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1. A computer system for searching databases and displaying search results, comprising: a network-based connection to one or more databases storing information regarding publications, said information comprising author, title, date of publication, cited references, and citing references data; a server in communication with and operable to transmit data to a Web browser resident on a user's computer, and a processor including programming to implement a search; said programming including XQuery statements that return citation values associated with said reference with at least one XQuery statement written as an estimated XPath step; said server is programmed to provide a citation overview details regarding reference citations resulting from a search request; said citation overview page transmitted to said user's browser, comprising: (a) a list of one or more titles of publications, and (b) two or more displayed numerals, each of said displayed numerals representing how many publications in one of a plurality of specified publication years cite to each of said publications. | 1. A computer system for searching databases and displaying search results, comprising: a network-based connection to one or more databases storing information regarding publications, said information comprising author, title, date of publication, cited references, and citing references data; a server in communication with and operable to transmit data to a Web browser resident on a user's computer, and a processor including programming to implement a search; said programming including XQuery statements that return citation values associated with said reference with at least one XQuery statement written as an estimated XPath step; said server is programmed to provide a citation overview details regarding reference citations resulting from a search request; said citation overview page transmitted to said user's browser, comprising: (a) a list of one or more titles of publications, and (b) two or more displayed numerals, each of said displayed numerals representing how many publications in one of a plurality of specified publication years cite to each of said publications. 2. A computer system as in claim 1 , wherein, said citation overview page further comprises at least one displayed numeral representing a grand total of how many publications of all specified publication years cite to any of said listed publications, and wherein said citation overview page further comprises a citation weight display that represents said grand total divided by how many publications are listed on said citation overview page. | 0.531395 |
24. A server system, comprising: one or more processors; one or more data stores configured to store client data for each of a plurality of clients that are each associated with a respective client device; a unique custom character reference, one or more tag words, and image data associated with each of a plurality of custom characters; and a server messaging application including instructions that are executable by the one or more processors, the server messaging application operable to: receive a unique custom character reference query including one or more standard characters from a said client device, and in response thereto, identify one or more of the unique custom character references that have a tag word associate therewith that includes the one or more standard characters included in the unique custom character reference query; send to the client device from which the unique custom character reference query was received, a list of the identified one or more of the unique custom character references that have a tag word associate therewith that includes the one or more standard characters included in the unique custom character reference query; receive an image data query including a unique custom character reference from the client device, and in response thereto, identify image data for a custom character associated with the unique custom character reference included in the image data query; and send to the client device from which the image data query was received, image data for the custom character associated with the unique custom character reference included in the image data query; wherein the standard characters that are included within the Unicode Standard are selectable by the user of the client device via a virtual keyboard of the user interface of the client device; wherein image data for the standard characters that are included within the Unicode Standard are provided by the operating system of the client device, which is stored in a local data store of the client device; and wherein the image data for each of the custom character(s) is not provided by the operating system of the client device. | 24. A server system, comprising: one or more processors; one or more data stores configured to store client data for each of a plurality of clients that are each associated with a respective client device; a unique custom character reference, one or more tag words, and image data associated with each of a plurality of custom characters; and a server messaging application including instructions that are executable by the one or more processors, the server messaging application operable to: receive a unique custom character reference query including one or more standard characters from a said client device, and in response thereto, identify one or more of the unique custom character references that have a tag word associate therewith that includes the one or more standard characters included in the unique custom character reference query; send to the client device from which the unique custom character reference query was received, a list of the identified one or more of the unique custom character references that have a tag word associate therewith that includes the one or more standard characters included in the unique custom character reference query; receive an image data query including a unique custom character reference from the client device, and in response thereto, identify image data for a custom character associated with the unique custom character reference included in the image data query; and send to the client device from which the image data query was received, image data for the custom character associated with the unique custom character reference included in the image data query; wherein the standard characters that are included within the Unicode Standard are selectable by the user of the client device via a virtual keyboard of the user interface of the client device; wherein image data for the standard characters that are included within the Unicode Standard are provided by the operating system of the client device, which is stored in a local data store of the client device; and wherein the image data for each of the custom character(s) is not provided by the operating system of the client device. 26. The server system of claim 24 , wherein the server messaging application is also operable to: receive from a said client device associate with a said user, image data associated with a new custom character created by the user and one or more tag words that the user specified as being associated with new custom character; store within at least one of the one or more data stores, a unique custom character reference for the new custom character, the one or more tag words associated therewith, and the image data associated therewith. | 0.686272 |
7. A non-transitory computer readable medium comprising computer software stored thereon improving the way a computer performs an internet search, said software comprising: index server code maintaining dynamic indices to internet web pages and employing a preexisting plurality of topic categories whose contents, including topics and links not provided by a particular end user, are maintained and updated by said index server code without end user intervention being required, wherein a master index is maintained as well as an end user's index for each user as customized by each user; link code updating the end user's index to include any subset of the plurality of topic categories specified by the end user; link code adding to an electronic medium controlled by the end user link information permitting execution of searches via said index server code in any category of said subset but only of categories in said subset; and link code permitting the end user to propose addition of an internet web page to said master index code in conjunction with one or more categories of said subset and automatically adding said proposed page to those indexed by said end user's index code wherein the end user can search said proposed page via said link information and wherein initially other users will not search said proposed page even if searching said proposed one or more categories; and wherein the index server updates web pages in the topic categories of the master index and the end user's index without any end user intervention and permits the end user to create and organize search indexes specific to the end user's needs. | 7. A non-transitory computer readable medium comprising computer software stored thereon improving the way a computer performs an internet search, said software comprising: index server code maintaining dynamic indices to internet web pages and employing a preexisting plurality of topic categories whose contents, including topics and links not provided by a particular end user, are maintained and updated by said index server code without end user intervention being required, wherein a master index is maintained as well as an end user's index for each user as customized by each user; link code updating the end user's index to include any subset of the plurality of topic categories specified by the end user; link code adding to an electronic medium controlled by the end user link information permitting execution of searches via said index server code in any category of said subset but only of categories in said subset; and link code permitting the end user to propose addition of an internet web page to said master index code in conjunction with one or more categories of said subset and automatically adding said proposed page to those indexed by said end user's index code wherein the end user can search said proposed page via said link information and wherein initially other users will not search said proposed page even if searching said proposed one or more categories; and wherein the index server updates web pages in the topic categories of the master index and the end user's index without any end user intervention and permits the end user to create and organize search indexes specific to the end user's needs. 8. The computer readable medium of claim 7 wherein said proposed addition link comprises code for invoking verification that a uniform resource locator address for said proposed page is valid and that said proposed page is not already indexed under said proposed one or more categories. | 0.5 |
5. A computer system for reducing diagnostic uncertainty using cross-referenced knowledge and image databases, comprising: a user-interface to solicit a plurality of characteristics of diagnoses from a user; a diagnostic engine operating under the programmatic control of the computer system and having access to the knowledge database, the knowledge database including a plurality of findings-diagnosis links representing relationships between findings and diagnoses, wherein said characteristics of diagnoses are employed to automatically identify, from the diagnoses for which data is stored in the knowledge database, a subset including a plurality of possible diagnoses from the knowledge database that are consistent with the characteristics; and using the subset of possible diagnoses identified from the findings-diagnosis links, automatically reorganizing an information space of the image database for presentation to the user, including concurrent presentation of a plurality of images on said user-interface for user review, the plurality of images being representative of at least two possible diagnoses. | 5. A computer system for reducing diagnostic uncertainty using cross-referenced knowledge and image databases, comprising: a user-interface to solicit a plurality of characteristics of diagnoses from a user; a diagnostic engine operating under the programmatic control of the computer system and having access to the knowledge database, the knowledge database including a plurality of findings-diagnosis links representing relationships between findings and diagnoses, wherein said characteristics of diagnoses are employed to automatically identify, from the diagnoses for which data is stored in the knowledge database, a subset including a plurality of possible diagnoses from the knowledge database that are consistent with the characteristics; and using the subset of possible diagnoses identified from the findings-diagnosis links, automatically reorganizing an information space of the image database for presentation to the user, including concurrent presentation of a plurality of images on said user-interface for user review, the plurality of images being representative of at least two possible diagnoses. 22. The system of claim 5 , wherein the system for reducing diagnostic uncertainty is applicable to and includes characteristics determined during an autopsy. | 0.605705 |
28. A non-transitory computer readable medium having instructions stored thereon, wherein the instructions are executable by at least one computer processor to perform a method, the method comprising: (A) applying automatic speech recognition to an audio signal to produce a structured document representing contents of the audio signal; (B) determining whether the structured document includes an indication of compliance for each of a plurality of best practices to produce a conclusion; (C) inserting content into the structured document, based on the conclusion, to produce a modified structured document; (D) generating a first indication that a user should provide additional input of a first type to conform the structured document to a first best practice in the plurality of best practices; and (E) generating a second indication that the user should provide additional input of a second type to conform the structured document to a second best practice in the plurality of best practices. | 28. A non-transitory computer readable medium having instructions stored thereon, wherein the instructions are executable by at least one computer processor to perform a method, the method comprising: (A) applying automatic speech recognition to an audio signal to produce a structured document representing contents of the audio signal; (B) determining whether the structured document includes an indication of compliance for each of a plurality of best practices to produce a conclusion; (C) inserting content into the structured document, based on the conclusion, to produce a modified structured document; (D) generating a first indication that a user should provide additional input of a first type to conform the structured document to a first best practice in the plurality of best practices; and (E) generating a second indication that the user should provide additional input of a second type to conform the structured document to a second best practice in the plurality of best practices. 33. The computer readable medium of claim 28 , wherein (B) further comprises: identifying a type of the structured document; identifying a best practice associated with the identified type; and determining whether the structured document includes an indication of compliance with the identified best practice to produce the conclusion. | 0.5 |
1. A method, comprising: accessing a voice mail record of a user within a voice mail system; accessing a recorded audio file of a name of the user in the voice mail record spoken by the user; providing the audio file to a speech recognition system that is operable with an automated attendant; processing the audio file in the speech recognition system and obtaining a text result; determining whether a confidence score of the text result is below a predetermined threshold; adding, at least, the name of the user to a list of low confidence names when the confidence score is below the predetermined threshold; when the name of the user is listed in the list of low confidence names, storing a plurality of actual alternate spellings for the name of the user, wherein the plurality of actual alternate spellings are accessible to the speech recognition system and are received via a user interface configured to be presented to an administrator of the automated attendant; receiving a voice call at the automated attendant including receiving a voice command comprising a spoken name of the user; and processing the spoken name of the user including comparing a spelled name result generated by the speech recognition system to the plurality of actual alternate spellings previously stored to identify the user. | 1. A method, comprising: accessing a voice mail record of a user within a voice mail system; accessing a recorded audio file of a name of the user in the voice mail record spoken by the user; providing the audio file to a speech recognition system that is operable with an automated attendant; processing the audio file in the speech recognition system and obtaining a text result; determining whether a confidence score of the text result is below a predetermined threshold; adding, at least, the name of the user to a list of low confidence names when the confidence score is below the predetermined threshold; when the name of the user is listed in the list of low confidence names, storing a plurality of actual alternate spellings for the name of the user, wherein the plurality of actual alternate spellings are accessible to the speech recognition system and are received via a user interface configured to be presented to an administrator of the automated attendant; receiving a voice call at the automated attendant including receiving a voice command comprising a spoken name of the user; and processing the spoken name of the user including comparing a spelled name result generated by the speech recognition system to the plurality of actual alternate spellings previously stored to identify the user. 4. The method of claim 1 , further comprising adding a link to the audio file in the list of low confidence names. | 0.527312 |
13. A program product stored on a recordable medium for exchanging automotive information between at least two automotive industry trading partners engaged in an automotive transaction, which when executed, comprises: a mapping system for mapping a transaction element, wherein the mapping system includes a system for determining: a source of the transaction element, an application to which the transaction element is regarding and a recipient to which the transaction element should be routed; a translation system for, after mapping the transaction element, translating a transaction element sent from a first trading partner intended for a second trading partner specified by the first trading partner, the transaction element being translated from a proprietary schema of the first trading partner into a universal schema and from the universal schema into a proprietary schema of the second trading partner, wherein translation of the transaction element comprises translating a data format and an application format of the transaction element; a routing system for, after translating a transaction element, routing the transaction element from the first trading partner in a first communication protocol to the second trading partner in a second different communication protocol of the second trading partner, wherein the first and second communication protocol comprise SOAP/XML, ODBC/JDBC, MQ, HTTP/XML, COM/COM+, RPC, CORBA/IIOP, OTMA, or WAP; a transaction management system for tracking a status of the transaction element, and providing the status of the transaction element to the first or second trading partner upon the first or second trading partner's inquiry; and a security system including a firewall for controlling access to the automotive information. | 13. A program product stored on a recordable medium for exchanging automotive information between at least two automotive industry trading partners engaged in an automotive transaction, which when executed, comprises: a mapping system for mapping a transaction element, wherein the mapping system includes a system for determining: a source of the transaction element, an application to which the transaction element is regarding and a recipient to which the transaction element should be routed; a translation system for, after mapping the transaction element, translating a transaction element sent from a first trading partner intended for a second trading partner specified by the first trading partner, the transaction element being translated from a proprietary schema of the first trading partner into a universal schema and from the universal schema into a proprietary schema of the second trading partner, wherein translation of the transaction element comprises translating a data format and an application format of the transaction element; a routing system for, after translating a transaction element, routing the transaction element from the first trading partner in a first communication protocol to the second trading partner in a second different communication protocol of the second trading partner, wherein the first and second communication protocol comprise SOAP/XML, ODBC/JDBC, MQ, HTTP/XML, COM/COM+, RPC, CORBA/IIOP, OTMA, or WAP; a transaction management system for tracking a status of the transaction element, and providing the status of the transaction element to the first or second trading partner upon the first or second trading partner's inquiry; and a security system including a firewall for controlling access to the automotive information. 15. The program product of claim 13 , wherein the first trading partner includes a mechanism for sending the transaction element to the automotive information exchange system. | 0.643967 |
4. The system of claim 2 , wherein the target image comprises a selection of text. | 4. The system of claim 2 , wherein the target image comprises a selection of text. 5. The system of claim 4 , wherein the selection of text comprises one or more of one or more randomly selected letters or meaningful words. | 0.958651 |
10. An apparatus comprising: a processor; and memory operatively coupled to the processor and storing computer readable instructions that, when executed, cause the apparatus to: receive text associated with a content item, the text including a plurality of term strings, each term string including one or more terms; determine a set of relevance intervals for a corresponding set of terms in the text, wherein each relevance interval of the set of relevance intervals identifies one or more sections of the content item that are relevant to a corresponding term; generate a first set of nodes for a first term string from the plurality of term strings, wherein the first set of nodes includes a node for each term in the first term string, and at least one node for a term different from the terms in the first term string but whose corresponding relevance interval includes the first term string; generate a second set of nodes for a second term string from the plurality of term strings, wherein the second set of nodes includes a node for each term in the second term string, and at least one node for a term different from the terms in the second term string but whose corresponding relevance interval includes the second term string; and determine a plurality of connections between nodes in the first set of nodes and the second set of nodes, wherein the plurality of connections includes a subset for a first node from the first set of nodes, wherein the subset for the first node includes a connection for each node from the second set of nodes; and use the first set of nodes, the second set of nodes or the plurality of connections to identify one or more segment boundaries within the content item. | 10. An apparatus comprising: a processor; and memory operatively coupled to the processor and storing computer readable instructions that, when executed, cause the apparatus to: receive text associated with a content item, the text including a plurality of term strings, each term string including one or more terms; determine a set of relevance intervals for a corresponding set of terms in the text, wherein each relevance interval of the set of relevance intervals identifies one or more sections of the content item that are relevant to a corresponding term; generate a first set of nodes for a first term string from the plurality of term strings, wherein the first set of nodes includes a node for each term in the first term string, and at least one node for a term different from the terms in the first term string but whose corresponding relevance interval includes the first term string; generate a second set of nodes for a second term string from the plurality of term strings, wherein the second set of nodes includes a node for each term in the second term string, and at least one node for a term different from the terms in the second term string but whose corresponding relevance interval includes the second term string; and determine a plurality of connections between nodes in the first set of nodes and the second set of nodes, wherein the plurality of connections includes a subset for a first node from the first set of nodes, wherein the subset for the first node includes a connection for each node from the second set of nodes; and use the first set of nodes, the second set of nodes or the plurality of connections to identify one or more segment boundaries within the content item. 12. The apparatus of claim 10 , wherein the memory further stores computer readable instructions that, when executed, cause the apparatus to: filter the plurality of connections based on at least one of a number of connections between the first set of nodes and the second set of nodes, or a cumulative value of connection strengths associated with the plurality of connections. | 0.5 |
4. The speech processing apparatus of claim 1 , further comprising a verification unit to compare a degree of relation of the mapped lower domain entities with a preset reference level and to output a verification signal as a result of the comparison, wherein the recognition unit recognizes the input speech in response to the verification signal. | 4. The speech processing apparatus of claim 1 , further comprising a verification unit to compare a degree of relation of the mapped lower domain entities with a preset reference level and to output a verification signal as a result of the comparison, wherein the recognition unit recognizes the input speech in response to the verification signal. 5. The speech processing apparatus of claim 4 , wherein the verification unit examines whether a combination of -selected plural lower domain entities, of the lower domain entities, are included in one of a preset plurality of combinations and outputs the verification signal as a result of the examination. | 0.900824 |
1. A machine learning based procurement system comprising: at least one machine learning classifier; at least one memory to store machine readable instructions; and at least one processor, connected to the memory, to execute the machine readable instructions to: generate a procurement request, the procurement request to solicit bids for providing at least one item; determine an item risk score for the procurement request based on a classification performed by the at least one machine learning classifier; display the item risk score in a graphical user interface; determine whether the at least one item is a high-risk item based on the item risk score; in response to determining the at least one item is high risk, generate a link in the graphical user interface, the link to provide access to at least one metric explaining the high-risk of the at least one item; generate a solicitation from the procurement request; receive bids to provide the at least one item in response to the solicitation; evaluate the bids based on classifications performed by the at least one machine learning classifier, where to evaluate the bids: the at least one machine learning classifier is to classify the bids as being associated with at least one of a high-risk supplier and a high-risk price; and the at least one processor is to: determine a price risk score and a supplier risk score for each of the bids based on the classifications; compare, for each bid, the price risk score and the supplier risk score to a respective threshold; determine if any of the received bids are associated with a high-risk procurement based on the comparing of the price risk score and the supplier risk score to the respective threshold; and in response to determining a bid is associated with a high-risk procurement, generate a bid evaluation link in the graphical user interface, the bid evaluation link providing access to information explaining the high-risk procurement. | 1. A machine learning based procurement system comprising: at least one machine learning classifier; at least one memory to store machine readable instructions; and at least one processor, connected to the memory, to execute the machine readable instructions to: generate a procurement request, the procurement request to solicit bids for providing at least one item; determine an item risk score for the procurement request based on a classification performed by the at least one machine learning classifier; display the item risk score in a graphical user interface; determine whether the at least one item is a high-risk item based on the item risk score; in response to determining the at least one item is high risk, generate a link in the graphical user interface, the link to provide access to at least one metric explaining the high-risk of the at least one item; generate a solicitation from the procurement request; receive bids to provide the at least one item in response to the solicitation; evaluate the bids based on classifications performed by the at least one machine learning classifier, where to evaluate the bids: the at least one machine learning classifier is to classify the bids as being associated with at least one of a high-risk supplier and a high-risk price; and the at least one processor is to: determine a price risk score and a supplier risk score for each of the bids based on the classifications; compare, for each bid, the price risk score and the supplier risk score to a respective threshold; determine if any of the received bids are associated with a high-risk procurement based on the comparing of the price risk score and the supplier risk score to the respective threshold; and in response to determining a bid is associated with a high-risk procurement, generate a bid evaluation link in the graphical user interface, the bid evaluation link providing access to information explaining the high-risk procurement. 6. The machine learning based procurement system of claim 1 , wherein the at least one machine learning classifier comprises: an ensemble classifier comprising a combination, the combination comprising: a machine learning logistic regression function, and at least one of: a decision tree function, a multicollinearity function, and a predictive strength analysis function, where: at least one of the decision tree function, the multicollinearity function, and the predictive strength analysis function are used to determine predictive variables, and the predictive variables are used in a training set and a validation set to generate the ensemble classifier according to the machine learning logistic regression function. | 0.5 |
7. A data collection system comprising: a data collection terminal having an encoded information reader device, the data collection terminal responsive to configuration data expressed in an extensible markup language for configuring operation of the data collection terminal; and a computer spaced apart from the data collection terminal that uses an existing extensible markup language document to create a data entry screen to receive desired parameter settings for the data collection terminal within data entry fields, combines the extensible markup language document with the desired parameter settings to create configuration data expressed in an extensible markup language, and initiates a transfer of the configuration data to said data collection terminal. | 7. A data collection system comprising: a data collection terminal having an encoded information reader device, the data collection terminal responsive to configuration data expressed in an extensible markup language for configuring operation of the data collection terminal; and a computer spaced apart from the data collection terminal that uses an existing extensible markup language document to create a data entry screen to receive desired parameter settings for the data collection terminal within data entry fields, combines the extensible markup language document with the desired parameter settings to create configuration data expressed in an extensible markup language, and initiates a transfer of the configuration data to said data collection terminal. 16. The data collection system of claim 7 , wherein the extensible markup language document comprises parameter settings and attributes of the parameter settings, wherein the attributes indicate an ability of a user to modify a parameter setting. | 0.749112 |
2. The method of claim 1 , wherein generating the graphical flowchart step includes generating a graphical flowchart step including an input, a fail output, and a pass output. | 2. The method of claim 1 , wherein generating the graphical flowchart step includes generating a graphical flowchart step including an input, a fail output, and a pass output. 3. The method of claim 2 , wherein receiving the plurality of input connections from the user includes receiving a plurality of input connections from the user, wherein each of the plurality of input connections connects the input of the displayed graphical flowchart step to at least one of a fail output and a pass output of an additional graphical flowchart step. | 0.880793 |
5. A translator as claimed in claim 4 wherein each address in said memory means that is addressable by an input data character in said first code has stored therein two identification bits, said identification bits having a special configuration if there is no character in said second code corresponding to the addressing character, said identification bits being applied to said identifying means when said memory is addressed. | 5. A translator as claimed in claim 4 wherein each address in said memory means that is addressable by an input data character in said first code has stored therein two identification bits, said identification bits having a special configuration if there is no character in said second code corresponding to the addressing character, said identification bits being applied to said identifying means when said memory is addressed. 6. A translator as claimed in claim 5 wherein said identification bits are coded according to whether or not they are accessed by input data characters representing function codes or non-function codes, said translator including means for applying said identification bits to said comparison means to inhibit operation thereof when said identification bits identify a non-function input data character; and, a further comparison means for comparing said identification bits with the output of said case indicating means to produce either said comparison or said non-comparison signal. | 0.90372 |
8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. 12. The method of claim 8, wherein the data block includes: (a) a byte indicating the default code page used for text in the file does not apply to a specific run of text; and (b) a plurality of bytes indicating the exception code page used for said specific run of text. | 0.652922 |
1. A computer implemented method of interrogating a database comprising a plurality of tables, said method comprising the steps of: defining a set of anticipated database queries directed to one or more of said tables in the database, the database executing in the data processing system; generating a base query directed only to tables common to all of said anticipated database queries; for each anticipated database query, generating a subquery module directed to tables not covered by said base query and required by a respective anticipated database query, wherein the subquery module includes logic to create a subquery and logic to create a filter; receiving a request for information from said database; selecting a subquery module directed to tables not covered by said base query and required by a respective anticipated database query; adding an output of said selected subquery module to said base query to form a refined query, wherein the logic included in the subquery module further includes logic for not creating the subquery when a table used in the filter already exists in the refined query; submitting said refined query to said database; and responsive to submitting said refined query, receiving data from said database. | 1. A computer implemented method of interrogating a database comprising a plurality of tables, said method comprising the steps of: defining a set of anticipated database queries directed to one or more of said tables in the database, the database executing in the data processing system; generating a base query directed only to tables common to all of said anticipated database queries; for each anticipated database query, generating a subquery module directed to tables not covered by said base query and required by a respective anticipated database query, wherein the subquery module includes logic to create a subquery and logic to create a filter; receiving a request for information from said database; selecting a subquery module directed to tables not covered by said base query and required by a respective anticipated database query; adding an output of said selected subquery module to said base query to form a refined query, wherein the logic included in the subquery module further includes logic for not creating the subquery when a table used in the filter already exists in the refined query; submitting said refined query to said database; and responsive to submitting said refined query, receiving data from said database. 2. The method of claim 1 wherein said step of selecting comprises selecting a plurality of subquery modules corresponding in aggregate all tables not covered by said base query and required by a respective anticipated database query, and wherein said refined query comprises said base query and outputs of said plurality of subquery modules. | 0.600669 |
1. A computer-implemented system comprising: a memory; and at least one processor coupled to the memory, the at least one processor to implement: a viewer to open a master copy of an electronic document in a local editor for display at a display device; a first queue associated with the local editor, the first queue being to store edit operations requested by the local editor, the first queue maintained by the local editor; a second queue associated with a remote editor, the remote editor residing at a remote client computer, the second queue being to store edit operations requested by the remote editor, the second queue maintained by the local editor; an update detector to detect a network request from the remote editor to perform an edit operation on a remote copy of the electronic document, the remote copy of the electronic document being opened by the remote editor; an update module to: in response to the network request from the remote editor to perform the edit operation on the remote copy of the electronic document, perform the edit operation on the master copy of the electronic document; and update the second queue with the edit operation in response to the performing of the edit operation on the master copy of the electronic document; and a distributor to propagate, via a network communication, the edit operation to the remote copy of the electronic document, the edit operation requested to be performed on the remote copy of the electronic document and performed on the master copy of the electronic document; wherein the viewer, the first queue, the second queue, the update detector, the update module, the local editor and the distributor are provided at a local client computer. | 1. A computer-implemented system comprising: a memory; and at least one processor coupled to the memory, the at least one processor to implement: a viewer to open a master copy of an electronic document in a local editor for display at a display device; a first queue associated with the local editor, the first queue being to store edit operations requested by the local editor, the first queue maintained by the local editor; a second queue associated with a remote editor, the remote editor residing at a remote client computer, the second queue being to store edit operations requested by the remote editor, the second queue maintained by the local editor; an update detector to detect a network request from the remote editor to perform an edit operation on a remote copy of the electronic document, the remote copy of the electronic document being opened by the remote editor; an update module to: in response to the network request from the remote editor to perform the edit operation on the remote copy of the electronic document, perform the edit operation on the master copy of the electronic document; and update the second queue with the edit operation in response to the performing of the edit operation on the master copy of the electronic document; and a distributor to propagate, via a network communication, the edit operation to the remote copy of the electronic document, the edit operation requested to be performed on the remote copy of the electronic document and performed on the master copy of the electronic document; wherein the viewer, the first queue, the second queue, the update detector, the update module, the local editor and the distributor are provided at a local client computer. 9. The system of claim 1 comprising a storing module to: detect, at the local editor, that the master copy of the electronic document is the only copy of the electronic document being opened; detect a request to close the master copy of the electronic document; and store the latest version of the electronic document, the latest version of the electronic document including results of operations stored in the local queue and the remote queue. | 0.525502 |
1. A computer-implemented method performed by a data processing apparatus, the method comprising: accessing command input logs storing data defining user device sessions; identifying, from the command input logs, user device sessions that each respectively store: a sequence of two or more command inputs, each command input specifying one or more parameter values, and each command input having a respective ordinal position in the sequence, and wherein the sequence includes at least one pair of a first command input that precedes a second command input in ordinal position in the sequence; first operation data indicating a first operation performed on data from a first resource property in response to the first command input; second operation data indicating a second operation performed on data from a second resource property in response to the second command input; identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of a first operation failure and a second operation success; and determining, from the identified pairs of first and second command inputs, command inputs for which a parsing rule that is associated with the second operation is to be generated. | 1. A computer-implemented method performed by a data processing apparatus, the method comprising: accessing command input logs storing data defining user device sessions; identifying, from the command input logs, user device sessions that each respectively store: a sequence of two or more command inputs, each command input specifying one or more parameter values, and each command input having a respective ordinal position in the sequence, and wherein the sequence includes at least one pair of a first command input that precedes a second command input in ordinal position in the sequence; first operation data indicating a first operation performed on data from a first resource property in response to the first command input; second operation data indicating a second operation performed on data from a second resource property in response to the second command input; identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of a first operation failure and a second operation success; and determining, from the identified pairs of first and second command inputs, command inputs for which a parsing rule that is associated with the second operation is to be generated. 2. The computer-implemented method of claim 1 , wherein identifying pairs of first and second command inputs from respective user device sessions for which the first and second operation data are indicative of and first operation failure and a second operation success comprises, for each pair of first and second command inputs: determining that the first command input included a parameter value specified by a user; and determining that the second command input included the same parameter value specified by the user. | 0.628005 |
8. The computer system of claim 7 , wherein the ontology includes an ontological description of the domain model based on entities, classes, and attributes. | 8. The computer system of claim 7 , wherein the ontology includes an ontological description of the domain model based on entities, classes, and attributes. 9. The computer system of claim 8 , wherein the syntax template specifies legal word sequences based on the ontological description. | 0.972452 |
1. A method to model and transfer the prosody of tag questions across languages, the method comprising: receiving speech of a first person speaking in a first language; analyzing the speech in the first language using automatic speech recognition; extracting prosodic parameters of the speech in the first language and outputting text in the first language corresponding to the speech in the first language based on the analyzing; searching the speech in the first language for a tag question in the first language; translating the text in the first language to text in a second language; outputting translated speech in the second language that is translated from the speech in the first language based on the translated text in the second language; analyzing the speech in the first language to find speech segments that correspond to the tag question in the first language; extracting a fundamental frequency from the speech segments that correspond to the tag question in the first language based on the extracted prosodic parameters of the speech in the first language; fitting a stylized smooth contour to the fundamental frequency; mapping the stylized smooth contour into a corresponding part of pitch range of the speech in the second language; stretching or contracting the stylized smooth contour over time; aligning the stylized smooth contour with corresponding speech segments in the second language that correspond to the tag question; and applying the smooth contour to the speech in the second language. | 1. A method to model and transfer the prosody of tag questions across languages, the method comprising: receiving speech of a first person speaking in a first language; analyzing the speech in the first language using automatic speech recognition; extracting prosodic parameters of the speech in the first language and outputting text in the first language corresponding to the speech in the first language based on the analyzing; searching the speech in the first language for a tag question in the first language; translating the text in the first language to text in a second language; outputting translated speech in the second language that is translated from the speech in the first language based on the translated text in the second language; analyzing the speech in the first language to find speech segments that correspond to the tag question in the first language; extracting a fundamental frequency from the speech segments that correspond to the tag question in the first language based on the extracted prosodic parameters of the speech in the first language; fitting a stylized smooth contour to the fundamental frequency; mapping the stylized smooth contour into a corresponding part of pitch range of the speech in the second language; stretching or contracting the stylized smooth contour over time; aligning the stylized smooth contour with corresponding speech segments in the second language that correspond to the tag question; and applying the smooth contour to the speech in the second language. 5. The method of claim 1 , wherein the tag question is a grammatical structure in which a declarative statement or an imperative is turned into a question by adding an interrogative fragment. | 0.5 |
12. An article of manufacture including a non-transitory computer readable storage medium to tangibly store instructions, which when executed by a computer, cause the computer to: receive a user interaction for modification of at least one report element in a report document, the report document presented in a user interface; classify the modification of the at least one report element, wherein the instructions to classify the modification of the at least one report elements further comprise instructions, which when executed by a computer, cause the computer to: receive a unique identifier of the at least one report element; match the unique identifier with the user interaction for modification of the at least one report element; and identify a class based on the unique identifier and the user interaction for modification; identify a visual effect based on the classified modification of the at least one report element; and update the report document by applying the identified visual effect together with the modification of the at least one report element. | 12. An article of manufacture including a non-transitory computer readable storage medium to tangibly store instructions, which when executed by a computer, cause the computer to: receive a user interaction for modification of at least one report element in a report document, the report document presented in a user interface; classify the modification of the at least one report element, wherein the instructions to classify the modification of the at least one report elements further comprise instructions, which when executed by a computer, cause the computer to: receive a unique identifier of the at least one report element; match the unique identifier with the user interaction for modification of the at least one report element; and identify a class based on the unique identifier and the user interaction for modification; identify a visual effect based on the classified modification of the at least one report element; and update the report document by applying the identified visual effect together with the modification of the at least one report element. 14. The article of manufacture of claim 12 , wherein the instructions to identify the visual effect based on the classified modification of the at least one report element further comprise instructions, which when executed by a computer, cause the computer to automatically select the visual effect from a set of predefined visual effects. | 0.5 |
5. An information processing apparatus comprising: a setting unit configured to accept, as a print setting, a setting for arranging a plurality of pages on one sheet of paper; a selection unit configured to receive a selection of either an original-view mode for displaying a preview in which the accepted print setting is not reflected or a print-view mode for displaying a preview in a form to be printed according to the accepted print setting, as a preview mode; and a display unit configured to display a preview in which one page is arranged on one sheet of paper in a state in which the accepted print setting, which is the setting for arranging the plurality of pages on one sheet of paper, is maintained, in a case where the selection of the original-view mode is received, and to display a preview in which the plurality of pages are arranged on one sheet of paper in a case where the selection of the print-view mode is received. | 5. An information processing apparatus comprising: a setting unit configured to accept, as a print setting, a setting for arranging a plurality of pages on one sheet of paper; a selection unit configured to receive a selection of either an original-view mode for displaying a preview in which the accepted print setting is not reflected or a print-view mode for displaying a preview in a form to be printed according to the accepted print setting, as a preview mode; and a display unit configured to display a preview in which one page is arranged on one sheet of paper in a state in which the accepted print setting, which is the setting for arranging the plurality of pages on one sheet of paper, is maintained, in a case where the selection of the original-view mode is received, and to display a preview in which the plurality of pages are arranged on one sheet of paper in a case where the selection of the print-view mode is received. 6. The information processing apparatus according to claim 5 , wherein the plurality of pages are included in document data, which is generated by an application. | 0.668539 |
1. A computer-implemented method comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning, by a computer, each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, by a computer and for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, by a computer and as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating, by a computer, a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. | 1. A computer-implemented method comprising: receiving selection criteria for a campaign, the selection criteria including a plurality of keywords that control distribution of content items associated with the campaign; assigning, by a computer, each of the selection criteria to one or more sets of topic clusters, wherein at least some of the selection criteria are assigned to multiple topic clusters; determining, by a computer and for pairs of selection criteria in one of the topic clusters, a measure of similarity between the topic clusters to which each selection criteria in the pair was assigned; identifying, by a computer and as related pairs of selection criteria, the pairs of selection criteria for which the measure of similarity meets a threshold; creating a new keyword cluster based on the related pairs, the new keyword cluster including fewer than all of the keywords in the received selection criteria, the creating comprising: identifying a first selection keyword and a second selection keyword that are included in one of the related pairs; and including each of the first selection keyword and the second selection keyword in the new keyword cluster; and creating, by a computer, a new group for the campaign, the new group specifying at least one content item that is selected for distribution using keywords in the new keyword cluster. 4. The method of claim 1 , further comprising selecting a name for the group based on one or more topic clusters to which the related pairs in the new keyword cluster were assigned. | 0.891795 |
1. A method of communication, messaging and searching in a network comprising the steps of: storing one or more user profiles, preferences, subscribers and subscriptions, dynamic relationships or connections among said users and privacy settings at a central unit; determining one or more target recipients by a sender; allowing the sender to perform one or more activities in one or more networks based on one or more applications, services, multimedia contents, user connections, communication, interactions, sharing and collaboration among users and/or to send one or more messages to the one or more target recipients via the central unit; receiving one or more messages from the sender at the central unit or auto-generating one or more messages and dynamically associating accessible metadata, fields, parameters and links with said auto generated messages based on monitoring, storing and managing of said one or more related activities, actions, events and transactions by the central unit; storing and processing said messages at the central unit; determining one or more target recipients by the central unit based on one or more preferences; sending to the one or more target recipients a representation of the one or more messages by the central unit; presenting one or more messages in chronological order and as per the target recipients' preferences and privacy settings by the central unit; and allowing the user to access one or more accessible metadata, fields, parameters and links associated with a message to view links and profile, communicate, collaborate, share and participate in the same activity as the sender, to subscribe to source of the message by searching or selecting said message(s) or message(s) associated one or more accessible metadata and links. | 1. A method of communication, messaging and searching in a network comprising the steps of: storing one or more user profiles, preferences, subscribers and subscriptions, dynamic relationships or connections among said users and privacy settings at a central unit; determining one or more target recipients by a sender; allowing the sender to perform one or more activities in one or more networks based on one or more applications, services, multimedia contents, user connections, communication, interactions, sharing and collaboration among users and/or to send one or more messages to the one or more target recipients via the central unit; receiving one or more messages from the sender at the central unit or auto-generating one or more messages and dynamically associating accessible metadata, fields, parameters and links with said auto generated messages based on monitoring, storing and managing of said one or more related activities, actions, events and transactions by the central unit; storing and processing said messages at the central unit; determining one or more target recipients by the central unit based on one or more preferences; sending to the one or more target recipients a representation of the one or more messages by the central unit; presenting one or more messages in chronological order and as per the target recipients' preferences and privacy settings by the central unit; and allowing the user to access one or more accessible metadata, fields, parameters and links associated with a message to view links and profile, communicate, collaborate, share and participate in the same activity as the sender, to subscribe to source of the message by searching or selecting said message(s) or message(s) associated one or more accessible metadata and links. 8. The method according to claim 1 , wherein the step of processing the one or more messages by the central unit comprises storing, formatting, indexing, and/or associating one or more metadata, fields, parameters and links. | 0.706223 |
3. The system of claim 1 , wherein the given rule represents a particular relationship between a first segment identifier and a second segment identifier. | 3. The system of claim 1 , wherein the given rule represents a particular relationship between a first segment identifier and a second segment identifier. 5. The system of claim 3 , wherein at least one of the lexical entries maps a plurality of different segment identifiers to a same textual string. | 0.947079 |
19. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the display represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective sub set; the user interface includes a user-selectable input by which the first Boolean query is changed without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. | 19. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising: causing, with one or more processors, a computing device to display a user interface with a result of a first Boolean query applied to a data set, wherein: the display represents subsets of the result as concurrently displayed graphical regions; each of the graphical regions representing a respective subset of query results has a visual attribute determined based on a respective statistic of the respective sub set; the user interface includes a user-selectable input by which the first Boolean query is changed without the user typing additional query terms; the user interface provides a plurality of candidate query terms that are user selectable without typing the candidate query terms; and the user interface graphically distinguishes between presented candidate query terms that are broadening terms and candidate query terms that are narrowing terms; receiving, with one or more processors, a user selection entered via the user-selectable input, the user selection indicating a term to be added to the first Boolean query; based on the user selection, with one or more processors, forming a second Boolean query; applying, with one or more processors, the second Boolean query to the data set to produce a result of the second Boolean query; and causing, with one or more processors, the computing device to display the result of the second Boolean query. 27. The medium of claim 19 , wherein causing a computing device to display a user interface with a result of a first Boolean query comprises: causing the computing device to display a proportional shape graph. | 0.905502 |
1. A computer-implemented method of searching speech data comprising in-vocabulary and out-of-vocabulary words, the method comprising, via a computer processor executing stored program instructions: Receiving, by the computer processor, a search query comprising a phrase comprising at least one in-vocabulary word and at least one out-of-vocabulary word; extracting, by the computer processor, search terms from the phrase, the search terms comprising at least one in-vocabulary search term and at least one out-of-vocabulary search term; retrieving, by the computer processor, a first list of occurrences of words for the at least one in-vocabulary search term, the first list retrieved from a first index of words having first timestamps; retrieving, by the computer processor, a second list of occurrences of sub-words for the at least one out-of-vocabulary search term, the second list retrieved from a second index of sub-words having second timestamps; and merging, by the computer processor, the first list of occurrences of words and the second list of occurrences of sub-words to create a merged list, wherein merging the first list and the second list comprises evaluating the first timestamps and the second timestamps and adding to the merged list occurrences of combinations of words from the first list and sub-words from the second list that satisfy at least one evaluation criterion, wherein the at least one evaluation criterion comprises a threshold for a difference between first and second timestamps. | 1. A computer-implemented method of searching speech data comprising in-vocabulary and out-of-vocabulary words, the method comprising, via a computer processor executing stored program instructions: Receiving, by the computer processor, a search query comprising a phrase comprising at least one in-vocabulary word and at least one out-of-vocabulary word; extracting, by the computer processor, search terms from the phrase, the search terms comprising at least one in-vocabulary search term and at least one out-of-vocabulary search term; retrieving, by the computer processor, a first list of occurrences of words for the at least one in-vocabulary search term, the first list retrieved from a first index of words having first timestamps; retrieving, by the computer processor, a second list of occurrences of sub-words for the at least one out-of-vocabulary search term, the second list retrieved from a second index of sub-words having second timestamps; and merging, by the computer processor, the first list of occurrences of words and the second list of occurrences of sub-words to create a merged list, wherein merging the first list and the second list comprises evaluating the first timestamps and the second timestamps and adding to the merged list occurrences of combinations of words from the first list and sub-words from the second list that satisfy at least one evaluation criterion, wherein the at least one evaluation criterion comprises a threshold for a difference between first and second timestamps. 5. The method of searching of claim 1 , wherein: a first timestamp comprises a start time for a word and a duration of the word; a second timestamp comprises a start time for a sub-word and a duration of the sub-word; and the method of searching further comprises checking that a word and a sub-word are adjacent by checking that either a difference between an end time of the word and a start time of the sub-word or a difference between an end time of the sub-word and a start time of the word is below a given threshold, wherein an end time comprises a start time plus a duration. | 0.5 |
33. A method of enabling a client application executing on a computer to perform operations on data objects defined by a model description stored in a machine-readable medium along with a database schema including one or more database tables configured to store a set of data object instances in a database created from the model description and a model application programming interface from the model description that enables the client application to access data objects in the set of data object instances in the same manner as other data objects, the method comprising: using the model application programming interface to create instance of data objects in the database schema including an instance of an object structure having one-to-one and one-to-many mappings; storing the created data object instances in a machine-readable medium; accessing the created data object instances as a separate data objects with the client application; and performing operations on the accessed data object instances including storing, reading and modifying attributes of the data objects. | 33. A method of enabling a client application executing on a computer to perform operations on data objects defined by a model description stored in a machine-readable medium along with a database schema including one or more database tables configured to store a set of data object instances in a database created from the model description and a model application programming interface from the model description that enables the client application to access data objects in the set of data object instances in the same manner as other data objects, the method comprising: using the model application programming interface to create instance of data objects in the database schema including an instance of an object structure having one-to-one and one-to-many mappings; storing the created data object instances in a machine-readable medium; accessing the created data object instances as a separate data objects with the client application; and performing operations on the accessed data object instances including storing, reading and modifying attributes of the data objects. 38. The method of claim 33 further comprising creating a set of functions corresponding to attributes of data objects defined by the model description including accessor functions that enable client applications to read or set attributes of instances of the data objects. | 0.812879 |
1. A system for processing an interaction with a person, comprising: a routing processor configured to receive data representing an utterance from the person; an automated recognition processor in communication with the routing processor and configured to receive therefrom the data, the automated recognition processor producing responsive to the data an output substantially in real time corresponding to a determination of an intent of the person; an analyst user interface device in communication with the routing processor, configured to present to a human analyst the utterance in perceptible form and to accept intent input from the human analyst; and a training subsystem in communication with the routing processor, the automated recognition processor, and the intent input and producing in response training information for the automated recognition processor. | 1. A system for processing an interaction with a person, comprising: a routing processor configured to receive data representing an utterance from the person; an automated recognition processor in communication with the routing processor and configured to receive therefrom the data, the automated recognition processor producing responsive to the data an output substantially in real time corresponding to a determination of an intent of the person; an analyst user interface device in communication with the routing processor, configured to present to a human analyst the utterance in perceptible form and to accept intent input from the human analyst; and a training subsystem in communication with the routing processor, the automated recognition processor, and the intent input and producing in response training information for the automated recognition processor. 4. The system of claim 1 , further comprising a second analyst user interface device in communication with the routing processor, configured to present to a second human analyst the utterance in perceptible form and to accept second intent input from the second human analyst, wherein the intent input is selectively processed by the training subsystem responsive to the intent input matching the second intent input. | 0.5 |
1. A machine-readable non-transitory medium having instructions stored thereon, where the instructions, when read by the machine, cause the machine to perform the steps of: accessing a semantic representation associated with a first dataset and a semantic representation associated with a second dataset, wherein at least one of the semantic representation associated with the first dataset and the semantic representation associated with the second dataset is a trainable semantic vector generated based on at least one data point included in a respective dataset and known relationships between predetermined data points and predetermined categories to which the predetermined data points may relate; determining a similarity between the semantic representation associated with the first dataset and the semantic representation associated with the second dataset; and selectively relating the first dataset to the second dataset based on a result of the determining step; wherein each attribute in a trainable semantic vector indicates how likely a dataset represented by the trainable semantic vector belongs to one of the predetermined categories, and the trainable semantic vector has a dimension equal to the number of the predetermined categories. | 1. A machine-readable non-transitory medium having instructions stored thereon, where the instructions, when read by the machine, cause the machine to perform the steps of: accessing a semantic representation associated with a first dataset and a semantic representation associated with a second dataset, wherein at least one of the semantic representation associated with the first dataset and the semantic representation associated with the second dataset is a trainable semantic vector generated based on at least one data point included in a respective dataset and known relationships between predetermined data points and predetermined categories to which the predetermined data points may relate; determining a similarity between the semantic representation associated with the first dataset and the semantic representation associated with the second dataset; and selectively relating the first dataset to the second dataset based on a result of the determining step; wherein each attribute in a trainable semantic vector indicates how likely a dataset represented by the trainable semantic vector belongs to one of the predetermined categories, and the trainable semantic vector has a dimension equal to the number of the predetermined categories. 4. The machine-readable medium of claim 1 further comprising the step of selectively conveying the first dataset along with the second dataset based on a result of the selectively relating step. | 0.691453 |
1. A method of modifying a classification scheme stored by a processing system for classifying hand-written characters to thereby make the classification scheme user dependent, the processing system storing the classification scheme to include a plurality of classes and user dependent weighted allographs, each class representing a respective letter and containing one or more of the allographs, each allograph including an associated weighting and representing a respective style of a respective letter and containing one or more prototypes, each prototype representing a variation in the respective allograph and being represented as a prototype vector, each prototype vector being formed from a number of values, each value quantifying a respective feature of the respective prototype vector, the method including the steps of: obtaining at least one hand-written character at an input of the processing system; determining, in the processing system, a selection value based on the similarity of the obtained character and a respective prototype vector of the stored classification scheme by: determining a feature vector representing the character, the feature vector being formed from a number of values, each value quantifying a respective feature of the character; and determining a distance value representing the distance between the determined feature vector and said respective prototype vector; selecting, in the processing system, a respective one of the prototype vectors of the stored classification scheme in accordance with the determined selection values; selecting, in the processing system, a class of the stored classification scheme in accordance with the selected prototype representing the character to thereby determine the letter represented by the character; selecting, in the processing system, one of the stored user dependent weighted allographs in accordance with the weightings and in accordance with said selected prototype vector representing the character; and modifying, in the processing system, one or more of the allographs in the respective class in accordance with the selection by modifying the weighting of one or more of the allographs; storing a modified classification scheme in the processing system which includes said modified allographs. | 1. A method of modifying a classification scheme stored by a processing system for classifying hand-written characters to thereby make the classification scheme user dependent, the processing system storing the classification scheme to include a plurality of classes and user dependent weighted allographs, each class representing a respective letter and containing one or more of the allographs, each allograph including an associated weighting and representing a respective style of a respective letter and containing one or more prototypes, each prototype representing a variation in the respective allograph and being represented as a prototype vector, each prototype vector being formed from a number of values, each value quantifying a respective feature of the respective prototype vector, the method including the steps of: obtaining at least one hand-written character at an input of the processing system; determining, in the processing system, a selection value based on the similarity of the obtained character and a respective prototype vector of the stored classification scheme by: determining a feature vector representing the character, the feature vector being formed from a number of values, each value quantifying a respective feature of the character; and determining a distance value representing the distance between the determined feature vector and said respective prototype vector; selecting, in the processing system, a respective one of the prototype vectors of the stored classification scheme in accordance with the determined selection values; selecting, in the processing system, a class of the stored classification scheme in accordance with the selected prototype representing the character to thereby determine the letter represented by the character; selecting, in the processing system, one of the stored user dependent weighted allographs in accordance with the weightings and in accordance with said selected prototype vector representing the character; and modifying, in the processing system, one or more of the allographs in the respective class in accordance with the selection by modifying the weighting of one or more of the allographs; storing a modified classification scheme in the processing system which includes said modified allographs. 3. The method according to claim 1 , the selection value being determined in accordance with the determined distance value and the weighting associated with the respective allograph. | 0.541283 |
17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. | 17. A non-transitory computer-readable medium having program code recorded thereon for analyzing data, the program code being executed by a processor and comprising: program code to generate, by an entity, a query based at least in part on a topic of interest; program code to execute the query on a plurality of data sources, at least one of the plurality of data sources comprising at least one of knowledge center information, frequently asked questions (FAQs), user comments, customer service data, or a combination thereof; program code to select, by the entity, a data source from the plurality of data sources for monitoring based on a correlation between the data source and the topic of interest, the correlation determined based on results of the executed query; program code to monitor, based on a set schedule, the data source for matches to the query to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to extract data from the data source when at least an update to stored data matches the query, newly added data matches the query, or a combination thereof; program code to determine an extraction rate for extracting the data, the extraction rate indicating an amount of the data that is extracted over a first time period; program code to determine a first processing rate for processing the extracted data with a number of parallel processors, the first processing rate indicating an amount of extracted data that is processed over a second time period; program code to dynamically adjust the number of parallel processors for analyzing the extracted data based on the extraction rate to obtain a second processing rate that is greater than the first processing rate; program code to analyze, with the parallel processors, the extracted data to determine at least one of a sentiment, an index, a pattern, or a combination thereof; program code to establish a two-way communication channel, between at least the entity that selected the data source for monitoring and a user device of a user that provided data to the data source, based on the analysis of the extracted data; program code to transmit, from the entity via the two-way communication channel, a first message directed to the user device based on the analysis of the extracted data; and program code to receive, from the user device via the two-way communication channel, a second message in response to the first message directed to the user device. 19. The non-transitory computer-readable medium of claim 17 , in which the two-way communication channel notifies the user device of at least one of a sentiment, a trend, or a combination thereof. | 0.524103 |
17. The computer system of claim 15 , wherein the recognition managing module is further programmed to: weight the combination of the two or more of the confidence values based on a frequency with which the particular recognition result occurs in the recognition results for the completed portion of the plurality of speech recognition tasks. | 17. The computer system of claim 15 , wherein the recognition managing module is further programmed to: weight the combination of the two or more of the confidence values based on a frequency with which the particular recognition result occurs in the recognition results for the completed portion of the plurality of speech recognition tasks. 19. The computer system of claim 17 , wherein the combination of the two or more of the confidence values are weighted further based on a distribution of the confidence values for one or more of the plurality of speech recognition tasks in the completed portion of the plurality of speech recognition tasks. | 0.899743 |
1. A system for analyzing voice-based communication sessions, comprising: a player configured to replay a recording of a communication session; an analysis engine coupled to the player, the analysis engine configured to process a stored communication session to generate a result responsive to an utterance-of-interest in the stored communication session, wherein the analysis engine uses a language model specific to a speaker when an identity of the speaker is known; a presentor coupled to the analysis engine and configured to present a representation of the result; and a storage device coupled to the analysis engine, the storage device configured to cache a representation of the result, wherein the representation of the result comprises an indication of a match of the utterance-of-interest in the stored communication session and an indication of a certainty that the match is an actual match of the utterance-of-interest. | 1. A system for analyzing voice-based communication sessions, comprising: a player configured to replay a recording of a communication session; an analysis engine coupled to the player, the analysis engine configured to process a stored communication session to generate a result responsive to an utterance-of-interest in the stored communication session, wherein the analysis engine uses a language model specific to a speaker when an identity of the speaker is known; a presentor coupled to the analysis engine and configured to present a representation of the result; and a storage device coupled to the analysis engine, the storage device configured to cache a representation of the result, wherein the representation of the result comprises an indication of a match of the utterance-of-interest in the stored communication session and an indication of a certainty that the match is an actual match of the utterance-of-interest. 8. The system of claim 1 , wherein the analysis engine comprises one of a phonetic analyzer and a large vocabulary speech recognition analyzer. | 0.554645 |
8. A non-transitory computer readable memory medium, including computer executable instructions for adjusting a call center application operable to associate a user utterance with an action-object based on a salient term in the user utterance, the instructions including instructions executable to: determine that at least one of a match rate for associating user utterances with the action-object and a performance rate for the associating user utterances with the action-object is below a corresponding threshold; and responsive to executing the instructions to determine, modify salient terms associated with the action-object; wherein the instructions executable to modify comprise instructions executable to remove an association of the salient term with the action-object based on a frequency with which the salient term occurs in a selected set of user utterances, and wherein a size of a set of salient terms matching the action-object is maintained near an optimum value with regard to the match rate and the performance rate. | 8. A non-transitory computer readable memory medium, including computer executable instructions for adjusting a call center application operable to associate a user utterance with an action-object based on a salient term in the user utterance, the instructions including instructions executable to: determine that at least one of a match rate for associating user utterances with the action-object and a performance rate for the associating user utterances with the action-object is below a corresponding threshold; and responsive to executing the instructions to determine, modify salient terms associated with the action-object; wherein the instructions executable to modify comprise instructions executable to remove an association of the salient term with the action-object based on a frequency with which the salient term occurs in a selected set of user utterances, and wherein a size of a set of salient terms matching the action-object is maintained near an optimum value with regard to the match rate and the performance rate. 11. The memory medium of claim 8 , wherein the instructions executable to remove comprise instructions executable to remove the association of the salient term based on a word count indicative of the frequency. | 0.5 |
1. A method comprising: receiving a respective tweet from each of a plurality of devices; analyzing the respective tweet based on a location of a respective device of the plurality of devices to yield a plurality of analyzed tweets; and transmitting, for display, at least a portion of a plurality of analyzed tweets to a host device viewed by a host of a broadcast to yield displayed tweets, wherein the displayed tweets are selectable by the host, and wherein icons associated with each of the display tweets comprises a first selectable portion, which, when selected causes a processor to display a text associated with the respective tweet and a second selectable portion which causes the processor to insert audio associated with the respective tweet into the broadcast transmitted to the plurality of devices. | 1. A method comprising: receiving a respective tweet from each of a plurality of devices; analyzing the respective tweet based on a location of a respective device of the plurality of devices to yield a plurality of analyzed tweets; and transmitting, for display, at least a portion of a plurality of analyzed tweets to a host device viewed by a host of a broadcast to yield displayed tweets, wherein the displayed tweets are selectable by the host, and wherein icons associated with each of the display tweets comprises a first selectable portion, which, when selected causes a processor to display a text associated with the respective tweet and a second selectable portion which causes the processor to insert audio associated with the respective tweet into the broadcast transmitted to the plurality of devices. 2. The method of claim 1 , wherein the respective tweet is text composed by a listener, each respective device being used for a respective telephone call between a broadcaster and the each respective device, wherein each listener hears the respective telephone call of the broadcast from the broadcaster on the each respective device. | 0.562016 |
1. A method of providing information associated with a selected item in an electronic document, comprising: receiving a selection of one of a text item, a display item, and a selectable object that is contained in an electronic document displayed in a first user interface of an application for processing the electronic document; passing data representing the selected item to an information source; at the information source, parsing a data source for information associated with the selection; returning the information associated with the selection, wherein the information is commonly presented by another application; if the information associated with the selection is received from more than one information source, displaying the information in a second lightweight user interface in a plurality of sections, where information from a first information source is displayed in a first section, and where information from a second information source is displayed in a second section; prioritizing the plurality of sections of information according to a preferred display orientation, where a most preferred section is displayed in a first orientation and a least preferred section is displayed in a second orientation, wherein the first orientation has a size that is larger than the second orientation and the second orientation comprises: a full display orientation that displays all of the least preferred section when available display space in the second lightweight user interface allows for full display of both the most preferred section and the least preferred section; a truncated display orientation that truncates a portion of the least preferred section so that only a portion of the information that will fit in the available display space provided in the second lightweight user interface is displayed if all of the information associated with the selection will not fit in an available display space provided in the second lightweight user interface; and a collapsed orientation that prevents viewing of the least preferred section when available display space in the second lightweight user interface disallows for full display of both the most preferred section and the least preferred section, wherein selection of a selectable control of the collapsed section causes display of the least preferred information and simultaneously causes collapse of the presently displayed information to prevent viewing of the information of the most preferred section; displaying the second lightweight user interface over the first user interface in proximity to the selection; and displaying the information associated with the selection in the second lightweight user interface without activating a third user interface for the other application. | 1. A method of providing information associated with a selected item in an electronic document, comprising: receiving a selection of one of a text item, a display item, and a selectable object that is contained in an electronic document displayed in a first user interface of an application for processing the electronic document; passing data representing the selected item to an information source; at the information source, parsing a data source for information associated with the selection; returning the information associated with the selection, wherein the information is commonly presented by another application; if the information associated with the selection is received from more than one information source, displaying the information in a second lightweight user interface in a plurality of sections, where information from a first information source is displayed in a first section, and where information from a second information source is displayed in a second section; prioritizing the plurality of sections of information according to a preferred display orientation, where a most preferred section is displayed in a first orientation and a least preferred section is displayed in a second orientation, wherein the first orientation has a size that is larger than the second orientation and the second orientation comprises: a full display orientation that displays all of the least preferred section when available display space in the second lightweight user interface allows for full display of both the most preferred section and the least preferred section; a truncated display orientation that truncates a portion of the least preferred section so that only a portion of the information that will fit in the available display space provided in the second lightweight user interface is displayed if all of the information associated with the selection will not fit in an available display space provided in the second lightweight user interface; and a collapsed orientation that prevents viewing of the least preferred section when available display space in the second lightweight user interface disallows for full display of both the most preferred section and the least preferred section, wherein selection of a selectable control of the collapsed section causes display of the least preferred information and simultaneously causes collapse of the presently displayed information to prevent viewing of the information of the most preferred section; displaying the second lightweight user interface over the first user interface in proximity to the selection; and displaying the information associated with the selection in the second lightweight user interface without activating a third user interface for the other application. 9. The method of claim 1 , further comprising: in response to receiving a selection for expanding the second lightweight user interface for providing additional display space in the second lightweight user interface, automatically expanding the second lightweight user interface for providing additional display space in the second lightweight user interface. | 0.543362 |
6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. | 6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. 9. The system of claim 6 wherein the request is transmitted from the requesting device when an advertisement is displayed or selected on the requesting device. | 0.554011 |
1. A computer-implemented method comprising: receiving, by a portable computing device, a spoken query from a user of the portable computing device; determining that the spoken query is classified as a television-related query; submitting, by the portable computing device to a remote server system, a digital recording of the spoken query and data indicating that the spoken query is classified as a television-related query; receiving, at the portable computing device from the remote server system, a transcription of the spoken query; and automatically transmitting the transcription of the spoken query from the portable computing device to a television system, wherein the television system is programmed to modify the transcription of the spoken query received from the remote server system via the portable computing device, to submit the modified transcription of the spoken query received from the remote server system via the portable computing device as a search query to a remote search engine, and to display to the user media-related results that are determined to be responsive to the search query. | 1. A computer-implemented method comprising: receiving, by a portable computing device, a spoken query from a user of the portable computing device; determining that the spoken query is classified as a television-related query; submitting, by the portable computing device to a remote server system, a digital recording of the spoken query and data indicating that the spoken query is classified as a television-related query; receiving, at the portable computing device from the remote server system, a transcription of the spoken query; and automatically transmitting the transcription of the spoken query from the portable computing device to a television system, wherein the television system is programmed to modify the transcription of the spoken query received from the remote server system via the portable computing device, to submit the modified transcription of the spoken query received from the remote server system via the portable computing device as a search query to a remote search engine, and to display to the user media-related results that are determined to be responsive to the search query. 8. The computer-implemented method of claim 1 , wherein the media-related results identify different broadcasts of a particular item of media content. | 0.865897 |
1. A computing device having adaptable image search, the computing device comprising: non-volatile memory configured to store a plurality of image recognition models; an image recognition program executed by a processor of the computing device, the computing device being a user computing device, and the image recognition program configured to: receive a query from a user, the query comprising text that is typed or converted from speech; receive a target image within which a search based on the query is to be performed; rank the image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models; determine whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, select at least one of the image recognition models whose confidence level is above the confidence threshold; perform the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and return a search result to the user. | 1. A computing device having adaptable image search, the computing device comprising: non-volatile memory configured to store a plurality of image recognition models; an image recognition program executed by a processor of the computing device, the computing device being a user computing device, and the image recognition program configured to: receive a query from a user, the query comprising text that is typed or converted from speech; receive a target image within which a search based on the query is to be performed; rank the image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models; determine whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, select at least one of the image recognition models whose confidence level is above the confidence threshold; perform the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and return a search result to the user. 6. The computing device of claim 1 , wherein the computing device comprises a camera and wherein the target image is captured by the camera. | 0.937389 |
1. A method of transferring information, the method comprising: transmitting, to a first device, a request from a handheld device for information displayed on a display device of the first device, wherein the information is viewable to a user of the handheld device viewing the display device, and wherein the information is not displayed on the handheld device; receiving a meta-language message from the first device based on the information; and converting, by a translator module of the handheld device, the meta-language message into a native language of the user of the handheld device. | 1. A method of transferring information, the method comprising: transmitting, to a first device, a request from a handheld device for information displayed on a display device of the first device, wherein the information is viewable to a user of the handheld device viewing the display device, and wherein the information is not displayed on the handheld device; receiving a meta-language message from the first device based on the information; and converting, by a translator module of the handheld device, the meta-language message into a native language of the user of the handheld device. 4. The method according to claim 1 , wherein the meta-language message comprises tagged graphical information of the information. | 0.638956 |
6. The method of claim 1 , wherein the external code comprises a web application, and the web page comprises hypertext markup language (HTML) code and at least one embedded code block written in a scripting language. | 6. The method of claim 1 , wherein the external code comprises a web application, and the web page comprises hypertext markup language (HTML) code and at least one embedded code block written in a scripting language. 8. The method of claim 6 , wherein the external code is contained in the at least one embedded code block, the at least one import file, or both. | 0.866852 |
11. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions for: receiving from a website a notification that includes a sitemap URL corresponding to a sitemap for the website; in response to the notification: accessing the sitemap at the sitemap URL; and retrieving from the sitemap document location information and metadata for a plurality of documents associated with the website; scheduling for downloading documents, from among the plurality of documents, based at least in part on the metadata retrieved from the sitemap; and downloading at least a subset of the documents scheduled for downloading. | 11. A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising instructions for: receiving from a website a notification that includes a sitemap URL corresponding to a sitemap for the website; in response to the notification: accessing the sitemap at the sitemap URL; and retrieving from the sitemap document location information and metadata for a plurality of documents associated with the website; scheduling for downloading documents, from among the plurality of documents, based at least in part on the metadata retrieved from the sitemap; and downloading at least a subset of the documents scheduled for downloading. 12. The computer program product of claim 11 , wherein the metadata retrieved from the sitemap comprises, for at least a plurality of respective documents associated with the website, document modification date information indicating when the respective documents were last modified; and wherein the scheduling is performed in accordance with the document modification date information for the respective documents. | 0.5 |
2. The system of claim 1 , further comprising a call monitor performing an automatic analysis of dialogue between the customer and a human customer service representative during interaction between the customer and the human customer service representative. | 2. The system of claim 1 , further comprising a call monitor performing an automatic analysis of dialogue between the customer and a human customer service representative during interaction between the customer and the human customer service representative. 10. The system of claim 2 , wherein said call monitor performs the automatic analysis of dialogue by recognizing speech content and comparing the speech content to key phrases adapted to detect frustration, polity, and resolution characteristics of the dialogue. | 0.873582 |
1. A computer-implemented method of generating domain specific search results, the method comprising: displaying a page of a web site obtained from a first search, the page having a domain tuned search interface that is embedded in the page and returns search results based on a domain tuned search definition that identifies subject matter content of the web site; receiving a search input at the embedded domain tuned search interface, the search input being separate from the domain tuned search definition; using a search engine, that is associated with the embedded domain tuned search interface, to search a network of sites and return generic, non-domain specific search results based on the search input; generating, from the non-domain specific search results, domain specific search results by ranking the non-domain specific search results, using a computer processor, based on how similar in terms of subject matter content the non-domain specific search results are to the domain tuned search definition, wherein ranking the non-domain specific search results comprises: accessing a definition data store that stores a plurality of search definitions, each of the search definitions identifying a topical area of interest; and selecting the search definition from the plurality of search definitions stored in the definition data store, based on an identification of the embedded domain tuned search interface through which the search input is received; and outputting the domain specific search results. | 1. A computer-implemented method of generating domain specific search results, the method comprising: displaying a page of a web site obtained from a first search, the page having a domain tuned search interface that is embedded in the page and returns search results based on a domain tuned search definition that identifies subject matter content of the web site; receiving a search input at the embedded domain tuned search interface, the search input being separate from the domain tuned search definition; using a search engine, that is associated with the embedded domain tuned search interface, to search a network of sites and return generic, non-domain specific search results based on the search input; generating, from the non-domain specific search results, domain specific search results by ranking the non-domain specific search results, using a computer processor, based on how similar in terms of subject matter content the non-domain specific search results are to the domain tuned search definition, wherein ranking the non-domain specific search results comprises: accessing a definition data store that stores a plurality of search definitions, each of the search definitions identifying a topical area of interest; and selecting the search definition from the plurality of search definitions stored in the definition data store, based on an identification of the embedded domain tuned search interface through which the search input is received; and outputting the domain specific search results. 3. The method of claim 1 , further comprising: in response to receiving the search input at the domain tuned search interface, displaying on the page in which the domain tuned search interface is displayed, a domain specific advertisement having a subject that is based on the domain tuned search definition. | 0.750404 |
19. The method of claim 7 , wherein said logical model is an XML schema, said logical message components comprise XML schema components, said logical message component classes comprise a global element class defining a logical structure for said message, and wherein said message class is associated with said global element class. | 19. The method of claim 7 , wherein said logical model is an XML schema, said logical message components comprise XML schema components, said logical message component classes comprise a global element class defining a logical structure for said message, and wherein said message class is associated with said global element class. 23. The method of claim 19 wherein said logical message component classes further comprise a complex type definition class and a group definition class and wherein said physical meta-model further comprises an extension class for extending said complex type definition class or group definition class, said extension class defining a content kind attribute indicating that a bit stream representation of a message for which a logical structure has been defined in said logical model contains elements or messages defined in a message set of said schema. | 0.758026 |
1. A method of indexing data and merging indexes within a database management system, the method comprising the following steps: assign a first temporal indicator associated with a start time of a first crawl to a first instance of an index generated by the first crawl, wherein the first instance of the index comprises a first index of a first plurality of indexes generated by the first crawl and wherein the first plurality of indexes are database files; assign the first instance of the index to a set of instances of the index to be merged; assign a second temporal indicator associated with a start time of a second crawl to a second instance of an index generated by the second crawl, wherein the second instance of the index comprises a second index of a second plurality of indexes generated by the second crawl and wherein the second plurality of indexes are database files; assign the second instance of the index to the set of instances to be merged; store the set of instances of the index to be merged; validate the set of instances to be merged so as to generate valid instances; merge the valid instances to create a merged index instance; and generate an index update dictionary that includes a table comprising meta-data about the instances of the index, an identifier for the table, a state indictor including the states StateNew when an object of the index is created but is not yet used, StateOpen when the index is in use but does not yet include any committed data, StateClosed when the index instance includes committed data and processing is complete and StatelnMerge when the index instance is being merged with other indexes, and an element that includes a number of rows in the index and an element that includes an estimate of a size of the instances of the index. | 1. A method of indexing data and merging indexes within a database management system, the method comprising the following steps: assign a first temporal indicator associated with a start time of a first crawl to a first instance of an index generated by the first crawl, wherein the first instance of the index comprises a first index of a first plurality of indexes generated by the first crawl and wherein the first plurality of indexes are database files; assign the first instance of the index to a set of instances of the index to be merged; assign a second temporal indicator associated with a start time of a second crawl to a second instance of an index generated by the second crawl, wherein the second instance of the index comprises a second index of a second plurality of indexes generated by the second crawl and wherein the second plurality of indexes are database files; assign the second instance of the index to the set of instances to be merged; store the set of instances of the index to be merged; validate the set of instances to be merged so as to generate valid instances; merge the valid instances to create a merged index instance; and generate an index update dictionary that includes a table comprising meta-data about the instances of the index, an identifier for the table, a state indictor including the states StateNew when an object of the index is created but is not yet used, StateOpen when the index is in use but does not yet include any committed data, StateClosed when the index instance includes committed data and processing is complete and StatelnMerge when the index instance is being merged with other indexes, and an element that includes a number of rows in the index and an element that includes an estimate of a size of the instances of the index. 2. The method of claim 1 , wherein the first temporal indicator is not less than the second temporal indicator. | 0.535455 |
1. A method for teaching gestures performable on a multi touch interface, the method comprising: presenting a display on a touch sensing touch screen, the display comprising a first display area and a second display area, the second display area comprising a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the first display area; detecting a practice gesture currently being performed on the touch sensing touch screen in the first display area; and presenting in the touch monitor window an interactive feedback mechanism that indicates an accuracy of the practice gesture currently being performed. | 1. A method for teaching gestures performable on a multi touch interface, the method comprising: presenting a display on a touch sensing touch screen, the display comprising a first display area and a second display area, the second display area comprising a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the first display area; detecting a practice gesture currently being performed on the touch sensing touch screen in the first display area; and presenting in the touch monitor window an interactive feedback mechanism that indicates an accuracy of the practice gesture currently being performed. 4. The method of claim 1 wherein the touch monitor window is displayed separately from the first display area. | 0.724082 |
20. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage subsequent to the creation of said particular webpage. | 20. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage subsequent to the creation of said particular webpage. 26. The one or more non-transitory machine-readable media of claim 20 , wherein: the new page contains the URLs corresponding to the subset of linking webpages; and the URLs are determined from searching substantially the entire World Wide Web. | 0.816946 |
1. A method comprising: receiving a search query; identifying, by a computer search system, an entity record in an entity data store using the search query, wherein the entity data store includes a plurality of entity records, wherein each of the entity records includes an entity name, an entity type, and entity information, and wherein the entity type indicates a category in which the entity name and the entity information belongs; generating, by the computer search system, a reformulated query by inserting one or more terms from the identified entity record into the search query; performing, by the computer search system, a search for software applications using the reformulated query; and generating a list of software applications identified during the search. | 1. A method comprising: receiving a search query; identifying, by a computer search system, an entity record in an entity data store using the search query, wherein the entity data store includes a plurality of entity records, wherein each of the entity records includes an entity name, an entity type, and entity information, and wherein the entity type indicates a category in which the entity name and the entity information belongs; generating, by the computer search system, a reformulated query by inserting one or more terms from the identified entity record into the search query; performing, by the computer search system, a search for software applications using the reformulated query; and generating a list of software applications identified during the search. 25. The method of claim 1 , wherein each of the entity records includes a list of associated software applications, wherein performing the search for software applications comprises selecting each of the software applications in the list of associated software applications of the identified entity record, and wherein the method further comprises: generating a result score for each of the software applications in the list of associated software applications; and ranking the software applications in the list of associated software applications based on the result scores. | 0.5 |
17. An apparatus configured to (i) receive a request from a device through a communication system, the request comprising data representing an image of an object, (ii) access at least one of a database, a search engine, and a data network to find information related to the object, the information comprising at least one of an image, a video, an audio file, text, a hypertext link, and a web site, and (iii) send titles of the found information through the communication system to the device. | 17. An apparatus configured to (i) receive a request from a device through a communication system, the request comprising data representing an image of an object, (ii) access at least one of a database, a search engine, and a data network to find information related to the object, the information comprising at least one of an image, a video, an audio file, text, a hypertext link, and a web site, and (iii) send titles of the found information through the communication system to the device. 20. The apparatus of claim 17 , comprising at least one of a transceiver, processor, a memory, a database, a search engine, an image processing module, an object identifier, a text recognition module, a language translation module, and an information blocker. | 0.768741 |
11. A speech recognition system embodied in a digital system, the speech recognition system comprising: a microphone; a plurality of acoustic models stored in a memory of the digital system; a speech recognizer operatively connected to the microphone to receive a speech signal and configured to use the acoustic models to recognize speech in the speech signal; and a model adaptor subsystem operatively connected to the microphone to receive the speech signal and configured to adapt at least one acoustic model of the plurality of acoustic models by estimating noise in a portion of the speech signal; determining a first estimated variance scaling vector using an estimated 2-order polynomial and the noise estimation, wherein the estimated 2-order polynomial represents a priori knowledge of a dependency of a variance scaling vector on noise; determining a second estimated variance scaling vector using statistics from prior portions of the speech signal; determining a variance scaling factor using the first estimated variance scaling vector and the second estimated variance scaling vector; and using the variance scaling factor to adapt the at least one acoustic model. | 11. A speech recognition system embodied in a digital system, the speech recognition system comprising: a microphone; a plurality of acoustic models stored in a memory of the digital system; a speech recognizer operatively connected to the microphone to receive a speech signal and configured to use the acoustic models to recognize speech in the speech signal; and a model adaptor subsystem operatively connected to the microphone to receive the speech signal and configured to adapt at least one acoustic model of the plurality of acoustic models by estimating noise in a portion of the speech signal; determining a first estimated variance scaling vector using an estimated 2-order polynomial and the noise estimation, wherein the estimated 2-order polynomial represents a priori knowledge of a dependency of a variance scaling vector on noise; determining a second estimated variance scaling vector using statistics from prior portions of the speech signal; determining a variance scaling factor using the first estimated variance scaling vector and the second estimated variance scaling vector; and using the variance scaling factor to adapt the at least one acoustic model. 18. The speech recognition system of claim 11 , wherein the digital system is comprised in a mobile device. | 0.623917 |
7. The method of claim 5 , wherein the selecting the two or more most temporally relevant photographs is based in part on a last action performed on the photograph in the social networking system. | 7. The method of claim 5 , wherein the selecting the two or more most temporally relevant photographs is based in part on a last action performed on the photograph in the social networking system. 8. The method of claim 7 , wherein the last action performed on the photograph is selected from a post of the photograph, a tag on the photograph, and a comment added to the photograph. | 0.939414 |
7. The method of claim 1 , wherein said generating step D) further comprises the steps of: i) determining, by said one or more server computers, whether a substring within said text string matches any of said one or more dictionary words; ii) responsive to a determination that said substring matches any of said one or more dictionary words: a) identifying, by said one or more server computers, a substring position comprising a range of character positions of said substring within said text string; b) appending, by said one or more server computers, said substring to a keyword array on said one or more sever computers; and c) removing, by said one or more server computers, said substring from said text string; iii) determining, by said one or more server computers, whether said text string comprises a remaining substring; iv) responsive to a determination that said text string comprises said remaining substring, determining, by said one or more server computers, whether said remaining substring matches any of said one or more dictionary words; v) responsive to a determination that said remaining substring matches any of said one or more dictionary words, repeating, by said one or more server computers, steps ii) a)-v) for said remaining substring; vi) responsive to a determination that said remaining substring does not match any of said one or more dictionary words: a) identifying, by said one or more server computers, said substring position for said remaining substring; and b) appending, by said one or more server computers, said remaining substring to said keyword array; and vii) generating, by said one or more server computers, a keyword string comprising said keyword array ordered and parsed according to said substring position of said substring and said remaining substring. | 7. The method of claim 1 , wherein said generating step D) further comprises the steps of: i) determining, by said one or more server computers, whether a substring within said text string matches any of said one or more dictionary words; ii) responsive to a determination that said substring matches any of said one or more dictionary words: a) identifying, by said one or more server computers, a substring position comprising a range of character positions of said substring within said text string; b) appending, by said one or more server computers, said substring to a keyword array on said one or more sever computers; and c) removing, by said one or more server computers, said substring from said text string; iii) determining, by said one or more server computers, whether said text string comprises a remaining substring; iv) responsive to a determination that said text string comprises said remaining substring, determining, by said one or more server computers, whether said remaining substring matches any of said one or more dictionary words; v) responsive to a determination that said remaining substring matches any of said one or more dictionary words, repeating, by said one or more server computers, steps ii) a)-v) for said remaining substring; vi) responsive to a determination that said remaining substring does not match any of said one or more dictionary words: a) identifying, by said one or more server computers, said substring position for said remaining substring; and b) appending, by said one or more server computers, said remaining substring to said keyword array; and vii) generating, by said one or more server computers, a keyword string comprising said keyword array ordered and parsed according to said substring position of said substring and said remaining substring. 8. The method of claim 7 further comprising the steps of: i) receiving, by said one or more server computers, said text string without spaces; ii) setting, by said one or more server computers, a substring length to a number greater than 0; iii) identifying, by said one or more server computers, one or more substring-length substrings comprising one or more contiguous substrings with a length of said substring length within said text string; iv) for each of said one or more substring-length substrings: a) determining, by said one or more server computers, whether one of said one or more substring-length substrings matches any of said one or more dictionary words; and b) responsive to a determination that said one of said one or more substring-length substrings matches any of said one or more dictionary words, appending, by said one or more server computers, said substring-length substring to a micro dictionary keyword array; v) determining, by said one or more server computers, whether said substring length is greater than a length of said text string; vi) responsive to a determination that said substring length is not greater than said length of said text string; a) incrementing, by said one or more server computers, said substring length by 1; and b) repeating, by said one or more server computers, steps iii) - vi) b); and vii) generating, by said one or more server computers, a micro dictionary comprising one or more keywords comprising said one or more substring-length substrings in said micro dictionary keyword array ordered from a highest substring length to a lowest substring length. | 0.631487 |
18. The method of claim 1 , further comprising assigning a relevancy level to portions of the media item, and wherein generating the content summary comprises generating the content summary based on the relevancy level of portions of the media item. | 18. The method of claim 1 , further comprising assigning a relevancy level to portions of the media item, and wherein generating the content summary comprises generating the content summary based on the relevancy level of portions of the media item. 19. The method of claim 18 , wherein generating the content summary based on the relevancy level comprises including a portion of the media item in the content summary based on the relevancy level of the portion. | 0.890888 |
13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, over a computer network, audio data for an utterance detected by a client device in communication with the one or more computers over the computer network; accessing association data that indicates a plurality of associations, each association indicating (i) uncorrupted audio data indicating characteristics of an uncorrupted audio segment, and (ii) a corresponding key based on a corrupted version of the same uncorrupted audio segment, the associations being determined before receiving the audio data for the utterance; selecting uncorrupted audio data based on a comparison of (i) one or more keys based on the audio data for the utterance, with (ii) the keys based on the corrupted audio data; constructing a representation of the utterance comprising the selected uncorrupted audio data; and performing speech recognition on the constructed representation of the utterance to determine a transcription of the utterance. | 13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, over a computer network, audio data for an utterance detected by a client device in communication with the one or more computers over the computer network; accessing association data that indicates a plurality of associations, each association indicating (i) uncorrupted audio data indicating characteristics of an uncorrupted audio segment, and (ii) a corresponding key based on a corrupted version of the same uncorrupted audio segment, the associations being determined before receiving the audio data for the utterance; selecting uncorrupted audio data based on a comparison of (i) one or more keys based on the audio data for the utterance, with (ii) the keys based on the corrupted audio data; constructing a representation of the utterance comprising the selected uncorrupted audio data; and performing speech recognition on the constructed representation of the utterance to determine a transcription of the utterance. 17. The system of claim 13 , wherein each corrupted version of an uncorrupted audio segment is a version of an uncorrupted audio segment that has been modified to include audio characteristics representative of one or more candidate environments. | 0.879395 |
21. The service creation environment of claim 19 , wherein the application comprises a modeling application, the graphical representation generated using the modeling application. | 21. The service creation environment of claim 19 , wherein the application comprises a modeling application, the graphical representation generated using the modeling application. 22. The service creation environment of claim 21 , wherein the modeling application is operable to generate the graphical representation in Unified Modeling Language or Freeform. | 0.923516 |
1. A computer-implemented method comprising: under control of one or more computing devices comprising one or more processors, receiving a text including multiple words; identifying multiple word segmentation units based on the multiple words; generating multiple word sequences by: designating a word segmentation unit of the multiple word segmentation unit as a word sequence; determining whether an additional word segmentation unit is after the word segmentation unit; and in an event that the additional word segmentation unit is not after the word segmentation unit, designating the additional word segmentation unit as an additional word sequence; determining that a boundary position of a word sequence of the multiple word sequences is identical to a boundary position of an additional word sequence of the multiple word sequences, the boundary position indicating a boundary between two adjacent word segmentation units of the multiple word segmentation units; and merging the word sequence and the additional word sequence to generate a merged word sequence based on the boundary position. | 1. A computer-implemented method comprising: under control of one or more computing devices comprising one or more processors, receiving a text including multiple words; identifying multiple word segmentation units based on the multiple words; generating multiple word sequences by: designating a word segmentation unit of the multiple word segmentation unit as a word sequence; determining whether an additional word segmentation unit is after the word segmentation unit; and in an event that the additional word segmentation unit is not after the word segmentation unit, designating the additional word segmentation unit as an additional word sequence; determining that a boundary position of a word sequence of the multiple word sequences is identical to a boundary position of an additional word sequence of the multiple word sequences, the boundary position indicating a boundary between two adjacent word segmentation units of the multiple word segmentation units; and merging the word sequence and the additional word sequence to generate a merged word sequence based on the boundary position. 2. The computer-implemented method of claim 1 , further comprising: performing a search based on one or more word segmentation units of the merged word sequence. | 0.895484 |
10. A computer implemented method for identifying propaganda, wherein a computer has a source dataset stored thereon, comprising: the computer tokenizing each document in the source dataset; the computer generating a term-by-document matrix; the computer applying weights to the term-by-document matrix to generate a weighted term-by-document matrix; the computer performing a matrix multiplication of a translation matrix and the weighted term-by-document matrix to generate a multilingualized weighted matrix; the computer factorizing the multilingualized weighted matrix to generate an ordered list of topics and a topic-by-document block matrix; and the computer calculating a contribution per user-specified grouping within the source dataset to each topic within the ordered list of topics; wherein the tokenization, generating of a matrix, applying weights, matrix multiplication, factorizing, calculating, and generating of output are performed regardless of the number, type, or size of documents, regardless of the number or type of terms associated with each document, and regardless of the provenance of the dataset. | 10. A computer implemented method for identifying propaganda, wherein a computer has a source dataset stored thereon, comprising: the computer tokenizing each document in the source dataset; the computer generating a term-by-document matrix; the computer applying weights to the term-by-document matrix to generate a weighted term-by-document matrix; the computer performing a matrix multiplication of a translation matrix and the weighted term-by-document matrix to generate a multilingualized weighted matrix; the computer factorizing the multilingualized weighted matrix to generate an ordered list of topics and a topic-by-document block matrix; and the computer calculating a contribution per user-specified grouping within the source dataset to each topic within the ordered list of topics; wherein the tokenization, generating of a matrix, applying weights, matrix multiplication, factorizing, calculating, and generating of output are performed regardless of the number, type, or size of documents, regardless of the number or type of terms associated with each document, and regardless of the provenance of the dataset. 12. A computer implemented method of claim 10 , wherein generating a term-by-document matrix comprises: listing unique documents along one axis of the matrix; listing unique terms along another axis of the matrix; and populating the matrix with non-zero values recording a number of times particular terms occur in conjunction with particular documents. | 0.630575 |
13. The apparatus of claim 9 , wherein the property has a linear temporal logic form X! pv 1 , where pv represents a proportional variable. | 13. The apparatus of claim 9 , wherein the property has a linear temporal logic form X! pv 1 , where pv represents a proportional variable. 14. The apparatus of claim 13 , wherein the auxiliary property has a linear temporal logic form X pv 3 , where pv 3 represents the condition. | 0.946617 |
1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing. | 1. A method for determining a person's response to a retail element, based on the person's facial expression and shopping behavior, comprising the following steps of: a) detecting and tracking a face from first input images captured by at least a first means for capturing images, estimating two-dimensional and three-dimensional poses of the face, and localizing facial features, using at least a control and processing system, b) estimating gaze direction of the person using the two-dimensional and three-dimensional poses and positions of the facial features and changes in affective state of the person by extracting emotion-sensitive features, and recognizing a demographic category of the person, c) detecting and tracking the person from second input images captured by at least a second means for capturing images, producing a trajectory of the person, and estimating body orientation, using the control and processing system, d) identifying the shopping behaviors of the person toward the retail element, utilizing position and the body orientation of the person relative to the retail element, and e) determining intermediate responses and end response of the person to the retail element by analyzing the changes in affective states and interest, in the context of the shopping behavior and the demographics category of the person, wherein the first means for capturing images and the second means for capturing images are connected to the control and processing system via at least a means for video interface, and wherein the shopping behaviors include showing interest, engagement, interaction, or purchasing. 15. The method according to claim 1 , wherein the method further comprises a step of detecting the person's engagement with the retail element based on a trajectory from tracking the person and the body orientation of the person. | 0.536344 |
1. A computer implemented method for managing a collaborative web page, the computer implemented method comprising: displaying a plurality of graphical representations of commands for adding and modifying dynamic content of the collaborative web page; responsive to a user selecting a command in the plurality of graphical representations of commands, presenting a property editor to modify properties of the dynamic content of the collaborative web page to form modifiable properties, wherein the modifiable properties in the property editor are selected from a group consisting of: a size of the dynamic content, an address for a map, a news aggregator for a data feed, a name of a data source a list of destinations for modifying the address for the map displayed on the collaborative web page and a combination thereof; creating a page tree view of a plurality of collaborative web pages using a tree structure including a plurality of nodes and a plurality of leaf nodes, wherein creating the page tree view comprises reading all rows in a wiki page database table and extracting the page names column values, iterating over the page name values to build a page tree view, and grouping a hierarchy of pages into nodes and lead nodes to form a visual tree structure, wherein a node in the plurality of nodes includes content of a first collaborative web page in the plurality of collaborative web pages and functions as a folder that contains one or more leaf nodes in the plurality of leaf nodes that are organized beneath the node in the tree structure, wherein a leaf node in the plurality of leaf nodes corresponds to object variables and content for a portion of the second collaborative web page in un-rendered form, and wherein the page tree view allows the user to navigate directly to the plurality of collaborative web pages; and including the page tree view in the collaborative web page, wherein the collaborative web page is a wiki page. | 1. A computer implemented method for managing a collaborative web page, the computer implemented method comprising: displaying a plurality of graphical representations of commands for adding and modifying dynamic content of the collaborative web page; responsive to a user selecting a command in the plurality of graphical representations of commands, presenting a property editor to modify properties of the dynamic content of the collaborative web page to form modifiable properties, wherein the modifiable properties in the property editor are selected from a group consisting of: a size of the dynamic content, an address for a map, a news aggregator for a data feed, a name of a data source a list of destinations for modifying the address for the map displayed on the collaborative web page and a combination thereof; creating a page tree view of a plurality of collaborative web pages using a tree structure including a plurality of nodes and a plurality of leaf nodes, wherein creating the page tree view comprises reading all rows in a wiki page database table and extracting the page names column values, iterating over the page name values to build a page tree view, and grouping a hierarchy of pages into nodes and lead nodes to form a visual tree structure, wherein a node in the plurality of nodes includes content of a first collaborative web page in the plurality of collaborative web pages and functions as a folder that contains one or more leaf nodes in the plurality of leaf nodes that are organized beneath the node in the tree structure, wherein a leaf node in the plurality of leaf nodes corresponds to object variables and content for a portion of the second collaborative web page in un-rendered form, and wherein the page tree view allows the user to navigate directly to the plurality of collaborative web pages; and including the page tree view in the collaborative web page, wherein the collaborative web page is a wiki page. 2. The computer implemented method of claim 1 , further comprising: creating the collaborative web page in response to receiving a user input requesting creation of the collaborative web page. | 0.634579 |
11. A computerized system for auditing a script code, the system comprising: a parser module stored on a computer and, when executed by the computer, configured to: parse the script code to generate script code metadata; and allow selection of one or more portions of the script code; a rules module stored on the computer and configured to audit the script code by applying rules to the selected one or more portions of the script code when the rules module is executed by the computer; and a reporting module stored on the computer and configured to use the script code metadata to generate a result of the audit when the reporting module is executed by the computer; wherein the parser module is configured to read the script code from an input script code file, the script code comprising at least one of a Quick Test Professional (QTP) script and a Load-runner script wherein the rules include a plurality of review points, the result includes a respective severity level associated with each of the plurality of review points, and applying the rules to the selected one or more portions of the script code includes checking a first review point of the plurality of review points against the selected one or more portions of the script code; recording a deviation if the selected one or more portions of the script code do not comply with the first review point; and checking a remainder of the review points of the plurality of review points against the selected one or more portions of the script code and recording deviations for each review point that the selected one or more portions of the script code does not comply with; wherein each of the plurality of review points is associated with a portion of the selected one or more portions of the script code to be audited; and wherein the result includes a respective (i) review field, (ii) review comment field, and (iii) status field associated with each of the plurality of review points. | 11. A computerized system for auditing a script code, the system comprising: a parser module stored on a computer and, when executed by the computer, configured to: parse the script code to generate script code metadata; and allow selection of one or more portions of the script code; a rules module stored on the computer and configured to audit the script code by applying rules to the selected one or more portions of the script code when the rules module is executed by the computer; and a reporting module stored on the computer and configured to use the script code metadata to generate a result of the audit when the reporting module is executed by the computer; wherein the parser module is configured to read the script code from an input script code file, the script code comprising at least one of a Quick Test Professional (QTP) script and a Load-runner script wherein the rules include a plurality of review points, the result includes a respective severity level associated with each of the plurality of review points, and applying the rules to the selected one or more portions of the script code includes checking a first review point of the plurality of review points against the selected one or more portions of the script code; recording a deviation if the selected one or more portions of the script code do not comply with the first review point; and checking a remainder of the review points of the plurality of review points against the selected one or more portions of the script code and recording deviations for each review point that the selected one or more portions of the script code does not comply with; wherein each of the plurality of review points is associated with a portion of the selected one or more portions of the script code to be audited; and wherein the result includes a respective (i) review field, (ii) review comment field, and (iii) status field associated with each of the plurality of review points. 12. The computerized system of claim 11 , wherein the result includes an indication of compliance of the audited portion with the each of the plurality of review points. | 0.501773 |
16. A computer system comprising: a processor; a non-transitory computer-readable storage medium coupled to the processor; and a plurality of instructions, encoded in the non-transitory computer-readable storage medium and configured to cause the processor to generate a first configurator for a customizable product, wherein the instructions configured to cause the processor to generate the first configurator comprise a first set of instructions configured to cause the processor to create a customizable product, wherein the customizable product comprises a set of one or more attributes, and the set of one or more attributes is configured to define, at least in part, the customizable product, assign the customizable product to a customizable product class, wherein the customizable product class is a parent class of a hierarchy defining the first configurator, add a component product class to the customizable product class, wherein the component product class is a subclass of the customizable product, add a customizable class rule to the customizable product class, wherein the customizable class rule comprises one or more expressions, and the one or more expressions are configured to define one or more constraints on one or more component products added to the customizable product, and map a customizable user interface (UI) to the customizable product class, wherein the customizable UI is configured to provide access structure to the first configurator, and generate a second configurator for another customizable product, wherein the instructions configured to cause the processor to generate the second configurator comprise at least one of the instructions performed in generating the first configurator, and the at least one of the instructions is performed on the another customizable product. | 16. A computer system comprising: a processor; a non-transitory computer-readable storage medium coupled to the processor; and a plurality of instructions, encoded in the non-transitory computer-readable storage medium and configured to cause the processor to generate a first configurator for a customizable product, wherein the instructions configured to cause the processor to generate the first configurator comprise a first set of instructions configured to cause the processor to create a customizable product, wherein the customizable product comprises a set of one or more attributes, and the set of one or more attributes is configured to define, at least in part, the customizable product, assign the customizable product to a customizable product class, wherein the customizable product class is a parent class of a hierarchy defining the first configurator, add a component product class to the customizable product class, wherein the component product class is a subclass of the customizable product, add a customizable class rule to the customizable product class, wherein the customizable class rule comprises one or more expressions, and the one or more expressions are configured to define one or more constraints on one or more component products added to the customizable product, and map a customizable user interface (UI) to the customizable product class, wherein the customizable UI is configured to provide access structure to the first configurator, and generate a second configurator for another customizable product, wherein the instructions configured to cause the processor to generate the second configurator comprise at least one of the instructions performed in generating the first configurator, and the at least one of the instructions is performed on the another customizable product. 22. The computer system of claim 16 , wherein the first configurator comprises: an operator property, wherein the operator property is configured to enable a function to be performed within an expression of the one or more expressions, and the expression comprises a property path. | 0.615353 |
1. A bill discriminating and counting apparatus comprising: a hopper which receives bills to be processed; a feeding and carrying section which feeds the bills received by said hopper one by one to a transport path and carries the bills; a discriminating and counting section which is provided on a downstream side of said feeding and carrying section, said discriminating and counting section discriminates denominations of the carried bills and counts the bills; a stacker which is provided on the downstream side of said discriminating and counting section, said stacker collects the bills in which normality is confirmed; an operation and display section which displays display data; a storage section in which the display data is stored, said storage section includes a first storage area in which the stored display data is an English word and a second storage area in which the stored display data is a bitmap data, wherein the bitmap data shows a non-English word translated from the English word in the first storage by an outside computer; and display selection means for arbitrarily selecting the display data written in English stored in said first storage area and the display data stored in said second storage area to display the display data on said operation and display section. | 1. A bill discriminating and counting apparatus comprising: a hopper which receives bills to be processed; a feeding and carrying section which feeds the bills received by said hopper one by one to a transport path and carries the bills; a discriminating and counting section which is provided on a downstream side of said feeding and carrying section, said discriminating and counting section discriminates denominations of the carried bills and counts the bills; a stacker which is provided on the downstream side of said discriminating and counting section, said stacker collects the bills in which normality is confirmed; an operation and display section which displays display data; a storage section in which the display data is stored, said storage section includes a first storage area in which the stored display data is an English word and a second storage area in which the stored display data is a bitmap data, wherein the bitmap data shows a non-English word translated from the English word in the first storage by an outside computer; and display selection means for arbitrarily selecting the display data written in English stored in said first storage area and the display data stored in said second storage area to display the display data on said operation and display section. 3. The bill discriminating and counting apparatus according to claim 1 , wherein said second storage area is rewritable. | 0.521049 |
1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising. | 1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising. 3. The system of claim 1 , wherein the one or more definitions of surprise are a function of frequency of occurrence of events that can be predicted by the predictive model component. | 0.609589 |
1. A method executed in a computer system for comparing the similarity of a target string to at least one string in a set of strings, the target string and each string in the set of strings being a sequence of symbols from an alphabet of symbols, the method comprising the steps of: (a) Generating a multi-level Trie associated with the set of strings, the Trie having a null level and a null node thereon, and a plurality of data levels having a plurality of data nodes thereon, each data node having a symbol of the alphabet associated therewith; (b) From the null node, traversing a plurality of levels of the Trie commencing with the first data level adjacent the null node, and thereafter descending level by level within the Trie; (c) For each data level of the Trie traversed, making a first selection of a set of data nodes from that level, which first selection step includes the steps of: i. In the case of the first data level of the Trie, selecting all of the data nodes in that level of the Trie; and ii. In the case of at least one other data levels of the Trie, for each such level A. Making a second selection of all of the children of the nodes of the first selection of the level immediately previously traversed; B. For each of the data nodes selected in step A, calculating a heuristic measurement between the sequence of symbols in the target string and the sequence formed by the symbols on the path from the null node to that selected data node; and C. For at least a first symbol represented, selecting a first cluster of nodes representing that first symbol that have the most optimal calculated heuristic measurement associated therewith, up to a bounded number of nodes and identifying the terminal nodes in the first cluster of nodes; (d) Continuing to traverse the Trie, level by level, repeating step (c) in respect of each level traversed, until step (c) has been completed on that level of the Trie for which there are no children of the selected nodes; and (e) In respect of each terminal node identified during the traversal of the plurality of levels of the Trie, comparing the calculated heuristic measurement associated therewith and reporting at least one string from the set of strings associated with the optimal calculated heuristic measurement. | 1. A method executed in a computer system for comparing the similarity of a target string to at least one string in a set of strings, the target string and each string in the set of strings being a sequence of symbols from an alphabet of symbols, the method comprising the steps of: (a) Generating a multi-level Trie associated with the set of strings, the Trie having a null level and a null node thereon, and a plurality of data levels having a plurality of data nodes thereon, each data node having a symbol of the alphabet associated therewith; (b) From the null node, traversing a plurality of levels of the Trie commencing with the first data level adjacent the null node, and thereafter descending level by level within the Trie; (c) For each data level of the Trie traversed, making a first selection of a set of data nodes from that level, which first selection step includes the steps of: i. In the case of the first data level of the Trie, selecting all of the data nodes in that level of the Trie; and ii. In the case of at least one other data levels of the Trie, for each such level A. Making a second selection of all of the children of the nodes of the first selection of the level immediately previously traversed; B. For each of the data nodes selected in step A, calculating a heuristic measurement between the sequence of symbols in the target string and the sequence formed by the symbols on the path from the null node to that selected data node; and C. For at least a first symbol represented, selecting a first cluster of nodes representing that first symbol that have the most optimal calculated heuristic measurement associated therewith, up to a bounded number of nodes and identifying the terminal nodes in the first cluster of nodes; (d) Continuing to traverse the Trie, level by level, repeating step (c) in respect of each level traversed, until step (c) has been completed on that level of the Trie for which there are no children of the selected nodes; and (e) In respect of each terminal node identified during the traversal of the plurality of levels of the Trie, comparing the calculated heuristic measurement associated therewith and reporting at least one string from the set of strings associated with the optimal calculated heuristic measurement. 3. A method according to claim 1 wherein the heuristic function is a distance measurement between the sequence of symbols in the target string and the sequence formed by the symbols on the path from the null node to that selected data node. | 0.521521 |
18. A method, comprising: obtaining, by a device, a test script document, the test script document including a set of words or a set of characters; identifying, by the device, a skip value for the test script document, and the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determining, by the device, one or more skip n-grams using the skip value for the test script document; extracting, by the device, one or more terms from the test script document based on the one or more skip n-grams, a term associated with a skip n-gram, of the one or more skip n-grams, corresponding to a sequence of words or characters skipped within an n-gram sequence of the skip n-gram; generating, by the device, a functional diagram representing the test script document using the one or more terms based on extracting the one or more terms; and providing, by the device and via a user interface, information associated with the functional diagram. | 18. A method, comprising: obtaining, by a device, a test script document, the test script document including a set of words or a set of characters; identifying, by the device, a skip value for the test script document, and the skip value relating to a quantity of words or a quantity of characters that are to be skipped in an n-gram; determining, by the device, one or more skip n-grams using the skip value for the test script document; extracting, by the device, one or more terms from the test script document based on the one or more skip n-grams, a term associated with a skip n-gram, of the one or more skip n-grams, corresponding to a sequence of words or characters skipped within an n-gram sequence of the skip n-gram; generating, by the device, a functional diagram representing the test script document using the one or more terms based on extracting the one or more terms; and providing, by the device and via a user interface, information associated with the functional diagram. 19. The method of claim 18 , further comprising: identifying a set of relationships associated with the one or more terms; and where generating the functional diagram representing the test script document is based on the set of relationships and the one or more terms. | 0.693355 |
1. A method for building a visual vocabulary, the method comprising: generating visual words based on a set of features, wherein the visual words are defined in a higher-dimensional space; projecting the visual words from the higher-dimensional space to a first lower-dimensional space, thereby producing projections of the visual words in the first lower-dimensional space; generating a first collection of buckets in the first lower-dimensional space based on the projections of the visual words in the first lower-dimensional space; projecting the visual words from the higher-dimensional space to a second lower-dimensional space, thereby producing projections of the visual words in the second lower-dimensional space; generating a second collection of buckets in the second lower-dimensional space based on the projections of the visual words in the second lower-dimensional space; and iteratively selecting a sub-collection of buckets from the first collection of buckets and from the second collection of buckets, wherein bucket selection during any iteration after an initial iteration is based at least in part on feedback from previously selected buckets. | 1. A method for building a visual vocabulary, the method comprising: generating visual words based on a set of features, wherein the visual words are defined in a higher-dimensional space; projecting the visual words from the higher-dimensional space to a first lower-dimensional space, thereby producing projections of the visual words in the first lower-dimensional space; generating a first collection of buckets in the first lower-dimensional space based on the projections of the visual words in the first lower-dimensional space; projecting the visual words from the higher-dimensional space to a second lower-dimensional space, thereby producing projections of the visual words in the second lower-dimensional space; generating a second collection of buckets in the second lower-dimensional space based on the projections of the visual words in the second lower-dimensional space; and iteratively selecting a sub-collection of buckets from the first collection of buckets and from the second collection of buckets, wherein bucket selection during any iteration after an initial iteration is based at least in part on feedback from previously selected buckets. 6. The method of claim 1 , further comprising generating labeled image representations based on the first collection of buckets, on the second collection of buckets, and on labeled images, wherein labels that are associated with an image are associated with a respective labeled image representation of the image. | 0.568599 |
10. The data processing system for performing the fuzzy inference operation of claim 9 wherein the rule bits generating circuit, comprises: a rule code memory for storing a plurality of rules, the rule code memory storing a first plurality of antecedents corresponding to a first one of the plurality of rules, the rule code memory being coupled to the input label sorter for receiving the input labels corresponding to the first portion of the plurality of grades in the second order based on magnitude and generating a first plurality of rule codes in response thereto; a decoder coupled to the rule code memory for receiving the first plurality of rule codes, the decoder decoding the first plurality of rule codes to generate a first plurality of decoded signals; and first logic means coupled to the decoder for receiving the first plurality of decoded signals, the first logic means logically combining the first plurality of decoded signals to generate a first plurality of rule signals. | 10. The data processing system for performing the fuzzy inference operation of claim 9 wherein the rule bits generating circuit, comprises: a rule code memory for storing a plurality of rules, the rule code memory storing a first plurality of antecedents corresponding to a first one of the plurality of rules, the rule code memory being coupled to the input label sorter for receiving the input labels corresponding to the first portion of the plurality of grades in the second order based on magnitude and generating a first plurality of rule codes in response thereto; a decoder coupled to the rule code memory for receiving the first plurality of rule codes, the decoder decoding the first plurality of rule codes to generate a first plurality of decoded signals; and first logic means coupled to the decoder for receiving the first plurality of decoded signals, the first logic means logically combining the first plurality of decoded signals to generate a first plurality of rule signals. 11. The data processing system for performing the fuzzy inference operation of claim 10 wherein the rule code memory stores a first plurality of antecedents corresponding to a second one of the plurality of rules and generates a second plurality of rule codes in response thereto. | 0.86674 |
9. The receiver of claim 4, further comprising means for descrambling a signal produced by said tuner. | 9. The receiver of claim 4, further comprising means for descrambling a signal produced by said tuner. 11. The apparatus of claim 9, further comprising frequency translation means for frequency translating a descrambled video signal into a signal within the radio frequency passband of a television receiver. | 0.956759 |
13. An apparatus, comprising: a subsystem, implemented at least partially by hardware, that extracts a set of accessed domain names from a set of events stored in a field-searchable data store, wherein each accessed domain name in the set of accessed domain names was not detected in events generated prior to generation of the set of events; a subsystem, implemented at least partially by hardware, that identifies a respective registration time for each accessed domain name in the set of accessed domain names, wherein the respective registration time is indicative of when the accessed domain name was first detected within the set of events; a subsystem, implemented at least partially by hardware, that identifies a subset of accessed domain names in the set of accessed domain names for which the identified respective registration time of each accessed domain name in the subset is recent relative to times for other accessed domain names in the set of accessed domain names; a subsystem, implemented at least partially by hardware, that determines, for each accessed domain name in the subset, an access count corresponding to how many times the set of events indicates that the accessed domain name in the subset was accessed; a subsystem, implemented at least partially by hardware, that causes display of information relating to the access count. | 13. An apparatus, comprising: a subsystem, implemented at least partially by hardware, that extracts a set of accessed domain names from a set of events stored in a field-searchable data store, wherein each accessed domain name in the set of accessed domain names was not detected in events generated prior to generation of the set of events; a subsystem, implemented at least partially by hardware, that identifies a respective registration time for each accessed domain name in the set of accessed domain names, wherein the respective registration time is indicative of when the accessed domain name was first detected within the set of events; a subsystem, implemented at least partially by hardware, that identifies a subset of accessed domain names in the set of accessed domain names for which the identified respective registration time of each accessed domain name in the subset is recent relative to times for other accessed domain names in the set of accessed domain names; a subsystem, implemented at least partially by hardware, that determines, for each accessed domain name in the subset, an access count corresponding to how many times the set of events indicates that the accessed domain name in the subset was accessed; a subsystem, implemented at least partially by hardware, that causes display of information relating to the access count. 21. The apparatus of claim 13 , wherein each accessed domain name in the set of accessed domain names corresponds to an accessed Web page. | 0.834057 |
15. A computer program stored on a non-transitory computer-readable medium with a method of providing electronic contract information, the program comprising computer-executable steps for: providing a contract document from the electronic storage; subdividing, responsive to a user, the contract document into sections; entering, responsive to the user, an annotation regarding a relationship between (i) at least one section within the contract document and (ii) at least one other section within the contract document or at least one other section within another electronic document; storing, by the computer processor, the annotation in the electronic storage for later retrieval, the contract documents are stored in the electronic storage separately from the annotations, wherein each annotation is different from other annotations in the electronic storage, wherein the annotation stored in the electronic storage: indicates the relationship between (i) the at least one section within the contract document and (ii) the at least one other section within the contract document or the at least one other section within the another electronic document, the annotation regarding the relationship further includes specific to the at least one section of the contract document to which the at least one annotations is applied and the at least one other section, a pre-defined conflict indication user-selected from at least two of pass, possible and fail, indicates a predetermined data portion within the contract document as stored in the electronic storage to which the annotation is related as indicated by a document-image-independent data schema, retrieving the at least one contract document from the electronic storage as document data, said document data including at least one element corresponding to the location of the at least one annotation within said document; retrieving the annotation to be applied to said at least one contract document from the electronic storage as annotation data; and combining the document data and the annotation data to form a unitary single logical document displaying the annotation embedded at the location in the document data that is indicated by the document-image-independent data schema; extracting the annotation data and the document data from the edited document, and determine the predetermined data portion for the annotation data within the edited document; store the extracted annotation data that is unedited as a same version in the electronic annotations; and updating said document data from the extracted document data as a next version in the electronic contract documents for later retrieval, the electronic annotations are stored separately from the electronic contract documents; receiving, from the user, an indication of a search request with annotation search criteria, the annotation search criteria is at least one of the pre-defined conflict indications; and searching, responsive to the annotation search criteria, in the electronic storage, for annotations that satisfy the annotation search criteria and to output, as a search result the contracts indicated by the annotations that satisfy the annotation search criteria. | 15. A computer program stored on a non-transitory computer-readable medium with a method of providing electronic contract information, the program comprising computer-executable steps for: providing a contract document from the electronic storage; subdividing, responsive to a user, the contract document into sections; entering, responsive to the user, an annotation regarding a relationship between (i) at least one section within the contract document and (ii) at least one other section within the contract document or at least one other section within another electronic document; storing, by the computer processor, the annotation in the electronic storage for later retrieval, the contract documents are stored in the electronic storage separately from the annotations, wherein each annotation is different from other annotations in the electronic storage, wherein the annotation stored in the electronic storage: indicates the relationship between (i) the at least one section within the contract document and (ii) the at least one other section within the contract document or the at least one other section within the another electronic document, the annotation regarding the relationship further includes specific to the at least one section of the contract document to which the at least one annotations is applied and the at least one other section, a pre-defined conflict indication user-selected from at least two of pass, possible and fail, indicates a predetermined data portion within the contract document as stored in the electronic storage to which the annotation is related as indicated by a document-image-independent data schema, retrieving the at least one contract document from the electronic storage as document data, said document data including at least one element corresponding to the location of the at least one annotation within said document; retrieving the annotation to be applied to said at least one contract document from the electronic storage as annotation data; and combining the document data and the annotation data to form a unitary single logical document displaying the annotation embedded at the location in the document data that is indicated by the document-image-independent data schema; extracting the annotation data and the document data from the edited document, and determine the predetermined data portion for the annotation data within the edited document; store the extracted annotation data that is unedited as a same version in the electronic annotations; and updating said document data from the extracted document data as a next version in the electronic contract documents for later retrieval, the electronic annotations are stored separately from the electronic contract documents; receiving, from the user, an indication of a search request with annotation search criteria, the annotation search criteria is at least one of the pre-defined conflict indications; and searching, responsive to the annotation search criteria, in the electronic storage, for annotations that satisfy the annotation search criteria and to output, as a search result the contracts indicated by the annotations that satisfy the annotation search criteria. 17. The computer program of claim 15 , wherein the annotation indicates how the at least one section relates to the at least one other section within the contract document or the at least one other section within another electronic document. | 0.792808 |
8. A non-transitory computer readable medium executable by a playback device to perform: presenting a language menu system for selecting a language from a plurality of languages; presenting an activity menu system containing selections comprising: a story and a vocabulary lesson; responsive to selection of the story, presenting the story as a read along activity in one or more of the plurality of languages; and responsive to selection of the vocabulary lesson: presenting the vocabulary lesson in one or more of the plurality of languages; displaying at least one visual story image and at least one sentence; presenting one or more vocabulary words corresponding to one or more of: the at least one story image and the at least one sentence; displaying one or more vocabulary word images visually representing the one or more vocabulary words; presenting a vocabulary lesson language menu within the vocabulary lesson for selecting another language of the plurality of languages for pronunciation of the one or more vocabulary words included in the vocabulary lesson; and after a predetermined period of silence, pronouncing the one or more vocabulary words in a selected language. | 8. A non-transitory computer readable medium executable by a playback device to perform: presenting a language menu system for selecting a language from a plurality of languages; presenting an activity menu system containing selections comprising: a story and a vocabulary lesson; responsive to selection of the story, presenting the story as a read along activity in one or more of the plurality of languages; and responsive to selection of the vocabulary lesson: presenting the vocabulary lesson in one or more of the plurality of languages; displaying at least one visual story image and at least one sentence; presenting one or more vocabulary words corresponding to one or more of: the at least one story image and the at least one sentence; displaying one or more vocabulary word images visually representing the one or more vocabulary words; presenting a vocabulary lesson language menu within the vocabulary lesson for selecting another language of the plurality of languages for pronunciation of the one or more vocabulary words included in the vocabulary lesson; and after a predetermined period of silence, pronouncing the one or more vocabulary words in a selected language. 10. The non-transitory computer readable medium of claim 8 , wherein presenting the story as a read along activity in one or more of the plurality of languages further comprises presenting one or more visual images corresponding to the story. | 0.821586 |
1. An apparatus comprising: at least one processor; a memory coupled to the at least one processor; a repository residing the memory that includes a plurality of documents; and a content management system residing in the memory and executed by the at least one processor, the content management system managing the plurality of documents in the repository, the content management system comprising: a content modification mechanism that detects a change to a shared document in the repository, and in response thereto, inserts applicability metadata in the shared document; and a voting mechanism that receives votes from parent documents of the shared document to accept or reject the change made to the shared document, wherein if the votes received from the parent documents to accept the change meet a defined voting threshold, the content modification mechanism removes the applicability metadata in the shared document. | 1. An apparatus comprising: at least one processor; a memory coupled to the at least one processor; a repository residing the memory that includes a plurality of documents; and a content management system residing in the memory and executed by the at least one processor, the content management system managing the plurality of documents in the repository, the content management system comprising: a content modification mechanism that detects a change to a shared document in the repository, and in response thereto, inserts applicability metadata in the shared document; and a voting mechanism that receives votes from parent documents of the shared document to accept or reject the change made to the shared document, wherein if the votes received from the parent documents to accept the change meet a defined voting threshold, the content modification mechanism removes the applicability metadata in the shared document. 3. The apparatus of claim 1 wherein if the votes received from the parent documents to accept the change do not meet the defined voting threshold, the content modification mechanism broadcasts a new profile corresponding to the change to the parent documents that voted to accept the change. | 0.67418 |
17. A non-transitory storage medium storing computer instructions that, when executed by data processing apparatus, causes the data processing apparatus to perform operations comprising: receiving data representative of a search query from a user located at a geographic location; determining whether multiple countries have a characteristic in common with the geographic location where the user is located; selecting, as a proper subset of the multiple countries, a plurality of countries that are each determined to have the characteristic in common with the geographic location where the user is located; identifying a plurality of search results responsive to the search query, wherein each search result refers to a respective particular document; accessing, for each particular search result of a plurality of the search results, a plurality of different country-specific click measures that correspond to different, single countries and correspond to a single document, wherein each country-specific click measure is a measure of behavior of users associated with a respective particular country in regards to the particular document when the particular document was referred to in a previously provided search result; for each particular search result of the plurality of the search results, generating a combined click measure, wherein each combined click measure is generated by combining the respective country-specific click measures that are (i) correspond to the particular document referred to by the search result and (ii) measures of behavior of users associated with the selected countries that are determined to have the characteristic in common with the geographic location where the user is located, and wherein each combined click measure excludes country-specific click measures for countries that are not determined to have the characteristic in common with the geographic location where the user is located; and ranking the search results based upon, at least, the combined click measures determined from the measures of behavior of users associated with the selected countries that are determined to have a characteristic in common with the geographic location where the user is located. | 17. A non-transitory storage medium storing computer instructions that, when executed by data processing apparatus, causes the data processing apparatus to perform operations comprising: receiving data representative of a search query from a user located at a geographic location; determining whether multiple countries have a characteristic in common with the geographic location where the user is located; selecting, as a proper subset of the multiple countries, a plurality of countries that are each determined to have the characteristic in common with the geographic location where the user is located; identifying a plurality of search results responsive to the search query, wherein each search result refers to a respective particular document; accessing, for each particular search result of a plurality of the search results, a plurality of different country-specific click measures that correspond to different, single countries and correspond to a single document, wherein each country-specific click measure is a measure of behavior of users associated with a respective particular country in regards to the particular document when the particular document was referred to in a previously provided search result; for each particular search result of the plurality of the search results, generating a combined click measure, wherein each combined click measure is generated by combining the respective country-specific click measures that are (i) correspond to the particular document referred to by the search result and (ii) measures of behavior of users associated with the selected countries that are determined to have the characteristic in common with the geographic location where the user is located, and wherein each combined click measure excludes country-specific click measures for countries that are not determined to have the characteristic in common with the geographic location where the user is located; and ranking the search results based upon, at least, the combined click measures determined from the measures of behavior of users associated with the selected countries that are determined to have a characteristic in common with the geographic location where the user is located. 18. The non-transitory storage medium of claim 17 , wherein combining the respective click measures comprises applying a weight to the combined respective click measures. | 0.872486 |
4. A method for partitioning a speech pattern into syllabic subunits according to claim 3 wherein said said step of generating said frame sequence of autocorrelation signals comprises forming a sequence of first order autocorrelation signals responsive to said speech pattern. | 4. A method for partitioning a speech pattern into syllabic subunits according to claim 3 wherein said said step of generating said frame sequence of autocorrelation signals comprises forming a sequence of first order autocorrelation signals responsive to said speech pattern. 5. A method for partitioning a speech pattern into syllabic subunits according to claim 4 wherein: said candidate syllabic unit signal producing step comprises selecting candidate peak and minimum energy frames jointly responsive to said peak energy signals, said minimum energy signals and said first order autocorrelation signals. | 0.932944 |
16. The RDF network construction method according to claim 11 , wherein the RDF triple includes a single RDF triple composed of two classes and one property and a multi-RDF triple composed of two or more classes and two or more properties. | 16. The RDF network construction method according to claim 11 , wherein the RDF triple includes a single RDF triple composed of two classes and one property and a multi-RDF triple composed of two or more classes and two or more properties. 17. The RDF network construction method according to claim 16 , wherein the multi-RDF triple is implemented by connecting two or more of the single RDF triples. | 0.978941 |
8. A computer storage medium having computer-executable instructions that when executed by a computer perform steps to process input received by the computer comprising the steps of: receiving input using a first modality; modifying a word graph based on the input; and rendering a hypothesis to a user for the input based on the word graph, and repeating the following steps until a desired hypothesis is obtained: modifying the word graph based on complementary information received using a second modality, the complementary information corresponding to at least a portion of the input, wherein the second modality is different from the first modality, in which modifying the word graph includes rescoring the word graph based on averaging posterior probabilities from the modalities of the input and the complementary information; and rendering a new hypothesis to the user for the input based on the word graph. | 8. A computer storage medium having computer-executable instructions that when executed by a computer perform steps to process input received by the computer comprising the steps of: receiving input using a first modality; modifying a word graph based on the input; and rendering a hypothesis to a user for the input based on the word graph, and repeating the following steps until a desired hypothesis is obtained: modifying the word graph based on complementary information received using a second modality, the complementary information corresponding to at least a portion of the input, wherein the second modality is different from the first modality, in which modifying the word graph includes rescoring the word graph based on averaging posterior probabilities from the modalities of the input and the complementary information; and rendering a new hypothesis to the user for the input based on the word graph. 10. The computer-readable medium of claim 8 wherein the step of modifying the word graph includes recording relevant nodes of each modality with respect to the word graph and rescoring the word graph includes rescoring the word graph beginning from a recorded node. | 0.611193 |
7. A device, comprising: a processor; a display communicatively coupled to the processor and configured to display images recognizable to a user; and a launch assist module communicatively coupled to the processor and configured to: analyze handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determine if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launch the one application for execution on the device. | 7. A device, comprising: a processor; a display communicatively coupled to the processor and configured to display images recognizable to a user; and a launch assist module communicatively coupled to the processor and configured to: analyze handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determine if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launch the one application for execution on the device. 11. The device according to claim 7 , wherein the one or more keywords are maintained in an application keyword database. | 0.621163 |
1. A method for associating documents and queries, comprising: receiving a first query submitted by a user; retrieving by said first query at least one reference to a document; displaying said at least one reference to a document; tracing at least one action of said user in relation to said at least one reference to a document; storing each of a) said first query as submitted by said user, and b) a relation between said first query and said retrieved at least one reference to a document based on said traced action; using at least in part a second query from any user to identify at least one stored query; and displaying to said any user said at least one reference to a document based on said relation to said at least one identified query; wherein a stored query comprises at least two query terms, and at least one query term comprises an expression containing more than one word. | 1. A method for associating documents and queries, comprising: receiving a first query submitted by a user; retrieving by said first query at least one reference to a document; displaying said at least one reference to a document; tracing at least one action of said user in relation to said at least one reference to a document; storing each of a) said first query as submitted by said user, and b) a relation between said first query and said retrieved at least one reference to a document based on said traced action; using at least in part a second query from any user to identify at least one stored query; and displaying to said any user said at least one reference to a document based on said relation to said at least one identified query; wherein a stored query comprises at least two query terms, and at least one query term comprises an expression containing more than one word. 19. A method according to claim 1 , comprising: receiving a selection from said user to filter search results based on one of: a. documents that have been reviewed by said user; and b. documents that have not been reviewed by said user; and displaying said filtered results. | 0.628236 |
14. An educational method for developing sight-word vocabulary in a student, comprising the steps of: providing a non-syllabified readable format text which is adapted to be or is already memorized verbatim by the student, said text having one or more words and each word having at least one syllable, and said text including a series of notations, each notation denoting at least one letter of said text, wherein portions of said words that require extended pronunciation are presented in a visually extended format so as to emphasize phonetic structure; providing a reinforcement means, separate from said text but adapted to be used together with said text, for reinforcing the student's sight recognition of words and syllables from said text; and having the student recite each word or syllable of the readable format text which the student can recite from memory while visually following along each successive notation corresponding to that word in the readable format text. | 14. An educational method for developing sight-word vocabulary in a student, comprising the steps of: providing a non-syllabified readable format text which is adapted to be or is already memorized verbatim by the student, said text having one or more words and each word having at least one syllable, and said text including a series of notations, each notation denoting at least one letter of said text, wherein portions of said words that require extended pronunciation are presented in a visually extended format so as to emphasize phonetic structure; providing a reinforcement means, separate from said text but adapted to be used together with said text, for reinforcing the student's sight recognition of words and syllables from said text; and having the student recite each word or syllable of the readable format text which the student can recite from memory while visually following along each successive notation corresponding to that word in the readable format text. 17. The educational method of claim 14, wherein said visual cues are placed below each word of said readable format text. | 0.601695 |
10. A system comprising: one or more processors configured to include: an accessing module to access first grammar data associated with a first grammar and second grammar data associated with a second grammar, wherein a grammar comprises one or more rules that define a programming language that corresponds to the grammar; a transformation module to determine from the first grammar data and the second grammar data whether the first grammar and the second grammar correspond to the same programming language, wherein determining whether the first grammar and the second grammar correspond to the same programming language includes: an application module to apply one or more transformational steps to both the first grammar data and the second grammar data; a corresponding module to, after each transformational step, determine whether the first grammar data and the second grammar data correspond; a comparison module, in accordance with a determination that the first grammar data and the second grammar data correspond, determine that the first grammar and the second grammar both correspond to the same programming language; a step selection module to, in accordance with a determination that the first grammar data and the second grammar data do not correspond, selecting a next transformational step in the one or more transformational steps, wherein prior to selecting the next transformational step: a determination module to determine whether there are any remaining transformational steps, and a difference module to, in accordance with a determination that there are no remaining transformational steps, determine that the first grammar and the second grammar do not correspond to the same programming language. | 10. A system comprising: one or more processors configured to include: an accessing module to access first grammar data associated with a first grammar and second grammar data associated with a second grammar, wherein a grammar comprises one or more rules that define a programming language that corresponds to the grammar; a transformation module to determine from the first grammar data and the second grammar data whether the first grammar and the second grammar correspond to the same programming language, wherein determining whether the first grammar and the second grammar correspond to the same programming language includes: an application module to apply one or more transformational steps to both the first grammar data and the second grammar data; a corresponding module to, after each transformational step, determine whether the first grammar data and the second grammar data correspond; a comparison module, in accordance with a determination that the first grammar data and the second grammar data correspond, determine that the first grammar and the second grammar both correspond to the same programming language; a step selection module to, in accordance with a determination that the first grammar data and the second grammar data do not correspond, selecting a next transformational step in the one or more transformational steps, wherein prior to selecting the next transformational step: a determination module to determine whether there are any remaining transformational steps, and a difference module to, in accordance with a determination that there are no remaining transformational steps, determine that the first grammar and the second grammar do not correspond to the same programming language. 11. The system of claim 10 , wherein the comparison module further includes a determination module to determine whether the first grammar is an exact text correspond for the second grammar. | 0.5 |
1. A method for generating an encryption dictionary, the method comprises: generating a random value for each plaintext symbol of multiple plaintext symbols; and calculating a random token for each plaintext symbol based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol; wherein the calculating comprises applying a monotonic increasing function; wherein the encryption dictionary comprises a mapping between the multiple plaintext symbols and random token of the multiple plaintext symbols based on a sensitivity level of one or more of the symbols, wherein the random token for each plaintext symbol is based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol. | 1. A method for generating an encryption dictionary, the method comprises: generating a random value for each plaintext symbol of multiple plaintext symbols; and calculating a random token for each plaintext symbol based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol; wherein the calculating comprises applying a monotonic increasing function; wherein the encryption dictionary comprises a mapping between the multiple plaintext symbols and random token of the multiple plaintext symbols based on a sensitivity level of one or more of the symbols, wherein the random token for each plaintext symbol is based on a random value of the plaintext symbol and on random values of other plaintext symbols that have a lower lexicographic value than the plaintext symbol. 8. The method according to claim 1 further comprising selecting the multiple plaintext symbols. | 0.701331 |
15. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: obtain at least one image of an advertisement associated with an event, the at least one image being captured by a camera of the computing device; process the at least one image of the advertisement to locate at least one region having properties of text; analyze the at least one region using an optical character recognition algorithm to recognize the text associated with the event; identify a text pattern corresponding to the recognized text; determine an application associated with the text pattern; and cause the recognized text to be sent to the application for performing an action with the text pattern associated with the event. | 15. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: obtain at least one image of an advertisement associated with an event, the at least one image being captured by a camera of the computing device; process the at least one image of the advertisement to locate at least one region having properties of text; analyze the at least one region using an optical character recognition algorithm to recognize the text associated with the event; identify a text pattern corresponding to the recognized text; determine an application associated with the text pattern; and cause the recognized text to be sent to the application for performing an action with the text pattern associated with the event. 16. The computing device of claim 15 , wherein the text pattern includes at least one of a pattern indicative of a telephone number for information associated with the event, a pattern indicative of an email address associated with the event, a pattern indicative of a URL associated with the event, or a pattern indicative of a street address for the event. | 0.559545 |
1. A method, comprising: transforming received source code according to a predefined rule set to create an encoded text string representation of each function of the received source code, where each encoded text string representation of each function of the received source code comprises a text string that identifies each parameter type of the respective function of the received source code, wherein the received source code comprises a plurality of functions; comparing, in real time, each encoded text string representation of each function of the received source code with encoded text string representations of stored source code fragments in a repository, where each stored source code fragment in the repository is transformed according to the same predefined rule set into the respective encoded text string representations that each comprise a text string that identifies each parameter type of a respective function of the respective stored source code fragment in the repository; and outputting an indication, in response to the real-time comparison, of each portion of the received source code determined to already exist as a stored source code fragment in the repository, wherein comparing, in real time, each encoded text string representation of each function of the received source code with the encoded text string representations of the stored source code fragments in the repository includes: forming a set of application programming interface (API) sequences that each represent one of a plurality of encoded text string representations transformed from the plurality of functions of the received source code; and performing independent searches against the stored source code fragments in the repository using the set of API sequences. | 1. A method, comprising: transforming received source code according to a predefined rule set to create an encoded text string representation of each function of the received source code, where each encoded text string representation of each function of the received source code comprises a text string that identifies each parameter type of the respective function of the received source code, wherein the received source code comprises a plurality of functions; comparing, in real time, each encoded text string representation of each function of the received source code with encoded text string representations of stored source code fragments in a repository, where each stored source code fragment in the repository is transformed according to the same predefined rule set into the respective encoded text string representations that each comprise a text string that identifies each parameter type of a respective function of the respective stored source code fragment in the repository; and outputting an indication, in response to the real-time comparison, of each portion of the received source code determined to already exist as a stored source code fragment in the repository, wherein comparing, in real time, each encoded text string representation of each function of the received source code with the encoded text string representations of the stored source code fragments in the repository includes: forming a set of application programming interface (API) sequences that each represent one of a plurality of encoded text string representations transformed from the plurality of functions of the received source code; and performing independent searches against the stored source code fragments in the repository using the set of API sequences. 3. The method of claim 1 , further comprising: determining that at least one of the encoded text string representations of the received source code exists as the stored source code fragment in the repository based upon identification of a matching pattern of an encoded text string representation of a stored source code fragment in the repository; and where outputting the indication, in response to the real-time comparison, of each portion of the received source code determined to already exist as the stored source code fragment in the repository includes: highlighting, within a software developer kit (SDK) as a potential area of code re-use, each portion of the received source code indicated to already exist as the stored source code fragment in the repository based upon the indication of the matching pattern. | 0.625547 |
8. A user computer for searching a user's content items hosted by an online content management service, the user computer comprising at least one processor configured to: obtain a search query; use the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; display, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; send the search query over a communications network to the online content management service; receive, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; update the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the update, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. | 8. A user computer for searching a user's content items hosted by an online content management service, the user computer comprising at least one processor configured to: obtain a search query; use the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; display, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; send the search query over a communications network to the online content management service; receive, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; update the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the update, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. 11. The user computer of claim 8 , the at least one processor further configured to: update the graphical user interface at the user computer to display, for a fourth content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a fourth search answer summary for the fourth content item; wherein the fourth content item is not stored at the user computer at the time the search query is obtained; and wherein the fourth search answer summary for the fourth content item indicates that the fourth content item is not stored at the user computer. | 0.649143 |
18. A method comprising: performing a data recovery process on data from a data storage medium including at least one data unit having a plurality of segments for storing data, the plurality of segments including k number of segments and r number of segments, each k and r segment including an inner code parity for providing inner code protection against errors within the segment and each r segment including outer code parity for providing outer code protection against inner code failures; associating the r number of segments with the k number of segments to derive a plurality of outer code words, wherein each outer code word contains m number of symbols from each segment for correcting m number of symbols in each outer code word; iteratively performing an error correction process by: determining if an inner code can correct errors in a first selected inner code word of the plurality of inner code words; when the inner code can correct errors in the first selected inner code word, then performing inner code error correction on the plurality of inner code words; when an error in at least one of the plurality of inner code words fails to be corrected by the inner code, then determining if an outer code can correct errors in a first selected outer code word of the plurality of outer code words; when the outer code can correct errors in the first selected outer code word, then performing outer code error correction on the plurality of outer code words; and when an error in at least one of the plurality of outer code words fails to be corrected by the outer code, then repeating the error correction process; wherein k, r and m are integers greater than or equal to 1. | 18. A method comprising: performing a data recovery process on data from a data storage medium including at least one data unit having a plurality of segments for storing data, the plurality of segments including k number of segments and r number of segments, each k and r segment including an inner code parity for providing inner code protection against errors within the segment and each r segment including outer code parity for providing outer code protection against inner code failures; associating the r number of segments with the k number of segments to derive a plurality of outer code words, wherein each outer code word contains m number of symbols from each segment for correcting m number of symbols in each outer code word; iteratively performing an error correction process by: determining if an inner code can correct errors in a first selected inner code word of the plurality of inner code words; when the inner code can correct errors in the first selected inner code word, then performing inner code error correction on the plurality of inner code words; when an error in at least one of the plurality of inner code words fails to be corrected by the inner code, then determining if an outer code can correct errors in a first selected outer code word of the plurality of outer code words; when the outer code can correct errors in the first selected outer code word, then performing outer code error correction on the plurality of outer code words; and when an error in at least one of the plurality of outer code words fails to be corrected by the outer code, then repeating the error correction process; wherein k, r and m are integers greater than or equal to 1. 19. The method of claim 18 , further comprising the error correction process including when the inner code cannot correct errors in the first selected inner code word, then proceeding to determining if an outer code can correct errors in a first selected outer code word of the plurality of outer code words without performing inner code error correction on the plurality of inner code words. | 0.5 |
18. The computer program product as in claim 12 , wherein the computer readable program code means for analyzing the plurality of training samples using the associative discoverer comprises computer readable program code means for analyzing the plurality of training samples using at least one of a neural network, a statistical system, and a symbolic machine learning system. | 18. The computer program product as in claim 12 , wherein the computer readable program code means for analyzing the plurality of training samples using the associative discoverer comprises computer readable program code means for analyzing the plurality of training samples using at least one of a neural network, a statistical system, and a symbolic machine learning system. 19. The computer program product as in claim 18 , wherein the computer readable program code means for analyzing the plurality of training samples comprises computer readable program code means for analyzing the plurality of training samples using an Adaptive Resonance Associative Map. | 0.888727 |
1. A method for determining a language of origin of a word comprising analyzing non-uniform letter sequence portions of the word, wherein analyzing comprises: using one or more processors of a computing system, segmenting the word into strings of letter chunks based on different criteria, the letter chunks being of non-uniform length of one or more letters; using one or more processors of a computing system, ascertaining a probability of the word belonging to a selected language by using a plurality of N-gram models based directly on the letter chunks segmented with the different criteria for each of a plurality of different languages, and providing results from using the plurality of N-gram models based directly on letter chunks extracted with the different criteria to a combined classifier that merges the results from the plurality of N-gram models to provide a hypothesis of the language of origin, wherein the combined classifier comprises a plurality of Gaussian mixture models wherein scores from multiple letter chunks models are treated as an eigenvector of a word and a Gaussian mixture model is provided for each of the plurality of different languages, and wherein the results from the plurality of N-gram models are scored by each of the Gaussian mixture models; and outputting the hypothesis of the language of origin of the word provided by the combined classifier. | 1. A method for determining a language of origin of a word comprising analyzing non-uniform letter sequence portions of the word, wherein analyzing comprises: using one or more processors of a computing system, segmenting the word into strings of letter chunks based on different criteria, the letter chunks being of non-uniform length of one or more letters; using one or more processors of a computing system, ascertaining a probability of the word belonging to a selected language by using a plurality of N-gram models based directly on the letter chunks segmented with the different criteria for each of a plurality of different languages, and providing results from using the plurality of N-gram models based directly on letter chunks extracted with the different criteria to a combined classifier that merges the results from the plurality of N-gram models to provide a hypothesis of the language of origin, wherein the combined classifier comprises a plurality of Gaussian mixture models wherein scores from multiple letter chunks models are treated as an eigenvector of a word and a Gaussian mixture model is provided for each of the plurality of different languages, and wherein the results from the plurality of N-gram models are scored by each of the Gaussian mixture models; and outputting the hypothesis of the language of origin of the word provided by the combined classifier. 7. The method of claim 1 further comprising selecting the word from within a context in a first language and identifying the word as being out of the vocabulary of the first language. | 0.773956 |
5. The method of claim 1 , further comprising selecting a context from a plurality of contexts for the training message, wherein each context is a collection of documents with commonality. | 5. The method of claim 1 , further comprising selecting a context from a plurality of contexts for the training message, wherein each context is a collection of documents with commonality. 7. The method of claim 5 , further comprising generating a new context in the plurality of contexts. | 0.905959 |
14. A computer program product, tangibly stored on a computer-readable storage device, the product comprising instructions operable to cause a computer system to: identify repurposable information in an electronic document, the repurposable information being less than all of the content in the electronic document; define one or more repurposing constraints for the repurposable information, the repurposing constraints identifying an authorized destination for the repurposable information; and receiving a digital signature for the repurposable information and the one or more repurposing constraints, the digital signature authenticating the repurposable information, the digital signature verifying that the repurposable information has not been altered since it was signed, the digital signature being maintained by the authorized destination when the repurposable information is repurposed. | 14. A computer program product, tangibly stored on a computer-readable storage device, the product comprising instructions operable to cause a computer system to: identify repurposable information in an electronic document, the repurposable information being less than all of the content in the electronic document; define one or more repurposing constraints for the repurposable information, the repurposing constraints identifying an authorized destination for the repurposable information; and receiving a digital signature for the repurposable information and the one or more repurposing constraints, the digital signature authenticating the repurposable information, the digital signature verifying that the repurposable information has not been altered since it was signed, the digital signature being maintained by the authorized destination when the repurposable information is repurposed. 25. The computer program product of claim 14 , further comprising instructions operable to cause a computer system to: create a template including one or more subsets of information in the electronic document; wherein the instructions operable to cause a computer system to identify repurposable information include instructions operable to cause a computer system to designate at least one of the one or more subsets of information as repurposable. | 0.5 |
1. A system for automatically extracting relations between concepts included in electronic text, comprising: a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and a linguistic engine for performing semantic disambiguation on the electronic text using the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. | 1. A system for automatically extracting relations between concepts included in electronic text, comprising: a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets; wherein the semantic network further includes semantic information comprising at least one of: an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language; and a linguistic engine for performing semantic disambiguation on the electronic text using the at least one of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference of the electronic text. 6. The system of claim 1 wherein the semantic network includes an expanded definition of a lemma such that the semantic network can store each lemma as any one of: a single word, a compound word, a collocation, an idiomatic expression, a locution, and a verbal lemma. | 0.569946 |
1. An album editing apparatus to control a giving of a same content warning regarding image files within an album and displayed images arranged on pages of the album, wherein the displayed images correspond to the image files, the album editing apparatus comprising: a storage unit configured to store an album having a plurality of image files, where each image file is configured to include information concerning at least one of an original image and a thumbnail image of that original image; an editing unit configured to operate an image editing processing to edit a displayed image arranged on a page of an album, wherein the displayed image is based on an original image; a warning management table storing size threshold values, wherein the size threshold values include a permissible overlapping size ratio; a computing unit configured, after a size of a first image from a first image file of a first album is edited and changed to produce an edited first image and the image editing processing has been terminated, to compute an actual overlapping size ratio that accounts for a change in image size resulting from removal of outer parts of an image; a determining unit configured to determine whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio; and a warning unit configured, in response to the actual overlapping size ratio being smaller than the permissible overlapping size ratio, to refrain from giving a same content warning, and, in response to the actual overlapping size ratio being larger than the permissible overlapping size ratio, to give a same content warning that is configured to warn a user that same images are displayed in plural image areas within the album, wherein, prior to determining whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio, the determining unit is configured to determine whether one of a first image file name and first image binary data of the first image file matches, one of a second image file name and second image binary data of the second image file and, in response to the first image file name and the second image file name not matching or the first image binary data and the second image binary data not matching, the determining unit does not determine whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio and the warning unit does not give a same content warning and, in response to the first image file name and the second image file name matching or the first image binary data and the second image binary data matching the determining unit then determines whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio. | 1. An album editing apparatus to control a giving of a same content warning regarding image files within an album and displayed images arranged on pages of the album, wherein the displayed images correspond to the image files, the album editing apparatus comprising: a storage unit configured to store an album having a plurality of image files, where each image file is configured to include information concerning at least one of an original image and a thumbnail image of that original image; an editing unit configured to operate an image editing processing to edit a displayed image arranged on a page of an album, wherein the displayed image is based on an original image; a warning management table storing size threshold values, wherein the size threshold values include a permissible overlapping size ratio; a computing unit configured, after a size of a first image from a first image file of a first album is edited and changed to produce an edited first image and the image editing processing has been terminated, to compute an actual overlapping size ratio that accounts for a change in image size resulting from removal of outer parts of an image; a determining unit configured to determine whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio; and a warning unit configured, in response to the actual overlapping size ratio being smaller than the permissible overlapping size ratio, to refrain from giving a same content warning, and, in response to the actual overlapping size ratio being larger than the permissible overlapping size ratio, to give a same content warning that is configured to warn a user that same images are displayed in plural image areas within the album, wherein, prior to determining whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio, the determining unit is configured to determine whether one of a first image file name and first image binary data of the first image file matches, one of a second image file name and second image binary data of the second image file and, in response to the first image file name and the second image file name not matching or the first image binary data and the second image binary data not matching, the determining unit does not determine whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio and the warning unit does not give a same content warning and, in response to the first image file name and the second image file name matching or the first image binary data and the second image binary data matching the determining unit then determines whether the actual overlapping size ratio is smaller than the permissible overlapping size ratio. 5. The album editing apparatus of claim 1 , wherein the edited first image is located on a first two-page-spread that is displayed on a display apparatus and the second image is located on a second two-page-spread that is not displayed on the display apparatus. | 0.652032 |
4. The method of claim 1 , further comprising using a database accessible by both the model-based expert system and the rule-based expert system, wherein the database comprises: (a) data pertaining to the configuration of the mathematical model in the model-based expert system; and (b) data pertaining to the configuration of the rules in the rule-based expert system. | 4. The method of claim 1 , further comprising using a database accessible by both the model-based expert system and the rule-based expert system, wherein the database comprises: (a) data pertaining to the configuration of the mathematical model in the model-based expert system; and (b) data pertaining to the configuration of the rules in the rule-based expert system. 5. The method of claim 4 , wherein the database further comprises: (c) data pertaining to the message suppression relationships in the integrated expert system. | 0.889607 |
9. A non-transitory computer-readable medium storing instructions, the instructions comprising: a plurality of instructions, which, when executed by one or more processors, cause the one or more processors to: determine a quantity of links to or from a document; determine an amount of time that has elapsed since an inception date associated with the document; calculate an average rate at which links to or from the document are created, based on: the quantity of links to or from the document, and the amount of time that has elapsed since the inception date associated with the document, the instructions to calculate the average rate including: instructions to perform a mathematical operation on a first value that is based on the quantity of links to or from the document and a second value that is based on the amount of time that has elapsed since the inception date associated with the document; and rank the document with regard to at least one other document based on the average rate at which links to or from the document are created. | 9. A non-transitory computer-readable medium storing instructions, the instructions comprising: a plurality of instructions, which, when executed by one or more processors, cause the one or more processors to: determine a quantity of links to or from a document; determine an amount of time that has elapsed since an inception date associated with the document; calculate an average rate at which links to or from the document are created, based on: the quantity of links to or from the document, and the amount of time that has elapsed since the inception date associated with the document, the instructions to calculate the average rate including: instructions to perform a mathematical operation on a first value that is based on the quantity of links to or from the document and a second value that is based on the amount of time that has elapsed since the inception date associated with the document; and rank the document with regard to at least one other document based on the average rate at which links to or from the document are created. 12. The computer-readable medium of claim 9 , where the inception date is a date on which a domain associated with the document is registered. | 0.727184 |
27. An electronic device comprising: a communication unit; a memory storing instructions; and a processor configured to execute the instructions to at least: control to receive a message via a messaging program executed by the processor, the message being received through a communication unit, control to identify a first token including a first plurality of alphanumeric characters from the received message based at least on the first plurality of alphanumeric characters being in a defined set of alphanumeric characters, control to identify a second token including a second plurality of alphanumeric characters related to a location from the received message, wherein a plurality of alphanumeric characters is determined to be related to the location based at least on a probability of the second plurality of alphanumeric characters being related to the location; control to obtain, based at least on the first token and descriptive data of the received message, first input data in a first format for specifying date and time, control to obtain, based at least on the second token, second input data in a second format for specifying the location, and control to execute a schedule management function program based on at least one of the first token or the second token and supply the first input data and the second input data to the schedule management function program so that the first input data and the second input data are automatically presented in an execution screen of the schedule management function program executed by the processor. | 27. An electronic device comprising: a communication unit; a memory storing instructions; and a processor configured to execute the instructions to at least: control to receive a message via a messaging program executed by the processor, the message being received through a communication unit, control to identify a first token including a first plurality of alphanumeric characters from the received message based at least on the first plurality of alphanumeric characters being in a defined set of alphanumeric characters, control to identify a second token including a second plurality of alphanumeric characters related to a location from the received message, wherein a plurality of alphanumeric characters is determined to be related to the location based at least on a probability of the second plurality of alphanumeric characters being related to the location; control to obtain, based at least on the first token and descriptive data of the received message, first input data in a first format for specifying date and time, control to obtain, based at least on the second token, second input data in a second format for specifying the location, and control to execute a schedule management function program based on at least one of the first token or the second token and supply the first input data and the second input data to the schedule management function program so that the first input data and the second input data are automatically presented in an execution screen of the schedule management function program executed by the processor. 30. The electronic device of claim 27 , wherein the processor is configured to execute the instructions further to: control to create a new schedule entry including the first input data and the second input data using the schedule management function program. | 0.691418 |
3. The computer implemented method of claim 2 , wherein data of the second data type is formatted according to a structured format of records and fields. | 3. The computer implemented method of claim 2 , wherein data of the second data type is formatted according to a structured format of records and fields. 4. The computer implemented method of claim 3 , wherein the fields include a series of ASCII characters followed by a TAB character. | 0.923077 |
24. The system of claim 18 , wherein determining the probability of the predicted word comprises determining, using the n-gram language model, the probability of the predicted word based on a plurality of words in the received input. | 24. The system of claim 18 , wherein determining the probability of the predicted word comprises determining, using the n-gram language model, the probability of the predicted word based on a plurality of words in the received input. 25. The system of claim 24 , wherein the plurality of words comprises a string of recently entered words. | 0.940819 |
6. A system for developing product runtime code, the system comprising: at least one processor; a computer readable storage device coupled to the at least one processor; and a set of instructions stored in the computer readable storage device, wherein the set of instructions is executable by the processor to cause the processor to: identify a first code component and a second code component, wherein the first code component is in a first runtime language, and wherein the second code component is in a second runtime language, wherein the first runtime language is different than the second runtime language; translate, by a programming interface, the first code component and the second code component into a common development language for development of the code components by: wrapping functions in the first code component in the first runtime language for use in the common development language, and wrapping functions in the second code component in the second runtime language for use in the common development language, wherein the programming interface includes a mapping between functions in the first and second runtime languages and the common development language; determine that the first code component and the second code component have been edited in the common development language; and translate the first edited code component from the common development language into the first runtime language, and the second edited code component into the second runtime language for execution. | 6. A system for developing product runtime code, the system comprising: at least one processor; a computer readable storage device coupled to the at least one processor; and a set of instructions stored in the computer readable storage device, wherein the set of instructions is executable by the processor to cause the processor to: identify a first code component and a second code component, wherein the first code component is in a first runtime language, and wherein the second code component is in a second runtime language, wherein the first runtime language is different than the second runtime language; translate, by a programming interface, the first code component and the second code component into a common development language for development of the code components by: wrapping functions in the first code component in the first runtime language for use in the common development language, and wrapping functions in the second code component in the second runtime language for use in the common development language, wherein the programming interface includes a mapping between functions in the first and second runtime languages and the common development language; determine that the first code component and the second code component have been edited in the common development language; and translate the first edited code component from the common development language into the first runtime language, and the second edited code component into the second runtime language for execution. 7. The system of claim 6 , wherein the programming interface facilities of the first runtime language and the second runtime language in the common development language. | 0.5 |
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