based on a comparison of the input sequence with each of a plurality of example sequences from the store, and using its paired translation as a translation basis; (b) the processor identifying a portion of the input sequence differing from a corresponding portion of the base example sequence, these portions being designated input and base example unmatched portions respectively and other portions that are not the unmatched portions being designated input and base example matched portions respectively; (c) the processor locating a portion of the translation basis corresponding to the base example unmatched portion, wherein, when the portion of the translation basis corresponds to the base example unmatched portion and an adjacent base example matched portion, extending the base example unmatched portion to include the adjacent base example matched portion, and extending the corresponding input unmatched portion to include an adjacent input matched portion corresponding to the adjacent base example matched portion; (d) the processor using the input unmatched portion to select a set of subsidiary example sequences from the store; (e) the processor determining from the set of subsidiary example sequences a choice of possible translations corresponding to the input unmatched portion; (f) the processor selecting a translation from the choice based on a predetermined selection algorithm and using the selected translation to replace the portion located in step (c); and (g) the processor using the result of step (f) as a basis for the output sequence of data items. | 1. A method performed in a Translation Memory Apparatus for translating an input sequence of data items in a first format to an output sequence of data items in a second format using a store comprising a plurality of example sequences in the first format each paired with its translation in the second format, comprising: (a) a processor of the apparatus choosing a base example sequence from the store based on a comparison of the input sequence with each of a plurality of example sequences from the store, and using its paired translation as a translation basis; (b) the processor identifying a portion of the input sequence differing from a corresponding portion of the base example sequence, these portions being designated input and base example unmatched portions respectively and other portions that are not the unmatched portions being designated input and base example matched portions respectively; (c) the processor locating a portion of the translation basis corresponding to the base example unmatched portion, wherein, when the portion of the translation basis corresponds to the base example unmatched portion and an adjacent base example matched portion, extending the base example unmatched portion to include the adjacent base example matched portion, and extending the corresponding input unmatched portion to include an adjacent input matched portion corresponding to the adjacent base example matched portion; (d) the processor using the input unmatched portion to select a set of subsidiary example sequences from the store; (e) the processor determining from the set of subsidiary example sequences a choice of possible translations corresponding to the input unmatched portion; (f) the processor selecting a translation from the choice based on a predetermined selection algorithm and using the selected translation to replace the portion located in step (c); and (g) the processor using the result of step (f) as a basis for the output sequence of data items. 14. The method as claimed in claim 1 , wherein step (d) comprises the processor selecting an example sequence for inclusion in the set if at least one data item in the example sequence matches or corresponds to at least one data item in the input unmatched portion. | 0.517486 |
19. The computer readable storage medium of claim 17 , further comprising: before completing the first process, providing a first processing status indicator associated with the first task; and before completing the second process, providing a second processing status indicator associated with the second task. | 19. The computer readable storage medium of claim 17 , further comprising: before completing the first process, providing a first processing status indicator associated with the first task; and before completing the second process, providing a second processing status indicator associated with the second task. 22. The computer readable storage medium of claim 19 , wherein the first processing status indicator and the second processing status indicator comprise one or more of an hourglass, an animation, or a status bar. | 0.924612 |
10. A document analysis method comprising: receiving, by a processor, a document, the document comprising one of structured document or a semi-structured document, rendering the received document, and storing the rendered document as an image in a storage unit; grouping document description elements of the document included in the image that are juxtaposed in a horizontal or vertical direction in the image, relating the grouped document description elements to layout components of the document that describe a layout of the document description elements of the document, and storing the related grouped document description elements and layout components in the storage unit; and outputting the layout based on the stored related grouped document description elements and layout components, the layout identifying the layout components, the layout components referencing the grouped document description elements. | 10. A document analysis method comprising: receiving, by a processor, a document, the document comprising one of structured document or a semi-structured document, rendering the received document, and storing the rendered document as an image in a storage unit; grouping document description elements of the document included in the image that are juxtaposed in a horizontal or vertical direction in the image, relating the grouped document description elements to layout components of the document that describe a layout of the document description elements of the document, and storing the related grouped document description elements and layout components in the storage unit; and outputting the layout based on the stored related grouped document description elements and layout components, the layout identifying the layout components, the layout components referencing the grouped document description elements. 17. The document analysis method according to claim 10 , further comprising: storing a URI of the document and an ID of an output component of the document as output component information; and generating and outputting a composite document based on the output component information, the document corresponding to the URL described in the output component information, and information of the layout of the document. | 0.746364 |
56. In the apparatus of claim 54 and wherein: the first receiving means and the extraction means are included in a first document processing system; the third receiving means and the composition means are included in a second document processing system; and the second receiving means includes network means connecting the first document processing system and the second document processing system. | 56. In the apparatus of claim 54 and wherein: the first receiving means and the extraction means are included in a first document processing system; the third receiving means and the composition means are included in a second document processing system; and the second receiving means includes network means connecting the first document processing system and the second document processing system. 57. In the apparatus of claim 56 and wherein: the second receiving means begins providing the interchange structure to the network means before the extraction means has finished producing the interchange structure; and the composition means begins producing the second structure before it has received all of the interchange structure from the network means. | 0.865658 |
1. A method for enhancing a media file to enable speech-recognition of spoken navigation commands, comprising: receiving a plurality of textual items relating to the subject matter of the media file; generating at least one grammar comprising one or more grammar entries, wherein the one or more grammar entries comprise grammar entries that are generated for at least some of the plurality of the textual items, and comprise a word or word sequence recognizable by a speech recognition engine; for each of the grammar entries corresponding to content in the media file, determining one or more time stamps for the grammar entry, each time stamp indicating a location in the media file of content corresponding to the grammar entry; and via a computer processor, locating content in the media file during playback of the media file by (a) receiving speech input from a user, (b) recognizing the speech input using the speech recognition engine and the at least one grammar to produce a speech recognition result corresponding at least in part to a recognized grammar entry of the at least one grammar, and (c) identifying one or more locations in the media file by identifying the one or more time stamps determined for the recognized grammar entry and the current time position of the media file at playback when the user input is received, wherein upon identifying the location in the media file a media controller navigates to the time stamp identified and presents the media file to the user at the identified timestamp location. | 1. A method for enhancing a media file to enable speech-recognition of spoken navigation commands, comprising: receiving a plurality of textual items relating to the subject matter of the media file; generating at least one grammar comprising one or more grammar entries, wherein the one or more grammar entries comprise grammar entries that are generated for at least some of the plurality of the textual items, and comprise a word or word sequence recognizable by a speech recognition engine; for each of the grammar entries corresponding to content in the media file, determining one or more time stamps for the grammar entry, each time stamp indicating a location in the media file of content corresponding to the grammar entry; and via a computer processor, locating content in the media file during playback of the media file by (a) receiving speech input from a user, (b) recognizing the speech input using the speech recognition engine and the at least one grammar to produce a speech recognition result corresponding at least in part to a recognized grammar entry of the at least one grammar, and (c) identifying one or more locations in the media file by identifying the one or more time stamps determined for the recognized grammar entry and the current time position of the media file at playback when the user input is received, wherein upon identifying the location in the media file a media controller navigates to the time stamp identified and presents the media file to the user at the identified timestamp location. 3. The method of claim 1 , wherein the step of receiving a plurality of textual items further comprises: receiving textual data provided by a user via a user input device and generating a plurality of textual items based on the textual data. | 0.579353 |
1. A system for performing an integration of an origin data set into a target data set, the system comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to: receive the origin data set, the origin data set being organized by an origin data set schema specifying a tabular format for data of the origin data set; receive a target data set ontology, the target data set ontology defining data objects of the target data set; generate, according to the origin data set schema and the target data set ontology, a domain-specific transform programming language specific to the origin data set schema and the target data set ontology; receive transform instructions programmed in the domain-specific transform programming language; generate a preview target data set from at least a portion of the origin data set using the transform instructions, the preview target data set generated in response to receiving the transform instructions; and integrate the at least a portion of the origin data set into the target data set according to the received transform instructions in response to the preview target data set corresponding to the target data set ontology. | 1. A system for performing an integration of an origin data set into a target data set, the system comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the system to: receive the origin data set, the origin data set being organized by an origin data set schema specifying a tabular format for data of the origin data set; receive a target data set ontology, the target data set ontology defining data objects of the target data set; generate, according to the origin data set schema and the target data set ontology, a domain-specific transform programming language specific to the origin data set schema and the target data set ontology; receive transform instructions programmed in the domain-specific transform programming language; generate a preview target data set from at least a portion of the origin data set using the transform instructions, the preview target data set generated in response to receiving the transform instructions; and integrate the at least a portion of the origin data set into the target data set according to the received transform instructions in response to the preview target data set corresponding to the target data set ontology. 8. The system of claim 1 , wherein the system caused to receive the transform instructions is further caused to provide autocomplete suggestions. | 0.626521 |
14. The computer system of claim 13 , wherein the instructions, when executed by the processor, further cause the computer system to: install the revised policy in a database server that manages the particular database. | 14. The computer system of claim 13 , wherein the instructions, when executed by the processor, further cause the computer system to: install the revised policy in a database server that manages the particular database. 15. The computer system of claim 14 , wherein the instructions, when executed by the processor, further cause the computer system to: identify a syntax that is supported by the database server; and perform said parsing of the sample database query statement using the syntax that is supported by the database server. | 0.913482 |
10. An apparatus according to claim 9 , wherein when said predicate comprises said noun phrase, said respective noun phrase is mapped to a further meta-model element in accordance with said first mapping. | 10. An apparatus according to claim 9 , wherein when said predicate comprises said noun phrase, said respective noun phrase is mapped to a further meta-model element in accordance with said first mapping. 11. An apparatus according to claim 10 , wherein said meta-model elements are meta-model classes. | 0.969931 |
13. The method according to claim 12 , wherein authenticating the user includes: receiving authentication information for the user; and verifying that the authentication information is for the user. | 13. The method according to claim 12 , wherein authenticating the user includes: receiving authentication information for the user; and verifying that the authentication information is for the user. 14. The method according to claim 13 , wherein receiving authentication information includes the content providing the authentication information to the portal. | 0.934434 |
8. A memory device storing computer program instructions that, when executed by a processor of a computer, cause the computer to perform a computer-implemented method comprising: receiving a query including: a selected record, an outer join that provides a joined table having NULLab 1 e records, and an Order By clause that provides a sort order for ordering records in the joined table based on one or more fields of the joined table; and generating, by the server, a separate query configured to fetch from the joined table a current row that corresponds to the selected record and either subsequent rows or previous rows relative to the current row, wherein generating the separate query comprises: determining whether a paging direction of the separate query is forward paging or backward paging, determining whether the sort order for the Order By clause is ascending or descending, determining an original inequality operator based on the sort order for the Order By clause and the paging direction of the separate query, determining whether the current row returns a NULL value, and generating a WHERE condition for the separate query configured to either change the original inequality operator or ignore the original inequality operator depending on whether the paging direction of the separate query is forward paging or backward paging, whether the sort order for the Order By clause is ascending or descending, and whether the current row returns a NULL value. | 8. A memory device storing computer program instructions that, when executed by a processor of a computer, cause the computer to perform a computer-implemented method comprising: receiving a query including: a selected record, an outer join that provides a joined table having NULLab 1 e records, and an Order By clause that provides a sort order for ordering records in the joined table based on one or more fields of the joined table; and generating, by the server, a separate query configured to fetch from the joined table a current row that corresponds to the selected record and either subsequent rows or previous rows relative to the current row, wherein generating the separate query comprises: determining whether a paging direction of the separate query is forward paging or backward paging, determining whether the sort order for the Order By clause is ascending or descending, determining an original inequality operator based on the sort order for the Order By clause and the paging direction of the separate query, determining whether the current row returns a NULL value, and generating a WHERE condition for the separate query configured to either change the original inequality operator or ignore the original inequality operator depending on whether the paging direction of the separate query is forward paging or backward paging, whether the sort order for the Order By clause is ascending or descending, and whether the current row returns a NULL value. 10. The memory device of claim 8 , wherein: the original inequality operator is ignored when the paging direction of the separate query is forward paging, the sort order for the Order By clause is descending, and the current row returns a NULL value. | 0.696339 |
1. A method of context adaptation of a speech-to-speech translation system comprising the steps of: extracting a plurality of sets of paralinguistic attribute values from a plurality of input signals, wherein each set of the plurality of sets of paralinguistic attribute values is extracted from a corresponding input signal of the plurality of input signals via a corresponding classifier of a plurality of classifiers; generating a final set of paralinguistic attribute values for the plurality of input signals from the plurality of sets of paralinguistic attribute values; and modifying performance of at least one of a speech recognition module, a translation module and a text-to-speech module of the speech-to-speech translation system in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier extracts is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest; further wherein the extracting, generating and modifying steps are implemented via instruction code that is executed by at least one processor device. | 1. A method of context adaptation of a speech-to-speech translation system comprising the steps of: extracting a plurality of sets of paralinguistic attribute values from a plurality of input signals, wherein each set of the plurality of sets of paralinguistic attribute values is extracted from a corresponding input signal of the plurality of input signals via a corresponding classifier of a plurality of classifiers; generating a final set of paralinguistic attribute values for the plurality of input signals from the plurality of sets of paralinguistic attribute values; and modifying performance of at least one of a speech recognition module, a translation module and a text-to-speech module of the speech-to-speech translation system in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier extracts is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest; further wherein the extracting, generating and modifying steps are implemented via instruction code that is executed by at least one processor device. 11. The method of claim 1 , wherein the step of modifying performance comprises the step of accessing an expression database to generate appropriate expression in the text-to-speech module based on the final set of paralinguistic attribute values. | 0.56594 |
1. A circuit for converting a first network packet into a second network packet, the circuit comprising: a state machine adapted to convert the first network packet into the second network packet according to at least one modification action from a textual language specification, wherein: each of the at least one modification action being one of an insertion action for inserting a data segment into the first network packet and a removal action for removing a data segment from the first network packet; the state machine including a plurality of states that each correspond to a pairing of a first data word from a first sequence of data words in the first network packet and a second data word from a second sequence of data words in the second network packet; each data word in the first and second network packets including a same number of a plurality of data units, the state for selecting the data units of the second data word from the data segment of each insertion action of the at least one modification action and the data units of both the first data word and a prior data word to the first data word in the first sequence; and each state specifying at least one next state that includes one of the states that corresponds the pairing of one of the first data word and a next data word after the first data word in the first sequence and one of the second data word and a next data word after the second data word in the second sequence; the state machine being configured to concurrently scan through a first plurality of data units in a first sequence of data words in the first network packet and a second plurality of data units in a second sequence of data words in the second network packet, wherein the scanning through the first plurality of data units is suspended throughout each insertion action, and the scanning through the second plurality of data units is suspended throughout each removal action; and a look-ahead stage, an operation stage coupled to the look-ahead stage, an insert/remove stage that includes the state machine and is coupled to the operation stage, and an interleave stage that is coupled to the insert/remove stage. | 1. A circuit for converting a first network packet into a second network packet, the circuit comprising: a state machine adapted to convert the first network packet into the second network packet according to at least one modification action from a textual language specification, wherein: each of the at least one modification action being one of an insertion action for inserting a data segment into the first network packet and a removal action for removing a data segment from the first network packet; the state machine including a plurality of states that each correspond to a pairing of a first data word from a first sequence of data words in the first network packet and a second data word from a second sequence of data words in the second network packet; each data word in the first and second network packets including a same number of a plurality of data units, the state for selecting the data units of the second data word from the data segment of each insertion action of the at least one modification action and the data units of both the first data word and a prior data word to the first data word in the first sequence; and each state specifying at least one next state that includes one of the states that corresponds the pairing of one of the first data word and a next data word after the first data word in the first sequence and one of the second data word and a next data word after the second data word in the second sequence; the state machine being configured to concurrently scan through a first plurality of data units in a first sequence of data words in the first network packet and a second plurality of data units in a second sequence of data words in the second network packet, wherein the scanning through the first plurality of data units is suspended throughout each insertion action, and the scanning through the second plurality of data units is suspended throughout each removal action; and a look-ahead stage, an operation stage coupled to the look-ahead stage, an insert/remove stage that includes the state machine and is coupled to the operation stage, and an interleave stage that is coupled to the insert/remove stage. 2. The circuit of claim 1 , wherein the state machine is automatically generated in response to the textual language specification. | 0.573185 |
1. A computer-implemented method, comprising: identifying, by a computer system, a search query including a text string; searching a first data set using a first search index based at least in part on the search query; obtaining first search results including a subset of the first data set; determining a context associated with the search query based at least in part on the first search results; identifying a second search index from among a plurality of indices based at least in part on the context associated with the search query, the plurality of indices created prior to identifying the second search index; searching the first search results using the second search index; obtaining second search results from among the subset of the first data set based at least in part on said searching the first search results using the second search index; ranking at least a part of the second search results with respect to each other based at least in part on a ranking algorithm of the second search index; and modifying the second search index based at least in part on the ranked part of the second search results, wherein the plurality of indices are modified at a rate that is greater than a rate at which the first search index is modified. | 1. A computer-implemented method, comprising: identifying, by a computer system, a search query including a text string; searching a first data set using a first search index based at least in part on the search query; obtaining first search results including a subset of the first data set; determining a context associated with the search query based at least in part on the first search results; identifying a second search index from among a plurality of indices based at least in part on the context associated with the search query, the plurality of indices created prior to identifying the second search index; searching the first search results using the second search index; obtaining second search results from among the subset of the first data set based at least in part on said searching the first search results using the second search index; ranking at least a part of the second search results with respect to each other based at least in part on a ranking algorithm of the second search index; and modifying the second search index based at least in part on the ranked part of the second search results, wherein the plurality of indices are modified at a rate that is greater than a rate at which the first search index is modified. 2. The computer-implemented method of claim 1 , wherein the search query is received from a user, and wherein said determining the context associated with the search query is further based at least in part on information associated with the user. | 0.520607 |
7. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors of a computing device, cause the one or more processors to perform acts comprising: receiving, at the computing device, a plurality of phrases, individual ones of the plurality of phrases being associated with one or more user-specified communication rules identifying different sets of one or more destination computer devices that are external to the computing device; storing the plurality of phrases and the one or more user-specified communication rules in a memory of the computing device; receiving, at the computing device from a user device over a network, a message having a syntax that includes a phrase, a user created content category, and a piece of content or an identification of the piece of content; interpreting the message to extract the phrase, the user created content category, and the piece of content or the identification of the piece of content; identifying, in the memory, the phrase within the plurality of phrases; determining that the piece of content or the identification of the piece of content is associated with one of a plurality of storage categories that are associated with a first combination of the phrase and the user created content category; identifying, from the memory, a particular user-specified communication rule that is associated with a second combination of the phrase and a storage category of the plurality of storage categories associated with the piece of content or the identification of the piece of content; and causing the piece of content, the identification of the piece of content, or information associated with the piece of content, to be sent over the network to the one or more destinations identified by the particular user-specified communication rule. | 7. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors of a computing device, cause the one or more processors to perform acts comprising: receiving, at the computing device, a plurality of phrases, individual ones of the plurality of phrases being associated with one or more user-specified communication rules identifying different sets of one or more destination computer devices that are external to the computing device; storing the plurality of phrases and the one or more user-specified communication rules in a memory of the computing device; receiving, at the computing device from a user device over a network, a message having a syntax that includes a phrase, a user created content category, and a piece of content or an identification of the piece of content; interpreting the message to extract the phrase, the user created content category, and the piece of content or the identification of the piece of content; identifying, in the memory, the phrase within the plurality of phrases; determining that the piece of content or the identification of the piece of content is associated with one of a plurality of storage categories that are associated with a first combination of the phrase and the user created content category; identifying, from the memory, a particular user-specified communication rule that is associated with a second combination of the phrase and a storage category of the plurality of storage categories associated with the piece of content or the identification of the piece of content; and causing the piece of content, the identification of the piece of content, or information associated with the piece of content, to be sent over the network to the one or more destinations identified by the particular user-specified communication rule. 10. One or more non-transitory computer-readable media as recited in claim 7 , wherein the piece of content or the identification of the piece of content comprises a string of text, a link, a web page, an image or a video. | 0.633739 |
19. A method, comprising: selecting a return value corresponding to a spoken input; generating a subset of alternative return values for the spoken input, wherein the alternative return value is related to the selected return value based on one of a synonym relationship and a phonetic similarity threshold between the grammars for the return value and the alternative return value; generating a first string in a pair of strings is from the grammar for a first return value, and a second string in the pair of strings is from the grammar for a second return value and is not in the grammar for the first return value, then selecting the second string as a likely alternative for the first return value, and constructing the subset of return values that are likely alternatives for each return value in a dictionary; and presenting the alternative return values to the user for selection, wherein the user is notified of each string that has a likelihood of being confused so that the user can make changes to the grammar. | 19. A method, comprising: selecting a return value corresponding to a spoken input; generating a subset of alternative return values for the spoken input, wherein the alternative return value is related to the selected return value based on one of a synonym relationship and a phonetic similarity threshold between the grammars for the return value and the alternative return value; generating a first string in a pair of strings is from the grammar for a first return value, and a second string in the pair of strings is from the grammar for a second return value and is not in the grammar for the first return value, then selecting the second string as a likely alternative for the first return value, and constructing the subset of return values that are likely alternatives for each return value in a dictionary; and presenting the alternative return values to the user for selection, wherein the user is notified of each string that has a likelihood of being confused so that the user can make changes to the grammar. 20. The method of claim 19 , wherein the step of generating the subset of alternative return values is performed at compile time as opposed to at runtime. | 0.623697 |
1. A method for searching for information in a distributed data processing system, the method comprising: providing a semantics-based search index by storing in the semantics-bases search index search keywords from documents according to semantics from selected document structure templates, the document structure templates selected in dependence upon the structures of the documents and upon model document structures in the document structure templates; establishing a search scope corresponding to semantics supported by the semantics-based search index; receiving from a client a search query message comprising search terms and, optionally, the search scope; retrieving, from the semantics-based search index, index entries satisfying the search terms and the search scope; creating from the retrieved index entries a search result message; and transmitting the search result message to the client. | 1. A method for searching for information in a distributed data processing system, the method comprising: providing a semantics-based search index by storing in the semantics-bases search index search keywords from documents according to semantics from selected document structure templates, the document structure templates selected in dependence upon the structures of the documents and upon model document structures in the document structure templates; establishing a search scope corresponding to semantics supported by the semantics-based search index; receiving from a client a search query message comprising search terms and, optionally, the search scope; retrieving, from the semantics-based search index, index entries satisfying the search terms and the search scope; creating from the retrieved index entries a search result message; and transmitting the search result message to the client. 7. The method of claim 1 wherein creating the search result message comprises sorting search result message entries according to measures of relevance for entries in the search result message. | 0.881595 |
1. A named entity dictionary update apparatus using a named entity dictionary and a mining rule combined with an ontology schema, the apparatus comprising: a named entity dictionary and mining rule database storage module for storing the named entity dictionary where a named entity of a terminology combined with the ontology schema and connected to a concept (class) is defined and a mining rule database where the mining rule configured with an RDF triple and a mining pattern combined with the ontology schema and connected to a relationship name is defined; a named entity and mining rule search module for searching for a corresponding mining rule and a named entity from the mining rule database and the named entity dictionary using a terminology included in an inputted mining pattern and the mining pattern; and a named entity dictionary update module for estimating a named entity of the terminology using the mining rule and storing the estimated named entity of the terminology in the named entity dictionary depending on a user's selection, if a named entity corresponding to the terminology is not searched from the named entity dictionary and the mining rule corresponding to the mining pattern is searched from the mining rule database. | 1. A named entity dictionary update apparatus using a named entity dictionary and a mining rule combined with an ontology schema, the apparatus comprising: a named entity dictionary and mining rule database storage module for storing the named entity dictionary where a named entity of a terminology combined with the ontology schema and connected to a concept (class) is defined and a mining rule database where the mining rule configured with an RDF triple and a mining pattern combined with the ontology schema and connected to a relationship name is defined; a named entity and mining rule search module for searching for a corresponding mining rule and a named entity from the mining rule database and the named entity dictionary using a terminology included in an inputted mining pattern and the mining pattern; and a named entity dictionary update module for estimating a named entity of the terminology using the mining rule and storing the estimated named entity of the terminology in the named entity dictionary depending on a user's selection, if a named entity corresponding to the terminology is not searched from the named entity dictionary and the mining rule corresponding to the mining pattern is searched from the mining rule database. 4. The apparatus according to claim 1 , wherein the named entity dictionary connects and stores authority data comprising a named entity corresponding to a concept (class) of the ontology schema, a terminology classified as the named entity, identification of the terminology, a representative terminology, and identification of the representative terminology in one format. | 0.732057 |
6. The computer-executable information retrieval apparatus as recited in claim 5 , further comprising an evaluation input portion to which evaluation is input. | 6. The computer-executable information retrieval apparatus as recited in claim 5 , further comprising an evaluation input portion to which evaluation is input. 7. The computer-executable information retrieval apparatus as recited in claim 6 , wherein said evaluation is input by selecting a stepwise value. | 0.958381 |
1. A computer implemented method of filtering context-sensitive search results, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications; formulating a first query and a second query based on the first aspect of the user context, the first query and the second query being different than the user context; submitting the first query to a first search engine; receiving a first plurality of search results from the first search engine, the first plurality of search results being based on the first query; submitting the second query to a second different search engine; receiving a second plurality of search results from the second different search engine, the second plurality of search results being based on the second query; determining a first plurality of scores associated with the first plurality of search results at least in part by comparing data indicative of the first plurality of search results to data indicative of the first aspect of the user context; determining a second plurality of scores associated with the second plurality of search results at least in part by comparing data indicative of the second plurality of search results to the data indicative of the first aspect of the user context; and displaying a subset of the plurality of search results on a client device, wherein at least one of the first plurality of search results is filtered from being displayed to the user based on at least a portion of the first plurality of scores, and wherein at least one of the second plurality of search results is filtered from being displayed to the user based on at least a portion of the second plurality of scores. | 1. A computer implemented method of filtering context-sensitive search results, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications; formulating a first query and a second query based on the first aspect of the user context, the first query and the second query being different than the user context; submitting the first query to a first search engine; receiving a first plurality of search results from the first search engine, the first plurality of search results being based on the first query; submitting the second query to a second different search engine; receiving a second plurality of search results from the second different search engine, the second plurality of search results being based on the second query; determining a first plurality of scores associated with the first plurality of search results at least in part by comparing data indicative of the first plurality of search results to data indicative of the first aspect of the user context; determining a second plurality of scores associated with the second plurality of search results at least in part by comparing data indicative of the second plurality of search results to the data indicative of the first aspect of the user context; and displaying a subset of the plurality of search results on a client device, wherein at least one of the first plurality of search results is filtered from being displayed to the user based on at least a portion of the first plurality of scores, and wherein at least one of the second plurality of search results is filtered from being displayed to the user based on at least a portion of the second plurality of scores. 7. The method of claim 1 , including comparing data indicative of the first plurality of search results to data indicative of the user context to determine a plurality of organization schemes, the plurality of organization schemes grouping at least a portion of the first plurality of search results into at least two genres. | 0.691693 |
15. The system of claim 11 , where, when identifying that the list is present within the document, the one or more processors are further to: analyze a corpus of documents to identify whether any lists are present within the corpus of documents, where the corpus of documents includes the document, and annotate the document with list information when the list is identified as present within the document. | 15. The system of claim 11 , where, when identifying that the list is present within the document, the one or more processors are further to: analyze a corpus of documents to identify whether any lists are present within the corpus of documents, where the corpus of documents includes the document, and annotate the document with list information when the list is identified as present within the document. 16. The system of claim 15 , where, when determining that the first and second terms appear in the list, the one or more processors are further to: compare the first and second terms to the annotated list information to determine that the first and second terms appear in the list. | 0.914841 |
9. A computer-implemented method for analyzing requirements data, comprising: receiving a search query comprising search terms; identifying a first requirement based on a degree of relatedness between the search terms and the textual content of the first requirement; identifying a plurality of soft links between the first requirement and a plurality of related requirements, wherein each of the plurality of soft links represents a relatedness score between the first requirement and a related requirement from the plurality of related requirements, and each of the relatedness scores exceeds a threshold; ranking the plurality of related requirements based on their relatedness scores; and providing the highest ranked requirement to a user via a computer device. | 9. A computer-implemented method for analyzing requirements data, comprising: receiving a search query comprising search terms; identifying a first requirement based on a degree of relatedness between the search terms and the textual content of the first requirement; identifying a plurality of soft links between the first requirement and a plurality of related requirements, wherein each of the plurality of soft links represents a relatedness score between the first requirement and a related requirement from the plurality of related requirements, and each of the relatedness scores exceeds a threshold; ranking the plurality of related requirements based on their relatedness scores; and providing the highest ranked requirement to a user via a computer device. 13. The computer-implemented method of claim 9 , further comprising adding a related term to the search query that is determined by a subject matter expert or technician to be related to a search term. | 0.707317 |
1. A method to be executed at least in part in a computing device for providing integrated user interface controls for web dialogs, the method comprising: presenting a parent web page displaying web page elements to a user from a web application; hiding at least a portion of the displayed web page elements in response to receiving a user selection in a parent web page including at least one of: a desire to edit content, a desire to create new content, or a desire to fill a form; presenting a dialog over the hidden web page elements within the web page, wherein the dialog includes a set of contextual controls for enabling the user to view content, edit the content, create the new content, and to perform data mining, search, and analysis on the content; enabling the user to transition between different states of the dialog associated with a category of tasks to be performed on a selected item, wherein a different set of contextual controls are displayed in association with each dialog state in a same style and position on each different state for performing one or more of: managing the selected item, editing an attribute of the selected item, editing a content of the selected item, or formatting the content of the selected item, such that consistency of the contextual controls is maintained; hiding at least a portion of the currently displayed dialog; and launching a new state in a new dialog over top of the hidden portion of the currently displayed dialog wherein the new state includes a tab for indicating which dialog state is presented, a header portion for indicating the web page and the selected item, and a different set of contextual controls displayed in association with the new state in a same style and position as the hidden dialog. | 1. A method to be executed at least in part in a computing device for providing integrated user interface controls for web dialogs, the method comprising: presenting a parent web page displaying web page elements to a user from a web application; hiding at least a portion of the displayed web page elements in response to receiving a user selection in a parent web page including at least one of: a desire to edit content, a desire to create new content, or a desire to fill a form; presenting a dialog over the hidden web page elements within the web page, wherein the dialog includes a set of contextual controls for enabling the user to view content, edit the content, create the new content, and to perform data mining, search, and analysis on the content; enabling the user to transition between different states of the dialog associated with a category of tasks to be performed on a selected item, wherein a different set of contextual controls are displayed in association with each dialog state in a same style and position on each different state for performing one or more of: managing the selected item, editing an attribute of the selected item, editing a content of the selected item, or formatting the content of the selected item, such that consistency of the contextual controls is maintained; hiding at least a portion of the currently displayed dialog; and launching a new state in a new dialog over top of the hidden portion of the currently displayed dialog wherein the new state includes a tab for indicating which dialog state is presented, a header portion for indicating the web page and the selected item, and a different set of contextual controls displayed in association with the new state in a same style and position as the hidden dialog. 10. The method of claim 1 , wherein the set of contextual controls enable a user to one of: close an existing dialog, open a new dialog, or change a state of the existing dialog without affecting a state of the parent web page. | 0.701003 |
23. A system for generating a ranked list of alternatives, the system comprising: means for generating a homogeneous matrix of scores based on a heterogeneous matrix of attributes and alternatives, means for receiving two or more tradeoff values, means for generating a ranked list of alternatives based on the homogeneous matrix of scores and the tradeoff value, and means for creating a logic graph using a training program. | 23. A system for generating a ranked list of alternatives, the system comprising: means for generating a homogeneous matrix of scores based on a heterogeneous matrix of attributes and alternatives, means for receiving two or more tradeoff values, means for generating a ranked list of alternatives based on the homogeneous matrix of scores and the tradeoff value, and means for creating a logic graph using a training program. 24. A system as recited in claim 23 , further comprising: means for generating a logic diagram, the logic diagram being used to generate the homogeneous matrix of scores. | 0.787433 |
6. A decompression system for decompression of compressed text data, the decompression system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute programmed instructions stored in the memory to: maintain a set of character tables and a cluster table in the memory, wherein each character table stores a set of Unicode characters corresponding to a character class of a set of characters classes, wherein each Unicode character from the character table is assigned with a shortened bit representation, and wherein the cluster table is configured to maintain a set of cluster types and a cluster identifier corresponding to each of the cluster type, wherein each cluster type corresponds to a character class or a valid combination of two or more character classes represented by the set of character tables; accept a compressed text string, wherein the compressed text string is a set of clusters, wherein each cluster is represented with a cluster identifier followed by shortened bit representation corresponding to each Unicode character in each cluster; classify the compressed text string into a set of clusters, wherein each cluster is identified based on a corresponding cluster identifier and the set of cluster types in the cluster table; identify a shortened bit representation and corresponding character table for each character in the cluster based on the cluster type applicable to the cluster; and generate a Unicode text string by representing each shortened bit representation in the cluster with a corresponding Unicode character, wherein the Unicode character is identified from the corresponding character table. | 6. A decompression system for decompression of compressed text data, the decompression system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute programmed instructions stored in the memory to: maintain a set of character tables and a cluster table in the memory, wherein each character table stores a set of Unicode characters corresponding to a character class of a set of characters classes, wherein each Unicode character from the character table is assigned with a shortened bit representation, and wherein the cluster table is configured to maintain a set of cluster types and a cluster identifier corresponding to each of the cluster type, wherein each cluster type corresponds to a character class or a valid combination of two or more character classes represented by the set of character tables; accept a compressed text string, wherein the compressed text string is a set of clusters, wherein each cluster is represented with a cluster identifier followed by shortened bit representation corresponding to each Unicode character in each cluster; classify the compressed text string into a set of clusters, wherein each cluster is identified based on a corresponding cluster identifier and the set of cluster types in the cluster table; identify a shortened bit representation and corresponding character table for each character in the cluster based on the cluster type applicable to the cluster; and generate a Unicode text string by representing each shortened bit representation in the cluster with a corresponding Unicode character, wherein the Unicode character is identified from the corresponding character table. 10. The decompression system of claim 6 , wherein the valid combination is determined based on a cluster types associated with at least one language of a set of languages. | 0.554622 |
27. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs in the computer readable storage medium comprising instructions for: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, wherein the presentation information is formatted such that: conversation identifying information for each conversation in the list of conversations is displayed as a single row in the set of rows; and the sender list associated with the conversation is displayed in the same single row, along with the conversation identifying information; and wherein a displayed sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. | 27. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs in the computer readable storage medium comprising instructions for: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, wherein the presentation information is formatted such that: conversation identifying information for each conversation in the list of conversations is displayed as a single row in the set of rows; and the sender list associated with the conversation is displayed in the same single row, along with the conversation identifying information; and wherein a displayed sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. 32. The computer readable storage medium of claim 27 , wherein at least one row in the set of rows includes a recipient indicator that indicates whether the user is a primary recipient or secondary recipient of any message in the conversation. | 0.644569 |
30. The method of claim 24 , wherein the displaying comprises: assigning a respective rank to each of the plurality of predefined suggestions according to one or more predetermined criteria; and displaying the plurality of predefined suggestions according to their respective ranks. | 30. The method of claim 24 , wherein the displaying comprises: assigning a respective rank to each of the plurality of predefined suggestions according to one or more predetermined criteria; and displaying the plurality of predefined suggestions according to their respective ranks. 33. The method of claim 30 , wherein the predetermined criteria include proximity of plurality of medical devices to the portable electronic device, and wherein the data entry is directed toward the medical devices. | 0.954962 |
7. A computer program product for using user preferences to customize answer output comprising: a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: for a first user and a first question: extract by a natural language processor from the question one or more user preferences and one or more sentiment levels; perform a semantic search on of the first question; receive a plurality of candidate answers from the semantic search; select one or more of the received candidate answers, wherein the selection is performed both according to the one or more sentiment levels and according to the one or more user preferences; and produce a first user output including the selected one or more candidate answers; for a second question and a second user, repeat the step of extracting preferences from the second question; accumulate the preferences and sentiments extracted from the second question with the preferences and sentiments extracted from the first question; and for the second question, repeat the steps of performing a semantic search, receiving candidate answers, selecting candidate answers according to the accumulated preferences and sentiments, and producing a second output. | 7. A computer program product for using user preferences to customize answer output comprising: a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: for a first user and a first question: extract by a natural language processor from the question one or more user preferences and one or more sentiment levels; perform a semantic search on of the first question; receive a plurality of candidate answers from the semantic search; select one or more of the received candidate answers, wherein the selection is performed both according to the one or more sentiment levels and according to the one or more user preferences; and produce a first user output including the selected one or more candidate answers; for a second question and a second user, repeat the step of extracting preferences from the second question; accumulate the preferences and sentiments extracted from the second question with the preferences and sentiments extracted from the first question; and for the second question, repeat the steps of performing a semantic search, receiving candidate answers, selecting candidate answers according to the accumulated preferences and sentiments, and producing a second output. 12. The computer program product as set forth in claim 7 wherein the program instructions which, when executed by a processor, cause a computing platform to select comprise program instructions which, when executed by a processor, cause a computing platform a weighting process. | 0.813065 |
1. A method of recommending a path comprising learning objects and learning vectors, the method comprising: automatically generating a learning object network, wherein generating the learning object network comprises: automatically receiving a plurality content objects from a plurality of data sources via a network at a processor, wherein each of the learning objects comprises an aggregation of learning content that is associated with an assessment; automatically generating a plurality of learning vectors connecting the plurality of content objects with the processor based on information received from a plurality of user devices, wherein each of the plurality of learning vectors connects two of the plurality of learning objects and identifies a prerequisite relationship between the connected two of the plurality of learning objects, wherein each of the plurality of learning vectors comprises a direction identifying the prerequisite relationship and a magnitude; and continuously updating the plurality of learning vectors based on signals received from one or several user devices identifying successes and failures in traversing the plurality of learning vectors; receiving at the processor an input from a student device via the network; automatically identifying a student user of the student device based on the received input and information retrieved from a student database; automatically retrieving information relating to a plurality of learning object networks; automatically identifying with the processor one of the plurality of learning object networks relevant to the student user of the student device; automatically identifying with a processor an incident learning object, wherein the incident learning object comprises an initial position of a student within the learning object network, wherein the incident learning object is identified by one of: a user input identifying the incident learning object, wherein the user comprises one of a teacher and the student user of the student device; and a student context, wherein the student context comprises the: student's learning history; and metadata identifying a student learning capability; automatically identifying with the processor a target learning object, wherein the target learning object is a learning object separated from the incident learning object by a plurality of learning vectors; automatically identifying with the processor a first path from the incident learning object to the target learning object, wherein the first path comprises a plurality of learning objects and a plurality of learning vectors connecting the incident learning object to the target learning object; automatically calculating with the processor the magnitude of the first path from the incident learning object to the target learning object, wherein calculating the magnitude of the first path from the incident learning object to the target learning object comprises: automatically varying the magnitudes of the plurality of learning vectors in the first and second path based on the student context; retrieving the magnitudes of the plurality of learning vectors in the first path; and calculating a combined magnitude of the first path; wherein retrieving the magnitudes of the plurality of learning vectors in the first path comprises: identifying a characteristic of the student, wherein the student characteristic is identified via a user input or via the student context; retrieving a learning vector context, wherein the learning vector context identifies magnitude data corresponding to aspects of the student context; and identifying magnitude data corresponding to the identified characteristic of the student; automatically identifying with the processor a second path from the incident learning object to the target learning object, wherein the second path comprises a plurality of learning objects and learning vectors connecting the incident learning object to the target learning object, wherein the second path comprises at least one learning object that is not in the first path automatically calculating with the processor the magnitude of the second path from the incident learning object to the target learning object; automatically comparing with the processor the magnitude of the first path to the magnitude of the second path; automatically providing one of the plurality of learning objects from the one of the first and second paths having the lesser magnitude to the student device, wherein the student device is remove from the processor; receiving an indicator of completion of the provided learning object; and automatically generating and sending a communication to the student device, wherein the communication comprises an enhancement object automatically triggered for providing to the student via a threshold, wherein the enhancement object is outside of the one of the first and second learning paths containing the provided learning object, and wherein the communication activates a user interface of the student device to provide the enhancement object to the user via a screen of the student device. | 1. A method of recommending a path comprising learning objects and learning vectors, the method comprising: automatically generating a learning object network, wherein generating the learning object network comprises: automatically receiving a plurality content objects from a plurality of data sources via a network at a processor, wherein each of the learning objects comprises an aggregation of learning content that is associated with an assessment; automatically generating a plurality of learning vectors connecting the plurality of content objects with the processor based on information received from a plurality of user devices, wherein each of the plurality of learning vectors connects two of the plurality of learning objects and identifies a prerequisite relationship between the connected two of the plurality of learning objects, wherein each of the plurality of learning vectors comprises a direction identifying the prerequisite relationship and a magnitude; and continuously updating the plurality of learning vectors based on signals received from one or several user devices identifying successes and failures in traversing the plurality of learning vectors; receiving at the processor an input from a student device via the network; automatically identifying a student user of the student device based on the received input and information retrieved from a student database; automatically retrieving information relating to a plurality of learning object networks; automatically identifying with the processor one of the plurality of learning object networks relevant to the student user of the student device; automatically identifying with a processor an incident learning object, wherein the incident learning object comprises an initial position of a student within the learning object network, wherein the incident learning object is identified by one of: a user input identifying the incident learning object, wherein the user comprises one of a teacher and the student user of the student device; and a student context, wherein the student context comprises the: student's learning history; and metadata identifying a student learning capability; automatically identifying with the processor a target learning object, wherein the target learning object is a learning object separated from the incident learning object by a plurality of learning vectors; automatically identifying with the processor a first path from the incident learning object to the target learning object, wherein the first path comprises a plurality of learning objects and a plurality of learning vectors connecting the incident learning object to the target learning object; automatically calculating with the processor the magnitude of the first path from the incident learning object to the target learning object, wherein calculating the magnitude of the first path from the incident learning object to the target learning object comprises: automatically varying the magnitudes of the plurality of learning vectors in the first and second path based on the student context; retrieving the magnitudes of the plurality of learning vectors in the first path; and calculating a combined magnitude of the first path; wherein retrieving the magnitudes of the plurality of learning vectors in the first path comprises: identifying a characteristic of the student, wherein the student characteristic is identified via a user input or via the student context; retrieving a learning vector context, wherein the learning vector context identifies magnitude data corresponding to aspects of the student context; and identifying magnitude data corresponding to the identified characteristic of the student; automatically identifying with the processor a second path from the incident learning object to the target learning object, wherein the second path comprises a plurality of learning objects and learning vectors connecting the incident learning object to the target learning object, wherein the second path comprises at least one learning object that is not in the first path automatically calculating with the processor the magnitude of the second path from the incident learning object to the target learning object; automatically comparing with the processor the magnitude of the first path to the magnitude of the second path; automatically providing one of the plurality of learning objects from the one of the first and second paths having the lesser magnitude to the student device, wherein the student device is remove from the processor; receiving an indicator of completion of the provided learning object; and automatically generating and sending a communication to the student device, wherein the communication comprises an enhancement object automatically triggered for providing to the student via a threshold, wherein the enhancement object is outside of the one of the first and second learning paths containing the provided learning object, and wherein the communication activates a user interface of the student device to provide the enhancement object to the user via a screen of the student device. 2. The method of claim 1 , wherein the student characteristic comprises one of: a learning style; a student's past performance; and a student preference. | 0.571332 |
50. For a database having records stored in memory which are organized to include logically grouped and indexable data elements, a processor controlled method of generating indexes comprising: identifying importance values for individual database requests; and designing indexes to the database for the requests based upon importance values of requests for which the indexes are created by ordering requests by importance values, identifying, by order of request importance, candidate indexes for requests, searching previously identified indexes for an index that is similar, to each candidate index, and building previously identified indexes by reusing existing indexes and modifying existing indexes based upon match between indexes. | 50. For a database having records stored in memory which are organized to include logically grouped and indexable data elements, a processor controlled method of generating indexes comprising: identifying importance values for individual database requests; and designing indexes to the database for the requests based upon importance values of requests for which the indexes are created by ordering requests by importance values, identifying, by order of request importance, candidate indexes for requests, searching previously identified indexes for an index that is similar, to each candidate index, and building previously identified indexes by reusing existing indexes and modifying existing indexes based upon match between indexes. 51. A method as claimed in claim 50 wherein the step of designing indexes comprises: identifying columns and associated operators for individual table contexts within each expression of each request; and identifying candidate indexes from the identified columns for individual contexts. | 0.919251 |
1. A method for authoring a document at a first computing device, the method comprising: at the first computing device, allowing a first unit of data of the document to be edited by a first user; at the first computing device, when the first unit of data is edited, providing a first annotation on the document indicating that the document is being edited by the first user; at the first computing device, sending a first metadata update to a second computing device, the first metadata update indicating that the first unit of data of the document is being edited; at the first computing device, receiving a second metadata update from the second computing device, the second metadata update indicating a name of a second user that is editing a second unit of data of the document; at the first computing device, setting a first lock on the second unit of data, the first lock on the second unit of data preventing the second unit of data from being edited at the first computing device; at the first computing device, providing a second annotation on the document, the second annotation indicating that the second unit of data is being edited by the second user; at the first computing device, receiving content updates for the document from the second computing device; at the first computing device, in response to receiving the content updates, receiving an instruction from the first user to instantiate the content updates into the document; and at the first computing device, in response to the instruction from the first user, updating the document to incorporate the content updates. | 1. A method for authoring a document at a first computing device, the method comprising: at the first computing device, allowing a first unit of data of the document to be edited by a first user; at the first computing device, when the first unit of data is edited, providing a first annotation on the document indicating that the document is being edited by the first user; at the first computing device, sending a first metadata update to a second computing device, the first metadata update indicating that the first unit of data of the document is being edited; at the first computing device, receiving a second metadata update from the second computing device, the second metadata update indicating a name of a second user that is editing a second unit of data of the document; at the first computing device, setting a first lock on the second unit of data, the first lock on the second unit of data preventing the second unit of data from being edited at the first computing device; at the first computing device, providing a second annotation on the document, the second annotation indicating that the second unit of data is being edited by the second user; at the first computing device, receiving content updates for the document from the second computing device; at the first computing device, in response to receiving the content updates, receiving an instruction from the first user to instantiate the content updates into the document; and at the first computing device, in response to the instruction from the first user, updating the document to incorporate the content updates. 7. The method of claim 1 , further comprising the first metadata update including a name of the first user. | 0.60214 |
2. A method comprising: displaying a tabstrip widget including at least first and second tabs, each of the at least first and second tabs further including a tab conditions panel and a tab summary panel, the tab summary panel configured to display a first statistic associated with a term of a Boolean expression defined by the corresponding tab conditions panel, a first update element operable to, in response to user selection, update the first statistic, a second statistic associated with the entire Boolean expression, and a second update element operable to, in response to user selection, update the second statistic, and the tabstrip widget being configured to display one tab conditions panel of the at least first and second tabs at a time; receiving a first user input defining a first term of a Boolean expression including a first number of condition statements; displaying the first term of the Boolean expression in the tab conditions panel of the first tab; superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab; receiving a second user input defining a second term of the Boolean expression including a second number of condition statements, the second number of condition statements being different than the first number of condition statements; displaying the second term of the Boolean expression in the tab conditions panel of the second tab; in response to user selection of the first update element included in the tab summary panel of the second tab, updating the first statistic included in the tab summary panel of the second tab based on the second term of the Boolean expression including the second number of condition statements; in response to user selection of the second update element included in the tab summary panel of the second tab, updating the second statistic included in the tab summary panel of the second tab based on the entire Boolean expression defined by the first term of the Boolean expression including the first number of condition statements and the second term of the Boolean expression including the second number of condition statements; and outputting data satisfying the first and second terms of the Boolean expression. | 2. A method comprising: displaying a tabstrip widget including at least first and second tabs, each of the at least first and second tabs further including a tab conditions panel and a tab summary panel, the tab summary panel configured to display a first statistic associated with a term of a Boolean expression defined by the corresponding tab conditions panel, a first update element operable to, in response to user selection, update the first statistic, a second statistic associated with the entire Boolean expression, and a second update element operable to, in response to user selection, update the second statistic, and the tabstrip widget being configured to display one tab conditions panel of the at least first and second tabs at a time; receiving a first user input defining a first term of a Boolean expression including a first number of condition statements; displaying the first term of the Boolean expression in the tab conditions panel of the first tab; superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab; receiving a second user input defining a second term of the Boolean expression including a second number of condition statements, the second number of condition statements being different than the first number of condition statements; displaying the second term of the Boolean expression in the tab conditions panel of the second tab; in response to user selection of the first update element included in the tab summary panel of the second tab, updating the first statistic included in the tab summary panel of the second tab based on the second term of the Boolean expression including the second number of condition statements; in response to user selection of the second update element included in the tab summary panel of the second tab, updating the second statistic included in the tab summary panel of the second tab based on the entire Boolean expression defined by the first term of the Boolean expression including the first number of condition statements and the second term of the Boolean expression including the second number of condition statements; and outputting data satisfying the first and second terms of the Boolean expression. 13. The method of claim 2 , further comprising hiding the tab conditions panel of the first tab based upon superimposing the tab conditions panel of the second tab on the tab conditions panel of the first tab. | 0.624545 |
1. A multiple citation corpus data structure stored in a computer memory for a user specified word or phrase comprising an entry for every occurrence of the user specified word or phrase, each entry comprising: a) prior context, b) the user specified word or phrase, c) subsequent context, and d) one or more internal citations, wherein the prior context, the user specified word or phrase, and the subsequent context forming a unique quote of each entry, wherein each internal citation identifies a document and the location inside the document where the unique quote of the entry is found in a plurality of formatted documents, and wherein the one or more internal citations of each entry is a combined citation comprising a complete list of every occurrence of the unique quote of the respective entry in the respective plurality of formatted documents. | 1. A multiple citation corpus data structure stored in a computer memory for a user specified word or phrase comprising an entry for every occurrence of the user specified word or phrase, each entry comprising: a) prior context, b) the user specified word or phrase, c) subsequent context, and d) one or more internal citations, wherein the prior context, the user specified word or phrase, and the subsequent context forming a unique quote of each entry, wherein each internal citation identifies a document and the location inside the document where the unique quote of the entry is found in a plurality of formatted documents, and wherein the one or more internal citations of each entry is a combined citation comprising a complete list of every occurrence of the unique quote of the respective entry in the respective plurality of formatted documents. 12. The multiple citation corpus data structure of claim 1 , wherein the user specified phrase comprises a plurality of words in a specified sequence. | 0.611477 |
51. The system of claim 50 , wherein the average hypothesis approximates a maximum likelihood estimate for a true pose of a corresponding tag. | 51. The system of claim 50 , wherein the average hypothesis approximates a maximum likelihood estimate for a true pose of a corresponding tag. 53. The system of claim 51 , wherein the average hypothesis comprises a rotational component. | 0.936047 |
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